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Sample records for striatal prediction error

  1. Episodic Memory Encoding Interferes with Reward Learning and Decreases Striatal Prediction Errors

    Science.gov (United States)

    Braun, Erin Kendall; Daw, Nathaniel D.

    2014-01-01

    Learning is essential for adaptive decision making. The striatum and its dopaminergic inputs are known to support incremental reward-based learning, while the hippocampus is known to support encoding of single events (episodic memory). Although traditionally studied separately, in even simple experiences, these two types of learning are likely to co-occur and may interact. Here we sought to understand the nature of this interaction by examining how incremental reward learning is related to concurrent episodic memory encoding. During the experiment, human participants made choices between two options (colored squares), each associated with a drifting probability of reward, with the goal of earning as much money as possible. Incidental, trial-unique object pictures, unrelated to the choice, were overlaid on each option. The next day, participants were given a surprise memory test for these pictures. We found that better episodic memory was related to a decreased influence of recent reward experience on choice, both within and across participants. fMRI analyses further revealed that during learning the canonical striatal reward prediction error signal was significantly weaker when episodic memory was stronger. This decrease in reward prediction error signals in the striatum was associated with enhanced functional connectivity between the hippocampus and striatum at the time of choice. Our results suggest a mechanism by which memory encoding may compete for striatal processing and provide insight into how interactions between different forms of learning guide reward-based decision making. PMID:25378157

  2. Episodic memory encoding interferes with reward learning and decreases striatal prediction errors.

    Science.gov (United States)

    Wimmer, G Elliott; Braun, Erin Kendall; Daw, Nathaniel D; Shohamy, Daphna

    2014-11-05

    Learning is essential for adaptive decision making. The striatum and its dopaminergic inputs are known to support incremental reward-based learning, while the hippocampus is known to support encoding of single events (episodic memory). Although traditionally studied separately, in even simple experiences, these two types of learning are likely to co-occur and may interact. Here we sought to understand the nature of this interaction by examining how incremental reward learning is related to concurrent episodic memory encoding. During the experiment, human participants made choices between two options (colored squares), each associated with a drifting probability of reward, with the goal of earning as much money as possible. Incidental, trial-unique object pictures, unrelated to the choice, were overlaid on each option. The next day, participants were given a surprise memory test for these pictures. We found that better episodic memory was related to a decreased influence of recent reward experience on choice, both within and across participants. fMRI analyses further revealed that during learning the canonical striatal reward prediction error signal was significantly weaker when episodic memory was stronger. This decrease in reward prediction error signals in the striatum was associated with enhanced functional connectivity between the hippocampus and striatum at the time of choice. Our results suggest a mechanism by which memory encoding may compete for striatal processing and provide insight into how interactions between different forms of learning guide reward-based decision making. Copyright © 2014 the authors 0270-6474/14/3414901-12$15.00/0.

  3. Moderation of the Relationship Between Reward Expectancy and Prediction Error-Related Ventral Striatal Reactivity by Anhedonia in Unmedicated Major Depressive Disorder: Findings From the EMBARC Study

    Science.gov (United States)

    Greenberg, Tsafrir; Chase, Henry W.; Almeida, Jorge R.; Stiffler, Richelle; Zevallos, Carlos R.; Aslam, Haris A.; Deckersbach, Thilo; Weyandt, Sarah; Cooper, Crystal; Toups, Marisa; Carmody, Thomas; Kurian, Benji; Peltier, Scott; Adams, Phillip; McInnis, Melvin G.; Oquendo, Maria A.; McGrath, Patrick J.; Fava, Maurizio; Weissman, Myrna; Parsey, Ramin; Trivedi, Madhukar H.; Phillips, Mary L.

    2016-01-01

    Objective Anhedonia, disrupted reward processing, is a core symptom of major depressive disorder. Recent findings demonstrate altered reward-related ventral striatal reactivity in depressed individuals, but the extent to which this is specific to anhedonia remains poorly understood. The authors examined the effect of anhedonia on reward expectancy (expected outcome value) and prediction error-(discrepancy between expected and actual outcome) related ventral striatal reactivity, as well as the relationship between these measures. Method A total of 148 unmedicated individuals with major depressive disorder and 31 healthy comparison individuals recruited for the multisite EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study underwent functional MRI during a well-validated reward task. Region of interest and whole-brain data were examined in the first- (N=78) and second- (N=70) recruited cohorts, as well as the total sample, of depressed individuals, and in healthy individuals. Results Healthy, but not depressed, individuals showed a significant inverse relationship between reward expectancy and prediction error-related right ventral striatal reactivity. Across all participants, and in depressed individuals only, greater anhedonia severity was associated with a reduced reward expectancy-prediction error inverse relationship, even after controlling for other symptoms. Conclusions The normal reward expectancy and prediction error-related ventral striatal reactivity inverse relationship concords with conditioning models, predicting a shift in ventral striatal responding from reward outcomes to reward cues. This study shows, for the first time, an absence of this relationship in two cohorts of unmedicated depressed individuals and a moderation of this relationship by anhedonia, suggesting reduced reward-contingency learning with greater anhedonia. These findings help elucidate neural mechanisms of anhedonia, as a step toward

  4. Moderation of the Relationship Between Reward Expectancy and Prediction Error-Related Ventral Striatal Reactivity by Anhedonia in Unmedicated Major Depressive Disorder: Findings From the EMBARC Study.

    Science.gov (United States)

    Greenberg, Tsafrir; Chase, Henry W; Almeida, Jorge R; Stiffler, Richelle; Zevallos, Carlos R; Aslam, Haris A; Deckersbach, Thilo; Weyandt, Sarah; Cooper, Crystal; Toups, Marisa; Carmody, Thomas; Kurian, Benji; Peltier, Scott; Adams, Phillip; McInnis, Melvin G; Oquendo, Maria A; McGrath, Patrick J; Fava, Maurizio; Weissman, Myrna; Parsey, Ramin; Trivedi, Madhukar H; Phillips, Mary L

    2015-09-01

    Anhedonia, disrupted reward processing, is a core symptom of major depressive disorder. Recent findings demonstrate altered reward-related ventral striatal reactivity in depressed individuals, but the extent to which this is specific to anhedonia remains poorly understood. The authors examined the effect of anhedonia on reward expectancy (expected outcome value) and prediction error- (discrepancy between expected and actual outcome) related ventral striatal reactivity, as well as the relationship between these measures. A total of 148 unmedicated individuals with major depressive disorder and 31 healthy comparison individuals recruited for the multisite EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study underwent functional MRI during a well-validated reward task. Region of interest and whole-brain data were examined in the first- (N=78) and second- (N=70) recruited cohorts, as well as the total sample, of depressed individuals, and in healthy individuals. Healthy, but not depressed, individuals showed a significant inverse relationship between reward expectancy and prediction error-related right ventral striatal reactivity. Across all participants, and in depressed individuals only, greater anhedonia severity was associated with a reduced reward expectancy-prediction error inverse relationship, even after controlling for other symptoms. The normal reward expectancy and prediction error-related ventral striatal reactivity inverse relationship concords with conditioning models, predicting a shift in ventral striatal responding from reward outcomes to reward cues. This study shows, for the first time, an absence of this relationship in two cohorts of unmedicated depressed individuals and a moderation of this relationship by anhedonia, suggesting reduced reward-contingency learning with greater anhedonia. These findings help elucidate neural mechanisms of anhedonia, as a step toward identifying potential biosignatures

  5. Hemispheric Asymmetries in Striatal Reward Responses Relate to Approach-Avoidance Learning and Encoding of Positive-Negative Prediction Errors in Dopaminergic Midbrain Regions.

    Science.gov (United States)

    Aberg, Kristoffer Carl; Doell, Kimberly C; Schwartz, Sophie

    2015-10-28

    Some individuals are better at learning about rewarding situations, whereas others are inclined to avoid punishments (i.e., enhanced approach or avoidance learning, respectively). In reinforcement learning, action values are increased when outcomes are better than predicted (positive prediction errors [PEs]) and decreased for worse than predicted outcomes (negative PEs). Because actions with high and low values are approached and avoided, respectively, individual differences in the neural encoding of PEs may influence the balance between approach-avoidance learning. Recent correlational approaches also indicate that biases in approach-avoidance learning involve hemispheric asymmetries in dopamine function. However, the computational and neural mechanisms underpinning such learning biases remain unknown. Here we assessed hemispheric reward asymmetry in striatal activity in 34 human participants who performed a task involving rewards and punishments. We show that the relative difference in reward response between hemispheres relates to individual biases in approach-avoidance learning. Moreover, using a computational modeling approach, we demonstrate that better encoding of positive (vs negative) PEs in dopaminergic midbrain regions is associated with better approach (vs avoidance) learning, specifically in participants with larger reward responses in the left (vs right) ventral striatum. Thus, individual dispositions or traits may be determined by neural processes acting to constrain learning about specific aspects of the world. Copyright © 2015 the authors 0270-6474/15/3514491-10$15.00/0.

  6. Striatal volume predicts level of video game skill acquisition.

    Science.gov (United States)

    Erickson, Kirk I; Boot, Walter R; Basak, Chandramallika; Neider, Mark B; Prakash, Ruchika S; Voss, Michelle W; Graybiel, Ann M; Simons, Daniel J; Fabiani, Monica; Gratton, Gabriele; Kramer, Arthur F

    2010-11-01

    Video game skills transfer to other tasks, but individual differences in performance and in learning and transfer rates make it difficult to identify the source of transfer benefits. We asked whether variability in initial acquisition and of improvement in performance on a demanding video game, the Space Fortress game, could be predicted by variations in the pretraining volume of either of 2 key brain regions implicated in learning and memory: the striatum, implicated in procedural learning and cognitive flexibility, and the hippocampus, implicated in declarative memory. We found that hippocampal volumes did not predict learning improvement but that striatal volumes did. Moreover, for the striatum, the volumes of the dorsal striatum predicted improvement in performance but the volumes of the ventral striatum did not. Both ventral and dorsal striatal volumes predicted early acquisition rates. Furthermore, this early-stage correlation between striatal volumes and learning held regardless of the cognitive flexibility demands of the game versions, whereas the predictive power of the dorsal striatal volumes held selectively for performance improvements in a game version emphasizing cognitive flexibility. These findings suggest a neuroanatomical basis for the superiority of training strategies that promote cognitive flexibility and transfer to untrained tasks.

  7. Dopamine reward prediction error coding

    OpenAIRE

    Schultz, Wolfram

    2016-01-01

    Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards?an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less...

  8. Dopamine reward prediction error coding.

    Science.gov (United States)

    Schultz, Wolfram

    2016-03-01

    Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.

  9. Striatal Activation Predicts Differential Therapeutic Responses to Methylphenidate and Atomoxetine.

    Science.gov (United States)

    Schulz, Kurt P; Bédard, Anne-Claude V; Fan, Jin; Hildebrandt, Thomas B; Stein, Mark A; Ivanov, Iliyan; Halperin, Jeffrey M; Newcorn, Jeffrey H

    2017-07-01

    Methylphenidate has prominent effects in the dopamine-rich striatum that are absent for the selective norepinephrine transporter inhibitor atomoxetine. This study tested whether baseline striatal activation would predict differential response to the two medications in youth with attention-deficit/hyperactivity disorder (ADHD). A total of 36 youth with ADHD performed a Go/No-Go test during functional magnetic resonance imaging at baseline and were treated with methylphenidate and atomoxetine using a randomized cross-over design. Whole-brain task-related activation was regressed on clinical response. Task-related activation in right caudate nucleus was predicted by an interaction of clinical responses to methylphenidate and atomoxetine (F 1,30  = 17.00; p atomoxetine. The rate of robust response was higher for methylphenidate than for atomoxetine in youth with high (94.4% vs. 38.8%; p = .003; number needed to treat = 2, 95% CI = 1.31-3.73) but not low (33.3% vs. 50.0%; p = .375) caudate activation. Furthermore, response to atomoxetine predicted motor cortex activation (F 1,30  = 14.99; p atomoxetine in youth with ADHD, purportedly reflecting the dopaminergic effects of methylphenidate but not atomoxetine in the striatum, whereas motor cortex activation may predict response to atomoxetine. These data do not yet translate directly to the clinical setting, but the approach is potentially important for informing future research and illustrates that it may be possible to predict differential treatment response using a biomarker-driven approach. Stimulant Versus Nonstimulant Medication for Attention Deficit Hyperactivity Disorder in Children; https://clinicaltrials.gov/; NCT00183391. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

  10. Does human presynaptic striatal dopamine function predict social conformity?

    Science.gov (United States)

    Stokes, Paul R A; Benecke, Aaf; Puraite, Julita; Bloomfield, Michael A P; Shotbolt, Paul; Reeves, Suzanne J; Lingford-Hughes, Anne R; Howes, Oliver; Egerton, Alice

    2014-03-01

    Socially desirable responding (SDR) is a personality trait which reflects either a tendency to present oneself in an overly positive manner to others, consistent with social conformity (impression management (IM)), or the tendency to view one's own behaviour in an overly positive light (self-deceptive enhancement (SDE)). Neurochemical imaging studies report an inverse relationship between SDR and dorsal striatal dopamine D₂/₃ receptor availability. This may reflect an association between SDR and D₂/₃ receptor expression, synaptic dopamine levels or a combination of the two. In this study, we used a [¹⁸F]-DOPA positron emission tomography (PET) image database to investigate whether SDR is associated with presynaptic dopamine function. Striatal [¹⁸F]-DOPA uptake, (k(i)(cer), min⁻¹), was determined in two independent healthy participant cohorts (n=27 and 19), by Patlak analysis using a cerebellar reference region. SDR was assessed using the revised Eysenck Personality Questionnaire (EPQ-R) Lie scale, and IM and SDE were measured using the Paulhus Deception Scales. No significant associations were detected between Lie, SDE or IM scores and striatal [¹⁸F]-DOPA k(i)(cer). These results indicate that presynaptic striatal dopamine function is not associated with social conformity and suggests that social conformity may be associated with striatal D₂/₃ receptor expression rather than with synaptic dopamine levels.

  11. Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

    Science.gov (United States)

    Bertolino, Alessandro; Taurisano, Paolo; Pisciotta, Nicola Marco; Blasi, Giuseppe; Fazio, Leonardo; Romano, Raffaella; Gelao, Barbara; Lo Bianco, Luciana; Lozupone, Madia; Di Giorgio, Annabella; Caforio, Grazia; Sambataro, Fabio; Niccoli-Asabella, Artor; Papp, Audrey; Ursini, Gianluca; Sinibaldi, Lorenzo; Popolizio, Teresa; Sadee, Wolfgang; Rubini, Giuseppe

    2010-02-22

    Variation of the gene coding for D2 receptors (DRD2) has been associated with risk for schizophrenia and with working memory deficits. A functional intronic SNP (rs1076560) predicts relative expression of the two D2 receptors isoforms, D2S (mainly pre-synaptic) and D2L (mainly post-synaptic). However, the effect of functional genetic variation of DRD2 on striatal dopamine D2 signaling and on its correlation with prefrontal activity during working memory in humans is not known. Thirty-seven healthy subjects were genotyped for rs1076560 (G>T) and underwent SPECT with [123I]IBZM (which binds primarily to post-synaptic D2 receptors) and with [123I]FP-CIT (which binds to pre-synaptic dopamine transporters, whose activity and density is also regulated by pre-synaptic D2 receptors), as well as BOLD fMRI during N-Back working memory. Subjects carrying the T allele (previously associated with reduced D2S expression) had striatal reductions of [123I]IBZM and of [123I]FP-CIT binding. DRD2 genotype also differentially predicted the correlation between striatal dopamine D2 signaling (as identified with factor analysis of the two radiotracers) and activity of the prefrontal cortex during working memory as measured with BOLD fMRI, which was positive in GG subjects and negative in GT. Our results demonstrate that this functional SNP within DRD2 predicts striatal binding of the two radiotracers to dopamine transporters and D2 receptors as well as the correlation between striatal D2 signaling with prefrontal cortex activity during performance of a working memory task. These data are consistent with the possibility that the balance of excitatory/inhibitory modulation of striatal neurons may also affect striatal outputs in relationship with prefrontal activity during working memory performance within the cortico-striatal-thalamic-cortical pathway.

  12. Genetically determined measures of striatal D2 signaling predict prefrontal activity during working memory performance.

    Directory of Open Access Journals (Sweden)

    Alessandro Bertolino

    2010-02-01

    Full Text Available Variation of the gene coding for D2 receptors (DRD2 has been associated with risk for schizophrenia and with working memory deficits. A functional intronic SNP (rs1076560 predicts relative expression of the two D2 receptors isoforms, D2S (mainly pre-synaptic and D2L (mainly post-synaptic. However, the effect of functional genetic variation of DRD2 on striatal dopamine D2 signaling and on its correlation with prefrontal activity during working memory in humans is not known.Thirty-seven healthy subjects were genotyped for rs1076560 (G>T and underwent SPECT with [123I]IBZM (which binds primarily to post-synaptic D2 receptors and with [123I]FP-CIT (which binds to pre-synaptic dopamine transporters, whose activity and density is also regulated by pre-synaptic D2 receptors, as well as BOLD fMRI during N-Back working memory.Subjects carrying the T allele (previously associated with reduced D2S expression had striatal reductions of [123I]IBZM and of [123I]FP-CIT binding. DRD2 genotype also differentially predicted the correlation between striatal dopamine D2 signaling (as identified with factor analysis of the two radiotracers and activity of the prefrontal cortex during working memory as measured with BOLD fMRI, which was positive in GG subjects and negative in GT.Our results demonstrate that this functional SNP within DRD2 predicts striatal binding of the two radiotracers to dopamine transporters and D2 receptors as well as the correlation between striatal D2 signaling with prefrontal cortex activity during performance of a working memory task. These data are consistent with the possibility that the balance of excitatory/inhibitory modulation of striatal neurons may also affect striatal outputs in relationship with prefrontal activity during working memory performance within the cortico-striatal-thalamic-cortical pathway.

  13. Reward positivity: Reward prediction error or salience prediction error?

    Science.gov (United States)

    Heydari, Sepideh; Holroyd, Clay B

    2016-08-01

    The reward positivity is a component of the human ERP elicited by feedback stimuli in trial-and-error learning and guessing tasks. A prominent theory holds that the reward positivity reflects a reward prediction error signal that is sensitive to outcome valence, being larger for unexpected positive events relative to unexpected negative events (Holroyd & Coles, 2002). Although the theory has found substantial empirical support, most of these studies have utilized either monetary or performance feedback to test the hypothesis. However, in apparent contradiction to the theory, a recent study found that unexpected physical punishments also elicit the reward positivity (Talmi, Atkinson, & El-Deredy, 2013). The authors of this report argued that the reward positivity reflects a salience prediction error rather than a reward prediction error. To investigate this finding further, in the present study participants navigated a virtual T maze and received feedback on each trial under two conditions. In a reward condition, the feedback indicated that they would either receive a monetary reward or not and in a punishment condition the feedback indicated that they would receive a small shock or not. We found that the feedback stimuli elicited a typical reward positivity in the reward condition and an apparently delayed reward positivity in the punishment condition. Importantly, this signal was more positive to the stimuli that predicted the omission of a possible punishment relative to stimuli that predicted a forthcoming punishment, which is inconsistent with the salience hypothesis. © 2016 Society for Psychophysiological Research.

  14. D2 receptor genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans.

    Science.gov (United States)

    Fazio, Leonardo; Blasi, Giuseppe; Taurisano, Paolo; Papazacharias, Apostolos; Romano, Raffaella; Gelao, Barbara; Ursini, Gianluca; Quarto, Tiziana; Lo Bianco, Luciana; Di Giorgio, Annabella; Mancini, Marina; Popolizio, Teresa; Rubini, Giuseppe; Bertolino, Alessandro

    2011-02-14

    Pre-synaptic D2 receptors regulate striatal dopamine release and DAT activity, key factors for modulation of motor pathways. A functional SNP of DRD2 (rs1076560 G>T) is associated with alternative splicing such that the relative expression of D2S (mainly pre-synaptic) vs. D2L (mainly post-synaptic) receptor isoforms is decreased in subjects with the T allele with a putative increase of striatal dopamine levels. To evaluate how DRD2 genotype and striatal dopamine signaling predict motor cortical activity and behavior in humans, we have investigated the association of rs1076560 with BOLD fMRI activity during a motor task. To further evaluate the relationship of this circuitry with dopamine signaling, we also explored the correlation between genotype based differences in motor brain activity and pre-synaptic striatal DAT binding measured with [(123)I] FP-CIT SPECT. Fifty healthy subjects, genotyped for DRD2 rs1076560 were studied with BOLD-fMRI at 3T while performing a visually paced motor task with their right hand; eleven of these subjects also underwent [(123)I]FP-CIT SPECT. SPM5 random-effects models were used for statistical analyses. Subjects carrying the T allele had greater BOLD responses in left basal ganglia, thalamus, supplementary motor area, and primary motor cortex, whose activity was also negatively correlated with reaction time at the task. Moreover, left striatal DAT binding and activity of left supplementary motor area were negatively correlated. The present results suggest that DRD2 genetic variation was associated with focusing of responses in the whole motor network, in which activity of predictable nodes was correlated with reaction time and with striatal pre-synaptic dopamine signaling. Our results in humans may help shed light on genetic risk for neurobiological mechanisms involved in the pathophysiology of disorders with dysregulation of striatal dopamine like Parkinson's disease. Copyright © 2010 Elsevier Inc. All rights reserved.

  15. Working Memory Load Strengthens Reward Prediction Errors.

    Science.gov (United States)

    Collins, Anne G E; Ciullo, Brittany; Frank, Michael J; Badre, David

    2017-04-19

    Reinforcement learning (RL) in simple instrumental tasks is usually modeled as a monolithic process in which reward prediction errors (RPEs) are used to update expected values of choice options. This modeling ignores the different contributions of different memory and decision-making systems thought to contribute even to simple learning. In an fMRI experiment, we investigated how working memory (WM) and incremental RL processes interact to guide human learning. WM load was manipulated by varying the number of stimuli to be learned across blocks. Behavioral results and computational modeling confirmed that learning was best explained as a mixture of two mechanisms: a fast, capacity-limited, and delay-sensitive WM process together with slower RL. Model-based analysis of fMRI data showed that striatum and lateral prefrontal cortex were sensitive to RPE, as shown previously, but, critically, these signals were reduced when the learning problem was within capacity of WM. The degree of this neural interaction related to individual differences in the use of WM to guide behavioral learning. These results indicate that the two systems do not process information independently, but rather interact during learning. SIGNIFICANCE STATEMENT Reinforcement learning (RL) theory has been remarkably productive at improving our understanding of instrumental learning as well as dopaminergic and striatal network function across many mammalian species. However, this neural network is only one contributor to human learning and other mechanisms such as prefrontal cortex working memory also play a key role. Our results also show that these other players interact with the dopaminergic RL system, interfering with its key computation of reward prediction errors. Copyright © 2017 the authors 0270-6474/17/374332-11$15.00/0.

  16. Striatal μ-opioid receptor availability predicts cold pressor pain threshold in healthy human subjects

    DEFF Research Database (Denmark)

    Hagelberg, Nora; Aalto, Sargo; Tuominen, Lauri

    2012-01-01

    the potential associations between μ-opioid receptor BP(ND) and psychophysical measures. The results show that striatal μ-opioid receptor BP(ND) predicts cold pressor pain threshold, but not cold pressor pain tolerance or tactile sensitivity. This finding suggests that striatal μ-opioid receptor density......Previous PET studies in healthy humans have shown that brain μ-opioid receptor activation during experimental pain is associated with reductions in the sensory and affective ratings of the individual pain experience. The aim of this study was to find out whether brain μ-opioid receptor binding...... at the resting state, in absence of painful stimulation, can be a long-term predictor of experimental pain sensitivity. We measured μ-opioid receptor binding potential (BP(ND)) with μ-opioid receptor selective radiotracer [(11)C]carfentanil and positron emission tomography (PET) in 12 healthy male subjects...

  17. Altered Functional Connectivity of Fronto-Cingulo-Striatal Circuits during Error Monitoring in Adolescents with a History of Childhood Abuse

    Directory of Open Access Journals (Sweden)

    Heledd Hart

    2018-01-01

    Full Text Available Childhood maltreatment is associated with error hypersensitivity. We examined the effect of childhood abuse and abuse-by-gene (5-HTTLPR, MAOA interaction on functional brain connectivity during error processing in medication/drug-free adolescents. Functional connectivity was compared, using generalized psychophysiological interaction (gPPI analysis of functional magnetic resonance imaging (fMRI data, between 22 age- and gender-matched medication-naïve and substance abuse-free adolescents exposed to severe childhood abuse and 27 healthy controls, while they performed an individually adjusted tracking stop-signal task, designed to elicit 50% inhibition failures. During inhibition failures, abused participants relative to healthy controls exhibited reduced connectivity between right and left putamen, bilateral caudate and anterior cingulate cortex (ACC, and between right supplementary motor area (SMA and right inferior and dorsolateral prefrontal cortex. Abuse-related connectivity abnormalities were associated with longer abuse duration. No group differences in connectivity were observed for successful inhibition. The findings suggest that childhood abuse is associated with decreased functional connectivity in fronto-cingulo-striatal networks during error processing. Furthermore that the severity of connectivity abnormalities increases with abuse duration. Reduced connectivity of error detection networks in maltreated individuals may be linked to constant monitoring of errors in order to avoid mistakes which, in abusive contexts, are often associated with harsh punishment.

  18. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which is a r...

  19. Blunted striatal response to monetary reward anticipation during smoking abstinence predicts lapse during a contingency-managed quit attempt.

    Science.gov (United States)

    Sweitzer, Maggie M; Geier, Charles F; Denlinger, Rachel; Forbes, Erika E; Raiff, Bethany R; Dallery, Jesse; McClernon, F J; Donny, Eric C

    2016-03-01

    Tobacco smoking is associated with dysregulated reward processing within the striatum, characterized by hypersensitivity to smoking rewards and hyposensitivity to non-smoking rewards. This bias toward smoking reward at the expense of alternative rewards is further exacerbated by deprivation from smoking, which may contribute to difficulty maintaining abstinence during a quit attempt. We examined whether abstinence-induced changes in striatal processing of rewards predicted lapse likelihood during a quit attempt supported by contingency management (CM), in which abstinence from smoking was reinforced with money. Thirty-six non-treatment-seeking smokers participated in two functional MRI (fMRI) sessions, one following 24-h abstinence and one following smoking as usual. During each scan, participants completed a rewarded guessing task designed to elicit striatal activation in which they could earn smoking and monetary rewards delivered after the scan. Participants then engaged in a 3-week CM-supported quit attempt. As previously reported, 24-h abstinence was associated with increased striatal activation in anticipation of smoking reward and decreased activation in anticipation of monetary reward. Individuals exhibiting greater decrements in right striatal activation to monetary reward during abstinence (controlling for activation during non-abstinence) were more likely to lapse during CM (p reward. These results are consistent with a growing number of studies indicating the specific importance of disrupted striatal processing of non-drug reward in nicotine dependence and highlight the importance of individual differences in abstinence-induced deficits in striatal function for smoking cessation.

  20. Interaction between striatal volume and DAT1 polymorphism predicts working memory development during adolescence

    Directory of Open Access Journals (Sweden)

    F. Nemmi

    2018-04-01

    Full Text Available There is considerable inter-individual variability in the rate at which working memory (WM develops during childhood and adolescence, but the neural and genetic basis for these differences are poorly understood. Dopamine-related genes, striatal activation and morphology have been associated with increased WM capacity after training. Here we tested the hypothesis that these factors would also explain some of the inter-individual differences in the rate of WM development.We measured WM performance in 487 healthy subjects twice: at age 14 and 19. At age 14 subjects underwent a structural MRI scan, and genotyping of five single nucleotide polymorphisms (SNPs in or close to the dopamine genes DRD2, DAT-1 and COMT, which have previously been associated with gains in WM after WM training. We then analyzed which biological factors predicted the rate of increase in WM between ages 14 and 19.We found a significant interaction between putamen size and DAT1/SLC6A3 rs40184 polymorphism, such that TC heterozygotes with a larger putamen at age 14 showed greater WM improvement at age 19.The effect of the DAT1 polymorphism on WM development was exerted in interaction with striatal morphology. These results suggest that development of WM partially share neuro-physiological mechanism with training-induced plasticity. Keywords: Working memory, Development, Dopamine, Striatum, DAT-1, rs40184

  1. Notes on human error analysis and prediction

    International Nuclear Information System (INIS)

    Rasmussen, J.

    1978-11-01

    The notes comprise an introductory discussion of the role of human error analysis and prediction in industrial risk analysis. Following this introduction, different classes of human errors and role in industrial systems are mentioned. Problems related to the prediction of human behaviour in reliability and safety analysis are formulated and ''criteria for analyzability'' which must be met by industrial systems so that a systematic analysis can be performed are suggested. The appendices contain illustrative case stories and a review of human error reports for the task of equipment calibration and testing as found in the US Licensee Event Reports. (author)

  2. Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time.

    Science.gov (United States)

    Limongi, Roberto; Silva, Angélica M

    2016-11-01

    The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production - where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

  3. Prediction-error of Prediction Error (PPE)-based Reversible Data Hiding

    OpenAIRE

    Wu, Han-Zhou; Wang, Hong-Xia; Shi, Yun-Qing

    2016-01-01

    This paper presents a novel reversible data hiding (RDH) algorithm for gray-scaled images, in which the prediction-error of prediction error (PPE) of a pixel is used to carry the secret data. In the proposed method, the pixels to be embedded are firstly predicted with their neighboring pixels to obtain the corresponding prediction errors (PEs). Then, by exploiting the PEs of the neighboring pixels, the prediction of the PEs of the pixels can be determined. And, a sorting technique based on th...

  4. Signed reward prediction errors drive declarative learning

    NARCIS (Netherlands)

    De Loof, E.; Ergo, K.; Naert, L.; Janssens, C.; Talsma, D.; van Opstal, F.; Verguts, T.

    2018-01-01

    Reward prediction errors (RPEs) are thought to drive learning. This has been established in procedural learning (e.g., classical and operant conditioning). However, empirical evidence on whether RPEs drive declarative learning–a quintessentially human form of learning–remains surprisingly absent. We

  5. Altered neural reward and loss processing and prediction error signalling in depression

    Science.gov (United States)

    Ubl, Bettina; Kuehner, Christine; Kirsch, Peter; Ruttorf, Michaela

    2015-01-01

    Dysfunctional processing of reward and punishment may play an important role in depression. However, functional magnetic resonance imaging (fMRI) studies have shown heterogeneous results for reward processing in fronto-striatal regions. We examined neural responsivity associated with the processing of reward and loss during anticipation and receipt of incentives and related prediction error (PE) signalling in depressed individuals. Thirty medication-free depressed persons and 28 healthy controls performed an fMRI reward paradigm. Regions of interest analyses focused on neural responses during anticipation and receipt of gains and losses and related PE-signals. Additionally, we assessed the relationship between neural responsivity during gain/loss processing and hedonic capacity. When compared with healthy controls, depressed individuals showed reduced fronto-striatal activity during anticipation of gains and losses. The groups did not significantly differ in response to reward and loss outcomes. In depressed individuals, activity increases in the orbitofrontal cortex and nucleus accumbens during reward anticipation were associated with hedonic capacity. Depressed individuals showed an absence of reward-related PEs but encoded loss-related PEs in the ventral striatum. Depression seems to be linked to blunted responsivity in fronto-striatal regions associated with limited motivational responses for rewards and losses. Alterations in PE encoding might mirror blunted reward- and enhanced loss-related associative learning in depression. PMID:25567763

  6. Signed reward prediction errors drive declarative learning.

    Directory of Open Access Journals (Sweden)

    Esther De Loof

    Full Text Available Reward prediction errors (RPEs are thought to drive learning. This has been established in procedural learning (e.g., classical and operant conditioning. However, empirical evidence on whether RPEs drive declarative learning-a quintessentially human form of learning-remains surprisingly absent. We therefore coupled RPEs to the acquisition of Dutch-Swahili word pairs in a declarative learning paradigm. Signed RPEs (SRPEs; "better-than-expected" signals during declarative learning improved recognition in a follow-up test, with increasingly positive RPEs leading to better recognition. In addition, classic declarative memory mechanisms such as time-on-task failed to explain recognition performance. The beneficial effect of SRPEs on recognition was subsequently affirmed in a replication study with visual stimuli.

  7. Signed reward prediction errors drive declarative learning.

    Science.gov (United States)

    De Loof, Esther; Ergo, Kate; Naert, Lien; Janssens, Clio; Talsma, Durk; Van Opstal, Filip; Verguts, Tom

    2018-01-01

    Reward prediction errors (RPEs) are thought to drive learning. This has been established in procedural learning (e.g., classical and operant conditioning). However, empirical evidence on whether RPEs drive declarative learning-a quintessentially human form of learning-remains surprisingly absent. We therefore coupled RPEs to the acquisition of Dutch-Swahili word pairs in a declarative learning paradigm. Signed RPEs (SRPEs; "better-than-expected" signals) during declarative learning improved recognition in a follow-up test, with increasingly positive RPEs leading to better recognition. In addition, classic declarative memory mechanisms such as time-on-task failed to explain recognition performance. The beneficial effect of SRPEs on recognition was subsequently affirmed in a replication study with visual stimuli.

  8. Mindfulness meditation modulates reward prediction errors in the striatum in a passive conditioning task

    Directory of Open Access Journals (Sweden)

    Ulrich eKirk

    2015-02-01

    Full Text Available Reinforcement learning models have demonstrated that phasic activity of dopamine neurons during reward expectation encodes information about the predictability of rewards and cues that predict reward. Evidence indicates that mindfulness-based approaches reduce reward anticipation signal in the striatum to negative and positive incentives suggesting the hypothesis that such training influence basic reward processing. Using a passive conditioning task and fMRI in a group of experienced mindfulness meditators and age-matched controls, we tested the hypothesis that mindfulness meditation influence reward and reward prediction error signals. We found diminished positive and negative prediction error-related blood-oxygen level-dependent (BOLD responses in the putamen in meditators compared with controls. In the meditators, this decrease in striatal BOLD responses to reward prediction was paralleled by increased activity in posterior insula, a primary interoceptive region. Critically, responses in the putamen during early trials of the conditioning procedure (run 1 were elevated in both meditators and controls. These results provide evidence that experienced mindfulness meditators show attenuated reward prediction signals to valenced stimuli, which may be related to interoceptive processes encoded in the posterior insula.

  9. A negative relationship between ventral striatal loss anticipation response and impulsivity in borderline personality disorder

    OpenAIRE

    Herbort, Maike C.; Soch, Joram; W?stenberg, Torsten; Krauel, Kerstin; Pujara, Maia; Koenigs, Michael; Gallinat, J?rgen; Walter, Henrik; Roepke, Stefan; Schott, Bj?rn H.

    2016-01-01

    Patients with borderline personality disorder (BPD) frequently exhibit impulsive behavior, and self-reported impulsivity is typically higher in BPD patients when compared to healthy controls. Previous functional neuroimaging studies have suggested a link between impulsivity, the ventral striatal response to reward anticipation, and prediction errors. Here we investigated the striatal neural response to monetary gain and loss anticipation and their relationship with impulsivity in 21 female BP...

  10. SHERPA: A systematic human error reduction and prediction approach

    International Nuclear Information System (INIS)

    Embrey, D.E.

    1986-01-01

    This paper describes a Systematic Human Error Reduction and Prediction Approach (SHERPA) which is intended to provide guidelines for human error reduction and quantification in a wide range of human-machine systems. The approach utilizes as its basic current cognitive models of human performance. The first module in SHERPA performs task and human error analyses, which identify likely error modes, together with guidelines for the reduction of these errors by training, procedures and equipment redesign. The second module uses a SARAH approach to quantify the probability of occurrence of the errors identified earlier, and provides cost benefit analyses to assist in choosing the appropriate error reduction approaches in the third module

  11. Learning from sensory and reward prediction errors during motor adaptation.

    Science.gov (United States)

    Izawa, Jun; Shadmehr, Reza

    2011-03-01

    Voluntary motor commands produce two kinds of consequences. Initially, a sensory consequence is observed in terms of activity in our primary sensory organs (e.g., vision, proprioception). Subsequently, the brain evaluates the sensory feedback and produces a subjective measure of utility or usefulness of the motor commands (e.g., reward). As a result, comparisons between predicted and observed consequences of motor commands produce two forms of prediction error. How do these errors contribute to changes in motor commands? Here, we considered a reach adaptation protocol and found that when high quality sensory feedback was available, adaptation of motor commands was driven almost exclusively by sensory prediction errors. This form of learning had a distinct signature: as motor commands adapted, the subjects altered their predictions regarding sensory consequences of motor commands, and generalized this learning broadly to neighboring motor commands. In contrast, as the quality of the sensory feedback degraded, adaptation of motor commands became more dependent on reward prediction errors. Reward prediction errors produced comparable changes in the motor commands, but produced no change in the predicted sensory consequences of motor commands, and generalized only locally. Because we found that there was a within subject correlation between generalization patterns and sensory remapping, it is plausible that during adaptation an individual's relative reliance on sensory vs. reward prediction errors could be inferred. We suggest that while motor commands change because of sensory and reward prediction errors, only sensory prediction errors produce a change in the neural system that predicts sensory consequences of motor commands.

  12. Error-related anterior cingulate cortex activity and the prediction of conscious error awareness

    Directory of Open Access Journals (Sweden)

    Catherine eOrr

    2012-06-01

    Full Text Available Research examining the neural mechanisms associated with error awareness has consistently identified dorsal anterior cingulate activity (ACC as necessary but not predictive of conscious error detection. Two recent studies (Steinhauser and Yeung, 2010; Wessel et al. 2011 have found a contrary pattern of greater dorsal ACC activity (in the form of the error-related negativity during detected errors, but suggested that the greater activity may instead reflect task influences (e.g., response conflict, error probability and or individual variability (e.g., statistical power. We re-analyzed fMRI BOLD data from 56 healthy participants who had previously been administered the Error Awareness Task, a motor Go/No-go response inhibition task in which subjects make errors of commission of which they are aware (Aware errors, or unaware (Unaware errors. Consistent with previous data, the activity in a number of cortical regions was predictive of error awareness, including bilateral inferior parietal and insula cortices, however in contrast to previous studies, including our own smaller sample studies using the same task, error-related dorsal ACC activity was significantly greater during aware errors when compared to unaware errors. While the significantly faster RT for aware errors (compared to unaware was consistent with the hypothesis of higher response conflict increasing ACC activity, we could find no relationship between dorsal ACC activity and the error RT difference. The data suggests that individual variability in error awareness is associated with error-related dorsal ACC activity, and therefore this region may be important to conscious error detection, but it remains unclear what task and individual factors influence error awareness.

  13. Critical evidence for the prediction error theory in associative learning.

    Science.gov (United States)

    Terao, Kanta; Matsumoto, Yukihisa; Mizunami, Makoto

    2015-03-10

    In associative learning in mammals, it is widely accepted that the discrepancy, or error, between actual and predicted reward determines whether learning occurs. Complete evidence for the prediction error theory, however, has not been obtained in any learning systems: Prediction error theory stems from the finding of a blocking phenomenon, but blocking can also be accounted for by other theories, such as the attentional theory. We demonstrated blocking in classical conditioning in crickets and obtained evidence to reject the attentional theory. To obtain further evidence supporting the prediction error theory and rejecting alternative theories, we constructed a neural model to match the prediction error theory, by modifying our previous model of learning in crickets, and we tested a prediction from the model: the model predicts that pharmacological intervention of octopaminergic transmission during appetitive conditioning impairs learning but not formation of reward prediction itself, and it thus predicts no learning in subsequent training. We observed such an "auto-blocking", which could be accounted for by the prediction error theory but not by other competitive theories to account for blocking. This study unambiguously demonstrates validity of the prediction error theory in associative learning.

  14. Scaling prediction errors to reward variability benefits error-driven learning in humans.

    Science.gov (United States)

    Diederen, Kelly M J; Schultz, Wolfram

    2015-09-01

    Effective error-driven learning requires individuals to adapt learning to environmental reward variability. The adaptive mechanism may involve decays in learning rate across subsequent trials, as shown previously, and rescaling of reward prediction errors. The present study investigated the influence of prediction error scaling and, in particular, the consequences for learning performance. Participants explicitly predicted reward magnitudes that were drawn from different probability distributions with specific standard deviations. By fitting the data with reinforcement learning models, we found scaling of prediction errors, in addition to the learning rate decay shown previously. Importantly, the prediction error scaling was closely related to learning performance, defined as accuracy in predicting the mean of reward distributions, across individual participants. In addition, participants who scaled prediction errors relative to standard deviation also presented with more similar performance for different standard deviations, indicating that increases in standard deviation did not substantially decrease "adapters'" accuracy in predicting the means of reward distributions. However, exaggerated scaling beyond the standard deviation resulted in impaired performance. Thus efficient adaptation makes learning more robust to changing variability. Copyright © 2015 the American Physiological Society.

  15. Predicting Error Bars for QSAR Models

    International Nuclear Information System (INIS)

    Schroeter, Timon; Schwaighofer, Anton; Mika, Sebastian; Ter Laak, Antonius; Suelzle, Detlev; Ganzer, Ursula; Heinrich, Nikolaus; Mueller, Klaus-Robert

    2007-01-01

    Unfavorable physicochemical properties often cause drug failures. It is therefore important to take lipophilicity and water solubility into account early on in lead discovery. This study presents log D 7 models built using Gaussian Process regression, Support Vector Machines, decision trees and ridge regression algorithms based on 14556 drug discovery compounds of Bayer Schering Pharma. A blind test was conducted using 7013 new measurements from the last months. We also present independent evaluations using public data. Apart from accuracy, we discuss the quality of error bars that can be computed by Gaussian Process models, and ensemble and distance based techniques for the other modelling approaches

  16. Human medial frontal cortex activity predicts learning from errors.

    Science.gov (United States)

    Hester, Robert; Barre, Natalie; Murphy, Kevin; Silk, Tim J; Mattingley, Jason B

    2008-08-01

    Learning from errors is a critical feature of human cognition. It underlies our ability to adapt to changing environmental demands and to tune behavior for optimal performance. The posterior medial frontal cortex (pMFC) has been implicated in the evaluation of errors to control behavior, although it has not previously been shown that activity in this region predicts learning from errors. Using functional magnetic resonance imaging, we examined activity in the pMFC during an associative learning task in which participants had to recall the spatial locations of 2-digit targets and were provided with immediate feedback regarding accuracy. Activity within the pMFC was significantly greater for errors that were subsequently corrected than for errors that were repeated. Moreover, pMFC activity during recall errors predicted future responses (correct vs. incorrect), despite a sizeable interval (on average 70 s) between an error and the next presentation of the same recall probe. Activity within the hippocampus also predicted future performance and correlated with error-feedback-related pMFC activity. A relationship between performance expectations and pMFC activity, in the absence of differing reinforcement value for errors, is consistent with the idea that error-related pMFC activity reflects the extent to which an outcome is "worse than expected."

  17. A causal link between prediction errors, dopamine neurons and learning.

    Science.gov (United States)

    Steinberg, Elizabeth E; Keiflin, Ronald; Boivin, Josiah R; Witten, Ilana B; Deisseroth, Karl; Janak, Patricia H

    2013-07-01

    Situations in which rewards are unexpectedly obtained or withheld represent opportunities for new learning. Often, this learning includes identifying cues that predict reward availability. Unexpected rewards strongly activate midbrain dopamine neurons. This phasic signal is proposed to support learning about antecedent cues by signaling discrepancies between actual and expected outcomes, termed a reward prediction error. However, it is unknown whether dopamine neuron prediction error signaling and cue-reward learning are causally linked. To test this hypothesis, we manipulated dopamine neuron activity in rats in two behavioral procedures, associative blocking and extinction, that illustrate the essential function of prediction errors in learning. We observed that optogenetic activation of dopamine neurons concurrent with reward delivery, mimicking a prediction error, was sufficient to cause long-lasting increases in cue-elicited reward-seeking behavior. Our findings establish a causal role for temporally precise dopamine neuron signaling in cue-reward learning, bridging a critical gap between experimental evidence and influential theoretical frameworks.

  18. Prediction-error in the context of real social relationships modulates reward system activity

    Directory of Open Access Journals (Sweden)

    Joshua ePoore

    2012-08-01

    Full Text Available The human reward system is sensitive to both social (e.g., validation and non-social rewards (e.g., money and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to a potent social reward—social validation—and this activity’s relation to both attachment security and trust in the context of real romantic relationships. During the experiment, participants’ expectations for their romantic partners’ positive regard of them were confirmed (validated or violated, in either positive or negative directions. Primary analyses were conducted using predefined regions of interest, the locations of which were taken from previously published research. Results indicate that activity for mid-brain and striatal reward system regions of interest was modulated by social reward expectation violation in ways consistent with prior research on reward prediction-error. Additionally, activity in the striatum during viewing of disconfirmatory information was associated with both increases in post-scan reports of attachment anxiety and decreases in post-scan trust, a finding that follows directly from representational models of attachment and trust.

  19. Prediction-error in the context of real social relationships modulates reward system activity.

    Science.gov (United States)

    Poore, Joshua C; Pfeifer, Jennifer H; Berkman, Elliot T; Inagaki, Tristen K; Welborn, Benjamin L; Lieberman, Matthew D

    2012-01-01

    The human reward system is sensitive to both social (e.g., validation) and non-social rewards (e.g., money) and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to a potent social reward-social validation-and this activity's relation to both attachment security and trust in the context of real romantic relationships. During the experiment, participants' expectations for their romantic partners' positive regard of them were confirmed (validated) or violated, in either positive or negative directions. Primary analyses were conducted using predefined regions of interest, the locations of which were taken from previously published research. Results indicate that activity for mid-brain and striatal reward system regions of interest was modulated by social reward expectation violation in ways consistent with prior research on reward prediction-error. Additionally, activity in the striatum during viewing of disconfirmatory information was associated with both increases in post-scan reports of attachment anxiety and decreases in post-scan trust, a finding that follows directly from representational models of attachment and trust.

  20. Prediction Error During Functional and Non-Functional Action Sequences

    DEFF Research Database (Denmark)

    Nielbo, Kristoffer Laigaard; Sørensen, Jesper

    2013-01-01

    recurrent networks were made and the results are presented in this article. The simulations show that non-functional action sequences do indeed increase prediction error, but that context representations, such as abstract goal information, can modulate the error signal considerably. It is also shown...... that the networks are sensitive to boundaries between sequences in both functional and non-functional actions....

  1. Mean Bias in Seasonal Forecast Model and ENSO Prediction Error.

    Science.gov (United States)

    Kim, Seon Tae; Jeong, Hye-In; Jin, Fei-Fei

    2017-07-20

    This study uses retrospective forecasts made using an APEC Climate Center seasonal forecast model to investigate the cause of errors in predicting the amplitude of El Niño Southern Oscillation (ENSO)-driven sea surface temperature variability. When utilizing Bjerknes coupled stability (BJ) index analysis, enhanced errors in ENSO amplitude with forecast lead times are found to be well represented by those in the growth rate estimated by the BJ index. ENSO amplitude forecast errors are most strongly associated with the errors in both the thermocline slope response and surface wind response to forcing over the tropical Pacific, leading to errors in thermocline feedback. This study concludes that upper ocean temperature bias in the equatorial Pacific, which becomes more intense with increasing lead times, is a possible cause of forecast errors in the thermocline feedback and thus in ENSO amplitude.

  2. Prediction and error of baldcypress stem volume from stump diameter

    Science.gov (United States)

    Bernard R. Parresol

    1998-01-01

    The need to estimate the volume of removals occurs for many reasons, such as in trespass cases, severance tax reports, and post-harvest assessments. A logarithmic model is presented for prediction of baldcypress total stem cubic foot volume using stump diameter as the independent variable. Because the error of prediction is as important as the volume estimate, the...

  3. The Pupillary Orienting Response Predicts Adaptive Behavioral Adjustment after Errors.

    Directory of Open Access Journals (Sweden)

    Peter R Murphy

    Full Text Available Reaction time (RT is commonly observed to slow down after an error. This post-error slowing (PES has been thought to arise from the strategic adoption of a more cautious response mode following deployment of cognitive control. Recently, an alternative account has suggested that PES results from interference due to an error-evoked orienting response. We investigated whether error-related orienting may in fact be a pre-cursor to adaptive post-error behavioral adjustment when the orienting response resolves before subsequent trial onset. We measured pupil dilation, a prototypical measure of autonomic orienting, during performance of a choice RT task with long inter-stimulus intervals, and found that the trial-by-trial magnitude of the error-evoked pupil response positively predicted both PES magnitude and the likelihood that the following response would be correct. These combined findings suggest that the magnitude of the error-related orienting response predicts an adaptive change of response strategy following errors, and thereby promote a reconciliation of the orienting and adaptive control accounts of PES.

  4. Prediction error, ketamine and psychosis: An updated model.

    Science.gov (United States)

    Corlett, Philip R; Honey, Garry D; Fletcher, Paul C

    2016-11-01

    In 2007, we proposed an explanation of delusion formation as aberrant prediction error-driven associative learning. Further, we argued that the NMDA receptor antagonist ketamine provided a good model for this process. Subsequently, we validated the model in patients with psychosis, relating aberrant prediction error signals to delusion severity. During the ensuing period, we have developed these ideas, drawing on the simple principle that brains build a model of the world and refine it by minimising prediction errors, as well as using it to guide perceptual inferences. While previously we focused on the prediction error signal per se, an updated view takes into account its precision, as well as the precision of prior expectations. With this expanded perspective, we see several possible routes to psychotic symptoms - which may explain the heterogeneity of psychotic illness, as well as the fact that other drugs, with different pharmacological actions, can produce psychotomimetic effects. In this article, we review the basic principles of this model and highlight specific ways in which prediction errors can be perturbed, in particular considering the reliability and uncertainty of predictions. The expanded model explains hallucinations as perturbations of the uncertainty mediated balance between expectation and prediction error. Here, expectations dominate and create perceptions by suppressing or ignoring actual inputs. Negative symptoms may arise due to poor reliability of predictions in service of action. By mapping from biology to belief and perception, the account proffers new explanations of psychosis. However, challenges remain. We attempt to address some of these concerns and suggest future directions, incorporating other symptoms into the model, building towards better understanding of psychosis. © The Author(s) 2016.

  5. Threat and error management for anesthesiologists: a predictive risk taxonomy

    Science.gov (United States)

    Ruskin, Keith J.; Stiegler, Marjorie P.; Park, Kellie; Guffey, Patrick; Kurup, Viji; Chidester, Thomas

    2015-01-01

    Purpose of review Patient care in the operating room is a dynamic interaction that requires cooperation among team members and reliance upon sophisticated technology. Most human factors research in medicine has been focused on analyzing errors and implementing system-wide changes to prevent them from recurring. We describe a set of techniques that has been used successfully by the aviation industry to analyze errors and adverse events and explain how these techniques can be applied to patient care. Recent findings Threat and error management (TEM) describes adverse events in terms of risks or challenges that are present in an operational environment (threats) and the actions of specific personnel that potentiate or exacerbate those threats (errors). TEM is a technique widely used in aviation, and can be adapted for the use in a medical setting to predict high-risk situations and prevent errors in the perioperative period. A threat taxonomy is a novel way of classifying and predicting the hazards that can occur in the operating room. TEM can be used to identify error-producing situations, analyze adverse events, and design training scenarios. Summary TEM offers a multifaceted strategy for identifying hazards, reducing errors, and training physicians. A threat taxonomy may improve analysis of critical events with subsequent development of specific interventions, and may also serve as a framework for training programs in risk mitigation. PMID:24113268

  6. Error analysis in predictive modelling demonstrated on mould data.

    Science.gov (United States)

    Baranyi, József; Csernus, Olívia; Beczner, Judit

    2014-01-17

    The purpose of this paper was to develop a predictive model for the effect of temperature and water activity on the growth rate of Aspergillus niger and to determine the sources of the error when the model is used for prediction. Parallel mould growth curves, derived from the same spore batch, were generated and fitted to determine their growth rate. The variances of replicate ln(growth-rate) estimates were used to quantify the experimental variability, inherent to the method of determining the growth rate. The environmental variability was quantified by the variance of the respective means of replicates. The idea is analogous to the "within group" and "between groups" variability concepts of ANOVA procedures. A (secondary) model, with temperature and water activity as explanatory variables, was fitted to the natural logarithm of the growth rates determined by the primary model. The model error and the experimental and environmental errors were ranked according to their contribution to the total error of prediction. Our method can readily be applied to analysing the error structure of predictive models of bacterial growth models, too. © 2013.

  7. Prospective detection of large prediction errors: a hypothesis testing approach

    International Nuclear Information System (INIS)

    Ruan, Dan

    2010-01-01

    Real-time motion management is important in radiotherapy. In addition to effective monitoring schemes, prediction is required to compensate for system latency, so that treatment can be synchronized with tumor motion. However, it is difficult to predict tumor motion at all times, and it is critical to determine when large prediction errors may occur. Such information can be used to pause the treatment beam or adjust monitoring/prediction schemes. In this study, we propose a hypothesis testing approach for detecting instants corresponding to potentially large prediction errors in real time. We treat the future tumor location as a random variable, and obtain its empirical probability distribution with the kernel density estimation-based method. Under the null hypothesis, the model probability is assumed to be a concentrated Gaussian centered at the prediction output. Under the alternative hypothesis, the model distribution is assumed to be non-informative uniform, which reflects the situation that the future position cannot be inferred reliably. We derive the likelihood ratio test (LRT) for this hypothesis testing problem and show that with the method of moments for estimating the null hypothesis Gaussian parameters, the LRT reduces to a simple test on the empirical variance of the predictive random variable. This conforms to the intuition to expect a (potentially) large prediction error when the estimate is associated with high uncertainty, and to expect an accurate prediction when the uncertainty level is low. We tested the proposed method on patient-derived respiratory traces. The 'ground-truth' prediction error was evaluated by comparing the prediction values with retrospective observations, and the large prediction regions were subsequently delineated by thresholding the prediction errors. The receiver operating characteristic curve was used to describe the performance of the proposed hypothesis testing method. Clinical implication was represented by miss

  8. Interaction between hippocampal and striatal systems predicts subsequent consolidation of motor sequence memory.

    Directory of Open Access Journals (Sweden)

    Geneviève Albouy

    Full Text Available The development of fast and reproducible motor behavior is a crucial human capacity. The aim of the present study was to address the relationship between the implementation of consistent behavior during initial training on a sequential motor task (the Finger Tapping Task and subsequent sleep-dependent motor sequence memory consolidation, using functional magnetic resonance imaging (fMRI and total sleep deprivation protocol. Our behavioral results indicated significant offline gains in performance speed after sleep whereas performance was only stabilized, but not enhanced, after sleep deprivation. At the cerebral level, we previously showed that responses in the caudate nucleus increase, in parallel to a decrease in its functional connectivity with frontal areas, as performance became more consistent. Here, the strength of the competitive interaction, assessed through functional connectivity analyses, between the caudate nucleus and hippocampo-frontal areas during initial training, predicted delayed gains in performance at retest in sleepers but not in sleep-deprived subjects. Moreover, during retest, responses increased in the hippocampus and medial prefrontal cortex in sleepers whereas in sleep-deprived subjects, responses increased in the putamen and cingulate cortex. Our results suggest that the strength of the competitive interplay between the striatum and the hippocampus, participating in the implementation of consistent motor behavior during initial training, conditions subsequent motor sequence memory consolidation. The latter process appears to be supported by a reorganisation of cerebral activity in hippocampo-neocortical networks after sleep.

  9. Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

    Science.gov (United States)

    Holmes, John B; Dodds, Ken G; Lee, Michael A

    2017-03-02

    An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

  10. Prediction-error identification of LPV systems : present and beyond

    NARCIS (Netherlands)

    Toth, R.; Heuberger, P.S.C.; Hof, Van den P.M.J.; Mohammadpour, J.; Scherer, C. W.

    2012-01-01

    The proposed chapter aims at presenting a unified framework of prediction-error based identification of LPV systems using freshly developed theoretical results. Recently, these methods have got a considerable attention as they have certain advantages in terms of computational complexity, optimality

  11. Testing the prediction error difference between two predictors

    NARCIS (Netherlands)

    van de Wiel, M.A.; Berkhof, J.; van Wieringen, W.N.

    2009-01-01

    We develop an inference framework for the difference in errors between 2 prediction procedures. The 2 procedures may differ in any aspect and possibly utilize different sets of covariates. We apply training and testing on the same data set, which is accommodated by sample splitting. For each split,

  12. Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors

    Science.gov (United States)

    Mercer, Joey; Hunt-Espinosa, Sarah; Bienert, Nancy; Laraway, Sean

    2016-01-01

    A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASA's Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlanta's Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the study's trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 30-knot over-predictions and 30-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

  13. How to Avoid Errors in Error Propagation: Prediction Intervals and Confidence Intervals in Forest Biomass

    Science.gov (United States)

    Lilly, P.; Yanai, R. D.; Buckley, H. L.; Case, B. S.; Woollons, R. C.; Holdaway, R. J.; Johnson, J.

    2016-12-01

    Calculations of forest biomass and elemental content require many measurements and models, each contributing uncertainty to the final estimates. While sampling error is commonly reported, based on replicate plots, error due to uncertainty in the regression used to estimate biomass from tree diameter is usually not quantified. Some published estimates of uncertainty due to the regression models have used the uncertainty in the prediction of individuals, ignoring uncertainty in the mean, while others have propagated uncertainty in the mean while ignoring individual variation. Using the simple case of the calcium concentration of sugar maple leaves, we compare the variation among individuals (the standard deviation) to the uncertainty in the mean (the standard error) and illustrate the declining importance in the prediction of individual concentrations as the number of individuals increases. For allometric models, the analogous statistics are the prediction interval (or the residual variation in the model fit) and the confidence interval (describing the uncertainty in the best fit model). The effect of propagating these two sources of error is illustrated using the mass of sugar maple foliage. The uncertainty in individual tree predictions was large for plots with few trees; for plots with 30 trees or more, the uncertainty in individuals was less important than the uncertainty in the mean. Authors of previously published analyses have reanalyzed their data to show the magnitude of these two sources of uncertainty in scales ranging from experimental plots to entire countries. The most correct analysis will take both sources of uncertainty into account, but for practical purposes, country-level reports of uncertainty in carbon stocks, as required by the IPCC, can ignore the uncertainty in individuals. Ignoring the uncertainty in the mean will lead to exaggerated estimates of confidence in estimates of forest biomass and carbon and nutrient contents.

  14. Climbing fibers predict movement kinematics and performance errors.

    Science.gov (United States)

    Streng, Martha L; Popa, Laurentiu S; Ebner, Timothy J

    2017-09-01

    Requisite for understanding cerebellar function is a complete characterization of the signals provided by complex spike (CS) discharge of Purkinje cells, the output neurons of the cerebellar cortex. Numerous studies have provided insights into CS function, with the most predominant view being that they are evoked by error events. However, several reports suggest that CSs encode other aspects of movements and do not always respond to errors or unexpected perturbations. Here, we evaluated CS firing during a pseudo-random manual tracking task in the monkey ( Macaca mulatta ). This task provides extensive coverage of the work space and relative independence of movement parameters, delivering a robust data set to assess the signals that activate climbing fibers. Using reverse correlation, we determined feedforward and feedback CSs firing probability maps with position, velocity, and acceleration, as well as position error, a measure of tracking performance. The direction and magnitude of the CS modulation were quantified using linear regression analysis. The major findings are that CSs significantly encode all three kinematic parameters and position error, with acceleration modulation particularly common. The modulation is not related to "events," either for position error or kinematics. Instead, CSs are spatially tuned and provide a linear representation of each parameter evaluated. The CS modulation is largely predictive. Similar analyses show that the simple spike firing is modulated by the same parameters as the CSs. Therefore, CSs carry a broader array of signals than previously described and argue for climbing fiber input having a prominent role in online motor control. NEW & NOTEWORTHY This article demonstrates that complex spike (CS) discharge of cerebellar Purkinje cells encodes multiple parameters of movement, including motor errors and kinematics. The CS firing is not driven by error or kinematic events; instead it provides a linear representation of each

  15. Error analysis of short term wind power prediction models

    International Nuclear Information System (INIS)

    De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco

    2011-01-01

    The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

  16. Error analysis of short term wind power prediction models

    Energy Technology Data Exchange (ETDEWEB)

    De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco [Dipartimento di Ingegneria dell' Innovazione, Universita del Salento, Via per Monteroni, 73100 Lecce (Italy)

    2011-04-15

    The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

  17. Measurement Error Correction for Predicted Spatiotemporal Air Pollution Exposures.

    Science.gov (United States)

    Keller, Joshua P; Chang, Howard H; Strickland, Matthew J; Szpiro, Adam A

    2017-05-01

    Air pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data. We analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated date of conception during 2002-2005 (n = 403,881). We predicted trimester-specific PM2.5 exposure using a complex spatiotemporal exposure model. To improve spatial compatibility, we restricted to mothers residing in counties with a PM2.5 monitor (n = 180,440). We accounted for additional measurement error via a nonparametric bootstrap. Third trimester PM2.5 exposure was associated with lower birth weight in the uncorrected (-2.4 g per 1 μg/m difference in exposure; 95% confidence interval [CI]: -3.9, -0.8) and bootstrap-corrected (-2.5 g, 95% CI: -4.2, -0.8) analyses. Results for the unrestricted analysis were attenuated (-0.66 g, 95% CI: -1.7, 0.35). This study presents a novel application of measurement error correction for spatiotemporal air pollution exposures. Our results demonstrate the importance of spatial compatibility between monitor and subject locations and provide evidence of the association between air pollution exposure and birth weight.

  18. Uncertainties of predictions from parton distributions 1, experimental errors

    CERN Document Server

    Martin, A D; Stirling, William James; Thorne, R S; CERN. Geneva

    2003-01-01

    We determine the uncertainties on observables arising from the errors on the experimental data that are fitted in the global MRST2001 parton analysis. By diagonalizing the error matrix we produce sets of partons suitable for use within the framework of linear propagation of errors, which is the most convenient method for calculating the uncertainties. Despite the potential limitations of this approach we find that it can be made to work well in practice. This is confirmed by our alternative approach of using the more rigorous Lagrange multiplier method to determine the errors on physical quantities directly. As particular examples we determine the uncertainties on the predictions of the charged-current deep-inelastic structure functions, on the cross-sections for W production and for Higgs boson production via gluon--gluon fusion at the Tevatron and the LHC, on the ratio of W-minus to W-plus production at the LHC and on the moments of the non-singlet quark distributions. We discuss the corresponding uncertain...

  19. Rats classified as low or high cocaine locomotor responders: A unique model involving striatal dopamine transporters that predicts cocaine addiction-like behaviors

    Science.gov (United States)

    Yamamoto, Dorothy J.; Nelson, Anna M.; Mandt, Bruce H.; Larson, Gaynor A.; Rorabaugh, Jacki M.; Ng, Christopher M.C.; Barcomb, Kelsey M.; Richards, Toni L.; Allen, Richard M.; Zahniser, Nancy R.

    2013-01-01

    Individual differences are a hallmark of drug addiction. Here, we describe a rat model based on differential initial responsiveness to low dose cocaine. Despite similar brain cocaine levels, individual outbred Sprague-Dawley rats exhibit markedly different magnitudes of acute cocaine-induced locomotor activity and, thereby, can be classified as low or high cocaine responders (LCRs or HCRs). LCRs and HCRs differ in drug-induced, but not novelty-associated, hyperactivity. LCRs have higher basal numbers of striatal dopamine transporters (DATs) than HCRs and exhibit marginal cocaine inhibition of in vivo DAT activity and cocaine-induced increases in extracellular DA. Importantly, lower initial cocaine response predicts greater locomotor sensitization, conditioned place preference and greater motivation to self-administer cocaine following low dose acquisition. Further, outbred Long-Evans rats classified as LCRs, versus HCRs, are more sensitive to cocaine’s discriminative stimulus effects. Overall, results to date with the LCR/HCR model underscore the contribution of striatal DATs to individual differences in initial cocaine responsiveness and the value of assessing the influence of initial drug response on subsequent expression of addiction-like behaviors. PMID:23850581

  20. Striatal dopamine D2 receptor availability predicts the thalamic and medial prefrontal responses to reward in cocaine abusers three years later

    International Nuclear Information System (INIS)

    Asensio, S.; Goldstein, R.; Romero, M.J.; Romero, F.J.; Wong, C.T.; Alia-Klein, N.; Tomasi, D.; Wang, G.-J.; Telang, F.; Volkow, N.D.; Goldstein, R.Z.

    2010-01-01

    Low levels of dopamine (DA) D2 receptor availability at a resting baseline have been previously reported in drug addicted individuals and have been associated with reduced ventral and dorsal prefrontal metabolism. The reduction in DA D2 receptor availability along with the reduced ventral frontal metabolism is thought to underlie compromised sensitivity to nondrug reward, a core characteristic of drug addiction. We therefore hypothesized that variability in DA D2 receptor availability at baseline will covary with dynamic responses to monetary reward in addicted individuals. Striatal DA D2 receptor availability was measured with ( 11 C)raclopride and positron emission tomography and response to monetary reward was measured (an average of three years later) with functional magnetic resonance imaging in seven cocaine-addicted individuals. Results show that low DA D2 receptor availability in the dorsal striatum was associated with decreased thalamic response to monetary reward; while low availability in ventral striatum was associated with increased medial prefrontal (Brodmann Area 6/8/32) response to monetary reward. These preliminary results, that need to be replicated in larger sample sizes and validated with healthy controls, suggest that resting striatal DA D2 receptor availability predicts variability in functional responses to a nondrug reinforcer (money) in prefrontal cortex, implicated in behavioral monitoring, and in thalamus, implicated in conditioned responses and expectation, in cocaine-addicted individuals.

  1. Striatal dopamine D2 receptor availability predicts the thalamic and medial prefrontal responses to reward in cocaine abusers three years later

    Energy Technology Data Exchange (ETDEWEB)

    Asensio, S.; Goldstein, R.; Asensio, S.; Romero, M.J.; Romero, F.J.; Wong, C.T.; Alia-Klein, N.; Tomasi, D.; Wang, G.-J.; Telang, F..; Volkow, N.D.; Goldstein, R.Z.

    2010-05-01

    Low levels of dopamine (DA) D2 receptor availability at a resting baseline have been previously reported in drug addicted individuals and have been associated with reduced ventral and dorsal prefrontal metabolism. The reduction in DA D2 receptor availability along with the reduced ventral frontal metabolism is thought to underlie compromised sensitivity to nondrug reward, a core characteristic of drug addiction. We therefore hypothesized that variability in DA D2 receptor availability at baseline will covary with dynamic responses to monetary reward in addicted individuals. Striatal DA D2 receptor availability was measured with [{sup 11}C]raclopride and positron emission tomography and response to monetary reward was measured (an average of three years later) with functional magnetic resonance imaging in seven cocaine-addicted individuals. Results show that low DA D2 receptor availability in the dorsal striatum was associated with decreased thalamic response to monetary reward; while low availability in ventral striatum was associated with increased medial prefrontal (Brodmann Area 6/8/32) response to monetary reward. These preliminary results, that need to be replicated in larger sample sizes and validated with healthy controls, suggest that resting striatal DA D2 receptor availability predicts variability in functional responses to a nondrug reinforcer (money) in prefrontal cortex, implicated in behavioral monitoring, and in thalamus, implicated in conditioned responses and expectation, in cocaine-addicted individuals.

  2. Failing to learn from negative prediction errors: Obesity is associated with alterations in a fundamental neural learning mechanism.

    Science.gov (United States)

    Mathar, David; Neumann, Jane; Villringer, Arno; Horstmann, Annette

    2017-10-01

    Prediction errors (PEs) encode the difference between expected and actual action outcomes in the brain via dopaminergic modulation. Integration of these learning signals ensures efficient behavioral adaptation. Obesity has recently been linked to altered dopaminergic fronto-striatal circuits, thus implying impairments in cognitive domains that rely on its integrity. 28 obese and 30 lean human participants performed an implicit stimulus-response learning paradigm inside an fMRI scanner. Computational modeling and psycho-physiological interaction (PPI) analysis was utilized for assessing PE-related learning and associated functional connectivity. We show that human obesity is associated with insufficient incorporation of negative PEs into behavioral adaptation even in a non-food context, suggesting differences in a fundamental neural learning mechanism. Obese subjects were less efficient in using negative PEs to improve implicit learning performance, despite proper coding of PEs in striatum. We further observed lower functional coupling between ventral striatum and supplementary motor area in obese subjects subsequent to negative PEs. Importantly, strength of functional coupling predicted task performance and negative PE utilization. These findings show that obesity is linked to insufficient behavioral adaptation specifically in response to negative PEs, and to associated alterations in function and connectivity within the fronto-striatal system. Recognition of neural differences as a central characteristic of obesity hopefully paves the way to rethink established intervention strategies: Differential behavioral sensitivity to negative and positive PEs should be considered when designing intervention programs. Measures relying on penalization of unwanted behavior may prove less effective in obese subjects than alternative approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. A new framework for cortico-striatal plasticity: behavioural theory meets in vitro data at the reinforcement-action interface.

    Directory of Open Access Journals (Sweden)

    Kevin N Gurney

    2015-01-01

    Full Text Available Operant learning requires that reinforcement signals interact with action representations at a suitable neural interface. Much evidence suggests that this occurs when phasic dopamine, acting as a reinforcement prediction error, gates plasticity at cortico-striatal synapses, and thereby changes the future likelihood of selecting the action(s coded by striatal neurons. But this hypothesis faces serious challenges. First, cortico-striatal plasticity is inexplicably complex, depending on spike timing, dopamine level, and dopamine receptor type. Second, there is a credit assignment problem-action selection signals occur long before the consequent dopamine reinforcement signal. Third, the two types of striatal output neuron have apparently opposite effects on action selection. Whether these factors rule out the interface hypothesis and how they interact to produce reinforcement learning is unknown. We present a computational framework that addresses these challenges. We first predict the expected activity changes over an operant task for both types of action-coding striatal neuron, and show they co-operate to promote action selection in learning and compete to promote action suppression in extinction. Separately, we derive a complete model of dopamine and spike-timing dependent cortico-striatal plasticity from in vitro data. We then show this model produces the predicted activity changes necessary for learning and extinction in an operant task, a remarkable convergence of a bottom-up data-driven plasticity model with the top-down behavioural requirements of learning theory. Moreover, we show the complex dependencies of cortico-striatal plasticity are not only sufficient but necessary for learning and extinction. Validating the model, we show it can account for behavioural data describing extinction, renewal, and reacquisition, and replicate in vitro experimental data on cortico-striatal plasticity. By bridging the levels between the single synapse and

  4. CREME96 and Related Error Rate Prediction Methods

    Science.gov (United States)

    Adams, James H., Jr.

    2012-01-01

    Predicting the rate of occurrence of single event effects (SEEs) in space requires knowledge of the radiation environment and the response of electronic devices to that environment. Several analytical models have been developed over the past 36 years to predict SEE rates. The first error rate calculations were performed by Binder, Smith and Holman. Bradford and Pickel and Blandford, in their CRIER (Cosmic-Ray-Induced-Error-Rate) analysis code introduced the basic Rectangular ParallelePiped (RPP) method for error rate calculations. For the radiation environment at the part, both made use of the Cosmic Ray LET (Linear Energy Transfer) spectra calculated by Heinrich for various absorber Depths. A more detailed model for the space radiation environment within spacecraft was developed by Adams and co-workers. This model, together with a reformulation of the RPP method published by Pickel and Blandford, was used to create the CR ME (Cosmic Ray Effects on Micro-Electronics) code. About the same time Shapiro wrote the CRUP (Cosmic Ray Upset Program) based on the RPP method published by Bradford. It was the first code to specifically take into account charge collection from outside the depletion region due to deformation of the electric field caused by the incident cosmic ray. Other early rate prediction methods and codes include the Single Event Figure of Merit, NOVICE, the Space Radiation code and the effective flux method of Binder which is the basis of the SEFA (Scott Effective Flux Approximation) model. By the early 1990s it was becoming clear that CREME and the other early models needed Revision. This revision, CREME96, was completed and released as a WWW-based tool, one of the first of its kind. The revisions in CREME96 included improved environmental models and improved models for calculating single event effects. The need for a revision of CREME also stimulated the development of the CHIME (CRRES/SPACERAD Heavy Ion Model of the Environment) and MACREE (Modeling and

  5. Error sensitivity analysis in 10-30-day extended range forecasting by using a nonlinear cross-prediction error model

    Science.gov (United States)

    Xia, Zhiye; Xu, Lisheng; Chen, Hongbin; Wang, Yongqian; Liu, Jinbao; Feng, Wenlan

    2017-06-01

    Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous meteorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear crossprediction error (NCPE) model, and their stability in the prediction validity period in 10-30-day extended range forecasting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small (10-6-10-2), minor variation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random error has minimal effect on the prediction. When the ratio is in the range of 10-1-2 (i.e., random error dominates), attention should be paid to the random error instead of only the initial error. When the ratio is around 10-2-10-1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecasting, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depicted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect ( m > 4) is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperature or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.

  6. Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

    Science.gov (United States)

    Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

    2016-01-01

    Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

  7. Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error.

    Science.gov (United States)

    Faber, Felix A; Hutchison, Luke; Huang, Bing; Gilmer, Justin; Schoenholz, Samuel S; Dahl, George E; Vinyals, Oriol; Kearnes, Steven; Riley, Patrick F; von Lilienfeld, O Anatole

    2017-11-14

    evidence that ML model predictions deviate from DFT (B3LYP) less than DFT (B3LYP) deviates from experiment for all properties. Furthermore, out-of-sample prediction errors with respect to hybrid DFT reference are on par with, or close to, chemical accuracy. The results suggest that ML models could be more accurate than hybrid DFT if explicitly electron correlated quantum (or experimental) data were available.

  8. Dopamine reward prediction error responses reflect marginal utility.

    Science.gov (United States)

    Stauffer, William R; Lak, Armin; Schultz, Wolfram

    2014-11-03

    Optimal choices require an accurate neuronal representation of economic value. In economics, utility functions are mathematical representations of subjective value that can be constructed from choices under risk. Utility usually exhibits a nonlinear relationship to physical reward value that corresponds to risk attitudes and reflects the increasing or decreasing marginal utility obtained with each additional unit of reward. Accordingly, neuronal reward responses coding utility should robustly reflect this nonlinearity. In two monkeys, we measured utility as a function of physical reward value from meaningful choices under risk (that adhered to first- and second-order stochastic dominance). The resulting nonlinear utility functions predicted the certainty equivalents for new gambles, indicating that the functions' shapes were meaningful. The monkeys were risk seeking (convex utility function) for low reward and risk avoiding (concave utility function) with higher amounts. Critically, the dopamine prediction error responses at the time of reward itself reflected the nonlinear utility functions measured at the time of choices. In particular, the reward response magnitude depended on the first derivative of the utility function and thus reflected the marginal utility. Furthermore, dopamine responses recorded outside of the task reflected the marginal utility of unpredicted reward. Accordingly, these responses were sufficient to train reinforcement learning models to predict the behaviorally defined expected utility of gambles. These data suggest a neuronal manifestation of marginal utility in dopamine neurons and indicate a common neuronal basis for fundamental explanatory constructs in animal learning theory (prediction error) and economic decision theory (marginal utility). Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

  9. Does the sensorimotor system minimize prediction error or select the most likely prediction during object lifting?

    Science.gov (United States)

    McGregor, Heather R.; Pun, Henry C. H.; Buckingham, Gavin; Gribble, Paul L.

    2016-01-01

    The human sensorimotor system is routinely capable of making accurate predictions about an object's weight, which allows for energetically efficient lifts and prevents objects from being dropped. Often, however, poor predictions arise when the weight of an object can vary and sensory cues about object weight are sparse (e.g., picking up an opaque water bottle). The question arises, what strategies does the sensorimotor system use to make weight predictions when one is dealing with an object whose weight may vary? For example, does the sensorimotor system use a strategy that minimizes prediction error (minimal squared error) or one that selects the weight that is most likely to be correct (maximum a posteriori)? In this study we dissociated the predictions of these two strategies by having participants lift an object whose weight varied according to a skewed probability distribution. We found, using a small range of weight uncertainty, that four indexes of sensorimotor prediction (grip force rate, grip force, load force rate, and load force) were consistent with a feedforward strategy that minimizes the square of prediction errors. These findings match research in the visuomotor system, suggesting parallels in underlying processes. We interpret our findings within a Bayesian framework and discuss the potential benefits of using a minimal squared error strategy. NEW & NOTEWORTHY Using a novel experimental model of object lifting, we tested whether the sensorimotor system models the weight of objects by minimizing lifting errors or by selecting the statistically most likely weight. We found that the sensorimotor system minimizes the square of prediction errors for object lifting. This parallels the results of studies that investigated visually guided reaching, suggesting an overlap in the underlying mechanisms between tasks that involve different sensory systems. PMID:27760821

  10. Error estimation for CFD aeroheating prediction under rarefied flow condition

    Science.gov (United States)

    Jiang, Yazhong; Gao, Zhenxun; Jiang, Chongwen; Lee, Chunhian

    2014-12-01

    Both direct simulation Monte Carlo (DSMC) and Computational Fluid Dynamics (CFD) methods have become widely used for aerodynamic prediction when reentry vehicles experience different flow regimes during flight. The implementation of slip boundary conditions in the traditional CFD method under Navier-Stokes-Fourier (NSF) framework can extend the validity of this approach further into transitional regime, with the benefit that much less computational cost is demanded compared to DSMC simulation. Correspondingly, an increasing error arises in aeroheating calculation as the flow becomes more rarefied. To estimate the relative error of heat flux when applying this method for a rarefied flow in transitional regime, theoretical derivation is conducted and a dimensionless parameter ɛ is proposed by approximately analyzing the ratio of the second order term to first order term in the heat flux expression in Burnett equation. DSMC simulation for hypersonic flow over a cylinder in transitional regime is performed to test the performance of parameter ɛ, compared with two other parameters, Knρ and MaṡKnρ.

  11. Dopamine reward prediction errors reflect hidden state inference across time

    Science.gov (United States)

    Starkweather, Clara Kwon; Babayan, Benedicte M.; Uchida, Naoshige; Gershman, Samuel J.

    2017-01-01

    Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a ‘belief state’). In this work, we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling exhibited a striking difference between two tasks that differed only with respect to whether reward was delivered deterministically. Our results favor an associative learning rule that combines cached values with hidden state inference. PMID:28263301

  12. Social learning through prediction error in the brain

    Science.gov (United States)

    Joiner, Jessica; Piva, Matthew; Turrin, Courtney; Chang, Steve W. C.

    2017-06-01

    Learning about the world is critical to survival and success. In social animals, learning about others is a necessary component of navigating the social world, ultimately contributing to increasing evolutionary fitness. How humans and nonhuman animals represent the internal states and experiences of others has long been a subject of intense interest in the developmental psychology tradition, and, more recently, in studies of learning and decision making involving self and other. In this review, we explore how psychology conceptualizes the process of representing others, and how neuroscience has uncovered correlates of reinforcement learning signals to explore the neural mechanisms underlying social learning from the perspective of representing reward-related information about self and other. In particular, we discuss self-referenced and other-referenced types of reward prediction errors across multiple brain structures that effectively allow reinforcement learning algorithms to mediate social learning. Prediction-based computational principles in the brain may be strikingly conserved between self-referenced and other-referenced information.

  13. The Attraction Effect Modulates Reward Prediction Errors and Intertemporal Choices.

    Science.gov (United States)

    Gluth, Sebastian; Hotaling, Jared M; Rieskamp, Jörg

    2017-01-11

    Classical economic theory contends that the utility of a choice option should be independent of other options. This view is challenged by the attraction effect, in which the relative preference between two options is altered by the addition of a third, asymmetrically dominated option. Here, we leveraged the attraction effect in the context of intertemporal choices to test whether both decisions and reward prediction errors (RPE) in the absence of choice violate the independence of irrelevant alternatives principle. We first demonstrate that intertemporal decision making is prone to the attraction effect in humans. In an independent group of participants, we then investigated how this affects the neural and behavioral valuation of outcomes using a novel intertemporal lottery task and fMRI. Participants' behavioral responses (i.e., satisfaction ratings) were modulated systematically by the attraction effect and this modulation was correlated across participants with the respective change of the RPE signal in the nucleus accumbens. Furthermore, we show that, because exponential and hyperbolic discounting models are unable to account for the attraction effect, recently proposed sequential sampling models might be more appropriate to describe intertemporal choices. Our findings demonstrate for the first time that the attraction effect modulates subjective valuation even in the absence of choice. The findings also challenge the prospect of using neuroscientific methods to measure utility in a context-free manner and have important implications for theories of reinforcement learning and delay discounting. Many theories of value-based decision making assume that people first assess the attractiveness of each option independently of each other and then pick the option with the highest subjective value. The attraction effect, however, shows that adding a new option to a choice set can change the relative value of the existing options, which is a violation of the independence

  14. Mini-review: Prediction errors, attention and associative learning.

    Science.gov (United States)

    Holland, Peter C; Schiffino, Felipe L

    2016-05-01

    Most modern theories of associative learning emphasize a critical role for prediction error (PE, the difference between received and expected events). One class of theories, exemplified by the Rescorla-Wagner (1972) model, asserts that PE determines the effectiveness of the reinforcer or unconditioned stimulus (US): surprising reinforcers are more effective than expected ones. A second class, represented by the Pearce-Hall (1980) model, argues that PE determines the associability of conditioned stimuli (CSs), the rate at which they may enter into new learning: the surprising delivery or omission of a reinforcer enhances subsequent processing of the CSs that were present when PE was induced. In this mini-review we describe evidence, mostly from our laboratory, for PE-induced changes in the associability of both CSs and USs, and the brain systems involved in the coding, storage and retrieval of these altered associability values. This evidence favors a number of modifications to behavioral models of how PE influences event processing, and suggests the involvement of widespread brain systems in animals' responses to PE. Copyright © 2016 Elsevier Inc. All rights reserved.

  15. Hierarchical prediction errors in midbrain and septum during social learning.

    Science.gov (United States)

    Diaconescu, Andreea O; Mathys, Christoph; Weber, Lilian A E; Kasper, Lars; Mauer, Jan; Stephan, Klaas E

    2017-04-01

    Social learning is fundamental to human interactions, yet its computational and physiological mechanisms are not well understood. One prominent open question concerns the role of neuromodulatory transmitters. We combined fMRI, computational modelling and genetics to address this question in two separate samples (N = 35, N = 47). Participants played a game requiring inference on an adviser's intentions whose motivation to help or mislead changed over time. Our analyses suggest that hierarchically structured belief updates about current advice validity and the adviser's trustworthiness, respectively, depend on different neuromodulatory systems. Low-level prediction errors (PEs) about advice accuracy not only activated regions known to support 'theory of mind', but also the dopaminergic midbrain. Furthermore, PE responses in ventral striatum were influenced by the Met/Val polymorphism of the Catechol-O-Methyltransferase (COMT) gene. By contrast, high-level PEs ('expected uncertainty') about the adviser's fidelity activated the cholinergic septum. These findings, replicated in both samples, have important implications: They suggest that social learning rests on hierarchically related PEs encoded by midbrain and septum activity, respectively, in the same manner as other forms of learning under volatility. Furthermore, these hierarchical PEs may be broadcast by dopaminergic and cholinergic projections to induce plasticity specifically in cortical areas known to represent beliefs about others. © The Author (2017). Published by Oxford University Press.

  16. Basic considerations in predicting error probabilities in human task performance

    International Nuclear Information System (INIS)

    Fleishman, E.A.; Buffardi, L.C.; Allen, J.A.; Gaskins, R.C. III

    1990-04-01

    It is well established that human error plays a major role in the malfunctioning of complex systems. This report takes a broad look at the study of human error and addresses the conceptual, methodological, and measurement issues involved in defining and describing errors in complex systems. In addition, a review of existing sources of human reliability data and approaches to human performance data base development is presented. Alternative task taxonomies, which are promising for establishing the comparability on nuclear and non-nuclear tasks, are also identified. Based on such taxonomic schemes, various data base prototypes for generalizing human error rates across settings are proposed. 60 refs., 3 figs., 7 tabs

  17. Seasonal prediction of Indian summer monsoon rainfall in NCEP CFSv2: forecast and predictability error

    Science.gov (United States)

    Pokhrel, Samir; Saha, Subodh Kumar; Dhakate, Ashish; Rahman, Hasibur; Chaudhari, Hemantkumar S.; Salunke, Kiran; Hazra, Anupam; Sujith, K.; Sikka, D. R.

    2016-04-01

    A detailed analysis of sensitivity to the initial condition for the simulation of the Indian summer monsoon using retrospective forecast by the latest version of the Climate Forecast System version-2 (CFSv2) is carried out. This study primarily focuses on the tropical region of Indian and Pacific Ocean basin, with special emphasis on the Indian land region. The simulated seasonal mean and the inter-annual standard deviations of rainfall, upper and lower level atmospheric circulations and Sea Surface Temperature (SST) tend to be more skillful as the lead forecast time decreases (5 month lead to 0 month lead time i.e. L5-L0). In general spatial correlation (bias) increases (decreases) as forecast lead time decreases. This is further substantiated by their averaged value over the selected study regions over the Indian and Pacific Ocean basins. The tendency of increase (decrease) of model bias with increasing (decreasing) forecast lead time also indicates the dynamical drift of the model. Large scale lower level circulation (850 hPa) shows enhancement of anomalous westerlies (easterlies) over the tropical region of the Indian Ocean (Western Pacific Ocean), which indicates the enhancement of model error with the decrease in lead time. At the upper level circulation (200 hPa) biases in both tropical easterly jet and subtropical westerlies jet tend to decrease as the lead time decreases. Despite enhancement of the prediction skill, mean SST bias seems to be insensitive to the initialization. All these biases are significant and together they make CFSv2 vulnerable to seasonal uncertainties in all the lead times. Overall the zeroth lead (L0) seems to have the best skill, however, in case of Indian summer monsoon rainfall (ISMR), the 3 month lead forecast time (L3) has the maximum ISMR prediction skill. This is valid using different independent datasets, wherein these maximum skill scores are 0.64, 0.42 and 0.57 with respect to the Global Precipitation Climatology Project

  18. Distinct prediction errors in mesostriatal circuits of the human brain mediate learning about the values of both states and actions: evidence from high-resolution fMRI.

    Science.gov (United States)

    Colas, Jaron T; Pauli, Wolfgang M; Larsen, Tobias; Tyszka, J Michael; O'Doherty, John P

    2017-10-01

    Prediction-error signals consistent with formal models of "reinforcement learning" (RL) have repeatedly been found within dopaminergic nuclei of the midbrain and dopaminoceptive areas of the striatum. However, the precise form of the RL algorithms implemented in the human brain is not yet well determined. Here, we created a novel paradigm optimized to dissociate the subtypes of reward-prediction errors that function as the key computational signatures of two distinct classes of RL models-namely, "actor/critic" models and action-value-learning models (e.g., the Q-learning model). The state-value-prediction error (SVPE), which is independent of actions, is a hallmark of the actor/critic architecture, whereas the action-value-prediction error (AVPE) is the distinguishing feature of action-value-learning algorithms. To test for the presence of these prediction-error signals in the brain, we scanned human participants with a high-resolution functional magnetic-resonance imaging (fMRI) protocol optimized to enable measurement of neural activity in the dopaminergic midbrain as well as the striatal areas to which it projects. In keeping with the actor/critic model, the SVPE signal was detected in the substantia nigra. The SVPE was also clearly present in both the ventral striatum and the dorsal striatum. However, alongside these purely state-value-based computations we also found evidence for AVPE signals throughout the striatum. These high-resolution fMRI findings suggest that model-free aspects of reward learning in humans can be explained algorithmically with RL in terms of an actor/critic mechanism operating in parallel with a system for more direct action-value learning.

  19. Development of a prototype system for prediction of the group error at the maintenance work

    International Nuclear Information System (INIS)

    Yoshino, Kenji; Hirotsu, Yuuko

    2001-01-01

    This paper described on development and performance evaluation of a prototype system for prediction of the group error at the maintenance work. The results so far are as follows. (1) When a user inputs the existence and the grade of the feature factor of the maintenance work as a prediction object, an organization and an organization factor and a group PSF put into the system. The maintenance group error to target can be predicted through the prediction model which consists of a class of seven stages. (2) This system by utilizing the information on a prediction result database, it can be use not only for prediction of a maintenance group but for various safe Activity, such as KYT(Kiken Yochi Training) and TBM(Tool Box Meeting). (3) This system predicts a cooperation error at highest rate, and subsequently. Predicts the detection error at a high rate. and to the decision-making. Error, the transfer error and the state cognitive error, and state error, it has the characteristics predicted at almost same rate. (4) if it has full knowledge even if the feature, such as the enforcement conditions of maintenance work, and organization, even if the user has neither the knowledge about a human factor, users experience, anyone of this system is slight about the extent, generating of a maintenance group error made difficult from the former logically and systematically, it can predict with business time for about 15 minutes. (author)

  20. Uncertainty in predictions of forest carbon dynamics: separating driver error from model error.

    Science.gov (United States)

    Spadavecchia, L; Williams, M; Law, B E

    2011-07-01

    We present an analysis of the relative magnitude and contribution of parameter and driver uncertainty to the confidence intervals on estimates of net carbon fluxes. Model parameters may be difficult or impractical to measure, while driver fields are rarely complete, with data gaps due to sensor failure and sparse observational networks. Parameters are generally derived through some optimization method, while driver fields may be interpolated from available data sources. For this study, we used data from a young ponderosa pine stand at Metolius, Central Oregon, and a simple daily model of coupled carbon and water fluxes (DALEC). An ensemble of acceptable parameterizations was generated using an ensemble Kalman filter and eddy covariance measurements of net C exchange. Geostatistical simulations generated an ensemble of meteorological driving variables for the site, consistent with the spatiotemporal autocorrelations inherent in the observational data from 13 local weather stations. Simulated meteorological data were propagated through the model to derive the uncertainty on the CO2 flux resultant from driver uncertainty typical of spatially extensive modeling studies. Furthermore, the model uncertainty was partitioned between temperature and precipitation. With at least one meteorological station within 25 km of the study site, driver uncertainty was relatively small ( 10% of the total net flux), while parameterization uncertainty was larger, 50% of the total net flux. The largest source of driver uncertainty was due to temperature (8% of the total flux). The combined effect of parameter and driver uncertainty was 57% of the total net flux. However, when the nearest meteorological station was > 100 km from the study site, uncertainty in net ecosystem exchange (NEE) predictions introduced by meteorological drivers increased by 88%. Precipitation estimates were a larger source of bias in NEE estimates than were temperature estimates, although the biases partly

  1. BANKRUPTCY PREDICTION MODEL WITH ZETAc OPTIMAL CUT-OFF SCORE TO CORRECT TYPE I ERRORS

    Directory of Open Access Journals (Sweden)

    Mohamad Iwan

    2005-06-01

    This research has successfully attained the following results: (1 type I error is in fact 59,83 times more costly compared to type II error, (2 22 ratios distinguish between bankrupt and non-bankrupt groups, (3 2 financial ratios proved to be effective in predicting bankruptcy, (4 prediction using ZETAc optimal cut-off score predicts more companies filing for bankruptcy within one year compared to prediction using Hair et al. optimum cutting score, (5 Although prediction using Hair et al. optimum cutting score is more accurate, prediction using ZETAc optimal cut-off score proved to be able to minimize cost incurred from classification errors.

  2. A Sensor Dynamic Measurement Error Prediction Model Based on NAPSO-SVM.

    Science.gov (United States)

    Jiang, Minlan; Jiang, Lan; Jiang, Dingde; Li, Fei; Song, Houbing

    2018-01-15

    Dynamic measurement error correction is an effective way to improve sensor precision. Dynamic measurement error prediction is an important part of error correction, and support vector machine (SVM) is often used for predicting the dynamic measurement errors of sensors. Traditionally, the SVM parameters were always set manually, which cannot ensure the model's performance. In this paper, a SVM method based on an improved particle swarm optimization (NAPSO) is proposed to predict the dynamic measurement errors of sensors. Natural selection and simulated annealing are added in the PSO to raise the ability to avoid local optima. To verify the performance of NAPSO-SVM, three types of algorithms are selected to optimize the SVM's parameters: the particle swarm optimization algorithm (PSO), the improved PSO optimization algorithm (NAPSO), and the glowworm swarm optimization (GSO). The dynamic measurement error data of two sensors are applied as the test data. The root mean squared error and mean absolute percentage error are employed to evaluate the prediction models' performances. The experimental results show that among the three tested algorithms the NAPSO-SVM method has a better prediction precision and a less prediction errors, and it is an effective method for predicting the dynamic measurement errors of sensors.

  3. Learning about Expectation Violation from Prediction Error Paradigms – A Meta-Analysis on Brain Processes Following a Prediction Error

    Directory of Open Access Journals (Sweden)

    Lisa D’Astolfo

    2017-07-01

    Full Text Available Modifying patients’ expectations by exposing them to expectation violation situations (thus maximizing the difference between the expected and the actual situational outcome is proposed to be a crucial mechanism for therapeutic success for a variety of different mental disorders. However, clinical observations suggest that patients often maintain their expectations regardless of experiences contradicting their expectations. It remains unclear which information processing mechanisms lead to modification or persistence of patients’ expectations. Insight in the processing could be provided by Neuroimaging studies investigating prediction error (PE, i.e., neuronal reactions to non-expected stimuli. Two methods are often used to investigate the PE: (1 paradigms, in which participants passively observe PEs (”passive” paradigms and (2 paradigms, which encourage a behavioral adaptation following a PE (“active” paradigms. These paradigms are similar to the methods used to induce expectation violations in clinical settings: (1 the confrontation with an expectation violation situation and (2 an enhanced confrontation in which the patient actively challenges his expectation. We used this similarity to gain insight in the different neuronal processing of the two PE paradigms. We performed a meta-analysis contrasting neuronal activity of PE paradigms encouraging a behavioral adaptation following a PE and paradigms enforcing passiveness following a PE. We found more neuronal activity in the striatum, the insula and the fusiform gyrus in studies encouraging behavioral adaptation following a PE. Due to the involvement of reward assessment and avoidance learning associated with the striatum and the insula we propose that the deliberate execution of action alternatives following a PE is associated with the integration of new information into previously existing expectations, therefore leading to an expectation change. While further research is needed

  4. Predicting positional error of MLC using volumetric analysis

    International Nuclear Information System (INIS)

    Hareram, E.S.

    2008-01-01

    IMRT normally using multiple beamlets (small width of the beam) for a particular field to deliver so that it is imperative to maintain the positional accuracy of the MLC in order to deliver integrated computed dose accurately. Different manufacturers have reported high precession on MLC devices with leaf positional accuracy nearing 0.1 mm but measuring and rectifying the error in this accuracy is very difficult. Various methods are used to check MLC position and among this volumetric analysis is one of the technique. Volumetric approach was adapted in our method using primus machine and 0.6cc chamber at 5 cm depth In perspex. MLC of 1 mm error introduces an error of 20%, more sensitive to other methods

  5. The conditions that promote fear learning: prediction error and Pavlovian fear conditioning.

    Science.gov (United States)

    Li, Susan Shi Yuan; McNally, Gavan P

    2014-02-01

    A key insight of associative learning theory is that learning depends on the actions of prediction error: a discrepancy between the actual and expected outcomes of a conditioning trial. When positive, such error causes increments in associative strength and, when negative, such error causes decrements in associative strength. Prediction error can act directly on fear learning by determining the effectiveness of the aversive unconditioned stimulus or indirectly by determining the effectiveness, or associability, of the conditioned stimulus. Evidence from a variety of experimental preparations in human and non-human animals suggest that discrete neural circuits code for these actions of prediction error during fear learning. Here we review the circuits and brain regions contributing to the neural coding of prediction error during fear learning and highlight areas of research (safety learning, extinction, and reconsolidation) that may profit from this approach to understanding learning. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

  6. A negative relationship between ventral striatal loss anticipation response and impulsivity in borderline personality disorder.

    Science.gov (United States)

    Herbort, Maike C; Soch, Joram; Wüstenberg, Torsten; Krauel, Kerstin; Pujara, Maia; Koenigs, Michael; Gallinat, Jürgen; Walter, Henrik; Roepke, Stefan; Schott, Björn H

    2016-01-01

    Patients with borderline personality disorder (BPD) frequently exhibit impulsive behavior, and self-reported impulsivity is typically higher in BPD patients when compared to healthy controls. Previous functional neuroimaging studies have suggested a link between impulsivity, the ventral striatal response to reward anticipation, and prediction errors. Here we investigated the striatal neural response to monetary gain and loss anticipation and their relationship with impulsivity in 21 female BPD patients and 23 age-matched female healthy controls using functional magnetic resonance imaging (fMRI). Participants performed a delayed monetary incentive task in which three categories of objects predicted a potential gain, loss, or neutral outcome. Impulsivity was assessed using the Barratt Impulsiveness Scale (BIS-11). Compared to healthy controls, BPD patients exhibited significantly reduced fMRI responses of the ventral striatum/nucleus accumbens (VS/NAcc) to both reward-predicting and loss-predicting cues. BIS-11 scores showed a significant positive correlation with the VS/NAcc reward anticipation responses in healthy controls, and this correlation, while also nominally positive, failed to reach significance in BPD patients. BPD patients, on the other hand, exhibited a significantly negative correlation between ventral striatal loss anticipation responses and BIS-11 scores, whereas this correlation was significantly positive in healthy controls. Our results suggest that patients with BPD show attenuated anticipation responses in the VS/NAcc and, furthermore, that higher impulsivity in BPD patients might be related to impaired prediction of aversive outcomes.

  7. Some Results on Mean Square Error for Factor Score Prediction

    Science.gov (United States)

    Krijnen, Wim P.

    2006-01-01

    For the confirmatory factor model a series of inequalities is given with respect to the mean square error (MSE) of three main factor score predictors. The eigenvalues of these MSE matrices are a monotonic function of the eigenvalues of the matrix gamma[subscript rho] = theta[superscript 1/2] lambda[subscript rho] 'psi[subscript rho] [superscript…

  8. Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia.

    Science.gov (United States)

    Diuk, Carlos; Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew; Niv, Yael

    2013-03-27

    Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.

  9. A second study of the prediction of cognitive errors using the 'CREAM' technique

    International Nuclear Information System (INIS)

    Collier, Steve; Andresen, Gisle

    2000-03-01

    Some human errors, such as errors of commission and knowledge-based errors, are not adequately modelled in probabilistic safety assessments. Even qualitative methods for handling these sorts of errors are comparatively underdeveloped. The 'Cognitive Reliability and Error Analysis Method' (CREAM) was recently developed for prediction of cognitive error modes. It has not yet been comprehensively established how reliable, valid and generally useful it could be to researchers and practitioners. A previous study of CREAM at Halden was promising, showing a relationship between errors predicted in advance and those that actually occurred in simulated fault scenarios. The present study continues this work. CREAM was used to make predictions of cognitive error modes throughout two rather difficult fault scenarios. Predictions were made of the most likely cognitive error mode, were one to occur at all, at several points throughout the expected scenarios, based upon the scenario design and description. Each scenario was then run 15 times with different operators. Error modes occurring during simulations were later scored using the task description for the scenario, videotapes of operator actions, eye-track recording, operators' verbal protocols and an expert's concurrent commentary. The scoring team had no previous substantive knowledge of the experiment or the techniques used, so as to provide a more stringent test of the data and knowledge needed for scoring. The scored error modes were then compared with the CREAM predictions to assess the degree of agreement. Some cognitive error modes were predicted successfully, but the results were generally not so encouraging as the previous study. Several problems were found with both the CREAM technique and the data needed to complete the analysis. It was felt that further development was needed before this kind of analysis can be reliable and valid, either in a research setting or as a practitioner's tool in a safety assessment

  10. Surprised at all the entropy: hippocampal, caudate and midbrain contributions to learning from prediction errors.

    Directory of Open Access Journals (Sweden)

    Anne-Marike Schiffer

    Full Text Available Influential concepts in neuroscientific research cast the brain a predictive machine that revises its predictions when they are violated by sensory input. This relates to the predictive coding account of perception, but also to learning. Learning from prediction errors has been suggested for take place in the hippocampal memory system as well as in the basal ganglia. The present fMRI study used an action-observation paradigm to investigate the contributions of the hippocampus, caudate nucleus and midbrain dopaminergic system to different types of learning: learning in the absence of prediction errors, learning from prediction errors, and responding to the accumulation of prediction errors in unpredictable stimulus configurations. We conducted analyses of the regions of interests' BOLD response towards these different types of learning, implementing a bootstrapping procedure to correct for false positives. We found both, caudate nucleus and the hippocampus to be activated by perceptual prediction errors. The hippocampal responses seemed to relate to the associative mismatch between a stored representation and current sensory input. Moreover, its response was significantly influenced by the average information, or Shannon entropy of the stimulus material. In accordance with earlier results, the habenula was activated by perceptual prediction errors. Lastly, we found that the substantia nigra was activated by the novelty of sensory input. In sum, we established that the midbrain dopaminergic system, the hippocampus, and the caudate nucleus were to different degrees significantly involved in the three different types of learning: acquisition of new information, learning from prediction errors and responding to unpredictable stimulus developments. We relate learning from perceptual prediction errors to the concept of predictive coding and related information theoretic accounts.

  11. Surprised at all the entropy: hippocampal, caudate and midbrain contributions to learning from prediction errors.

    Science.gov (United States)

    Schiffer, Anne-Marike; Ahlheim, Christiane; Wurm, Moritz F; Schubotz, Ricarda I

    2012-01-01

    Influential concepts in neuroscientific research cast the brain a predictive machine that revises its predictions when they are violated by sensory input. This relates to the predictive coding account of perception, but also to learning. Learning from prediction errors has been suggested for take place in the hippocampal memory system as well as in the basal ganglia. The present fMRI study used an action-observation paradigm to investigate the contributions of the hippocampus, caudate nucleus and midbrain dopaminergic system to different types of learning: learning in the absence of prediction errors, learning from prediction errors, and responding to the accumulation of prediction errors in unpredictable stimulus configurations. We conducted analyses of the regions of interests' BOLD response towards these different types of learning, implementing a bootstrapping procedure to correct for false positives. We found both, caudate nucleus and the hippocampus to be activated by perceptual prediction errors. The hippocampal responses seemed to relate to the associative mismatch between a stored representation and current sensory input. Moreover, its response was significantly influenced by the average information, or Shannon entropy of the stimulus material. In accordance with earlier results, the habenula was activated by perceptual prediction errors. Lastly, we found that the substantia nigra was activated by the novelty of sensory input. In sum, we established that the midbrain dopaminergic system, the hippocampus, and the caudate nucleus were to different degrees significantly involved in the three different types of learning: acquisition of new information, learning from prediction errors and responding to unpredictable stimulus developments. We relate learning from perceptual prediction errors to the concept of predictive coding and related information theoretic accounts.

  12. A Generalized Process Model of Human Action Selection and Error and its Application to Error Prediction

    Science.gov (United States)

    2014-07-01

    Macmillan & Creelman , 2005). This is a quite high degree of discriminability and it means that when the decision model predicts a probability of...ROC analysis. Pattern Recognition Letters, 27(8), 861-874. Retrieved from Google Scholar. Macmillan, N. A., & Creelman , C. D. (2005). Detection

  13. Physical predictions from lattice QCD. Reducing systematic errors

    International Nuclear Information System (INIS)

    Pittori, C.

    1994-01-01

    Some recent developments in the theoretical understanding of lattice quantum chromodynamics and of its possible sources of systematic errors are reported, and a review of some of the latest Monte Carlo results for light quarks phenomenology is presented. A very general introduction on a quantum field theory on a discrete spacetime lattice is given, and the Monte Carlo methods which allow to compute many interesting physical quantities in the non-perturbative domain of strong interactions, is illustrated. (author). 17 refs., 3 figs., 3 tabs

  14. Competition between learned reward and error outcome predictions in anterior cingulate cortex.

    Science.gov (United States)

    Alexander, William H; Brown, Joshua W

    2010-02-15

    The anterior cingulate cortex (ACC) is implicated in performance monitoring and cognitive control. Non-human primate studies of ACC show prominent reward signals, but these are elusive in human studies, which instead show mainly conflict and error effects. Here we demonstrate distinct appetitive and aversive activity in human ACC. The error likelihood hypothesis suggests that ACC activity increases in proportion to the likelihood of an error, and ACC is also sensitive to the consequence magnitude of the predicted error. Previous work further showed that error likelihood effects reach a ceiling as the potential consequences of an error increase, possibly due to reductions in the average reward. We explored this issue by independently manipulating reward magnitude of task responses and error likelihood while controlling for potential error consequences in an Incentive Change Signal Task. The fMRI results ruled out a modulatory effect of expected reward on error likelihood effects in favor of a competition effect between expected reward and error likelihood. Dynamic causal modeling showed that error likelihood and expected reward signals are intrinsic to the ACC rather than received from elsewhere. These findings agree with interpretations of ACC activity as signaling both perceptions of risk and predicted reward. Copyright 2009 Elsevier Inc. All rights reserved.

  15. Parsing Heterogeneous Striatal Activity

    Directory of Open Access Journals (Sweden)

    Kae Nakamura

    2017-05-01

    Full Text Available The striatum is an input channel of the basal ganglia and is well known to be involved in reward-based decision making and learning. At the macroscopic level, the striatum has been postulated to contain parallel functional modules, each of which includes neurons that perform similar computations to support selection of appropriate actions for different task contexts. At the single-neuron level, however, recent studies in monkeys and rodents have revealed heterogeneity in neuronal activity even within restricted modules of the striatum. Looking for generality in the complex striatal activity patterns, here we briefly survey several types of striatal activity, focusing on their usefulness for mediating behaviors. In particular, we focus on two types of behavioral tasks: reward-based tasks that use salient sensory cues and manipulate outcomes associated with the cues; and perceptual decision tasks that manipulate the quality of noisy sensory cues and associate all correct decisions with the same outcome. Guided by previous insights on the modular organization and general selection-related functions of the basal ganglia, we relate striatal activity patterns on these tasks to two types of computations: implementation of selection and evaluation. We suggest that a parsing with the selection/evaluation categories encourages a focus on the functional commonalities revealed by studies with different animal models and behavioral tasks, instead of a focus on aspects of striatal activity that may be specific to a particular task setting. We then highlight several questions in the selection-evaluation framework for future explorations.

  16. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...... values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles....

  17. Measurement error and timing of predictor values for multivariable risk prediction models are poorly reported.

    Science.gov (United States)

    Whittle, Rebecca; Peat, George; Belcher, John; Collins, Gary S; Riley, Richard D

    2018-05-18

    Measurement error in predictor variables may threaten the validity of clinical prediction models. We sought to evaluate the possible extent of the problem. A secondary objective was to examine whether predictors are measured at the intended moment of model use. A systematic search of Medline was used to identify a sample of articles reporting the development of a clinical prediction model published in 2015. After screening according to a predefined inclusion criteria, information on predictors, strategies to control for measurement error and intended moment of model use were extracted. Susceptibility to measurement error for each predictor was classified into low and high risk. Thirty-three studies were reviewed, including 151 different predictors in the final prediction models. Fifty-one (33.7%) predictors were categorised as high risk of error, however this was not accounted for in the model development. Only 8 (24.2%) studies explicitly stated the intended moment of model use and when the predictors were measured. Reporting of measurement error and intended moment of model use is poor in prediction model studies. There is a need to identify circumstances where ignoring measurement error in prediction models is consequential and whether accounting for the error will improve the predictions. Copyright © 2018. Published by Elsevier Inc.

  18. Estimation of Separation Buffers for Wind-Prediction Error in an Airborne Separation Assistance System

    Science.gov (United States)

    Consiglio, Maria C.; Hoadley, Sherwood T.; Allen, B. Danette

    2009-01-01

    Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.

  19. Analysts’ forecast error: A robust prediction model and its short term trading profitability

    NARCIS (Netherlands)

    Boudt, K.M.R.; de Goei, P.; Thewissen, J.; van Campenhout, G.

    2015-01-01

    This paper contributes to the empirical evidence on the investment horizon salient to trading based on predicting the error in analysts' earnings forecasts. An econometric framework is proposed that accommodates the stylized fact of extreme values in the forecast error series. We find that between

  20. Analysts forecast error : A robust prediction model and its short term trading

    NARCIS (Netherlands)

    Boudt, Kris; de Goeij, Peter; Thewissen, James; Van Campenhout, Geert

    We examine the profitability of implementing a short term trading strategy based on predicting the error in analysts' earnings per share forecasts using publicly available information. Since large earnings surprises may lead to extreme values in the forecast error series that disrupt their smooth

  1. Reward Prediction Errors in Drug Addiction and Parkinson's Disease: from Neurophysiology to Neuroimaging.

    Science.gov (United States)

    García-García, Isabel; Zeighami, Yashar; Dagher, Alain

    2017-06-01

    Surprises are important sources of learning. Cognitive scientists often refer to surprises as "reward prediction errors," a parameter that captures discrepancies between expectations and actual outcomes. Here, we integrate neurophysiological and functional magnetic resonance imaging (fMRI) results addressing the processing of reward prediction errors and how they might be altered in drug addiction and Parkinson's disease. By increasing phasic dopamine responses, drugs might accentuate prediction error signals, causing increases in fMRI activity in mesolimbic areas in response to drugs. Chronic substance dependence, by contrast, has been linked with compromised dopaminergic function, which might be associated with blunted fMRI responses to pleasant non-drug stimuli in mesocorticolimbic areas. In Parkinson's disease, dopamine replacement therapies seem to induce impairments in learning from negative outcomes. The present review provides a holistic overview of reward prediction errors across different pathologies and might inform future clinical strategies targeting impulsive/compulsive disorders.

  2. Curiosity and reward: Valence predicts choice and information prediction errors enhance learning.

    Science.gov (United States)

    Marvin, Caroline B; Shohamy, Daphna

    2016-03-01

    Curiosity drives many of our daily pursuits and interactions; yet, we know surprisingly little about how it works. Here, we harness an idea implied in many conceptualizations of curiosity: that information has value in and of itself. Reframing curiosity as the motivation to obtain reward-where the reward is information-allows one to leverage major advances in theoretical and computational mechanisms of reward-motivated learning. We provide new evidence supporting 2 predictions that emerge from this framework. First, we find an asymmetric effect of positive versus negative information, with positive information enhancing both curiosity and long-term memory for information. Second, we find that it is not the absolute value of information that drives learning but, rather, the gap between the reward expected and reward received, an "information prediction error." These results support the idea that information functions as a reward, much like money or food, guiding choices and driving learning in systematic ways. (c) 2016 APA, all rights reserved).

  3. Artificial neural network implementation of a near-ideal error prediction controller

    Science.gov (United States)

    Mcvey, Eugene S.; Taylor, Lynore Denise

    1992-01-01

    A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error

  4. Estimation of Mechanical Signals in Induction Motors using the Recursive Prediction Error Method

    DEFF Research Database (Denmark)

    Børsting, H.; Knudsen, Morten; Rasmussen, Henrik

    1993-01-01

    Sensor feedback of mechanical quantities for control applications in induction motors is troublesome and relative expensive. In this paper a recursive prediction error (RPE) method has successfully been used to estimate the angular rotor speed ........Sensor feedback of mechanical quantities for control applications in induction motors is troublesome and relative expensive. In this paper a recursive prediction error (RPE) method has successfully been used to estimate the angular rotor speed .....

  5. An MEG signature corresponding to an axiomatic model of reward prediction error.

    Science.gov (United States)

    Talmi, Deborah; Fuentemilla, Lluis; Litvak, Vladimir; Duzel, Emrah; Dolan, Raymond J

    2012-01-02

    Optimal decision-making is guided by evaluating the outcomes of previous decisions. Prediction errors are theoretical teaching signals which integrate two features of an outcome: its inherent value and prior expectation of its occurrence. To uncover the magnetic signature of prediction errors in the human brain we acquired magnetoencephalographic (MEG) data while participants performed a gambling task. Our primary objective was to use formal criteria, based upon an axiomatic model (Caplin and Dean, 2008a), to determine the presence and timing profile of MEG signals that express prediction errors. We report analyses at the sensor level, implemented in SPM8, time locked to outcome onset. We identified, for the first time, a MEG signature of prediction error, which emerged approximately 320 ms after an outcome and expressed as an interaction between outcome valence and probability. This signal followed earlier, separate signals for outcome valence and probability, which emerged approximately 200 ms after an outcome. Strikingly, the time course of the prediction error signal, as well as the early valence signal, resembled the Feedback-Related Negativity (FRN). In simultaneously acquired EEG data we obtained a robust FRN, but the win and loss signals that comprised this difference wave did not comply with the axiomatic model. Our findings motivate an explicit examination of the critical issue of timing embodied in computational models of prediction errors as seen in human electrophysiological data. Copyright © 2011 Elsevier Inc. All rights reserved.

  6. Roles of dopamine neurons in mediating the prediction error in aversive learning in insects.

    Science.gov (United States)

    Terao, Kanta; Mizunami, Makoto

    2017-10-31

    In associative learning in mammals, it is widely accepted that the discrepancy, or error, between actual and predicted reward determines whether learning occurs. The prediction error theory has been proposed to account for the finding of a blocking phenomenon, in which pairing of a stimulus X with an unconditioned stimulus (US) could block subsequent association of a second stimulus Y to the US when the two stimuli were paired in compound with the same US. Evidence for this theory, however, has been imperfect since blocking can also be accounted for by competitive theories. We recently reported blocking in classical conditioning of an odor with water reward in crickets. We also reported an "auto-blocking" phenomenon in appetitive learning, which supported the prediction error theory and rejected alternative theories. The presence of auto-blocking also suggested that octopamine neurons mediate reward prediction error signals. Here we show that blocking and auto-blocking occur in aversive learning to associate an odor with salt water (US) in crickets, and our results suggest that dopamine neurons mediate aversive prediction error signals. We conclude that the prediction error theory is applicable to both appetitive learning and aversive learning in insects.

  7. Model-free and model-based reward prediction errors in EEG.

    Science.gov (United States)

    Sambrook, Thomas D; Hardwick, Ben; Wills, Andy J; Goslin, Jeremy

    2018-05-24

    Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

  8. Prediction-error variance in Bayesian model updating: a comparative study

    Science.gov (United States)

    Asadollahi, Parisa; Li, Jian; Huang, Yong

    2017-04-01

    In Bayesian model updating, the likelihood function is commonly formulated by stochastic embedding in which the maximum information entropy probability model of prediction error variances plays an important role and it is Gaussian distribution subject to the first two moments as constraints. The selection of prediction error variances can be formulated as a model class selection problem, which automatically involves a trade-off between the average data-fit of the model class and the information it extracts from the data. Therefore, it is critical for the robustness in the updating of the structural model especially in the presence of modeling errors. To date, three ways of considering prediction error variances have been seem in the literature: 1) setting constant values empirically, 2) estimating them based on the goodness-of-fit of the measured data, and 3) updating them as uncertain parameters by applying Bayes' Theorem at the model class level. In this paper, the effect of different strategies to deal with the prediction error variances on the model updating performance is investigated explicitly. A six-story shear building model with six uncertain stiffness parameters is employed as an illustrative example. Transitional Markov Chain Monte Carlo is used to draw samples of the posterior probability density function of the structure model parameters as well as the uncertain prediction variances. The different levels of modeling uncertainty and complexity are modeled through three FE models, including a true model, a model with more complexity, and a model with modeling error. Bayesian updating is performed for the three FE models considering the three aforementioned treatments of the prediction error variances. The effect of number of measurements on the model updating performance is also examined in the study. The results are compared based on model class assessment and indicate that updating the prediction error variances as uncertain parameters at the model

  9. The Human Bathtub: Safety and Risk Predictions Including the Dynamic Probability of Operator Errors

    International Nuclear Information System (INIS)

    Duffey, Romney B.; Saull, John W.

    2006-01-01

    Reactor safety and risk are dominated by the potential and major contribution for human error in the design, operation, control, management, regulation and maintenance of the plant, and hence to all accidents. Given the possibility of accidents and errors, now we need to determine the outcome (error) probability, or the chance of failure. Conventionally, reliability engineering is associated with the failure rate of components, or systems, or mechanisms, not of human beings in and interacting with a technological system. The probability of failure requires a prior knowledge of the total number of outcomes, which for any predictive purposes we do not know or have. Analysis of failure rates due to human error and the rate of learning allow a new determination of the dynamic human error rate in technological systems, consistent with and derived from the available world data. The basis for the analysis is the 'learning hypothesis' that humans learn from experience, and consequently the accumulated experience defines the failure rate. A new 'best' equation has been derived for the human error, outcome or failure rate, which allows for calculation and prediction of the probability of human error. We also provide comparisons to the empirical Weibull parameter fitting used in and by conventional reliability engineering and probabilistic safety analysis methods. These new analyses show that arbitrary Weibull fitting parameters and typical empirical hazard function techniques cannot be used to predict the dynamics of human errors and outcomes in the presence of learning. Comparisons of these new insights show agreement with human error data from the world's commercial airlines, the two shuttle failures, and from nuclear plant operator actions and transient control behavior observed in transients in both plants and simulators. The results demonstrate that the human error probability (HEP) is dynamic, and that it may be predicted using the learning hypothesis and the minimum

  10. Period, epoch, and prediction errors of ephemerides from continuous sets of timing measurements

    Science.gov (United States)

    Deeg, H. J.

    2015-06-01

    Space missions such as Kepler and CoRoT have led to large numbers of eclipse or transit measurements in nearly continuous time series. This paper shows how to obtain the period error in such measurements from a basic linear least-squares fit, and how to correctly derive the timing error in the prediction of future transit or eclipse events. Assuming strict periodicity, a formula for the period error of these time series is derived, σP = σT (12 / (N3-N))1 / 2, where σP is the period error, σT the timing error of a single measurement, and N the number of measurements. Compared to the iterative method for period error estimation by Mighell & Plavchan (2013), this much simpler formula leads to smaller period errors, whose correctness has been verified through simulations. For the prediction of times of future periodic events, usual linear ephemeris were epoch errors are quoted for the first time measurement, are prone to an overestimation of the error of that prediction. This may be avoided by a correction for the duration of the time series. An alternative is the derivation of ephemerides whose reference epoch and epoch error are given for the centre of the time series. For long continuous or near-continuous time series whose acquisition is completed, such central epochs should be the preferred way for the quotation of linear ephemerides. While this work was motivated from the analysis of eclipse timing measures in space-based light curves, it should be applicable to any other problem with an uninterrupted sequence of discrete timings for which the determination of a zero point, of a constant period and of the associated errors is needed.

  11. Glutamatergic model psychoses: prediction error, learning, and inference.

    Science.gov (United States)

    Corlett, Philip R; Honey, Garry D; Krystal, John H; Fletcher, Paul C

    2011-01-01

    Modulating glutamatergic neurotransmission induces alterations in conscious experience that mimic the symptoms of early psychotic illness. We review studies that use intravenous administration of ketamine, focusing on interindividual variability in the profundity of the ketamine experience. We will consider this individual variability within a hypothetical model of brain and cognitive function centered upon learning and inference. Within this model, the brains, neural systems, and even single neurons specify expectations about their inputs and responding to violations of those expectations with new learning that renders future inputs more predictable. We argue that ketamine temporarily deranges this ability by perturbing both the ways in which prior expectations are specified and the ways in which expectancy violations are signaled. We suggest that the former effect is predominantly mediated by NMDA blockade and the latter by augmented and inappropriate feedforward glutamatergic signaling. We suggest that the observed interindividual variability emerges from individual differences in neural circuits that normally underpin the learning and inference processes described. The exact source for that variability is uncertain, although it is likely to arise not only from genetic variation but also from subjects' previous experiences and prior learning. Furthermore, we argue that chronic, unlike acute, NMDA blockade alters the specification of expectancies more profoundly and permanently. Scrutinizing individual differences in the effects of acute and chronic ketamine administration in the context of the Bayesian brain model may generate new insights about the symptoms of psychosis; their underlying cognitive processes and neurocircuitry.

  12. Mismatch Negativity Encoding of Prediction Errors Predicts S-ketamine-Induced Cognitive Impairments

    Science.gov (United States)

    Schmidt, André; Bachmann, Rosilla; Kometer, Michael; Csomor, Philipp A; Stephan, Klaas E; Seifritz, Erich; Vollenweider, Franz X

    2012-01-01

    Psychotomimetics like the N-methyl--aspartate receptor (NMDAR) antagonist ketamine and the 5-hydroxytryptamine2A receptor (5-HT2AR) agonist psilocybin induce psychotic symptoms in healthy volunteers that resemble those of schizophrenia. Recent theories of psychosis posit that aberrant encoding of prediction errors (PE) may underlie the expression of psychotic symptoms. This study used a roving mismatch negativity (MMN) paradigm to investigate whether the encoding of PE is affected by pharmacological manipulation of NMDAR or 5-HT2AR, and whether the encoding of PE under placebo can be used to predict drug-induced symptoms. Using a double-blind within-subject placebo-controlled design, S-ketamine and psilocybin, respectively, were administrated to two groups of healthy subjects. Psychological alterations were assessed using a revised version of the Altered States of Consciousness (ASC-R) questionnaire. As an index of PE, we computed changes in MMN amplitudes as a function of the number of preceding standards (MMN memory trace effect) during a roving paradigm. S-ketamine, but not psilocybin, disrupted PE processing as expressed by a frontally disrupted MMN memory trace effect. Although both drugs produced positive-like symptoms, the extent of PE processing under placebo only correlated significantly with the severity of cognitive impairments induced by S-ketamine. Our results suggest that the NMDAR, but not the 5-HT2AR system, is implicated in PE processing during the MMN paradigm, and that aberrant PE signaling may contribute to the formation of cognitive impairments. The assessment of the MMN memory trace in schizophrenia may allow detecting early phases of the illness and might also serve to assess the efficacy of novel pharmacological treatments, in particular of cognitive impairments. PMID:22030715

  13. Association of Elevated Reward Prediction Error Response With Weight Gain in Adolescent Anorexia Nervosa.

    Science.gov (United States)

    DeGuzman, Marisa; Shott, Megan E; Yang, Tony T; Riederer, Justin; Frank, Guido K W

    2017-06-01

    Anorexia nervosa is a psychiatric disorder of unknown etiology. Understanding associations between behavior and neurobiology is important in treatment development. Using a novel monetary reward task during functional magnetic resonance brain imaging, the authors tested how brain reward learning in adolescent anorexia nervosa changes with weight restoration. Female adolescents with anorexia nervosa (N=21; mean age, 16.4 years [SD=1.9]) underwent functional MRI (fMRI) before and after treatment; similarly, healthy female control adolescents (N=21; mean age, 15.2 years [SD=2.4]) underwent fMRI on two occasions. Brain function was tested using the reward prediction error construct, a computational model for reward receipt and omission related to motivation and neural dopamine responsiveness. Compared with the control group, the anorexia nervosa group exhibited greater brain response 1) for prediction error regression within the caudate, ventral caudate/nucleus accumbens, and anterior and posterior insula, 2) to unexpected reward receipt in the anterior and posterior insula, and 3) to unexpected reward omission in the caudate body. Prediction error and unexpected reward omission response tended to normalize with treatment, while unexpected reward receipt response remained significantly elevated. Greater caudate prediction error response when underweight was associated with lower weight gain during treatment. Punishment sensitivity correlated positively with ventral caudate prediction error response. Reward system responsiveness is elevated in adolescent anorexia nervosa when underweight and after weight restoration. Heightened prediction error activity in brain reward regions may represent a phenotype of adolescent anorexia nervosa that does not respond well to treatment. Prediction error response could be a neurobiological marker of illness severity that can indicate individual treatment needs.

  14. Using lexical variables to predict picture-naming errors in jargon aphasia

    Directory of Open Access Journals (Sweden)

    Catherine Godbold

    2015-04-01

    Full Text Available Introduction Individuals with jargon aphasia produce fluent output which often comprises high proportions of non-word errors (e.g., maf for dog. Research has been devoted to identifying the underlying mechanisms behind such output. Some accounts posit a reduced flow of spreading activation between levels in the lexical network (e.g., Robson et al., 2003. If activation level differences across the lexical network are a cause of non-word outputs, we would predict improved performance when target items reflect an increased flow of activation between levels (e.g. more frequently-used words are often represented by higher resting levels of activation. This research investigates the effect of lexical properties of targets (e.g., frequency, imageability on accuracy, error type (real word vs. non-word and target-error overlap of non-word errors in a picture naming task by individuals with jargon aphasia. Method Participants were 17 individuals with Wernicke’s aphasia, who produced a high proportion of non-word errors (>20% of errors on the Philadelphia Naming Test (PNT; Roach et al., 1996. The data were retrieved from the Moss Aphasic Psycholinguistic Database Project (MAPPD, Mirman et al., 2010. We used a series of mixed models to test whether lexical variables predicted accuracy, error type (real word vs. non-word and target-error overlap for the PNT data. As lexical variables tend to be highly correlated, we performed a principal components analysis to reduce the variables into five components representing variables associated with phonology (length, phonotactic probability, neighbourhood density and neighbourhood frequency, semantics (imageability and concreteness, usage (frequency and age-of-acquisition, name agreement and visual complexity. Results and Discussion Table 1 shows the components that made a significant contribution to each model. Individuals with jargon aphasia produced more correct responses and fewer non-word errors relative to

  15. Interaction of Instrumental and Goal-Directed Learning Modulates Prediction Error Representations in the Ventral Striatum.

    Science.gov (United States)

    Guo, Rong; Böhmer, Wendelin; Hebart, Martin; Chien, Samson; Sommer, Tobias; Obermayer, Klaus; Gläscher, Jan

    2016-12-14

    Goal-directed and instrumental learning are both important controllers of human behavior. Learning about which stimulus event occurs in the environment and the reward associated with them allows humans to seek out the most valuable stimulus and move through the environment in a goal-directed manner. Stimulus-response associations are characteristic of instrumental learning, whereas response-outcome associations are the hallmark of goal-directed learning. Here we provide behavioral, computational, and neuroimaging results from a novel task in which stimulus-response and response-outcome associations are learned simultaneously but dominate behavior at different stages of the experiment. We found that prediction error representations in the ventral striatum depend on which type of learning dominates. Furthermore, the amygdala tracks the time-dependent weighting of stimulus-response versus response-outcome learning. Our findings suggest that the goal-directed and instrumental controllers dynamically engage the ventral striatum in representing prediction errors whenever one of them is dominating choice behavior. Converging evidence in human neuroimaging studies has shown that the reward prediction errors are correlated with activity in the ventral striatum. Our results demonstrate that this region is simultaneously correlated with a stimulus prediction error. Furthermore, the learning system that is currently dominating behavioral choice dynamically engages the ventral striatum for computing its prediction errors. This demonstrates that the prediction error representations are highly dynamic and influenced by various experimental context. This finding points to a general role of the ventral striatum in detecting expectancy violations and encoding error signals regardless of the specific nature of the reinforcer itself. Copyright © 2016 the authors 0270-6474/16/3612650-11$15.00/0.

  16. Seismic attenuation relationship with homogeneous and heterogeneous prediction-error variance models

    Science.gov (United States)

    Mu, He-Qing; Xu, Rong-Rong; Yuen, Ka-Veng

    2014-03-01

    Peak ground acceleration (PGA) estimation is an important task in earthquake engineering practice. One of the most well-known models is the Boore-Joyner-Fumal formula, which estimates the PGA using the moment magnitude, the site-to-fault distance and the site foundation properties. In the present study, the complexity for this formula and the homogeneity assumption for the prediction-error variance are investigated and an efficiency-robustness balanced formula is proposed. For this purpose, a reduced-order Monte Carlo simulation algorithm for Bayesian model class selection is presented to obtain the most suitable predictive formula and prediction-error model for the seismic attenuation relationship. In this approach, each model class (a predictive formula with a prediction-error model) is evaluated according to its plausibility given the data. The one with the highest plausibility is robust since it possesses the optimal balance between the data fitting capability and the sensitivity to noise. A database of strong ground motion records in the Tangshan region of China is obtained from the China Earthquake Data Center for the analysis. The optimal predictive formula is proposed based on this database. It is shown that the proposed formula with heterogeneous prediction-error variance is much simpler than the attenuation model suggested by Boore, Joyner and Fumal (1993).

  17. Cognitive emotion regulation enhances aversive prediction error activity while reducing emotional responses.

    Science.gov (United States)

    Mulej Bratec, Satja; Xie, Xiyao; Schmid, Gabriele; Doll, Anselm; Schilbach, Leonhard; Zimmer, Claus; Wohlschläger, Afra; Riedl, Valentin; Sorg, Christian

    2015-12-01

    Cognitive emotion regulation is a powerful way of modulating emotional responses. However, despite the vital role of emotions in learning, it is unknown whether the effect of cognitive emotion regulation also extends to the modulation of learning. Computational models indicate prediction error activity, typically observed in the striatum and ventral tegmental area, as a critical neural mechanism involved in associative learning. We used model-based fMRI during aversive conditioning with and without cognitive emotion regulation to test the hypothesis that emotion regulation would affect prediction error-related neural activity in the striatum and ventral tegmental area, reflecting an emotion regulation-related modulation of learning. Our results show that cognitive emotion regulation reduced emotion-related brain activity, but increased prediction error-related activity in a network involving ventral tegmental area, hippocampus, insula and ventral striatum. While the reduction of response activity was related to behavioral measures of emotion regulation success, the enhancement of prediction error-related neural activity was related to learning performance. Furthermore, functional connectivity between the ventral tegmental area and ventrolateral prefrontal cortex, an area involved in regulation, was specifically increased during emotion regulation and likewise related to learning performance. Our data, therefore, provide first-time evidence that beyond reducing emotional responses, cognitive emotion regulation affects learning by enhancing prediction error-related activity, potentially via tegmental dopaminergic pathways. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Haptic Data Processing for Teleoperation Systems: Prediction, Compression and Error Correction

    OpenAIRE

    Lee, Jae-young

    2013-01-01

    This thesis explores haptic data processing methods for teleoperation systems, including prediction, compression, and error correction. In the proposed haptic data prediction method, unreliable network conditions, such as time-varying delay and packet loss, are detected by a transport layer protocol. Given the information from the transport layer, a Bayesian approach is introduced to predict position and force data in haptic teleoperation systems. Stability of the proposed method within stoch...

  19. How we learn to make decisions: rapid propagation of reinforcement learning prediction errors in humans.

    Science.gov (United States)

    Krigolson, Olav E; Hassall, Cameron D; Handy, Todd C

    2014-03-01

    Our ability to make decisions is predicated upon our knowledge of the outcomes of the actions available to us. Reinforcement learning theory posits that actions followed by a reward or punishment acquire value through the computation of prediction errors-discrepancies between the predicted and the actual reward. A multitude of neuroimaging studies have demonstrated that rewards and punishments evoke neural responses that appear to reflect reinforcement learning prediction errors [e.g., Krigolson, O. E., Pierce, L. J., Holroyd, C. B., & Tanaka, J. W. Learning to become an expert: Reinforcement learning and the acquisition of perceptual expertise. Journal of Cognitive Neuroscience, 21, 1833-1840, 2009; Bayer, H. M., & Glimcher, P. W. Midbrain dopamine neurons encode a quantitative reward prediction error signal. Neuron, 47, 129-141, 2005; O'Doherty, J. P. Reward representations and reward-related learning in the human brain: Insights from neuroimaging. Current Opinion in Neurobiology, 14, 769-776, 2004; Holroyd, C. B., & Coles, M. G. H. The neural basis of human error processing: Reinforcement learning, dopamine, and the error-related negativity. Psychological Review, 109, 679-709, 2002]. Here, we used the brain ERP technique to demonstrate that not only do rewards elicit a neural response akin to a prediction error but also that this signal rapidly diminished and propagated to the time of choice presentation with learning. Specifically, in a simple, learnable gambling task, we show that novel rewards elicited a feedback error-related negativity that rapidly decreased in amplitude with learning. Furthermore, we demonstrate the existence of a reward positivity at choice presentation, a previously unreported ERP component that has a similar timing and topography as the feedback error-related negativity that increased in amplitude with learning. The pattern of results we observed mirrored the output of a computational model that we implemented to compute reward

  20. Correction for Measurement Error from Genotyping-by-Sequencing in Genomic Variance and Genomic Prediction Models

    DEFF Research Database (Denmark)

    Ashraf, Bilal; Janss, Luc; Jensen, Just

    sample). The GBSeq data can be used directly in genomic models in the form of individual SNP allele-frequency estimates (e.g., reference reads/total reads per polymorphic site per individual), but is subject to measurement error due to the low sequencing depth per individual. Due to technical reasons....... In the current work we show how the correction for measurement error in GBSeq can also be applied in whole genome genomic variance and genomic prediction models. Bayesian whole-genome random regression models are proposed to allow implementation of large-scale SNP-based models with a per-SNP correction...... for measurement error. We show correct retrieval of genomic explained variance, and improved genomic prediction when accounting for the measurement error in GBSeq data...

  1. Human error prediction and countermeasures based on CREAM in spent nuclear fuel (SNF) transportation

    International Nuclear Information System (INIS)

    Kim, Jae San

    2007-02-01

    Since the 1980s, in order to secure the storage capacity of spent nuclear fuel (SNF) at NPPs, SNF assemblies have been transported on-site from one unit to another unit nearby. However in the future the amount of the spent fuel will approach capacity in the areas used, and some of these SNFs will have to be transported to an off-site spent fuel repository. Most SNF materials used at NPPs will be transported by general cargo ships from abroad, and these SNFs will be stored in an interim storage facility. In the process of transporting SNF, human interactions will involve inspecting and preparing the cask and spent fuel, loading the cask onto the vehicle or ship, transferring the cask as well as storage or monitoring the cask. The transportation of SNF involves a number of activities that depend on reliable human performance. In the case of the transport of a cask, human errors may include spent fuel bundle misidentification or cask transport accidents among others. Reviews of accident events when transporting the Radioactive Material (RAM) throughout the world indicate that human error is the major causes for more than 65% of significant events. For the safety of SNF transportation, it is very important to predict human error and to deduce a method that minimizes the human error. This study examines the human factor effects on the safety of transporting spent nuclear fuel (SNF). It predicts and identifies the possible human errors in the SNF transport process (loading, transfer and storage of the SNF). After evaluating the human error mode in each transport process, countermeasures to minimize the human error are deduced. The human errors in SNF transportation were analyzed using Hollnagel's Cognitive Reliability and Error Analysis Method (CREAM). After determining the important factors for each process, countermeasures to minimize human error are provided in three parts: System design, Operational environment, and Human ability

  2. Advanced error-prediction LDPC with temperature compensation for highly reliable SSDs

    Science.gov (United States)

    Tokutomi, Tsukasa; Tanakamaru, Shuhei; Iwasaki, Tomoko Ogura; Takeuchi, Ken

    2015-09-01

    To improve the reliability of NAND Flash memory based solid-state drives (SSDs), error-prediction LDPC (EP-LDPC) has been proposed for multi-level-cell (MLC) NAND Flash memory (Tanakamaru et al., 2012, 2013), which is effective for long retention times. However, EP-LDPC is not as effective for triple-level cell (TLC) NAND Flash memory, because TLC NAND Flash has higher error rates and is more sensitive to program-disturb error. Therefore, advanced error-prediction LDPC (AEP-LDPC) has been proposed for TLC NAND Flash memory (Tokutomi et al., 2014). AEP-LDPC can correct errors more accurately by precisely describing the error phenomena. In this paper, the effects of AEP-LDPC are investigated in a 2×nm TLC NAND Flash memory with temperature characterization. Compared with LDPC-with-BER-only, the SSD's data-retention time is increased by 3.4× and 9.5× at room-temperature (RT) and 85 °C, respectively. Similarly, the acceptable BER is increased by 1.8× and 2.3×, respectively. Moreover, AEP-LDPC can correct errors with pre-determined tables made at higher temperatures to shorten the measurement time before shipping. Furthermore, it is found that one table can cover behavior over a range of temperatures in AEP-LDPC. As a result, the total table size can be reduced to 777 kBytes, which makes this approach more practical.

  3. Predictive error detection in pianists: A combined ERP and motion capture study

    Directory of Open Access Journals (Sweden)

    Clemens eMaidhof

    2013-09-01

    Full Text Available Performing a piece of music involves the interplay of several cognitive and motor processes and requires extensive training to achieve a high skill level. However, even professional musicians commit errors occasionally. Previous event-related potential (ERP studies have investigated the neurophysiological correlates of pitch errors during piano performance, and reported pre-error negativity already occurring approximately 70-100 ms before the error had been committed and audible. It was assumed that this pre-error negativity reflects predictive control processes that compare predicted consequences with actual consequences of one’s own actions. However, in previous investigations, correct and incorrect pitch events were confounded by their different tempi. In addition, no data about the underlying movements were available. In the present study, we exploratively recorded the ERPs and 3D movement data of pianists’ fingers simultaneously while they performed fingering exercises from memory. Results showed a pre-error negativity for incorrect keystrokes when both correct and incorrect keystrokes were performed with comparable tempi. Interestingly, even correct notes immediately preceding erroneous keystrokes elicited a very similar negativity. In addition, we explored the possibility of computing ERPs time-locked to a kinematic landmark in the finger motion trajectories defined by when a finger makes initial contact with the key surface, that is, at the onset of tactile feedback. Results suggest that incorrect notes elicited a small difference after the onset of tactile feedback, whereas correct notes preceding incorrect ones elicited negativity before the onset of tactile feedback. The results tentatively suggest that tactile feedback plays an important role in error-monitoring during piano performance, because the comparison between predicted and actual sensory (tactile feedback may provide the information necessary for the detection of an

  4. Brain negativity as an indicator of predictive error processing: the contribution of visual action effect monitoring.

    Science.gov (United States)

    Joch, Michael; Hegele, Mathias; Maurer, Heiko; Müller, Hermann; Maurer, Lisa Katharina

    2017-07-01

    The error (related) negativity (Ne/ERN) is an event-related potential in the electroencephalogram (EEG) correlating with error processing. Its conditions of appearance before terminal external error information suggest that the Ne/ERN is indicative of predictive processes in the evaluation of errors. The aim of the present study was to specifically examine the Ne/ERN in a complex motor task and to particularly rule out other explaining sources of the Ne/ERN aside from error prediction processes. To this end, we focused on the dependency of the Ne/ERN on visual monitoring about the action outcome after movement termination but before result feedback (action effect monitoring). Participants performed a semi-virtual throwing task by using a manipulandum to throw a virtual ball displayed on a computer screen to hit a target object. Visual feedback about the ball flying to the target was masked to prevent action effect monitoring. Participants received a static feedback about the action outcome (850 ms) after each trial. We found a significant negative deflection in the average EEG curves of the error trials peaking at ~250 ms after ball release, i.e., before error feedback. Furthermore, this Ne/ERN signal did not depend on visual ball-flight monitoring after release. We conclude that the Ne/ERN has the potential to indicate error prediction in motor tasks and that it exists even in the absence of action effect monitoring. NEW & NOTEWORTHY In this study, we are separating different kinds of possible contributors to an electroencephalogram (EEG) error correlate (Ne/ERN) in a throwing task. We tested the influence of action effect monitoring on the Ne/ERN amplitude in the EEG. We used a task that allows us to restrict movement correction and action effect monitoring and to control the onset of result feedback. We ascribe the Ne/ERN to predictive error processing where a conscious feeling of failure is not a prerequisite. Copyright © 2017 the American Physiological

  5. Error-related brain activity predicts cocaine use after treatment at 3-month follow-up.

    Science.gov (United States)

    Marhe, Reshmi; van de Wetering, Ben J M; Franken, Ingmar H A

    2013-04-15

    Relapse after treatment is one of the most important problems in drug dependency. Several studies suggest that lack of cognitive control is one of the causes of relapse. In this study, a relative new electrophysiologic index of cognitive control, the error-related negativity, is investigated to examine its suitability as a predictor of relapse. The error-related negativity was measured in 57 cocaine-dependent patients during their first week in detoxification treatment. Data from 49 participants were used to predict cocaine use at 3-month follow-up. Cocaine use at follow-up was measured by means of self-reported days of cocaine use in the last month verified by urine screening. A multiple hierarchical regression model was used to examine the predictive value of the error-related negativity while controlling for addiction severity and self-reported craving in the week before treatment. The error-related negativity was the only significant predictor in the model and added 7.4% of explained variance to the control variables, resulting in a total of 33.4% explained variance in the prediction of days of cocaine use at follow-up. A reduced error-related negativity measured during the first week of treatment was associated with more days of cocaine use at 3-month follow-up. Moreover, the error-related negativity was a stronger predictor of recent cocaine use than addiction severity and craving. These results suggest that underactive error-related brain activity might help to identify patients who are at risk of relapse as early as in the first week of detoxification treatment. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  6. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.

    Science.gov (United States)

    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M; Berman, D M; Blume-Jensen, P

    2014-09-09

    Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Prostatectomy samples from a large patient cohort with long follow-up were blindly assessed by expert pathologists who identified the tissue regions with the highest and lowest Gleason grade from each patient. To simulate biopsy-sampling error, a core from a high- and a low-Gleason area from each patient sample was used to generate a 'high' and a 'low' tumour microarray, respectively. Using a quantitative proteomics approach, we identified from 160 candidates 12 biomarkers that predicted prostate cancer aggressiveness (surgical Gleason and TNM stage) and lethal outcome robustly in both high- and low-Gleason areas. Conversely, a previously reported lethal outcome-predictive marker signature for prostatectomy tissue was unable to perform under circumstances of maximal sampling error. Our results have important implications for cancer biomarker discovery in general and development of a sampling error-resistant clinical biopsy test for prediction of prostate cancer aggressiveness.

  7. Predictive error dependencies when using pilot points and singular value decomposition in groundwater model calibration

    DEFF Research Database (Denmark)

    Christensen, Steen; Doherty, John

    2008-01-01

    super parameters), and that the structural errors caused by using pilot points and super parameters to parameterize the highly heterogeneous log-transmissivity field can be significant. For the test case much effort is put into studying how the calibrated model's ability to make accurate predictions...

  8. Prediction error demarcates the transition from retrieval, to reconsolidation, to new learning

    NARCIS (Netherlands)

    Sevenster, Dieuwke|info:eu-repo/dai/nl/375491104; Beckers, Tom; Kindt, Merel

    2014-01-01

    Although disrupting reconsolidation is promising in targeting emotional memories, the conditions under which memory becomes labile are still unclear. The current study showed that post-retrieval changes in expectancy as an index for prediction error may serve as a read-out for the underlying

  9. Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors

    Science.gov (United States)

    McInerney, David; Thyer, Mark; Kavetski, Dmitri; Lerat, Julien; Kuczera, George

    2017-03-01

    Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. This study focuses on approaches for representing error heteroscedasticity with respect to simulated streamflow, i.e., the pattern of larger errors in higher streamflow predictions. We evaluate eight common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter λ) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and the United States, and two lumped hydrological models. Performance is quantified using predictive reliability, precision, and volumetric bias metrics. We find the choice of heteroscedastic error modeling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with λ of 0.2 and 0.5, and the log scheme (λ = 0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Paradoxically, calibration of λ is often counterproductive: in perennial catchments, it tends to overfit low flows at the expense of abysmal precision in high flows. The log-sinh transformation is dominated by the simpler Pareto optimal schemes listed above. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.

  10. Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modelling heteroscedastic residual errors

    Science.gov (United States)

    David, McInerney; Mark, Thyer; Dmitri, Kavetski; George, Kuczera

    2017-04-01

    This study provides guidance to hydrological researchers which enables them to provide probabilistic predictions of daily streamflow with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality). Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. It is commonly known that hydrological model residual errors are heteroscedastic, i.e. there is a pattern of larger errors in higher streamflow predictions. Although multiple approaches exist for representing this heteroscedasticity, few studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating 8 common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter, lambda) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and USA, and two lumped hydrological models. We find the choice of heteroscedastic error modelling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with lambda of 0.2 and 0.5, and the log scheme (lambda=0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.

  11. Early behavioral inhibition and increased error monitoring predict later social phobia symptoms in childhood.

    Science.gov (United States)

    Lahat, Ayelet; Lamm, Connie; Chronis-Tuscano, Andrea; Pine, Daniel S; Henderson, Heather A; Fox, Nathan A

    2014-04-01

    Behavioral inhibition (BI) is an early childhood temperament characterized by fearful responses to novelty and avoidance of social interactions. During adolescence, a subset of children with stable childhood BI develop social anxiety disorder and concurrently exhibit increased error monitoring. The current study examines whether increased error monitoring in 7-year-old, behaviorally inhibited children prospectively predicts risk for symptoms of social phobia at age 9 years. A total of 291 children were characterized on BI at 24 and 36 months of age. Children were seen again at 7 years of age, when they performed a Flanker task, and event-related potential (ERP) indices of response monitoring were generated. At age 9, self- and maternal-report of social phobia symptoms were obtained. Children high in BI, compared to those low in BI, displayed increased error monitoring at age 7, as indexed by larger (i.e., more negative) error-related negativity (ERN) amplitudes. In addition, early BI was related to later childhood social phobia symptoms at age 9 among children with a large difference in amplitude between ERN and correct-response negativity (CRN) at age 7. Heightened error monitoring predicts risk for later social phobia symptoms in children with high BI. Research assessing response monitoring in children with BI may refine our understanding of the mechanisms underlying risk for later anxiety disorders and inform prevention efforts. Copyright © 2014 American Academy of Child and Adolescent Psychiatry. All rights reserved.

  12. Reversible Watermarking Using Prediction-Error Expansion and Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Guangyong Gao

    2015-01-01

    Full Text Available Currently, the research for reversible watermarking focuses on the decreasing of image distortion. Aiming at this issue, this paper presents an improvement method to lower the embedding distortion based on the prediction-error expansion (PE technique. Firstly, the extreme learning machine (ELM with good generalization ability is utilized to enhance the prediction accuracy for image pixel value during the watermarking embedding, and the lower prediction error results in the reduction of image distortion. Moreover, an optimization operation for strengthening the performance of ELM is taken to further lessen the embedding distortion. With two popular predictors, that is, median edge detector (MED predictor and gradient-adjusted predictor (GAP, the experimental results for the classical images and Kodak image set indicate that the proposed scheme achieves improvement for the lowering of image distortion compared with the classical PE scheme proposed by Thodi et al. and outperforms the improvement method presented by Coltuc and other existing approaches.

  13. Practical guidance on representing the heteroscedasticity of residual errors of hydrological predictions

    Science.gov (United States)

    McInerney, David; Thyer, Mark; Kavetski, Dmitri; Kuczera, George

    2016-04-01

    Appropriate representation of residual errors in hydrological modelling is essential for accurate and reliable probabilistic streamflow predictions. In particular, residual errors of hydrological predictions are often heteroscedastic, with large errors associated with high runoff events. Although multiple approaches exist for representing this heteroscedasticity, few if any studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating a range of approaches for representing heteroscedasticity in residual errors. These approaches include the 'direct' weighted least squares approach and 'transformational' approaches, such as logarithmic, Box-Cox (with and without fitting the transformation parameter), logsinh and the inverse transformation. The study reports (1) theoretical comparison of heteroscedasticity approaches, (2) empirical evaluation of heteroscedasticity approaches using a range of multiple catchments / hydrological models / performance metrics and (3) interpretation of empirical results using theory to provide practical guidance on the selection of heteroscedasticity approaches. Importantly, for hydrological practitioners, the results will simplify the choice of approaches to represent heteroscedasticity. This will enhance their ability to provide hydrological probabilistic predictions with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality).

  14. Pupil dilation indicates the coding of past prediction errors: Evidence for attentional learning theory.

    Science.gov (United States)

    Koenig, Stephan; Uengoer, Metin; Lachnit, Harald

    2018-04-01

    The attentional learning theory of Pearce and Hall () predicts more attention to uncertain cues that have caused a high prediction error in the past. We examined how the cue-elicited pupil dilation during associative learning was linked to such error-driven attentional processes. In three experiments, participants were trained to acquire associations between different cues and their appetitive (Experiment 1), motor (Experiment 2), or aversive (Experiment 3) outcomes. All experiments were designed to examine differences in the processing of continuously reinforced cues (consistently followed by the outcome) versus partially reinforced, uncertain cues (randomly followed by the outcome). We measured the pupil dilation elicited by the cues in anticipation of the outcome and analyzed how this conditioned pupil response changed over the course of learning. In all experiments, changes in pupil size complied with the same basic pattern: During early learning, consistently reinforced cues elicited greater pupil dilation than uncertain, randomly reinforced cues, but this effect gradually reversed to yield a greater pupil dilation for uncertain cues toward the end of learning. The pattern of data accords with the changes in prediction error and error-driven attention formalized by the Pearce-Hall theory. © 2017 The Authors. Psychophysiology published by Wiley Periodicals, Inc. on behalf of Society for Psychophysiological Research.

  15. Predicting diagnostic error in Radiology via eye-tracking and image analytics: Application in mammography

    Energy Technology Data Exchange (ETDEWEB)

    Voisin, Sophie [ORNL; Pinto, Frank M [ORNL; Morin-Ducote, Garnetta [University of Tennessee, Knoxville (UTK); Hudson, Kathy [University of Tennessee, Knoxville (UTK); Tourassi, Georgia [ORNL

    2013-01-01

    Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels. Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from 4 Radiology residents and 2 breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADs images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated. Results: Diagnostic error can be predicted reliably by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model (AUC=0.79). Personalized user modeling was far more accurate for the more experienced readers (average AUC of 0.837 0.029) than for the less experienced ones (average AUC of 0.667 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features. Conclusions: Diagnostic errors in mammography can be predicted reliably by leveraging the radiologists gaze behavior and image content.

  16. Predicting diagnostic error in radiology via eye-tracking and image analytics: Preliminary investigation in mammography

    Energy Technology Data Exchange (ETDEWEB)

    Voisin, Sophie; Tourassi, Georgia D. [Biomedical Science and Engineering Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Pinto, Frank [School of Engineering, Science, and Technology, Virginia State University, Petersburg, Virginia 23806 (United States); Morin-Ducote, Garnetta; Hudson, Kathleen B. [Department of Radiology, University of Tennessee Medical Center at Knoxville, Knoxville, Tennessee 37920 (United States)

    2013-10-15

    Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists’ gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels.Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from four Radiology residents and two breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADS images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated.Results: Machine learning can be used to predict diagnostic error by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model [area under the ROC curve (AUC) = 0.792 ± 0.030]. Personalized user modeling was far more accurate for the more experienced readers (AUC = 0.837 ± 0.029) than for the less experienced ones (AUC = 0.667 ± 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features.Conclusions: Diagnostic errors in mammography can be predicted to a good extent by leveraging the radiologists’ gaze behavior and image content.

  17. Predicting diagnostic error in radiology via eye-tracking and image analytics: Preliminary investigation in mammography

    International Nuclear Information System (INIS)

    Voisin, Sophie; Tourassi, Georgia D.; Pinto, Frank; Morin-Ducote, Garnetta; Hudson, Kathleen B.

    2013-01-01

    Purpose: The primary aim of the present study was to test the feasibility of predicting diagnostic errors in mammography by merging radiologists’ gaze behavior and image characteristics. A secondary aim was to investigate group-based and personalized predictive models for radiologists of variable experience levels.Methods: The study was performed for the clinical task of assessing the likelihood of malignancy of mammographic masses. Eye-tracking data and diagnostic decisions for 40 cases were acquired from four Radiology residents and two breast imaging experts as part of an IRB-approved pilot study. Gaze behavior features were extracted from the eye-tracking data. Computer-generated and BIRADS images features were extracted from the images. Finally, machine learning algorithms were used to merge gaze and image features for predicting human error. Feature selection was thoroughly explored to determine the relative contribution of the various features. Group-based and personalized user modeling was also investigated.Results: Machine learning can be used to predict diagnostic error by merging gaze behavior characteristics from the radiologist and textural characteristics from the image under review. Leveraging data collected from multiple readers produced a reasonable group model [area under the ROC curve (AUC) = 0.792 ± 0.030]. Personalized user modeling was far more accurate for the more experienced readers (AUC = 0.837 ± 0.029) than for the less experienced ones (AUC = 0.667 ± 0.099). The best performing group-based and personalized predictive models involved combinations of both gaze and image features.Conclusions: Diagnostic errors in mammography can be predicted to a good extent by leveraging the radiologists’ gaze behavior and image content

  18. Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors

    Energy Technology Data Exchange (ETDEWEB)

    Nelms, Benjamin E.; Zhen Heming; Tome, Wolfgang A. [Canis Lupus LLC and Department of Human Oncology, University of Wisconsin, Merrimac, Wisconsin 53561 (United States); Department of Medical Physics, University of Wisconsin, Madison, Wisconsin 53705 (United States); Departments of Human Oncology, Medical Physics, and Biomedical Engineering, University of Wisconsin, Madison, Wisconsin 53792 (United States)

    2011-02-15

    Purpose: The purpose of this work is to determine the statistical correlation between per-beam, planar IMRT QA passing rates and several clinically relevant, anatomy-based dose errors for per-patient IMRT QA. The intent is to assess the predictive power of a common conventional IMRT QA performance metric, the Gamma passing rate per beam. Methods: Ninety-six unique data sets were created by inducing four types of dose errors in 24 clinical head and neck IMRT plans, each planned with 6 MV Varian 120-leaf MLC linear accelerators using a commercial treatment planning system and step-and-shoot delivery. The error-free beams/plans were used as ''simulated measurements'' (for generating the IMRT QA dose planes and the anatomy dose metrics) to compare to the corresponding data calculated by the error-induced plans. The degree of the induced errors was tuned to mimic IMRT QA passing rates that are commonly achieved using conventional methods. Results: Analysis of clinical metrics (parotid mean doses, spinal cord max and D1cc, CTV D95, and larynx mean) vs IMRT QA Gamma analysis (3%/3 mm, 2/2, 1/1) showed that in all cases, there were only weak to moderate correlations (range of Pearson's r-values: -0.295 to 0.653). Moreover, the moderate correlations actually had positive Pearson's r-values (i.e., clinically relevant metric differences increased with increasing IMRT QA passing rate), indicating that some of the largest anatomy-based dose differences occurred in the cases of high IMRT QA passing rates, which may be called ''false negatives.'' The results also show numerous instances of false positives or cases where low IMRT QA passing rates do not imply large errors in anatomy dose metrics. In none of the cases was there correlation consistent with high predictive power of planar IMRT passing rates, i.e., in none of the cases did high IMRT QA Gamma passing rates predict low errors in anatomy dose metrics or vice versa

  19. A Conceptual Framework for Predicting Error in Complex Human-Machine Environments

    Science.gov (United States)

    Freed, Michael; Remington, Roger; Null, Cynthia H. (Technical Monitor)

    1998-01-01

    We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely.

  20. Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors

    International Nuclear Information System (INIS)

    Nelms, Benjamin E.; Zhen Heming; Tome, Wolfgang A.

    2011-01-01

    Purpose: The purpose of this work is to determine the statistical correlation between per-beam, planar IMRT QA passing rates and several clinically relevant, anatomy-based dose errors for per-patient IMRT QA. The intent is to assess the predictive power of a common conventional IMRT QA performance metric, the Gamma passing rate per beam. Methods: Ninety-six unique data sets were created by inducing four types of dose errors in 24 clinical head and neck IMRT plans, each planned with 6 MV Varian 120-leaf MLC linear accelerators using a commercial treatment planning system and step-and-shoot delivery. The error-free beams/plans were used as ''simulated measurements'' (for generating the IMRT QA dose planes and the anatomy dose metrics) to compare to the corresponding data calculated by the error-induced plans. The degree of the induced errors was tuned to mimic IMRT QA passing rates that are commonly achieved using conventional methods. Results: Analysis of clinical metrics (parotid mean doses, spinal cord max and D1cc, CTV D95, and larynx mean) vs IMRT QA Gamma analysis (3%/3 mm, 2/2, 1/1) showed that in all cases, there were only weak to moderate correlations (range of Pearson's r-values: -0.295 to 0.653). Moreover, the moderate correlations actually had positive Pearson's r-values (i.e., clinically relevant metric differences increased with increasing IMRT QA passing rate), indicating that some of the largest anatomy-based dose differences occurred in the cases of high IMRT QA passing rates, which may be called ''false negatives.'' The results also show numerous instances of false positives or cases where low IMRT QA passing rates do not imply large errors in anatomy dose metrics. In none of the cases was there correlation consistent with high predictive power of planar IMRT passing rates, i.e., in none of the cases did high IMRT QA Gamma passing rates predict low errors in anatomy dose metrics or vice versa. Conclusions: There is a lack of correlation between

  1. Motivational state controls the prediction error in Pavlovian appetitive-aversive interactions.

    Science.gov (United States)

    Laurent, Vincent; Balleine, Bernard W; Westbrook, R Frederick

    2018-01-01

    Contemporary theories of learning emphasize the role of a prediction error signal in driving learning, but the nature of this signal remains hotly debated. Here, we used Pavlovian conditioning in rats to investigate whether primary motivational and emotional states interact to control prediction error. We initially generated cues that positively or negatively predicted an appetitive food outcome. We then assessed how these cues modulated aversive conditioning when a novel cue was paired with a foot shock. We found that a positive predictor of food enhances, whereas a negative predictor of that same food impairs, aversive conditioning. Critically, we also showed that the enhancement produced by the positive predictor is removed by reducing the value of its associated food. In contrast, the impairment triggered by the negative predictor remains insensitive to devaluation of its associated food. These findings provide compelling evidence that the motivational value attributed to a predicted food outcome can directly control appetitive-aversive interactions and, therefore, that motivational processes can modulate emotional processes to generate the final error term on which subsequent learning is based. Copyright © 2017 Elsevier Inc. All rights reserved.

  2. Different populations of subthalamic neurons encode cocaine vs. sucrose reward and predict future error.

    Science.gov (United States)

    Lardeux, Sylvie; Paleressompoulle, Dany; Pernaud, Remy; Cador, Martine; Baunez, Christelle

    2013-10-01

    The search for treatment of cocaine addiction raises the challenge to find a way to diminish motivation for the drug without decreasing it for natural rewards. Subthalamic nucleus (STN) inactivation decreases motivation for cocaine while increasing motivation for food, suggesting that STN can dissociate different rewards. Here, we investigated how rat STN neurons respond to cues predicting cocaine or sucrose and to reward delivery while rats are performing a discriminative stimuli task. We show that different neuronal populations of STN neurons encode cocaine and sucrose. In addition, we show that STN activity at the cue onset predicts future error. When changing the reward predicted unexpectedly, STN neurons show capacities of adaptation, suggesting a role in reward-prediction error. Furthermore, some STN neurons show a response to executive error (i.e., "oops neurons") that is specific to the missed reward. These results position the STN as a nexus where natural rewards and drugs of abuse are coded differentially and can influence the performance. Therefore, STN can be viewed as a structure where action could be taken for the treatment of cocaine addiction.

  3. Dopamine prediction errors in reward learning and addiction: from theory to neural circuitry

    Science.gov (United States)

    Keiflin, Ronald; Janak, Patricia H.

    2015-01-01

    Summary Midbrain dopamine (DA) neurons are proposed to signal reward prediction error (RPE), a fundamental parameter in associative learning models. This RPE hypothesis provides a compelling theoretical framework for understanding DA function in reward learning and addiction. New studies support a causal role for DA-mediated RPE activity in promoting learning about natural reward; however, this question has not been explicitly tested in the context of drug addiction. In this review, we integrate theoretical models with experimental findings on the activity of DA systems, and on the causal role of specific neuronal projections and cell types, to provide a circuit-based framework for probing DA-RPE function in addiction. By examining error-encoding DA neurons in the neural network in which they are embedded, hypotheses regarding circuit-level adaptations that possibly contribute to pathological error-signaling and addiction can be formulated and tested. PMID:26494275

  4. Dopamine Prediction Errors in Reward Learning and Addiction: From Theory to Neural Circuitry.

    Science.gov (United States)

    Keiflin, Ronald; Janak, Patricia H

    2015-10-21

    Midbrain dopamine (DA) neurons are proposed to signal reward prediction error (RPE), a fundamental parameter in associative learning models. This RPE hypothesis provides a compelling theoretical framework for understanding DA function in reward learning and addiction. New studies support a causal role for DA-mediated RPE activity in promoting learning about natural reward; however, this question has not been explicitly tested in the context of drug addiction. In this review, we integrate theoretical models with experimental findings on the activity of DA systems, and on the causal role of specific neuronal projections and cell types, to provide a circuit-based framework for probing DA-RPE function in addiction. By examining error-encoding DA neurons in the neural network in which they are embedded, hypotheses regarding circuit-level adaptations that possibly contribute to pathological error signaling and addiction can be formulated and tested. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. A machine learning approach to the accurate prediction of multi-leaf collimator positional errors

    Science.gov (United States)

    Carlson, Joel N. K.; Park, Jong Min; Park, So-Yeon; In Park, Jong; Choi, Yunseok; Ye, Sung-Joon

    2016-03-01

    Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD  =  1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be

  6. Development and performance evaluation of a prototype system for prediction of the group error at the maintenance work

    International Nuclear Information System (INIS)

    Yoshino, Kenji; Hirotsu, Yuko

    2000-01-01

    In order to attain zero-izing of much more error rather than it can set to a nuclear power plant, Authors development and its system-izing of the error prediction causal model which predicts group error action at the time of maintenance work were performed. This prototype system has the following feature. (1) When a user inputs the existence and the grade of the existence of the 'feature factor of the maintenance work' as a prediction object, 'an organization and an organization factor', and a 'group PSF (Performance Shaping Factor) factor' into this system. The maintenance group error to target can be predicted through the prediction model which consists of a class of seven stages. (2) This system by utilizing the information on a prediction result database, it can use not only for prediction of a maintenance group error but for various safe activity, such as KYT (dangerous forecast training) and TBM (Tool Box Meeting). (3) This system predicts a cooperation error' at highest rate, and, subsequently predicts the detection error' at a high rate. And to the 'decision-making error', the transfer error' and the 'state cognitive error', it has the characteristic predicted at almost same rate. (4) If it has full knowledge even of the features, such as the enforcement conditions of maintenance work, and organization, even if the user has neither the knowledge about a human factor, nor experience, anyone of this system is slight about the existence, its extent, etc. of generating of a maintenance group error made difficult from the former logically and systematically easily, it can predict in business time for about 15 minutes. (author)

  7. Influence of precision of emission characteristic parameters on model prediction error of VOCs/formaldehyde from dry building material.

    Directory of Open Access Journals (Sweden)

    Wenjuan Wei

    Full Text Available Mass transfer models are useful in predicting the emissions of volatile organic compounds (VOCs and formaldehyde from building materials in indoor environments. They are also useful for human exposure evaluation and in sustainable building design. The measurement errors in the emission characteristic parameters in these mass transfer models, i.e., the initial emittable concentration (C 0, the diffusion coefficient (D, and the partition coefficient (K, can result in errors in predicting indoor VOC and formaldehyde concentrations. These errors have not yet been quantitatively well analyzed in the literature. This paper addresses this by using modelling to assess these errors for some typical building conditions. The error in C 0, as measured in environmental chambers and applied to a reference living room in Beijing, has the largest influence on the model prediction error in indoor VOC and formaldehyde concentration, while the error in K has the least effect. A correlation between the errors in D, K, and C 0 and the error in the indoor VOC and formaldehyde concentration prediction is then derived for engineering applications. In addition, the influence of temperature on the model prediction of emissions is investigated. It shows the impact of temperature fluctuations on the prediction errors in indoor VOC and formaldehyde concentrations to be less than 7% at 23±0.5°C and less than 30% at 23±2°C.

  8. Predicting areas of sustainable error growth in quasigeostrophic flows using perturbation alignment properties

    Science.gov (United States)

    Rivière, G.; Hua, B. L.

    2004-10-01

    A new perturbation initialization method is used to quantify error growth due to inaccuracies of the forecast model initial conditions in a quasigeostrophic box ocean model describing a wind-driven double gyre circulation. This method is based on recent analytical results on Lagrangian alignment dynamics of the perturbation velocity vector in quasigeostrophic flows. More specifically, it consists in initializing a unique perturbation from the sole knowledge of the control flow properties at the initial time of the forecast and whose velocity vector orientation satisfies a Lagrangian equilibrium criterion. This Alignment-based Initialization method is hereafter denoted as the AI method.In terms of spatial distribution of the errors, we have compared favorably the AI error forecast with the mean error obtained with a Monte-Carlo ensemble prediction. It is shown that the AI forecast is on average as efficient as the error forecast initialized with the leading singular vector for the palenstrophy norm, and significantly more efficient than that for total energy and enstrophy norms. Furthermore, a more precise examination shows that the AI forecast is systematically relevant for all control flows whereas the palenstrophy singular vector forecast leads sometimes to very good scores and sometimes to very bad ones.A principal component analysis at the final time of the forecast shows that the AI mode spatial structure is comparable to that of the first eigenvector of the error covariance matrix for a "bred mode" ensemble. Furthermore, the kinetic energy of the AI mode grows at the same constant rate as that of the "bred modes" from the initial time to the final time of the forecast and is therefore characterized by a sustained phase of error growth. In this sense, the AI mode based on Lagrangian dynamics of the perturbation velocity orientation provides a rationale of the "bred mode" behavior.

  9. Predicting the outcomes of performance error indicators on accreditation status in the nuclear power industry

    International Nuclear Information System (INIS)

    Wilson, P.A.

    1986-01-01

    The null hypothesis for this study suggested that there was no significant difference in the types of performance error indicators between accredited and non-accredited programs on the following types of indicators: (1) number of significant event reports per unit, (2) number of forced outages per unit, (3) number of unplanned automatic scrams per unit, and (4) amount of equivalent availability per unit. A sample of 90 nuclear power plants was selected for this study. Data were summarized from two data bases maintained by the Institute of Nuclear Power Operations. Results of this study did not support the research hypothesis. There was no significant difference between the accredited and non-accredited programs on any of the four performance error indicators. The primary conclusions of this include the following: (1) The four selected performance error indicators cannot be used individually or collectively to predict accreditation status in the nuclear power industry. (2) Annual performance error indicator ratings cannot be used to determine the effects of performance-based training on plant performance. (3) The four selected performance error indicators cannot be used to measure the effect of operator job performance on plant effectiveness

  10. Prediction of Monte Carlo errors by a theory generalized to treat track-length estimators

    International Nuclear Information System (INIS)

    Booth, T.E.; Amster, H.J.

    1978-01-01

    Present theories for predicting expected Monte Carlo errors in neutron transport calculations apply to estimates of flux-weighted integrals sampled directly by scoring individual collisions. To treat track-length estimators, the recent theory of Amster and Djomehri is generalized to allow the score distribution functions to depend on the coordinates of two successive collisions. It has long been known that the expected track length in a region of phase space equals the expected flux integrated over that region, but that the expected statistical error of the Monte Carlo estimate of the track length is different from that of the flux integral obtained by sampling the sum of the reciprocals of the cross sections for all collisions in the region. These conclusions are shown to be implied by the generalized theory, which provides explicit equations for the expected values and errors of both types of estimators. Sampling expected contributions to the track-length estimator is also treated. Other general properties of the errors for both estimators are derived from the equations and physically interpreted. The actual values of these errors are then obtained and interpreted for a simple specific example

  11. Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error

    OpenAIRE

    Shipitsin, M; Small, C; Choudhury, S; Giladi, E; Friedlander, S; Nardone, J; Hussain, S; Hurley, A D; Ernst, C; Huang, Y E; Chang, H; Nifong, T P; Rimm, D L; Dunyak, J; Loda, M

    2014-01-01

    Background: Key challenges of biopsy-based determination of prostate cancer aggressiveness include tumour heterogeneity, biopsy-sampling error, and variations in biopsy interpretation. The resulting uncertainty in risk assessment leads to significant overtreatment, with associated costs and morbidity. We developed a performance-based strategy to identify protein biomarkers predictive of prostate cancer aggressiveness and lethality regardless of biopsy-sampling variation. Methods: Prostatectom...

  12. Safety analysis methodology with assessment of the impact of the prediction errors of relevant parameters

    International Nuclear Information System (INIS)

    Galia, A.V.

    2011-01-01

    The best estimate plus uncertainty approach (BEAU) requires the use of extensive resources and therefore it is usually applied for cases in which the available safety margin obtained with a conservative methodology can be questioned. Outside the BEAU methodology, there is not a clear approach on how to deal with the issue of considering the uncertainties resulting from prediction errors in the safety analyses performed for licensing submissions. However, the regulatory document RD-310 mentions that the analysis method shall account for uncertainties in the analysis data and models. A possible approach is presented, that is simple and reasonable, representing just the author's views, to take into account the impact of prediction errors and other uncertainties when performing safety analysis in line with regulatory requirements. The approach proposes taking into account the prediction error of relevant parameters. Relevant parameters would be those plant parameters that are surveyed and are used to initiate the action of a mitigating system or those that are representative of the most challenging phenomena for the integrity of a fission barrier. Examples of the application of the methodology are presented involving a comparison between the results with the new approach and a best estimate calculation during the blowdown phase for two small breaks in a generic CANDU 6 station. The calculations are performed with the CATHENA computer code. (author)

  13. Dissociable neural representations of reinforcement and belief prediction errors underlie strategic learning.

    Science.gov (United States)

    Zhu, Lusha; Mathewson, Kyle E; Hsu, Ming

    2012-01-31

    Decision-making in the presence of other competitive intelligent agents is fundamental for social and economic behavior. Such decisions require agents to behave strategically, where in addition to learning about the rewards and punishments available in the environment, they also need to anticipate and respond to actions of others competing for the same rewards. However, whereas we know much about strategic learning at both theoretical and behavioral levels, we know relatively little about the underlying neural mechanisms. Here, we show using a multi-strategy competitive learning paradigm that strategic choices can be characterized by extending the reinforcement learning (RL) framework to incorporate agents' beliefs about the actions of their opponents. Furthermore, using this characterization to generate putative internal values, we used model-based functional magnetic resonance imaging to investigate neural computations underlying strategic learning. We found that the distinct notions of prediction errors derived from our computational model are processed in a partially overlapping but distinct set of brain regions. Specifically, we found that the RL prediction error was correlated with activity in the ventral striatum. In contrast, activity in the ventral striatum, as well as the rostral anterior cingulate (rACC), was correlated with a previously uncharacterized belief-based prediction error. Furthermore, activity in rACC reflected individual differences in degree of engagement in belief learning. These results suggest a model of strategic behavior where learning arises from interaction of dissociable reinforcement and belief-based inputs.

  14. Effect of heteroscedasticity treatment in residual error models on model calibration and prediction uncertainty estimation

    Science.gov (United States)

    Sun, Ruochen; Yuan, Huiling; Liu, Xiaoli

    2017-11-01

    The heteroscedasticity treatment in residual error models directly impacts the model calibration and prediction uncertainty estimation. This study compares three methods to deal with the heteroscedasticity, including the explicit linear modeling (LM) method and nonlinear modeling (NL) method using hyperbolic tangent function, as well as the implicit Box-Cox transformation (BC). Then a combined approach (CA) combining the advantages of both LM and BC methods has been proposed. In conjunction with the first order autoregressive model and the skew exponential power (SEP) distribution, four residual error models are generated, namely LM-SEP, NL-SEP, BC-SEP and CA-SEP, and their corresponding likelihood functions are applied to the Variable Infiltration Capacity (VIC) hydrologic model over the Huaihe River basin, China. Results show that the LM-SEP yields the poorest streamflow predictions with the widest uncertainty band and unrealistic negative flows. The NL and BC methods can better deal with the heteroscedasticity and hence their corresponding predictive performances are improved, yet the negative flows cannot be avoided. The CA-SEP produces the most accurate predictions with the highest reliability and effectively avoids the negative flows, because the CA approach is capable of addressing the complicated heteroscedasticity over the study basin.

  15. Learning Similar Actions by Reinforcement or Sensory-Prediction Errors Rely on Distinct Physiological Mechanisms.

    Science.gov (United States)

    Uehara, Shintaro; Mawase, Firas; Celnik, Pablo

    2017-09-14

    Humans can acquire knowledge of new motor behavior via different forms of learning. The two forms most commonly studied have been the development of internal models based on sensory-prediction errors (error-based learning) and success-based feedback (reinforcement learning). Human behavioral studies suggest these are distinct learning processes, though the neurophysiological mechanisms that are involved have not been characterized. Here, we evaluated physiological markers from the cerebellum and the primary motor cortex (M1) using noninvasive brain stimulations while healthy participants trained finger-reaching tasks. We manipulated the extent to which subjects rely on error-based or reinforcement by providing either vector or binary feedback about task performance. Our results demonstrated a double dissociation where learning the task mainly via error-based mechanisms leads to cerebellar plasticity modifications but not long-term potentiation (LTP)-like plasticity changes in M1; while learning a similar action via reinforcement mechanisms elicited M1 LTP-like plasticity but not cerebellar plasticity changes. Our findings indicate that learning complex motor behavior is mediated by the interplay of different forms of learning, weighing distinct neural mechanisms in M1 and the cerebellum. Our study provides insights for designing effective interventions to enhance human motor learning. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  16. Quantifying the predictive consequences of model error with linear subspace analysis

    Science.gov (United States)

    White, Jeremy T.; Doherty, John E.; Hughes, Joseph D.

    2014-01-01

    All computer models are simplified and imperfect simulators of complex natural systems. The discrepancy arising from simplification induces bias in model predictions, which may be amplified by the process of model calibration. This paper presents a new method to identify and quantify the predictive consequences of calibrating a simplified computer model. The method is based on linear theory, and it scales efficiently to the large numbers of parameters and observations characteristic of groundwater and petroleum reservoir models. The method is applied to a range of predictions made with a synthetic integrated surface-water/groundwater model with thousands of parameters. Several different observation processing strategies and parameterization/regularization approaches are examined in detail, including use of the Karhunen-Loève parameter transformation. Predictive bias arising from model error is shown to be prediction specific and often invisible to the modeler. The amount of calibration-induced bias is influenced by several factors, including how expert knowledge is applied in the design of parameterization schemes, the number of parameters adjusted during calibration, how observations and model-generated counterparts are processed, and the level of fit with observations achieved through calibration. Failure to properly implement any of these factors in a prediction-specific manner may increase the potential for predictive bias in ways that are not visible to the calibration and uncertainty analysis process.

  17. Study on the methodology for predicting and preventing errors to improve reliability of maintenance task in nuclear power plant

    International Nuclear Information System (INIS)

    Hanafusa, Hidemitsu; Iwaki, Toshio; Embrey, D.

    2000-01-01

    The objective of this study was to develop and effective methodology for predicting and preventing errors in nuclear power plant maintenance tasks. A method was established by which chief maintenance personnel can predict and reduce errors when reviewing the maintenance procedures and while referring to maintenance supporting systems and methods in other industries including aviation and chemical plant industries. The method involves the following seven steps: 1. Identification of maintenance tasks. 2. Specification of important tasks affecting safety. 3. Assessment of human errors occurring during important tasks. 4. Identification of Performance Degrading Factors. 5. Dividing important tasks into sub-tasks. 6. Extraction of errors using Predictive Human Error Analysis (PHEA). 7. Development of strategies for reducing errors and for recovering from errors. By way of a trial, this method was applied to the pump maintenance procedure in nuclear power plants. This method is believed to be capable of identifying the expected errors in important tasks and supporting the development of error reduction measures. By applying this method, the number of accidents resulting form human errors during maintenance can be reduced. Moreover, the maintenance support base using computers was developed. (author)

  18. Recursive prediction error methods for online estimation in nonlinear state-space models

    Directory of Open Access Journals (Sweden)

    Dag Ljungquist

    1994-04-01

    Full Text Available Several recursive algorithms for online, combined state and parameter estimation in nonlinear state-space models are discussed in this paper. Well-known algorithms such as the extended Kalman filter and alternative formulations of the recursive prediction error method are included, as well as a new method based on a line-search strategy. A comparison of the algorithms illustrates that they are very similar although the differences can be important for the online tracking capabilities and robustness. Simulation experiments on a simple nonlinear process show that the performance under certain conditions can be improved by including a line-search strategy.

  19. Suppressing my memories by listening to yours: The effect of socially triggered context-based prediction error on memory.

    Science.gov (United States)

    Vlasceanu, Madalina; Drach, Rae; Coman, Alin

    2018-05-03

    The mind is a prediction machine. In most situations, it has expectations as to what might happen. But when predictions are invalidated by experience (i.e., prediction errors), the memories that generate these predictions are suppressed. Here, we explore the effect of prediction error on listeners' memories following social interaction. We find that listening to a speaker recounting experiences similar to one's own triggers prediction errors on the part of the listener that lead to the suppression of her memories. This effect, we show, is sensitive to a perspective-taking manipulation, such that individuals who are instructed to take the perspective of the speaker experience memory suppression, whereas individuals who undergo a low-perspective-taking manipulation fail to show a mnemonic suppression effect. We discuss the relevance of these findings for our understanding of the bidirectional influences between cognition and social contexts, as well as for the real-world situations that involve memory-based predictions.

  20. Chronology of prescribing error during the hospital stay and prediction of pharmacist's alerts overriding: a prospective analysis

    Directory of Open Access Journals (Sweden)

    Bruni Vanida

    2010-01-01

    Full Text Available Abstract Background Drug prescribing errors are frequent in the hospital setting and pharmacists play an important role in detection of these errors. The objectives of this study are (1 to describe the drug prescribing errors rate during the patient's stay, (2 to find which characteristics for a prescribing error are the most predictive of their reproduction the next day despite pharmacist's alert (i.e. override the alert. Methods We prospectively collected all medication order lines and prescribing errors during 18 days in 7 medical wards' using computerized physician order entry. We described and modelled the errors rate according to the chronology of hospital stay. We performed a classification and regression tree analysis to find which characteristics of alerts were predictive of their overriding (i.e. prescribing error repeated. Results 12 533 order lines were reviewed, 117 errors (errors rate 0.9% were observed and 51% of these errors occurred on the first day of the hospital stay. The risk of a prescribing error decreased over time. 52% of the alerts were overridden (i.e error uncorrected by prescribers on the following day. Drug omissions were the most frequently taken into account by prescribers. The classification and regression tree analysis showed that overriding pharmacist's alerts is first related to the ward of the prescriber and then to either Anatomical Therapeutic Chemical class of the drug or the type of error. Conclusions Since 51% of prescribing errors occurred on the first day of stay, pharmacist should concentrate his analysis of drug prescriptions on this day. The difference of overriding behavior between wards and according drug Anatomical Therapeutic Chemical class or type of error could also guide the validation tasks and programming of electronic alerts.

  1. Model structural uncertainty quantification and hydrologic parameter and prediction error analysis using airborne electromagnetic data

    DEFF Research Database (Denmark)

    Minsley, B. J.; Christensen, Nikolaj Kruse; Christensen, Steen

    Model structure, or the spatial arrangement of subsurface lithological units, is fundamental to the hydrological behavior of Earth systems. Knowledge of geological model structure is critically important in order to make informed hydrological predictions and management decisions. Model structure...... is never perfectly known, however, and incorrect assumptions can be a significant source of error when making model predictions. We describe a systematic approach for quantifying model structural uncertainty that is based on the integration of sparse borehole observations and large-scale airborne...... electromagnetic (AEM) data. Our estimates of model structural uncertainty follow a Bayesian framework that accounts for both the uncertainties in geophysical parameter estimates given AEM data, and the uncertainties in the relationship between lithology and geophysical parameters. Using geostatistical sequential...

  2. What roles do errors serve in motor skill learning? An examination of two theoretical predictions.

    Science.gov (United States)

    Sanli, Elizabeth A; Lee, Timothy D

    2014-01-01

    Easy-to-difficult and difficult-to-easy progressions of task difficulty during skill acquisition were examined in 2 experiments that assessed retention, dual-task, and transfer tests of learning. Findings of the first experiment suggest that an easy-to difficult progression did not consistently induce implicit learning processes and was not consistently beneficial to performance under a secondary-task load. The findings of experiment two did not support the predictions made based on schema theory and only partially supported predictions based on reinvestment theory. The authors interpret these findings to suggest that the timing of error in relation to the difficulty of the task (functional task difficulty) plays a role in the transfer of learning to novel versions of a task.

  3. The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

    Science.gov (United States)

    Butcher, Peter A; Ivry, Richard B; Kuo, Sheng-Han; Rydz, David; Krakauer, John W; Taylor, Jordan A

    2017-09-01

    Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly ( experiment 1 ) or gradually ( experiment 2 ). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability ( experiment 3 ). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials. NEW & NOTEWORTHY Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory

  4. Current error vector based prediction control of the section winding permanent magnet linear synchronous motor

    Energy Technology Data Exchange (ETDEWEB)

    Hong Junjie, E-mail: hongjjie@mail.sysu.edu.cn [School of Engineering, Sun Yat-Sen University, Guangzhou 510006 (China); Li Liyi, E-mail: liliyi@hit.edu.cn [Dept. Electrical Engineering, Harbin Institute of Technology, Harbin 150000 (China); Zong Zhijian; Liu Zhongtu [School of Engineering, Sun Yat-Sen University, Guangzhou 510006 (China)

    2011-10-15

    Highlights: {yields} The structure of the permanent magnet linear synchronous motor (SW-PMLSM) is new. {yields} A new current control method CEVPC is employed in this motor. {yields} The sectional power supply method is different to the others and effective. {yields} The performance gets worse with voltage and current limitations. - Abstract: To include features such as greater thrust density, higher efficiency without reducing the thrust stability, this paper proposes a section winding permanent magnet linear synchronous motor (SW-PMLSM), whose iron core is continuous, whereas winding is divided. The discrete system model of the motor is derived. With the definition of the current error vector and selection of the value function, the theory of the current error vector based prediction control (CEVPC) for the motor currents is explained clearly. According to the winding section feature, the motion region of the mover is divided into five zones, in which the implementation of the current predictive control method is proposed. Finally, the experimental platform is constructed and experiments are carried out. The results show: the current control effect has good dynamic response, and the thrust on the mover remains constant basically.

  5. Tax revenue and inflation rate predictions in Banda Aceh using Vector Error Correction Model (VECM)

    Science.gov (United States)

    Maulia, Eva; Miftahuddin; Sofyan, Hizir

    2018-05-01

    A country has some important parameters to achieve the welfare of the economy, such as tax revenues and inflation. One of the largest revenues of the state budget in Indonesia comes from the tax sector. Besides, the rate of inflation occurring in a country can be used as one measure, to measure economic problems that the country facing. Given the importance of tax revenue and inflation rate control in achieving economic prosperity, it is necessary to analyze the relationship and forecasting tax revenue and inflation rate. VECM (Vector Error Correction Model) was chosen as the method used in this research, because of the data used in the form of multivariate time series data. This study aims to produce a VECM model with optimal lag and to predict the tax revenue and inflation rate of the VECM model. The results show that the best model for data of tax revenue and the inflation rate in Banda Aceh City is VECM with 3rd optimal lag or VECM (3). Of the seven models formed, there is a significant model that is the acceptance model of income tax. The predicted results of tax revenue and the inflation rate in Kota Banda Aceh for the next 6, 12 and 24 periods (months) obtained using VECM (3) are considered valid, since they have a minimum error value compared to other models.

  6. Neural prediction errors reveal a risk-sensitive reinforcement-learning process in the human brain.

    Science.gov (United States)

    Niv, Yael; Edlund, Jeffrey A; Dayan, Peter; O'Doherty, John P

    2012-01-11

    Humans and animals are exquisitely, though idiosyncratically, sensitive to risk or variance in the outcomes of their actions. Economic, psychological, and neural aspects of this are well studied when information about risk is provided explicitly. However, we must normally learn about outcomes from experience, through trial and error. Traditional models of such reinforcement learning focus on learning about the mean reward value of cues and ignore higher order moments such as variance. We used fMRI to test whether the neural correlates of human reinforcement learning are sensitive to experienced risk. Our analysis focused on anatomically delineated regions of a priori interest in the nucleus accumbens, where blood oxygenation level-dependent (BOLD) signals have been suggested as correlating with quantities derived from reinforcement learning. We first provide unbiased evidence that the raw BOLD signal in these regions corresponds closely to a reward prediction error. We then derive from this signal the learned values of cues that predict rewards of equal mean but different variance and show that these values are indeed modulated by experienced risk. Moreover, a close neurometric-psychometric coupling exists between the fluctuations of the experience-based evaluations of risky options that we measured neurally and the fluctuations in behavioral risk aversion. This suggests that risk sensitivity is integral to human learning, illuminating economic models of choice, neuroscientific models of affective learning, and the workings of the underlying neural mechanisms.

  7. Model parameter-related optimal perturbations and their contributions to El Niño prediction errors

    Science.gov (United States)

    Tao, Ling-Jiang; Gao, Chuan; Zhang, Rong-Hua

    2018-04-01

    Errors in initial conditions and model parameters (MPs) are the main sources that limit the accuracy of ENSO predictions. In addition to exploring the initial error-induced prediction errors, model errors are equally important in determining prediction performance. In this paper, the MP-related optimal errors that can cause prominent error growth in ENSO predictions are investigated using an intermediate coupled model (ICM) and a conditional nonlinear optimal perturbation (CNOP) approach. Two MPs related to the Bjerknes feedback are considered in the CNOP analysis: one involves the SST-surface wind coupling ({α _τ } ), and the other involves the thermocline effect on the SST ({α _{Te}} ). The MP-related optimal perturbations (denoted as CNOP-P) are found uniformly positive and restrained in a small region: the {α _τ } component is mainly concentrated in the central equatorial Pacific, and the {α _{Te}} component is mainly located in the eastern cold tongue region. This kind of CNOP-P enhances the strength of the Bjerknes feedback and induces an El Niño- or La Niña-like error evolution, resulting in an El Niño-like systematic bias in this model. The CNOP-P is also found to play a role in the spring predictability barrier (SPB) for ENSO predictions. Evidently, such error growth is primarily attributed to MP errors in small areas based on the localized distribution of CNOP-P. Further sensitivity experiments firmly indicate that ENSO simulations are sensitive to the representation of SST-surface wind coupling in the central Pacific and to the thermocline effect in the eastern Pacific in the ICM. These results provide guidance and theoretical support for the future improvement in numerical models to reduce the systematic bias and SPB phenomenon in ENSO predictions.

  8. A two-dimensional matrix correction for off-axis portal dose prediction errors

    International Nuclear Information System (INIS)

    Bailey, Daniel W.; Kumaraswamy, Lalith; Bakhtiari, Mohammad; Podgorsak, Matthew B.

    2013-01-01

    Purpose: This study presents a follow-up to a modified calibration procedure for portal dosimetry published by Bailey et al. [“An effective correction algorithm for off-axis portal dosimetry errors,” Med. Phys. 36, 4089–4094 (2009)]. A commercial portal dose prediction system exhibits disagreement of up to 15% (calibrated units) between measured and predicted images as off-axis distance increases. The previous modified calibration procedure accounts for these off-axis effects in most regions of the detecting surface, but is limited by the simplistic assumption of radial symmetry. Methods: We find that a two-dimensional (2D) matrix correction, applied to each calibrated image, accounts for off-axis prediction errors in all regions of the detecting surface, including those still problematic after the radial correction is performed. The correction matrix is calculated by quantitative comparison of predicted and measured images that span the entire detecting surface. The correction matrix was verified for dose-linearity, and its effectiveness was verified on a number of test fields. The 2D correction was employed to retrospectively examine 22 off-axis, asymmetric electronic-compensation breast fields, five intensity-modulated brain fields (moderate-high modulation) manipulated for far off-axis delivery, and 29 intensity-modulated clinical fields of varying complexity in the central portion of the detecting surface. Results: Employing the matrix correction to the off-axis test fields and clinical fields, predicted vs measured portal dose agreement improves by up to 15%, producing up to 10% better agreement than the radial correction in some areas of the detecting surface. Gamma evaluation analyses (3 mm, 3% global, 10% dose threshold) of predicted vs measured portal dose images demonstrate pass rate improvement of up to 75% with the matrix correction, producing pass rates that are up to 30% higher than those resulting from the radial correction technique alone. As

  9. Modeling Input Errors to Improve Uncertainty Estimates for Sediment Transport Model Predictions

    Science.gov (United States)

    Jung, J. Y.; Niemann, J. D.; Greimann, B. P.

    2016-12-01

    Bayesian methods using Markov chain Monte Carlo algorithms have recently been applied to sediment transport models to assess the uncertainty in the model predictions due to the parameter values. Unfortunately, the existing approaches can only attribute overall uncertainty to the parameters. This limitation is critical because no model can produce accurate forecasts if forced with inaccurate input data, even if the model is well founded in physical theory. In this research, an existing Bayesian method is modified to consider the potential errors in input data during the uncertainty evaluation process. The input error is modeled using Gaussian distributions, and the means and standard deviations are treated as uncertain parameters. The proposed approach is tested by coupling it to the Sedimentation and River Hydraulics - One Dimension (SRH-1D) model and simulating a 23-km reach of the Tachia River in Taiwan. The Wu equation in SRH-1D is used for computing the transport capacity for a bed material load of non-cohesive material. Three types of input data are considered uncertain: (1) the input flowrate at the upstream boundary, (2) the water surface elevation at the downstream boundary, and (3) the water surface elevation at a hydraulic structure in the middle of the reach. The benefits of modeling the input errors in the uncertainty analysis are evaluated by comparing the accuracy of the most likely forecast and the coverage of the observed data by the credible intervals to those of the existing method. The results indicate that the internal boundary condition has the largest uncertainty among those considered. Overall, the uncertainty estimates from the new method are notably different from those of the existing method for both the calibration and forecast periods.

  10. Triangle network motifs predict complexes by complementing high-error interactomes with structural information.

    Science.gov (United States)

    Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

    2009-06-27

    A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient

  11. Triangle network motifs predict complexes by complementing high-error interactomes with structural information

    Directory of Open Access Journals (Sweden)

    Labudde Dirk

    2009-06-01

    Full Text Available Abstract Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS. PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that

  12. Reducing NIR prediction errors with nonlinear methods and large populations of intact compound feedstuffs

    International Nuclear Information System (INIS)

    Fernández-Ahumada, E; Gómez, A; Vallesquino, P; Guerrero, J E; Pérez-Marín, D; Garrido-Varo, A; Fearn, T

    2008-01-01

    According to the current demands of the authorities, the manufacturers and the consumers, controls and assessments of the feed compound manufacturing process have become a key concern. Among others, it must be assured that a given compound feed is well manufactured and labelled in terms of the ingredient composition. When near-infrared spectroscopy (NIRS) together with linear models were used for the prediction of the ingredient composition, the results were not always acceptable. Therefore, the performance of nonlinear methods has been investigated. Artificial neural networks and least squares support vector machines (LS-SVM) have been applied to a large (N = 20 320) and heterogeneous population of non-milled feed compounds for the NIR prediction of the inclusion percentage of wheat and sunflower meal, as representative of two different classes of ingredients. Compared to partial least squares regression, results showed considerable reductions of standard error of prediction values for both methods and ingredients: reductions of 45% with ANN and 49% with LS-SVM for wheat and reductions of 44% with ANN and 46% with LS-SVM for sunflower meal. These improvements together with the facility of NIRS technology to be implemented in the process make it ideal for meeting the requirements of the animal feed industry

  13. When theory and biology differ: The relationship between reward prediction errors and expectancy.

    Science.gov (United States)

    Williams, Chad C; Hassall, Cameron D; Trska, Robert; Holroyd, Clay B; Krigolson, Olave E

    2017-10-01

    Comparisons between expectations and outcomes are critical for learning. Termed prediction errors, the violations of expectancy that occur when outcomes differ from expectations are used to modify value and shape behaviour. In the present study, we examined how a wide range of expectancy violations impacted neural signals associated with feedback processing. Participants performed a time estimation task in which they had to guess the duration of one second while their electroencephalogram was recorded. In a key manipulation, we varied task difficulty across the experiment to create a range of different feedback expectancies - reward feedback was either very expected, expected, 50/50, unexpected, or very unexpected. As predicted, the amplitude of the reward positivity, a component of the human event-related brain potential associated with feedback processing, scaled inversely with expectancy (e.g., unexpected feedback yielded a larger reward positivity than expected feedback). Interestingly, the scaling of the reward positivity to outcome expectancy was not linear as would be predicted by some theoretical models. Specifically, we found that the amplitude of the reward positivity was about equivalent for very expected and expected feedback, and for very unexpected and unexpected feedback. As such, our results demonstrate a sigmoidal relationship between reward expectancy and the amplitude of the reward positivity, with interesting implications for theories of reinforcement learning. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Harsh parenting and fearfulness in toddlerhood interact to predict amplitudes of preschool error-related negativity

    Directory of Open Access Journals (Sweden)

    Rebecca J. Brooker

    2014-07-01

    Full Text Available Temperamentally fearful children are at increased risk for the development of anxiety problems relative to less-fearful children. This risk is even greater when early environments include high levels of harsh parenting behaviors. However, the mechanisms by which harsh parenting may impact fearful children's risk for anxiety problems are largely unknown. Recent neuroscience work has suggested that punishment is associated with exaggerated error-related negativity (ERN, an event-related potential linked to performance monitoring, even after the threat of punishment is removed. In the current study, we examined the possibility that harsh parenting interacts with fearfulness, impacting anxiety risk via neural processes of performance monitoring. We found that greater fearfulness and harsher parenting at 2 years of age predicted greater fearfulness and greater ERN amplitudes at age 4. Supporting the role of cognitive processes in this association, greater fearfulness and harsher parenting also predicted less efficient neural processing during preschool. This study provides initial evidence that performance monitoring may be a candidate process by which early parenting interacts with fearfulness to predict risk for anxiety problems.

  15. Harsh parenting and fearfulness in toddlerhood interact to predict amplitudes of preschool error-related negativity.

    Science.gov (United States)

    Brooker, Rebecca J; Buss, Kristin A

    2014-07-01

    Temperamentally fearful children are at increased risk for the development of anxiety problems relative to less-fearful children. This risk is even greater when early environments include high levels of harsh parenting behaviors. However, the mechanisms by which harsh parenting may impact fearful children's risk for anxiety problems are largely unknown. Recent neuroscience work has suggested that punishment is associated with exaggerated error-related negativity (ERN), an event-related potential linked to performance monitoring, even after the threat of punishment is removed. In the current study, we examined the possibility that harsh parenting interacts with fearfulness, impacting anxiety risk via neural processes of performance monitoring. We found that greater fearfulness and harsher parenting at 2 years of age predicted greater fearfulness and greater ERN amplitudes at age 4. Supporting the role of cognitive processes in this association, greater fearfulness and harsher parenting also predicted less efficient neural processing during preschool. This study provides initial evidence that performance monitoring may be a candidate process by which early parenting interacts with fearfulness to predict risk for anxiety problems. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  16. Spared internal but impaired external reward prediction error signals in major depressive disorder during reinforcement learning.

    Science.gov (United States)

    Bakic, Jasmina; Pourtois, Gilles; Jepma, Marieke; Duprat, Romain; De Raedt, Rudi; Baeken, Chris

    2017-01-01

    Major depressive disorder (MDD) creates debilitating effects on a wide range of cognitive functions, including reinforcement learning (RL). In this study, we sought to assess whether reward processing as such, or alternatively the complex interplay between motivation and reward might potentially account for the abnormal reward-based learning in MDD. A total of 35 treatment resistant MDD patients and 44 age matched healthy controls (HCs) performed a standard probabilistic learning task. RL was titrated using behavioral, computational modeling and event-related brain potentials (ERPs) data. MDD patients showed comparable learning rate compared to HCs. However, they showed decreased lose-shift responses as well as blunted subjective evaluations of the reinforcers used during the task, relative to HCs. Moreover, MDD patients showed normal internal (at the level of error-related negativity, ERN) but abnormal external (at the level of feedback-related negativity, FRN) reward prediction error (RPE) signals during RL, selectively when additional efforts had to be made to establish learning. Collectively, these results lend support to the assumption that MDD does not impair reward processing per se during RL. Instead, it seems to alter the processing of the emotional value of (external) reinforcers during RL, when additional intrinsic motivational processes have to be engaged. © 2016 Wiley Periodicals, Inc.

  17. Comparison of two stochastic techniques for reliable urban runoff prediction by modeling systematic errors

    DEFF Research Database (Denmark)

    Del Giudice, Dario; Löwe, Roland; Madsen, Henrik

    2015-01-01

    from different fields and have not yet been compared in environmental modeling. To compare the two approaches, we develop a unifying terminology, evaluate them theoretically, and apply them to conceptual rainfall-runoff modeling in the same drainage system. Our results show that both approaches can......In urban rainfall-runoff, commonly applied statistical techniques for uncertainty quantification mostly ignore systematic output errors originating from simplified models and erroneous inputs. Consequently, the resulting predictive uncertainty is often unreliable. Our objective is to present two...... approaches which use stochastic processes to describe systematic deviations and to discuss their advantages and drawbacks for urban drainage modeling. The two methodologies are an external bias description (EBD) and an internal noise description (IND, also known as stochastic gray-box modeling). They emerge...

  18. Human dorsal striatum encodes prediction errors during observational learning of instrumental actions.

    Science.gov (United States)

    Cooper, Jeffrey C; Dunne, Simon; Furey, Teresa; O'Doherty, John P

    2012-01-01

    The dorsal striatum plays a key role in the learning and expression of instrumental reward associations that are acquired through direct experience. However, not all learning about instrumental actions require direct experience. Instead, humans and other animals are also capable of acquiring instrumental actions by observing the experiences of others. In this study, we investigated the extent to which human dorsal striatum is involved in observational as well as experiential instrumental reward learning. Human participants were scanned with fMRI while they observed a confederate over a live video performing an instrumental conditioning task to obtain liquid juice rewards. Participants also performed a similar instrumental task for their own rewards. Using a computational model-based analysis, we found reward prediction errors in the dorsal striatum not only during the experiential learning condition but also during observational learning. These results suggest a key role for the dorsal striatum in learning instrumental associations, even when those associations are acquired purely by observing others.

  19. Observing others stay or switch - How social prediction errors are integrated into reward reversal learning.

    Science.gov (United States)

    Ihssen, Niklas; Mussweiler, Thomas; Linden, David E J

    2016-08-01

    Reward properties of stimuli can undergo sudden changes, and the detection of these 'reversals' is often made difficult by the probabilistic nature of rewards/punishments. Here we tested whether and how humans use social information (someone else's choices) to overcome uncertainty during reversal learning. We show a substantial social influence during reversal learning, which was modulated by the type of observed behavior. Participants frequently followed observed conservative choices (no switches after punishment) made by the (fictitious) other player but ignored impulsive choices (switches), even though the experiment was set up so that both types of response behavior would be similarly beneficial/detrimental (Study 1). Computational modeling showed that participants integrated the observed choices as a 'social prediction error' instead of ignoring or blindly following the other player. Modeling also confirmed higher learning rates for 'conservative' versus 'impulsive' social prediction errors. Importantly, this 'conservative bias' was boosted by interpersonal similarity, which in conjunction with the lack of effects observed in a non-social control experiment (Study 2) confirmed its social nature. A third study suggested that relative weighting of observed impulsive responses increased with increased volatility (frequency of reversals). Finally, simulations showed that in the present paradigm integrating social and reward information was not necessarily more adaptive to maximize earnings than learning from reward alone. Moreover, integrating social information increased accuracy only when conservative and impulsive choices were weighted similarly during learning. These findings suggest that to guide decisions in choice contexts that involve reward reversals humans utilize social cues conforming with their preconceptions more strongly than cues conflicting with them, especially when the other is similar. Copyright © 2016 The Authors. Published by Elsevier B

  20. Improving filtering and prediction of spatially extended turbulent systems with model errors through stochastic parameter estimation

    International Nuclear Information System (INIS)

    Gershgorin, B.; Harlim, J.; Majda, A.J.

    2010-01-01

    The filtering and predictive skill for turbulent signals is often limited by the lack of information about the true dynamics of the system and by our inability to resolve the assumed dynamics with sufficiently high resolution using the current computing power. The standard approach is to use a simple yet rich family of constant parameters to account for model errors through parameterization. This approach can have significant skill by fitting the parameters to some statistical feature of the true signal; however in the context of real-time prediction, such a strategy performs poorly when intermittent transitions to instability occur. Alternatively, we need a set of dynamic parameters. One strategy for estimating parameters on the fly is a stochastic parameter estimation through partial observations of the true signal. In this paper, we extend our newly developed stochastic parameter estimation strategy, the Stochastic Parameterization Extended Kalman Filter (SPEKF), to filtering sparsely observed spatially extended turbulent systems which exhibit abrupt stability transition from time to time despite a stable average behavior. For our primary numerical example, we consider a turbulent system of externally forced barotropic Rossby waves with instability introduced through intermittent negative damping. We find high filtering skill of SPEKF applied to this toy model even in the case of very sparse observations (with only 15 out of the 105 grid points observed) and with unspecified external forcing and damping. Additive and multiplicative bias corrections are used to learn the unknown features of the true dynamics from observations. We also present a comprehensive study of predictive skill in the one-mode context including the robustness toward variation of stochastic parameters, imperfect initial conditions and finite ensemble effect. Furthermore, the proposed stochastic parameter estimation scheme applied to the same spatially extended Rossby wave system demonstrates

  1. Quantifying uncertainty for predictions with model error in non-Gaussian systems with intermittency

    International Nuclear Information System (INIS)

    Branicki, Michal; Majda, Andrew J

    2012-01-01

    This paper discusses a range of important mathematical issues arising in applications of a newly emerging stochastic-statistical framework for quantifying and mitigating uncertainties associated with prediction of partially observed and imperfectly modelled complex turbulent dynamical systems. The need for such a framework is particularly severe in climate science where the true climate system is vastly more complicated than any conceivable model; however, applications in other areas, such as neural networks and materials science, are just as important. The mathematical tools employed here rely on empirical information theory and fluctuation–dissipation theorems (FDTs) and it is shown that they seamlessly combine into a concise systematic framework for measuring and optimizing consistency and sensitivity of imperfect models. Here, we utilize a simple statistically exactly solvable ‘perfect’ system with intermittent hidden instabilities and with time-periodic features to address a number of important issues encountered in prediction of much more complex dynamical systems. These problems include the role and mitigation of model error due to coarse-graining, moment closure approximations, and the memory of initial conditions in producing short, medium and long-range predictions. Importantly, based on a suite of increasingly complex imperfect models of the perfect test system, we show that the predictive skill of the imperfect models and their sensitivity to external perturbations is improved by ensuring their consistency on the statistical attractor (i.e. the climate) with the perfect system. Furthermore, the discussed link between climate fidelity and sensitivity via the FDT opens up an enticing prospect of developing techniques for improving imperfect model sensitivity based on specific tests carried out in the training phase of the unperturbed statistical equilibrium/climate. (paper)

  2. SU-F-J-208: Prompt Gamma Imaging-Based Prediction of Bragg Peak Position for Realistic Treatment Error Scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Xing, Y; Macq, B; Bondar, L [Universite catholique de Louvain, Louvain-la-Neuve (Belgium); Janssens, G [IBA, Louvain-la-Neuve (Belgium)

    2016-06-15

    Purpose: To quantify the accuracy in predicting the Bragg peak position using simulated in-room measurements of prompt gamma (PG) emissions for realistic treatment error scenarios that combine several sources of errors. Methods: Prompt gamma measurements by a knife-edge slit camera were simulated using an experimentally validated analytical simulation tool. Simulations were performed, for 143 treatment error scenarios, on an anthropomorphic phantom and a pencil beam scanning plan for nasal cavity. Three types of errors were considered: translation along each axis, rotation around each axis, and CT-calibration errors with magnitude ranging respectively, between −3 and 3 mm, −5 and 5 degrees, and between −5 and +5%. We investigated the correlation between the Bragg peak (BP) shift and the horizontal shift of PG profiles. The shifts were calculated between the planned (reference) position and the position by the error scenario. The prediction error for one spot was calculated as the absolute difference between the PG profile shift and the BP shift. Results: The PG shift was significantly and strongly correlated with the BP shift for 92% of the cases (p<0.0001, Pearson correlation coefficient R>0.8). Moderate but significant correlations were obtained for all cases that considered only CT-calibration errors and for 1 case that combined translation and CT-errors (p<0.0001, R ranged between 0.61 and 0.8). The average prediction errors for the simulated scenarios ranged between 0.08±0.07 and 1.67±1.3 mm (grand mean 0.66±0.76 mm). The prediction error was moderately correlated with the value of the BP shift (p=0, R=0.64). For the simulated scenarios the average BP shift ranged between −8±6.5 mm and 3±1.1 mm. Scenarios that considered combinations of the largest treatment errors were associated with large BP shifts. Conclusion: Simulations of in-room measurements demonstrate that prompt gamma profiles provide reliable estimation of the Bragg peak position for

  3. Spatiotemporal neural characterization of prediction error valence and surprise during reward learning in humans.

    Science.gov (United States)

    Fouragnan, Elsa; Queirazza, Filippo; Retzler, Chris; Mullinger, Karen J; Philiastides, Marios G

    2017-07-06

    Reward learning depends on accurate reward associations with potential choices. These associations can be attained with reinforcement learning mechanisms using a reward prediction error (RPE) signal (the difference between actual and expected rewards) for updating future reward expectations. Despite an extensive body of literature on the influence of RPE on learning, little has been done to investigate the potentially separate contributions of RPE valence (positive or negative) and surprise (absolute degree of deviation from expectations). Here, we coupled single-trial electroencephalography with simultaneously acquired fMRI, during a probabilistic reversal-learning task, to offer evidence of temporally overlapping but largely distinct spatial representations of RPE valence and surprise. Electrophysiological variability in RPE valence correlated with activity in regions of the human reward network promoting approach or avoidance learning. Electrophysiological variability in RPE surprise correlated primarily with activity in regions of the human attentional network controlling the speed of learning. Crucially, despite the largely separate spatial extend of these representations our EEG-informed fMRI approach uniquely revealed a linear superposition of the two RPE components in a smaller network encompassing visuo-mnemonic and reward areas. Activity in this network was further predictive of stimulus value updating indicating a comparable contribution of both signals to reward learning.

  4. Hierarchical prediction errors in midbrain and basal forebrain during sensory learning.

    Science.gov (United States)

    Iglesias, Sandra; Mathys, Christoph; Brodersen, Kay H; Kasper, Lars; Piccirelli, Marco; den Ouden, Hanneke E M; Stephan, Klaas E

    2013-10-16

    In Bayesian brain theories, hierarchically related prediction errors (PEs) play a central role for predicting sensory inputs and inferring their underlying causes, e.g., the probabilistic structure of the environment and its volatility. Notably, PEs at different hierarchical levels may be encoded by different neuromodulatory transmitters. Here, we tested this possibility in computational fMRI studies of audio-visual learning. Using a hierarchical Bayesian model, we found that low-level PEs about visual stimulus outcome were reflected by widespread activity in visual and supramodal areas but also in the midbrain. In contrast, high-level PEs about stimulus probabilities were encoded by the basal forebrain. These findings were replicated in two groups of healthy volunteers. While our fMRI measures do not reveal the exact neuron types activated in midbrain and basal forebrain, they suggest a dichotomy between neuromodulatory systems, linking dopamine to low-level PEs about stimulus outcome and acetylcholine to more abstract PEs about stimulus probabilities. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Neural correlates of sensory prediction errors in monkeys: evidence for internal models of voluntary self-motion in the cerebellum.

    Science.gov (United States)

    Cullen, Kathleen E; Brooks, Jessica X

    2015-02-01

    During self-motion, the vestibular system makes essential contributions to postural stability and self-motion perception. To ensure accurate perception and motor control, it is critical to distinguish between vestibular sensory inputs that are the result of externally applied motion (exafference) and that are the result of our own actions (reafference). Indeed, although the vestibular sensors encode vestibular afference and reafference with equal fidelity, neurons at the first central stage of sensory processing selectively encode vestibular exafference. The mechanism underlying this reafferent suppression compares the brain's motor-based expectation of sensory feedback with the actual sensory consequences of voluntary self-motion, effectively computing the sensory prediction error (i.e., exafference). It is generally thought that sensory prediction errors are computed in the cerebellum, yet it has been challenging to explicitly demonstrate this. We have recently addressed this question and found that deep cerebellar nuclei neurons explicitly encode sensory prediction errors during self-motion. Importantly, in everyday life, sensory prediction errors occur in response to changes in the effector or world (muscle strength, load, etc.), as well as in response to externally applied sensory stimulation. Accordingly, we hypothesize that altering the relationship between motor commands and the actual movement parameters will result in the updating in the cerebellum-based computation of exafference. If our hypothesis is correct, under these conditions, neuronal responses should initially be increased--consistent with a sudden increase in the sensory prediction error. Then, over time, as the internal model is updated, response modulation should decrease in parallel with a reduction in sensory prediction error, until vestibular reafference is again suppressed. The finding that the internal model predicting the sensory consequences of motor commands adapts for new

  6. Impact bias or underestimation? Outcome specifications predict the direction of affective forecasting errors.

    Science.gov (United States)

    Buechel, Eva C; Zhang, Jiao; Morewedge, Carey K

    2017-05-01

    Affective forecasts are used to anticipate the hedonic impact of future events and decide which events to pursue or avoid. We propose that because affective forecasters are more sensitive to outcome specifications of events than experiencers, the outcome specification values of an event, such as its duration, magnitude, probability, and psychological distance, can be used to predict the direction of affective forecasting errors: whether affective forecasters will overestimate or underestimate its hedonic impact. When specifications are positively correlated with the hedonic impact of an event, forecasters will overestimate the extent to which high specification values will intensify and low specification values will discount its impact. When outcome specifications are negatively correlated with its hedonic impact, forecasters will overestimate the extent to which low specification values will intensify and high specification values will discount its impact. These affective forecasting errors compound additively when multiple specifications are aligned in their impact: In Experiment 1, affective forecasters underestimated the hedonic impact of winning a smaller prize that they expected to win, and they overestimated the hedonic impact of winning a larger prize that they did not expect to win. In Experiment 2, affective forecasters underestimated the hedonic impact of a short unpleasant video about a temporally distant event, and they overestimated the hedonic impact of a long unpleasant video about a temporally near event. Experiments 3A and 3B showed that differences in the affect-richness of forecasted and experienced events underlie these differences in sensitivity to outcome specifications, therefore accounting for both the impact bias and its reversal. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  7. EFFECT OF MEASUREMENT ERRORS ON PREDICTED COSMOLOGICAL CONSTRAINTS FROM SHEAR PEAK STATISTICS WITH LARGE SYNOPTIC SURVEY TELESCOPE

    Energy Technology Data Exchange (ETDEWEB)

    Bard, D.; Chang, C.; Kahn, S. M.; Gilmore, K.; Marshall, S. [KIPAC, Stanford University, 452 Lomita Mall, Stanford, CA 94309 (United States); Kratochvil, J. M.; Huffenberger, K. M. [Department of Physics, University of Miami, Coral Gables, FL 33124 (United States); May, M. [Physics Department, Brookhaven National Laboratory, Upton, NY 11973 (United States); AlSayyad, Y.; Connolly, A.; Gibson, R. R.; Jones, L.; Krughoff, S. [Department of Astronomy, University of Washington, Seattle, WA 98195 (United States); Ahmad, Z.; Bankert, J.; Grace, E.; Hannel, M.; Lorenz, S. [Department of Physics, Purdue University, West Lafayette, IN 47907 (United States); Haiman, Z.; Jernigan, J. G., E-mail: djbard@slac.stanford.edu [Department of Astronomy and Astrophysics, Columbia University, New York, NY 10027 (United States); and others

    2013-09-01

    We study the effect of galaxy shape measurement errors on predicted cosmological constraints from the statistics of shear peak counts with the Large Synoptic Survey Telescope (LSST). We use the LSST Image Simulator in combination with cosmological N-body simulations to model realistic shear maps for different cosmological models. We include both galaxy shape noise and, for the first time, measurement errors on galaxy shapes. We find that the measurement errors considered have relatively little impact on the constraining power of shear peak counts for LSST.

  8. Improved model predictive control of resistive wall modes by error field estimator in EXTRAP T2R

    Science.gov (United States)

    Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

    2016-12-01

    Many implementations of a model-based approach for toroidal plasma have shown better control performance compared to the conventional type of feedback controller. One prerequisite of model-based control is the availability of a control oriented model. This model can be obtained empirically through a systematic procedure called system identification. Such a model is used in this work to design a model predictive controller to stabilize multiple resistive wall modes in EXTRAP T2R reversed-field pinch. Model predictive control is an advanced control method that can optimize the future behaviour of a system. Furthermore, this paper will discuss an additional use of the empirical model which is to estimate the error field in EXTRAP T2R. Two potential methods are discussed that can estimate the error field. The error field estimator is then combined with the model predictive control and yields better radial magnetic field suppression.

  9. Toward a better understanding on the role of prediction error on memory processes: From bench to clinic.

    Science.gov (United States)

    Krawczyk, María C; Fernández, Rodrigo S; Pedreira, María E; Boccia, Mariano M

    2017-07-01

    Experimental psychology defines Prediction Error (PE) as a mismatch between expected and current events. It represents a unifier concept within the memory field, as it is the driving force of memory acquisition and updating. Prediction error induces updating of consolidated memories in strength or content by memory reconsolidation. This process has two different neurobiological phases, which involves the destabilization (labilization) of a consolidated memory followed by its restabilization. The aim of this work is to emphasize the functional role of PE on the neurobiology of learning and memory, integrating and discussing different research areas: behavioral, neurobiological, computational and clinical psychiatry. Copyright © 2016 Elsevier Inc. All rights reserved.

  10. A bottom-up model of spatial attention predicts human error patterns in rapid scene recognition.

    Science.gov (United States)

    Einhäuser, Wolfgang; Mundhenk, T Nathan; Baldi, Pierre; Koch, Christof; Itti, Laurent

    2007-07-20

    Humans demonstrate a peculiar ability to detect complex targets in rapidly presented natural scenes. Recent studies suggest that (nearly) no focal attention is required for overall performance in such tasks. Little is known, however, of how detection performance varies from trial to trial and which stages in the processing hierarchy limit performance: bottom-up visual processing (attentional selection and/or recognition) or top-down factors (e.g., decision-making, memory, or alertness fluctuations)? To investigate the relative contribution of these factors, eight human observers performed an animal detection task in natural scenes presented at 20 Hz. Trial-by-trial performance was highly consistent across observers, far exceeding the prediction of independent errors. This consistency demonstrates that performance is not primarily limited by idiosyncratic factors but by visual processing. Two statistical stimulus properties, contrast variation in the target image and the information-theoretical measure of "surprise" in adjacent images, predict performance on a trial-by-trial basis. These measures are tightly related to spatial attention, demonstrating that spatial attention and rapid target detection share common mechanisms. To isolate the causal contribution of the surprise measure, eight additional observers performed the animal detection task in sequences that were reordered versions of those all subjects had correctly recognized in the first experiment. Reordering increased surprise before and/or after the target while keeping the target and distractors themselves unchanged. Surprise enhancement impaired target detection in all observers. Consequently, and contrary to several previously published findings, our results demonstrate that attentional limitations, rather than target recognition alone, affect the detection of targets in rapidly presented visual sequences.

  11. Accounting for the measurement error of spectroscopically inferred soil carbon data for improved precision of spatial predictions.

    Science.gov (United States)

    Somarathna, P D S N; Minasny, Budiman; Malone, Brendan P; Stockmann, Uta; McBratney, Alex B

    2018-08-01

    Spatial modelling of environmental data commonly only considers spatial variability as the single source of uncertainty. In reality however, the measurement errors should also be accounted for. In recent years, infrared spectroscopy has been shown to offer low cost, yet invaluable information needed for digital soil mapping at meaningful spatial scales for land management. However, spectrally inferred soil carbon data are known to be less accurate compared to laboratory analysed measurements. This study establishes a methodology to filter out the measurement error variability by incorporating the measurement error variance in the spatial covariance structure of the model. The study was carried out in the Lower Hunter Valley, New South Wales, Australia where a combination of laboratory measured, and vis-NIR and MIR inferred topsoil and subsoil soil carbon data are available. We investigated the applicability of residual maximum likelihood (REML) and Markov Chain Monte Carlo (MCMC) simulation methods to generate parameters of the Matérn covariance function directly from the data in the presence of measurement error. The results revealed that the measurement error can be effectively filtered-out through the proposed technique. When the measurement error was filtered from the data, the prediction variance almost halved, which ultimately yielded a greater certainty in spatial predictions of soil carbon. Further, the MCMC technique was successfully used to define the posterior distribution of measurement error. This is an important outcome, as the MCMC technique can be used to estimate the measurement error if it is not explicitly quantified. Although this study dealt with soil carbon data, this method is amenable for filtering the measurement error of any kind of continuous spatial environmental data. Copyright © 2018 Elsevier B.V. All rights reserved.

  12. Cardiac Concomitants of Feedback and Prediction Error Processing in Reinforcement Learning

    Science.gov (United States)

    Kastner, Lucas; Kube, Jana; Villringer, Arno; Neumann, Jane

    2017-01-01

    Successful learning hinges on the evaluation of positive and negative feedback. We assessed differential learning from reward and punishment in a monetary reinforcement learning paradigm, together with cardiac concomitants of positive and negative feedback processing. On the behavioral level, learning from reward resulted in more advantageous behavior than learning from punishment, suggesting a differential impact of reward and punishment on successful feedback-based learning. On the autonomic level, learning and feedback processing were closely mirrored by phasic cardiac responses on a trial-by-trial basis: (1) Negative feedback was accompanied by faster and prolonged heart rate deceleration compared to positive feedback. (2) Cardiac responses shifted from feedback presentation at the beginning of learning to stimulus presentation later on. (3) Most importantly, the strength of phasic cardiac responses to the presentation of feedback correlated with the strength of prediction error signals that alert the learner to the necessity for behavioral adaptation. Considering participants' weight status and gender revealed obesity-related deficits in learning to avoid negative consequences and less consistent behavioral adaptation in women compared to men. In sum, our results provide strong new evidence for the notion that during learning phasic cardiac responses reflect an internal value and feedback monitoring system that is sensitive to the violation of performance-based expectations. Moreover, inter-individual differences in weight status and gender may affect both behavioral and autonomic responses in reinforcement-based learning. PMID:29163004

  13. Comparison of the prediction error in cataract surgery with Lenstar and conventional ultrasound

    Directory of Open Access Journals (Sweden)

    Hou-Cheng Liang

    2013-12-01

    Full Text Available AIM: To compare the prediction errors(PEin cataract surgery with Lenstar and conventional ultrasound. METHODS: The data of age-related cataract patients were retrospectively analyzed from March, 2013 to June, 2013 in our hospital. Preoperative measurements of ocular biological parameters and calculation of intraocular lens(IOLdegree using SRK/T's formula with ultrasound, keratometry and Lenstar were performed. Cataract extraction combined with IOL implantation in capsule was taken in every patient. Retinoscopy was taken postoperatively after 3 months. Comparison of the two inspection methods for measuring axial length, mean corneal curvature and postoperative refractive PE and absolute value of PE(APE. RESULTS: Preoperative axial length was 24.68±1.70mm and 24.42±1.65mm with Lenstar and ultrasound, respectively, and there was significant difference(t=-12.688, Pr=0.992, Pt=-1.241, P=0.217, but was the significant correlation(r=0.963, Pt=-5.494, Pt=6.379, PCONCLUSION: Accurate ocular biological parameters can be achieved with Lenstar, and postoperative PE is more precise with Lenstar compared with conventional ultrasound. Lenstar can be used for precise calculation of IOL degree in cataract operation.

  14. On the improvement of neural cryptography using erroneous transmitted information with error prediction.

    Science.gov (United States)

    Allam, Ahmed M; Abbas, Hazem M

    2010-12-01

    Neural cryptography deals with the problem of "key exchange" between two neural networks using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between the two communicating parties is eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process. Therefore, diminishing the probability of such a threat improves the reliability of exchanging the output bits through a public channel. The synchronization with feedback algorithm is one of the existing algorithms that enhances the security of neural cryptography. This paper proposes three new algorithms to enhance the mutual learning process. They mainly depend on disrupting the attacker confidence in the exchanged outputs and input patterns during training. The first algorithm is called "Do not Trust My Partner" (DTMP), which relies on one party sending erroneous output bits, with the other party being capable of predicting and correcting this error. The second algorithm is called "Synchronization with Common Secret Feedback" (SCSFB), where inputs are kept partially secret and the attacker has to train its network on input patterns that are different from the training sets used by the communicating parties. The third algorithm is a hybrid technique combining the features of the DTMP and SCSFB. The proposed approaches are shown to outperform the synchronization with feedback algorithm in the time needed for the parties to synchronize.

  15. Cardiac Concomitants of Feedback and Prediction Error Processing in Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Lucas Kastner

    2017-10-01

    Full Text Available Successful learning hinges on the evaluation of positive and negative feedback. We assessed differential learning from reward and punishment in a monetary reinforcement learning paradigm, together with cardiac concomitants of positive and negative feedback processing. On the behavioral level, learning from reward resulted in more advantageous behavior than learning from punishment, suggesting a differential impact of reward and punishment on successful feedback-based learning. On the autonomic level, learning and feedback processing were closely mirrored by phasic cardiac responses on a trial-by-trial basis: (1 Negative feedback was accompanied by faster and prolonged heart rate deceleration compared to positive feedback. (2 Cardiac responses shifted from feedback presentation at the beginning of learning to stimulus presentation later on. (3 Most importantly, the strength of phasic cardiac responses to the presentation of feedback correlated with the strength of prediction error signals that alert the learner to the necessity for behavioral adaptation. Considering participants' weight status and gender revealed obesity-related deficits in learning to avoid negative consequences and less consistent behavioral adaptation in women compared to men. In sum, our results provide strong new evidence for the notion that during learning phasic cardiac responses reflect an internal value and feedback monitoring system that is sensitive to the violation of performance-based expectations. Moreover, inter-individual differences in weight status and gender may affect both behavioral and autonomic responses in reinforcement-based learning.

  16. Prediction errors to emotional expressions: the roles of the amygdala in social referencing.

    Science.gov (United States)

    Meffert, Harma; Brislin, Sarah J; White, Stuart F; Blair, James R

    2015-04-01

    Social referencing paradigms in humans and observational learning paradigms in animals suggest that emotional expressions are important for communicating valence. It has been proposed that these expressions initiate stimulus-reinforcement learning. Relatively little is known about the role of emotional expressions in reinforcement learning, particularly in the context of social referencing. In this study, we examined object valence learning in the context of a social referencing paradigm. Participants viewed objects and faces that turned toward the objects and displayed a fearful, happy or neutral reaction to them, while judging the gender of these faces. Notably, amygdala activation was larger when the expressions following an object were less expected. Moreover, when asked, participants were both more likely to want to approach, and showed stronger amygdala responses to, objects associated with happy relative to objects associated with fearful expressions. This suggests that the amygdala plays two roles in social referencing: (i) initiating learning regarding the valence of an object as a function of prediction errors to expressions displayed toward this object and (ii) orchestrating an emotional response to the object when value judgments are being made regarding this object. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

  17. Prediction of DVH parameter changes due to setup errors for breast cancer treatment based on 2D portal dosimetry

    International Nuclear Information System (INIS)

    Nijsten, S. M. J. J. G.; Elmpt, W. J. C. van; Mijnheer, B. J.; Minken, A. W. H.; Persoon, L. C. G. G.; Lambin, P.; Dekker, A. L. A. J.

    2009-01-01

    Electronic portal imaging devices (EPIDs) are increasingly used for portal dosimetry applications. In our department, EPIDs are clinically used for two-dimensional (2D) transit dosimetry. Predicted and measured portal dose images are compared to detect dose delivery errors caused for instance by setup errors or organ motion. The aim of this work is to develop a model to predict dose-volume histogram (DVH) changes due to setup errors during breast cancer treatment using 2D transit dosimetry. First, correlations between DVH parameter changes and 2D gamma parameters are investigated for different simulated setup errors, which are described by a binomial logistic regression model. The model calculates the probability that a DVH parameter changes more than a specific tolerance level and uses several gamma evaluation parameters for the planning target volume (PTV) projection in the EPID plane as input. Second, the predictive model is applied to clinically measured portal images. Predicted DVH parameter changes are compared to calculated DVH parameter changes using the measured setup error resulting from a dosimetric registration procedure. Statistical accuracy is investigated by using receiver operating characteristic (ROC) curves and values for the area under the curve (AUC), sensitivity, specificity, positive and negative predictive values. Changes in the mean PTV dose larger than 5%, and changes in V 90 and V 95 larger than 10% are accurately predicted based on a set of 2D gamma parameters. Most pronounced changes in the three DVH parameters are found for setup errors in the lateral-medial direction. AUC, sensitivity, specificity, and negative predictive values were between 85% and 100% while the positive predictive values were lower but still higher than 54%. Clinical predictive value is decreased due to the occurrence of patient rotations or breast deformations during treatment, but the overall reliability of the predictive model remains high. Based on our

  18. Thermal-Induced Errors Prediction and Compensation for a Coordinate Boring Machine Based on Time Series Analysis

    Directory of Open Access Journals (Sweden)

    Jun Yang

    2014-01-01

    Full Text Available To improve the CNC machine tools precision, a thermal error modeling for the motorized spindle was proposed based on time series analysis, considering the length of cutting tools and thermal declined angles, and the real-time error compensation was implemented. A five-point method was applied to measure radial thermal declinations and axial expansion of the spindle with eddy current sensors, solving the problem that the three-point measurement cannot obtain the radial thermal angle errors. Then the stationarity of the thermal error sequences was determined by the Augmented Dickey-Fuller Test Algorithm, and the autocorrelation/partial autocorrelation function was applied to identify the model pattern. By combining both Yule-Walker equations and information criteria, the order and parameters of the models were solved effectively, which improved the prediction accuracy and generalization ability. The results indicated that the prediction accuracy of the time series model could reach up to 90%. In addition, the axial maximum error decreased from 39.6 μm to 7 μm after error compensation, and the machining accuracy was improved by 89.7%. Moreover, the X/Y-direction accuracy can reach up to 77.4% and 86%, respectively, which demonstrated that the proposed methods of measurement, modeling, and compensation were effective.

  19. Estimating Prediction Uncertainty from Geographical Information System Raster Processing: A User's Manual for the Raster Error Propagation Tool (REPTool)

    Science.gov (United States)

    Gurdak, Jason J.; Qi, Sharon L.; Geisler, Michael L.

    2009-01-01

    The U.S. Geological Survey Raster Error Propagation Tool (REPTool) is a custom tool for use with the Environmental System Research Institute (ESRI) ArcGIS Desktop application to estimate error propagation and prediction uncertainty in raster processing operations and geospatial modeling. REPTool is designed to introduce concepts of error and uncertainty in geospatial data and modeling and provide users of ArcGIS Desktop a geoprocessing tool and methodology to consider how error affects geospatial model output. Similar to other geoprocessing tools available in ArcGIS Desktop, REPTool can be run from a dialog window, from the ArcMap command line, or from a Python script. REPTool consists of public-domain, Python-based packages that implement Latin Hypercube Sampling within a probabilistic framework to track error propagation in geospatial models and quantitatively estimate the uncertainty of the model output. Users may specify error for each input raster or model coefficient represented in the geospatial model. The error for the input rasters may be specified as either spatially invariant or spatially variable across the spatial domain. Users may specify model output as a distribution of uncertainty for each raster cell. REPTool uses the Relative Variance Contribution method to quantify the relative error contribution from the two primary components in the geospatial model - errors in the model input data and coefficients of the model variables. REPTool is appropriate for many types of geospatial processing operations, modeling applications, and related research questions, including applications that consider spatially invariant or spatially variable error in geospatial data.

  20. Online visual feedback during error-free channel trials leads to active unlearning of movement dynamics: evidence for adaptation to trajectory prediction errors.

    Directory of Open Access Journals (Sweden)

    Angel Lago-Rodriguez

    2016-09-01

    Full Text Available Prolonged exposure to movement perturbations leads to creation of motor memories which decay towards previous states when the perturbations are removed. However, it remains unclear whether this decay is due only to a spontaneous and passive recovery of the previous state. It has recently been reported that activation of reinforcement-based learning mechanisms delays the onset of the decay. This raises the question whether other motor learning mechanisms may also contribute to the retention and/or decay of the motor memory. Therefore, we aimed to test whether mechanisms of error-based motor adaptation are active during the decay of the motor memory. Forty-five right-handed participants performed point-to-point reaching movements under an external dynamic perturbation. We measured the expression of the motor memory through error-clamped (EC trials, in which lateral forces constrained movements to a straight line towards the target. We found greater and faster decay of the motor memory for participants who had access to full online visual feedback during these EC trials (Cursor group, when compared with participants who had no EC feedback regarding movement trajectory (Arc group. Importantly, we did not find between-group differences in adaptation to the external perturbation. In addition, we found greater decay of the motor memory when we artificially increased feedback errors through the manipulation of visual feedback (Augmented-Error group. Our results then support the notion of an active decay of the motor memory, suggesting that adaptive mechanisms are involved in correcting for the mismatch between predicted movement trajectories and actual sensory feedback, which leads to greater and faster decay of the motor memory.

  1. Quality prediction modeling for sintered ores based on mechanism models of sintering and extreme learning machine based error compensation

    Science.gov (United States)

    Tiebin, Wu; Yunlian, Liu; Xinjun, Li; Yi, Yu; Bin, Zhang

    2018-06-01

    Aiming at the difficulty in quality prediction of sintered ores, a hybrid prediction model is established based on mechanism models of sintering and time-weighted error compensation on the basis of the extreme learning machine (ELM). At first, mechanism models of drum index, total iron, and alkalinity are constructed according to the chemical reaction mechanism and conservation of matter in the sintering process. As the process is simplified in the mechanism models, these models are not able to describe high nonlinearity. Therefore, errors are inevitable. For this reason, the time-weighted ELM based error compensation model is established. Simulation results verify that the hybrid model has a high accuracy and can meet the requirement for industrial applications.

  2. MK-801 protection against methamphetamine-induced striatal dopamine terminal injury is associated with attenuated dopamine overflow.

    Science.gov (United States)

    Weihmuller, F B; O'Dell, S J; Marshall, J F

    1992-06-01

    Repeated administrations of methamphetamine (m-AMPH) produce high extracellular levels of dopamine (DA) and subsequent striatal DA terminal damage. Pharmacological blockade of N-methyl-D-aspartate (NMDA) receptors has been shown previously to prevent m-AMPH-induced striatal DA terminal injury, but the mechanism for this protection is unclear. In the present study, in vivo microdialysis was used to determine the effects of blockade of NMDA receptors with the noncompetitive antagonist MK-801 on m-AMPH-induced striatal DA overflow. Four injections of MK-801 (0.5 mg/kg, ip) alone did not significantly change extracellular striatal DA concentrations from pretreatment values. Four treatments with m-AMPH (4.0 mg/kg, sc at 2-hr intervals) increased striatal DA overflow, and the overflow was particularly extensive following the fourth injection. This m-AMPH regimen produced a 40% reduction in striatal DA tissue content 1 week later. Treatment with MK-801 15 min before each of the four m-AMPH injections or prior to only the last two m-AMPH administrations attenuated the m-AMPH-induced increase in striatal DA overflow and protected completely against striatal DA depletions. Other MK-801 treatment regimens less effectively reduced the m-AMPH-induced striatal DA efflux and were ineffective in protecting against striatal DA depletions. Linear regression analysis indicated that cumulative DA overflow was strongly predictive (r = -.68) of striatal DA tissue levels measured one week later. These findings suggest that the extensive DA overflow seen during a neurotoxic regimen of m-AMPH is a crucial component of the subsequent neurotoxicity.(ABSTRACT TRUNCATED AT 250 WORDS)

  3. Absorbed in the task : Personality measures predict engagement during task performance as tracked by error negativity and asymmetrical frontal activity

    NARCIS (Netherlands)

    Tops, Mattie; Boksem, Maarten A. S.

    2010-01-01

    We hypothesized that interactions between traits and context predict task engagement, as measured by the amplitude of the error-related negativity (ERN), performance, and relative frontal activity asymmetry (RFA). In Study 1, we found that drive for reward, absorption, and constraint independently

  4. Preschool Speech Error Patterns Predict Articulation and Phonological Awareness Outcomes in Children with Histories of Speech Sound Disorders

    Science.gov (United States)

    Preston, Jonathan L.; Hull, Margaret; Edwards, Mary Louise

    2013-01-01

    Purpose: To determine if speech error patterns in preschoolers with speech sound disorders (SSDs) predict articulation and phonological awareness (PA) outcomes almost 4 years later. Method: Twenty-five children with histories of preschool SSDs (and normal receptive language) were tested at an average age of 4;6 (years;months) and were followed up…

  5. A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non-Gaussian errors

    NARCIS (Netherlands)

    Schoups, G.; Vrugt, J.A.

    2010-01-01

    Estimation of parameter and predictive uncertainty of hydrologic models has traditionally relied on several simplifying assumptions. Residual errors are often assumed to be independent and to be adequately described by a Gaussian probability distribution with a mean of zero and a constant variance.

  6. CLIM : A cross-level workload-aware timing error prediction model for functional units

    NARCIS (Netherlands)

    Jiao, Xun; Rahimi, Abbas; Jiang, Yu; Wang, Jianguo; Fatemi, Hamed; De Gyvez, Jose Pineda; Gupta, Rajesh K.

    2018-01-01

    Timing errors that are caused by the timing violations of sensitized circuit paths, have emerged as an important threat to the reliability of synchronous digital circuits. To protect circuits from these timing errors, designers typically use a conservative timing margin, which leads to operational

  7. Prediction of human errors by maladaptive changes in event-related brain networks

    NARCIS (Netherlands)

    Eichele, T.; Debener, S.; Calhoun, V.D.; Specht, K.; Engel, A.K.; Hugdahl, K.; Cramon, D.Y. von; Ullsperger, M.

    2008-01-01

    Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional Mill and applying independent component analysis followed by deconvolution of hemodynamic responses, we

  8. Beyond reward prediction errors: the role of dopamine in movement kinematics

    Directory of Open Access Journals (Sweden)

    Joseph eBarter

    2015-05-01

    Full Text Available We recorded activity of dopamine (DA neurons in the substantia nigra pars compacta in unrestrained mice while monitoring their movements with video tracking. Our approach allows an unbiased examination of the continuous relationship between single unit activity and behavior. Although DA neurons show characteristic burst firing following cue or reward presentation, as previously reported, their activity can be explained by the representation of actual movement kinematics. Unlike neighboring pars reticulata GABAergic output neurons, which can represent vector components of position, DA neurons represent vector components of velocity or acceleration. We found neurons related to movements in four directions—up, down, left right. For horizontal movements, there is significant lateralization of neurons: the left nigra contains more rightward neurons, whereas the right nigra contains more leftward neurons. The relationship between DA activity and movement kinematics was found on both appetitive trials using sucrose and aversive trials using air puff, showing that these neurons belong to a velocity control circuit that can be used for any number of purposes, whether to seek reward or to avoid harm. In support of this conclusion, mimicry of the phasic activation of DA neurons with selective optogenetic stimulation could also generate movements. Contrary to the popular hypothesis that DA neurons encode reward prediction errors, our results suggest that nigrostriatal DA plays an essential role in controlling the kinematics of voluntary movements. We hypothesize that DA signaling implements gain adjustment for adaptive transition control, and describe a new model of BG in which DA functions to adjust the gain of a transition controller. This model has significant implications for our understanding of movement disorders implicating DA and the BG.

  9. Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features

    Energy Technology Data Exchange (ETDEWEB)

    Grimm, Lars J., E-mail: Lars.grimm@duke.edu; Ghate, Sujata V.; Yoon, Sora C.; Kim, Connie [Department of Radiology, Duke University Medical Center, Box 3808, Durham, North Carolina 27710 (United States); Kuzmiak, Cherie M. [Department of Radiology, University of North Carolina School of Medicine, 2006 Old Clinic, CB No. 7510, Chapel Hill, North Carolina 27599 (United States); Mazurowski, Maciej A. [Duke University Medical Center, Box 2731 Medical Center, Durham, North Carolina 27710 (United States)

    2014-03-15

    Purpose: The purpose of this study is to explore Breast Imaging-Reporting and Data System (BI-RADS) features as predictors of individual errors made by trainees when detecting masses in mammograms. Methods: Ten radiology trainees and three expert breast imagers reviewed 100 mammograms comprised of bilateral medial lateral oblique and craniocaudal views on a research workstation. The cases consisted of normal and biopsy proven benign and malignant masses. For cases with actionable abnormalities, the experts recorded breast (density and axillary lymph nodes) and mass (shape, margin, and density) features according to the BI-RADS lexicon, as well as the abnormality location (depth and clock face). For each trainee, a user-specific multivariate model was constructed to predict the trainee's likelihood of error based on BI-RADS features. The performance of the models was assessed using area under the receive operating characteristic curves (AUC). Results: Despite the variability in errors between different trainees, the individual models were able to predict the likelihood of error for the trainees with a mean AUC of 0.611 (range: 0.502–0.739, 95% Confidence Interval: 0.543–0.680,p < 0.002). Conclusions: Patterns in detection errors for mammographic masses made by radiology trainees can be modeled using BI-RADS features. These findings may have potential implications for the development of future educational materials that are personalized to individual trainees.

  10. Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features.

    Science.gov (United States)

    Grimm, Lars J; Ghate, Sujata V; Yoon, Sora C; Kuzmiak, Cherie M; Kim, Connie; Mazurowski, Maciej A

    2014-03-01

    The purpose of this study is to explore Breast Imaging-Reporting and Data System (BI-RADS) features as predictors of individual errors made by trainees when detecting masses in mammograms. Ten radiology trainees and three expert breast imagers reviewed 100 mammograms comprised of bilateral medial lateral oblique and craniocaudal views on a research workstation. The cases consisted of normal and biopsy proven benign and malignant masses. For cases with actionable abnormalities, the experts recorded breast (density and axillary lymph nodes) and mass (shape, margin, and density) features according to the BI-RADS lexicon, as well as the abnormality location (depth and clock face). For each trainee, a user-specific multivariate model was constructed to predict the trainee's likelihood of error based on BI-RADS features. The performance of the models was assessed using area under the receive operating characteristic curves (AUC). Despite the variability in errors between different trainees, the individual models were able to predict the likelihood of error for the trainees with a mean AUC of 0.611 (range: 0.502-0.739, 95% Confidence Interval: 0.543-0.680,p errors for mammographic masses made by radiology trainees can be modeled using BI-RADS features. These findings may have potential implications for the development of future educational materials that are personalized to individual trainees.

  11. Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI-RADS features

    International Nuclear Information System (INIS)

    Grimm, Lars J.; Ghate, Sujata V.; Yoon, Sora C.; Kim, Connie; Kuzmiak, Cherie M.; Mazurowski, Maciej A.

    2014-01-01

    Purpose: The purpose of this study is to explore Breast Imaging-Reporting and Data System (BI-RADS) features as predictors of individual errors made by trainees when detecting masses in mammograms. Methods: Ten radiology trainees and three expert breast imagers reviewed 100 mammograms comprised of bilateral medial lateral oblique and craniocaudal views on a research workstation. The cases consisted of normal and biopsy proven benign and malignant masses. For cases with actionable abnormalities, the experts recorded breast (density and axillary lymph nodes) and mass (shape, margin, and density) features according to the BI-RADS lexicon, as well as the abnormality location (depth and clock face). For each trainee, a user-specific multivariate model was constructed to predict the trainee's likelihood of error based on BI-RADS features. The performance of the models was assessed using area under the receive operating characteristic curves (AUC). Results: Despite the variability in errors between different trainees, the individual models were able to predict the likelihood of error for the trainees with a mean AUC of 0.611 (range: 0.502–0.739, 95% Confidence Interval: 0.543–0.680,p < 0.002). Conclusions: Patterns in detection errors for mammographic masses made by radiology trainees can be modeled using BI-RADS features. These findings may have potential implications for the development of future educational materials that are personalized to individual trainees

  12. The application of SHERPA (Systematic Human Error Reduction and Prediction Approach) in the development of compensatory cognitive rehabilitation strategies for stroke patients with left and right brain damage.

    Science.gov (United States)

    Hughes, Charmayne M L; Baber, Chris; Bienkiewicz, Marta; Worthington, Andrew; Hazell, Alexa; Hermsdörfer, Joachim

    2015-01-01

    Approximately 33% of stroke patients have difficulty performing activities of daily living, often committing errors during the planning and execution of such activities. The objective of this study was to evaluate the ability of the human error identification (HEI) technique SHERPA (Systematic Human Error Reduction and Prediction Approach) to predict errors during the performance of daily activities in stroke patients with left and right hemisphere lesions. Using SHERPA we successfully predicted 36 of the 38 observed errors, with analysis indicating that the proportion of predicted and observed errors was similar for all sub-tasks and severity levels. HEI results were used to develop compensatory cognitive strategies that clinicians could employ to reduce or prevent errors from occurring. This study provides evidence for the reliability and validity of SHERPA in the design of cognitive rehabilitation strategies in stroke populations.

  13. Supervised learning based model for predicting variability-induced timing errors

    NARCIS (Netherlands)

    Jiao, X.; Rahimi, A.; Narayanaswamy, B.; Fatemi, H.; Pineda de Gyvez, J.; Gupta, R.K.

    2015-01-01

    Circuit designers typically combat variations in hardware and workload by increasing conservative guardbanding that leads to operational inefficiency. Reducing this excessive guardband is highly desirable, but causes timing errors in synchronous circuits. We propose a methodology for supervised

  14. Reward prediction error signal enhanced by striatum-amygdala interaction explains the acceleration of probabilistic reward learning by emotion.

    Science.gov (United States)

    Watanabe, Noriya; Sakagami, Masamichi; Haruno, Masahiko

    2013-03-06

    Learning does not only depend on rationality, because real-life learning cannot be isolated from emotion or social factors. Therefore, it is intriguing to determine how emotion changes learning, and to identify which neural substrates underlie this interaction. Here, we show that the task-independent presentation of an emotional face before a reward-predicting cue increases the speed of cue-reward association learning in human subjects compared with trials in which a neutral face is presented. This phenomenon was attributable to an increase in the learning rate, which regulates reward prediction errors. Parallel to these behavioral findings, functional magnetic resonance imaging demonstrated that presentation of an emotional face enhanced reward prediction error (RPE) signal in the ventral striatum. In addition, we also found a functional link between this enhanced RPE signal and increased activity in the amygdala following presentation of an emotional face. Thus, this study revealed an acceleration of cue-reward association learning by emotion, and underscored a role of striatum-amygdala interactions in the modulation of the reward prediction errors by emotion.

  15. Accuracy Enhancement with Processing Error Prediction and Compensation of a CNC Flame Cutting Machine Used in Spatial Surface Operating Conditions

    Directory of Open Access Journals (Sweden)

    Shenghai Hu

    2017-04-01

    Full Text Available This study deals with the precision performance of the CNC flame-cutting machine used in spatial surface operating conditions and presents an accuracy enhancement method based on processing error modeling prediction and real-time compensation. Machining coordinate systems and transformation matrix models were established for the CNC flame processing system considering both geometric errors and thermal deformation effects. Meanwhile, prediction and compensation models were constructed related to the actual cutting situation. Focusing on the thermal deformation elements, finite element analysis was used to measure the testing data of thermal errors, the grey system theory was applied to optimize the key thermal points, and related thermal dynamics models were carried out to achieve high-precision prediction values. Comparison experiments between the proposed method and the teaching method were conducted on the processing system after performing calibration. The results showed that the proposed method is valid and the cutting quality could be improved by more than 30% relative to the teaching method. Furthermore, the proposed method can be used under any working condition by making a few adjustments to the prediction and compensation models.

  16. Minimising the expectation value of the procurement cost in electricity markets based on the prediction error of energy consumption

    OpenAIRE

    Yamaguchi, Naoya; Hori, Maiya; Ideguchi, Yoshinari

    2018-01-01

    In this paper, we formulate a method for minimising the expectation value of the procurement cost of electricity in two popular spot markets: {\\it day-ahead} and {\\it intra-day}, under the assumption that expectation value of unit prices and the distributions of prediction errors for the electricity demand traded in two markets are known. The expectation value of the total electricity cost is minimised over two parameters that change the amounts of electricity. Two parameters depend only on t...

  17. Real-time prediction of atmospheric Lagrangian coherent structures based on forecast data: An application and error analysis

    Science.gov (United States)

    BozorgMagham, Amir E.; Ross, Shane D.; Schmale, David G.

    2013-09-01

    The language of Lagrangian coherent structures (LCSs) provides a new means for studying transport and mixing of passive particles advected by an atmospheric flow field. Recent observations suggest that LCSs govern the large-scale atmospheric motion of airborne microorganisms, paving the way for more efficient models and management strategies for the spread of infectious diseases affecting plants, domestic animals, and humans. In addition, having reliable predictions of the timing of hyperbolic LCSs may contribute to improved aerobiological sampling of microorganisms with unmanned aerial vehicles and LCS-based early warning systems. Chaotic atmospheric dynamics lead to unavoidable forecasting errors in the wind velocity field, which compounds errors in LCS forecasting. In this study, we reveal the cumulative effects of errors of (short-term) wind field forecasts on the finite-time Lyapunov exponent (FTLE) fields and the associated LCSs when realistic forecast plans impose certain limits on the forecasting parameters. Objectives of this paper are to (a) quantify the accuracy of prediction of FTLE-LCS features and (b) determine the sensitivity of such predictions to forecasting parameters. Results indicate that forecasts of attracting LCSs exhibit less divergence from the archive-based LCSs than the repelling features. This result is important since attracting LCSs are the backbone of long-lived features in moving fluids. We also show under what circumstances one can trust the forecast results if one merely wants to know if an LCS passed over a region and does not need to precisely know the passage time.

  18. Prediction and error growth in the daily forecast of precipitation from ...

    Indian Academy of Sciences (India)

    J. Earth Syst. Sci. 125, No. 1, February ... various climate models (Shukla 1985; Savijarvi. 1994; Shukla and ... of view of the socio-economic impact perspective. The rate of error ..... bias over the Indian Ocean, cloud parameteriza- tion schemes ...

  19. The predictability of name pronunciation errors in four South African languages

    CSIR Research Space (South Africa)

    Kgampe, M

    2011-11-01

    Full Text Available of the the typical errors made by speakers from four South African languages (Setswana, English, isiZulu) when producing names from the same four languages. We compare these results with the pronunciations generated by four language-specific grapheme-to-phoneme (G2P...

  20. Individual Differences in Working Memory Capacity Predict Action Monitoring and the Error-Related Negativity

    Science.gov (United States)

    Miller, A. Eve; Watson, Jason M.; Strayer, David L.

    2012-01-01

    Neuroscience suggests that the anterior cingulate cortex (ACC) is responsible for conflict monitoring and the detection of errors in cognitive tasks, thereby contributing to the implementation of attentional control. Though individual differences in frontally mediated goal maintenance have clearly been shown to influence outward behavior in…

  1. Reward inference by primate prefrontal and striatal neurons.

    Science.gov (United States)

    Pan, Xiaochuan; Fan, Hongwei; Sawa, Kosuke; Tsuda, Ichiro; Tsukada, Minoru; Sakagami, Masamichi

    2014-01-22

    The brain contains multiple yet distinct systems involved in reward prediction. To understand the nature of these processes, we recorded single-unit activity from the lateral prefrontal cortex (LPFC) and the striatum in monkeys performing a reward inference task using an asymmetric reward schedule. We found that neurons both in the LPFC and in the striatum predicted reward values for stimuli that had been previously well experienced with set reward quantities in the asymmetric reward task. Importantly, these LPFC neurons could predict the reward value of a stimulus using transitive inference even when the monkeys had not yet learned the stimulus-reward association directly; whereas these striatal neurons did not show such an ability. Nevertheless, because there were two set amounts of reward (large and small), the selected striatal neurons were able to exclusively infer the reward value (e.g., large) of one novel stimulus from a pair after directly experiencing the alternative stimulus with the other reward value (e.g., small). Our results suggest that although neurons that predict reward value for old stimuli in the LPFC could also do so for new stimuli via transitive inference, those in the striatum could only predict reward for new stimuli via exclusive inference. Moreover, the striatum showed more complex functions than was surmised previously for model-free learning.

  2. Error associated with model predictions of wildland fire rate of spread

    Science.gov (United States)

    Miguel G. Cruz; Martin E. Alexander

    2015-01-01

    How well can we expect to predict the spread rate of wildfires and prescribed fires? The degree of accuracy in model predictions of wildland fire behaviour characteristics are dependent on the model's applicability to a given situation, the validity of the model's relationships, and the reliability of the model input data (Alexander and Cruz 2013b#. We...

  3. Human Error Prediction and Countermeasures based on CREAM in Loading and Storage Phase of Spent Nuclear Fuel (SNF)

    International Nuclear Information System (INIS)

    Kim, Jae San; Kim, Min Su; Jo, Seong Youn

    2007-01-01

    With the steady demands for nuclear power energy in Korea, the amount of accumulated SNF has inevitably increased year by year. Thus far, SNF has been on-site transported from one unit to a nearby unit or an on-site dry storage facility. In the near future, as the amount of SNF generated approaches the capacity of these facilities, a percentage of it will be transported to another SNF storage facility. In the process of transporting SNF, human interactions involve inspecting and preparing the cask and spent fuel, loading the cask, transferring the cask and storage or monitoring the cask, etc. So, human actions play a significant role in SNF transportation. In analyzing incidents that have occurred during transport operations, several recent studies have indicated that 'human error' is a primary cause. Therefore, the objectives of this study are to predict and identify possible human errors during the loading and storage of SNF. Furthermore, after evaluating human error for each process, countermeasures to minimize human error are deduced

  4. An Empirical Analysis for the Prediction of a Financial Crisis in Turkey through the Use of Forecast Error Measures

    Directory of Open Access Journals (Sweden)

    Seyma Caliskan Cavdar

    2015-08-01

    Full Text Available In this study, we try to examine whether the forecast errors obtained by the ANN models affect the breakout of financial crises. Additionally, we try to investigate how much the asymmetric information and forecast errors are reflected on the output values. In our study, we used the exchange rate of USD/TRY (USD, the Borsa Istanbul 100 Index (BIST, and gold price (GP as our output variables of our Artificial Neural Network (ANN models. We observe that the predicted ANN model has a strong explanation capability for the 2001 and 2008 crises. Our calculations of some symmetry measures such as mean absolute percentage error (MAPE, symmetric mean absolute percentage error (sMAPE, and Shannon entropy (SE, clearly demonstrate the degree of asymmetric information and the deterioration of the financial system prior to, during, and after the financial crisis. We found that the asymmetric information prior to crisis is larger as compared to other periods. This situation can be interpreted as early warning signals before the potential crises. This evidence seems to favor an asymmetric information view of financial crises.

  5. The predicted CLARREO sampling error of the inter-annual SW variability

    Science.gov (United States)

    Doelling, D. R.; Keyes, D. F.; Nguyen, C.; Macdonnell, D.; Young, D. F.

    2009-12-01

    The NRC Decadal Survey has called for SI traceability of long-term hyper-spectral flux measurements in order to monitor climate variability. This mission is called the Climate Absolute Radiance and Refractivity Observatory (CLARREO) and is currently defining its mission requirements. The requirements are focused on the ability to measure decadal change of key climate variables at very high accuracy. The accuracy goals are set using anticipated climate change magnitudes, but the accuracy achieved for any given climate variable must take into account the temporal and spatial sampling errors based on satellite orbits and calibration accuracy. The time period to detect a significant trend in the CLARREO record depends on the magnitude of the sampling calibration errors relative to the current inter-annual variability. The largest uncertainty in climate feedbacks remains the effect of changing clouds on planetary energy balance. Some regions on earth have strong diurnal cycles, such as maritime stratus and afternoon land convection; other regions have strong seasonal cycles, such as the monsoon. However, when monitoring inter-annual variability these cycles are only important if the strength of these cycles vary on decadal time scales. This study will attempt to determine the best satellite constellations to reduce sampling error and to compare the error with the current inter-annual variability signal to ensure the viability of the mission. The study will incorporate Clouds and the Earth's Radiant Energy System (CERES) (Monthly TOA/Surface Averages) SRBAVG product TOA LW and SW climate quality fluxes. The fluxes are derived by combining Terra (10:30 local equator crossing time) CERES fluxes with 3-hourly 5-geostationary satellite estimated broadband fluxes, which are normalized using the CERES fluxes, to complete the diurnal cycle. These fluxes were saved hourly during processing and considered the truth dataset. 90°, 83° and 74° inclination precessionary orbits as

  6. Spatial measurement error and correction by spatial SIMEX in linear regression models when using predicted air pollution exposures.

    Science.gov (United States)

    Alexeeff, Stacey E; Carroll, Raymond J; Coull, Brent

    2016-04-01

    Spatial modeling of air pollution exposures is widespread in air pollution epidemiology research as a way to improve exposure assessment. However, there are key sources of exposure model uncertainty when air pollution is modeled, including estimation error and model misspecification. We examine the use of predicted air pollution levels in linear health effect models under a measurement error framework. For the prediction of air pollution exposures, we consider a universal Kriging framework, which may include land-use regression terms in the mean function and a spatial covariance structure for the residuals. We derive the bias induced by estimation error and by model misspecification in the exposure model, and we find that a misspecified exposure model can induce asymptotic bias in the effect estimate of air pollution on health. We propose a new spatial simulation extrapolation (SIMEX) procedure, and we demonstrate that the procedure has good performance in correcting this asymptotic bias. We illustrate spatial SIMEX in a study of air pollution and birthweight in Massachusetts. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  7. Dorsal Anterior Cingulate Cortices Differentially Lateralize Prediction Errors and Outcome Valence in a Decision-Making Task

    Directory of Open Access Journals (Sweden)

    Alexander R. Weiss

    2018-05-01

    Full Text Available The dorsal anterior cingulate cortex (dACC is proposed to facilitate learning by signaling mismatches between the expected outcome of decisions and the actual outcomes in the form of prediction errors. The dACC is also proposed to discriminate outcome valence—whether a result has positive (either expected or desirable or negative (either unexpected or undesirable value. However, direct electrophysiological recordings from human dACC to validate these separate, but integrated, dimensions have not been previously performed. We hypothesized that local field potentials (LFPs would reveal changes in the dACC related to prediction error and valence and used the unique opportunity offered by deep brain stimulation (DBS surgery in the dACC of three human subjects to test this hypothesis. We used a cognitive task that involved the presentation of object pairs, a motor response, and audiovisual feedback to guide future object selection choices. The dACC displayed distinctly lateralized theta frequency (3–8 Hz event-related potential responses—the left hemisphere dACC signaled outcome valence and prediction errors while the right hemisphere dACC was involved in prediction formation. Multivariate analyses provided evidence that the human dACC response to decision outcomes reflects two spatiotemporally distinct early and late systems that are consistent with both our lateralized electrophysiological results and the involvement of the theta frequency oscillatory activity in dACC cognitive processing. Further findings suggested that dACC does not respond to other phases of action-outcome-feedback tasks such as the motor response which supports the notion that dACC primarily signals information that is crucial for behavioral monitoring and not for motor control.

  8. Predicting crystalline lens fall caused by accommodation from changes in wavefront error

    Science.gov (United States)

    He, Lin; Applegate, Raymond A.

    2011-01-01

    PURPOSE To illustrate and develop a method for estimating crystalline lens decentration as a function of accommodative response using changes in wavefront error and show the method and limitations using previously published data (2004) from 2 iridectomized monkey eyes so that clinicians understand how spherical aberration can induce coma, in particular in intraocular lens surgery. SETTINGS College of Optometry, University of Houston, Houston, USA. DESIGN Evaluation of diagnostic test or technology. METHODS Lens decentration was estimated by displacing downward the wavefront error of the lens with respect to the limiting aperture (7.0 mm) and ocular first surface wavefront error for each accommodative response (0.00 to 11.00 diopters) until measured values of vertical coma matched previously published experimental data (2007). Lens decentration was also calculated using an approximation formula that only included spherical aberration and vertical coma. RESULTS The change in calculated vertical coma was consistent with downward lens decentration. Calculated downward lens decentration peaked at approximately 0.48 mm of vertical decentration in the right eye and approximately 0.31 mm of decentration in the left eye using all Zernike modes through the 7th radial order. Calculated lens decentration using only coma and spherical aberration formulas was peaked at approximately 0.45 mm in the right eye and approximately 0.23 mm in the left eye. CONCLUSIONS Lens fall as a function of accommodation was quantified noninvasively using changes in vertical coma driven principally by the accommodation-induced changes in spherical aberration. The newly developed method was valid for a large pupil only. PMID:21700108

  9. Numerical Predictions of Static-Pressure-Error Corrections for a Modified T-38C Aircraft

    Science.gov (United States)

    2014-12-15

    but the more modern work of Latif et al . [11] demonstrated that compensated Pitot-static probes can be simulated accurately for subsonic and...what was originally estimated from CFD simulations in Bhamidipati et al . [3] by extracting the static-pressure error in front of the production probe...Aerodynamically Compensating Pitot Tube,” Journal of Aircraft, Vol. 25, No. 6, 1988, pp. 544–547. doi:10.2514/3.45620 [11] Latif , A., Masud, J., Sheikh, S. R., and

  10. Evaluation of dose prediction errors and optimization convergence errors of deliverable-based head-and-neck IMRT plans computed with a superposition/convolution dose algorithm

    International Nuclear Information System (INIS)

    Mihaylov, I. B.; Siebers, J. V.

    2008-01-01

    The purpose of this study is to evaluate dose prediction errors (DPEs) and optimization convergence errors (OCEs) resulting from use of a superposition/convolution dose calculation algorithm in deliverable intensity-modulated radiation therapy (IMRT) optimization for head-and-neck (HN) patients. Thirteen HN IMRT patient plans were retrospectively reoptimized. The IMRT optimization was performed in three sequential steps: (1) fast optimization in which an initial nondeliverable IMRT solution was achieved and then converted to multileaf collimator (MLC) leaf sequences; (2) mixed deliverable optimization that used a Monte Carlo (MC) algorithm to account for the incident photon fluence modulation by the MLC, whereas a superposition/convolution (SC) dose calculation algorithm was utilized for the patient dose calculations; and (3) MC deliverable-based optimization in which both fluence and patient dose calculations were performed with a MC algorithm. DPEs of the mixed method were quantified by evaluating the differences between the mixed optimization SC dose result and a MC dose recalculation of the mixed optimization solution. OCEs of the mixed method were quantified by evaluating the differences between the MC recalculation of the mixed optimization solution and the final MC optimization solution. The results were analyzed through dose volume indices derived from the cumulative dose-volume histograms for selected anatomic structures. Statistical equivalence tests were used to determine the significance of the DPEs and the OCEs. Furthermore, a correlation analysis between DPEs and OCEs was performed. The evaluated DPEs were within ±2.8% while the OCEs were within 5.5%, indicating that OCEs can be clinically significant even when DPEs are clinically insignificant. The full MC-dose-based optimization reduced normal tissue dose by as much as 8.5% compared with the mixed-method optimization results. The DPEs and the OCEs in the targets had correlation coefficients greater

  11. Straight line fitting and predictions: On a marginal likelihood approach to linear regression and errors-in-variables models

    Science.gov (United States)

    Christiansen, Bo

    2015-04-01

    Linear regression methods are without doubt the most used approaches to describe and predict data in the physical sciences. They are often good first order approximations and they are in general easier to apply and interpret than more advanced methods. However, even the properties of univariate regression can lead to debate over the appropriateness of various models as witnessed by the recent discussion about climate reconstruction methods. Before linear regression is applied important choices have to be made regarding the origins of the noise terms and regarding which of the two variables under consideration that should be treated as the independent variable. These decisions are often not easy to make but they may have a considerable impact on the results. We seek to give a unified probabilistic - Bayesian with flat priors - treatment of univariate linear regression and prediction by taking, as starting point, the general errors-in-variables model (Christiansen, J. Clim., 27, 2014-2031, 2014). Other versions of linear regression can be obtained as limits of this model. We derive the likelihood of the model parameters and predictands of the general errors-in-variables model by marginalizing over the nuisance parameters. The resulting likelihood is relatively simple and easy to analyze and calculate. The well known unidentifiability of the errors-in-variables model is manifested as the absence of a well-defined maximum in the likelihood. However, this does not mean that probabilistic inference can not be made; the marginal likelihoods of model parameters and the predictands have, in general, well-defined maxima. We also include a probabilistic version of classical calibration and show how it is related to the errors-in-variables model. The results are illustrated by an example from the coupling between the lower stratosphere and the troposphere in the Northern Hemisphere winter.

  12. Optimal classifier selection and negative bias in error rate estimation: an empirical study on high-dimensional prediction

    Directory of Open Access Journals (Sweden)

    Boulesteix Anne-Laure

    2009-12-01

    Full Text Available Abstract Background In biometric practice, researchers often apply a large number of different methods in a "trial-and-error" strategy to get as much as possible out of their data and, due to publication pressure or pressure from the consulting customer, present only the most favorable results. This strategy may induce a substantial optimistic bias in prediction error estimation, which is quantitatively assessed in the present manuscript. The focus of our work is on class prediction based on high-dimensional data (e.g. microarray data, since such analyses are particularly exposed to this kind of bias. Methods In our study we consider a total of 124 variants of classifiers (possibly including variable selection or tuning steps within a cross-validation evaluation scheme. The classifiers are applied to original and modified real microarray data sets, some of which are obtained by randomly permuting the class labels to mimic non-informative predictors while preserving their correlation structure. Results We assess the minimal misclassification rate over the different variants of classifiers in order to quantify the bias arising when the optimal classifier is selected a posteriori in a data-driven manner. The bias resulting from the parameter tuning (including gene selection parameters as a special case and the bias resulting from the choice of the classification method are examined both separately and jointly. Conclusions The median minimal error rate over the investigated classifiers was as low as 31% and 41% based on permuted uninformative predictors from studies on colon cancer and prostate cancer, respectively. We conclude that the strategy to present only the optimal result is not acceptable because it yields a substantial bias in error rate estimation, and suggest alternative approaches for properly reporting classification accuracy.

  13. A national prediction model for PM2.5 component exposures and measurement error-corrected health effect inference.

    Science.gov (United States)

    Bergen, Silas; Sheppard, Lianne; Sampson, Paul D; Kim, Sun-Young; Richards, Mark; Vedal, Sverre; Kaufman, Joel D; Szpiro, Adam A

    2013-09-01

    Studies estimating health effects of long-term air pollution exposure often use a two-stage approach: building exposure models to assign individual-level exposures, which are then used in regression analyses. This requires accurate exposure modeling and careful treatment of exposure measurement error. To illustrate the importance of accounting for exposure model characteristics in two-stage air pollution studies, we considered a case study based on data from the Multi-Ethnic Study of Atherosclerosis (MESA). We built national spatial exposure models that used partial least squares and universal kriging to estimate annual average concentrations of four PM2.5 components: elemental carbon (EC), organic carbon (OC), silicon (Si), and sulfur (S). We predicted PM2.5 component exposures for the MESA cohort and estimated cross-sectional associations with carotid intima-media thickness (CIMT), adjusting for subject-specific covariates. We corrected for measurement error using recently developed methods that account for the spatial structure of predicted exposures. Our models performed well, with cross-validated R2 values ranging from 0.62 to 0.95. Naïve analyses that did not account for measurement error indicated statistically significant associations between CIMT and exposure to OC, Si, and S. EC and OC exhibited little spatial correlation, and the corrected inference was unchanged from the naïve analysis. The Si and S exposure surfaces displayed notable spatial correlation, resulting in corrected confidence intervals (CIs) that were 50% wider than the naïve CIs, but that were still statistically significant. The impact of correcting for measurement error on health effect inference is concordant with the degree of spatial correlation in the exposure surfaces. Exposure model characteristics must be considered when performing two-stage air pollution epidemiologic analyses because naïve health effect inference may be inappropriate.

  14. Analysis of errors introduced by geographic coordinate systems on weather numeric prediction modeling

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    Y. Cao

    2017-09-01

    Full Text Available Most atmospheric models, including the Weather Research and Forecasting (WRF model, use a spherical geographic coordinate system to internally represent input data and perform computations. However, most geographic information system (GIS input data used by the models are based on a spheroid datum because it better represents the actual geometry of the earth. WRF and other atmospheric models use these GIS input layers as if they were in a spherical coordinate system without accounting for the difference in datum. When GIS layers are not properly reprojected, latitudinal errors of up to 21 km in the midlatitudes are introduced. Recent studies have suggested that for very high-resolution applications, the difference in datum in the GIS input data (e.g., terrain land use, orography should be taken into account. However, the magnitude of errors introduced by the difference in coordinate systems remains unclear. This research quantifies the effect of using a spherical vs. a spheroid datum for the input GIS layers used by WRF to study greenhouse gas transport and dispersion in northeast Pennsylvania.

  15. Efficient thermal error prediction in a machine tool using finite element analysis

    International Nuclear Information System (INIS)

    Mian, Naeem S; Fletcher, Simon; Longstaff, Andrew P; Myers, Alan

    2011-01-01

    Thermally induced errors have a major significance on the positional accuracy of a machine tool. Heat generated during the machining process produces thermal gradients that flow through the machine structure causing linear and nonlinear thermal expansions and distortions of associated complex discrete structures, producing deformations that adversely affect structural stability. The heat passes through structural linkages and mechanical joints where interfacial parameters such as the roughness and form of the contacting surfaces affect the thermal resistance and thus the heat transfer coefficients. This paper presents a novel offline technique using finite element analysis (FEA) to simulate the effects of the major internal heat sources such as bearings, motors and belt drives of a small vertical milling machine (VMC) and the effects of ambient temperature pockets that build up during the machine operation. Simplified models of the machine have been created offline using FEA software and evaluated experimental results applied for offline thermal behaviour simulation of the full machine structure. The FEA simulated results are in close agreement with the experimental results ranging from 65% to 90% for a variety of testing regimes and revealed a maximum error range of 70 µm reduced to less than 10 µm

  16. A simple solution for model comparison in bold imaging: the special case of reward prediction error and reward outcomes.

    Science.gov (United States)

    Erdeniz, Burak; Rohe, Tim; Done, John; Seidler, Rachael D

    2013-01-01

    Conventional neuroimaging techniques provide information about condition-related changes of the BOLD (blood-oxygen-level dependent) signal, indicating only where and when the underlying cognitive processes occur. Recently, with the help of a new approach called "model-based" functional neuroimaging (fMRI), researchers are able to visualize changes in the internal variables of a time varying learning process, such as the reward prediction error or the predicted reward value of a conditional stimulus. However, despite being extremely beneficial to the imaging community in understanding the neural correlates of decision variables, a model-based approach to brain imaging data is also methodologically challenging due to the multicollinearity problem in statistical analysis. There are multiple sources of multicollinearity in functional neuroimaging including investigations of closely related variables and/or experimental designs that do not account for this. The source of multicollinearity discussed in this paper occurs due to correlation between different subjective variables that are calculated very close in time. Here, we review methodological approaches to analyzing such data by discussing the special case of separating the reward prediction error signal from reward outcomes.

  17. Error Concealment Method Based on Motion Vector Prediction Using Particle Filters

    Directory of Open Access Journals (Sweden)

    B. Hrusovsky

    2011-09-01

    Full Text Available Video transmitted over unreliable environment, such as wireless channel or in generally any network with unreliable transport protocol, is facing the losses of video packets due to network congestion and different kind of noises. The problem is becoming more important using highly effective video codecs. Visual quality degradation could propagate into subsequent frames due to redundancy elimination in order to obtain high compression ratio. Since the video stream transmission in real time is limited by transmission channel delay, it is not possible to retransmit all faulty or lost packets. It is therefore inevitable to conceal these defects. To reduce the undesirable effects of information losses, the lost data is usually estimated from the received data, which is generally known as error concealment problem. This paper discusses packet loss modeling in order to simulate losses during video transmission, packet losses analysis and their impacts on the motion vectors losses.

  18. Elevated Striatal Reactivity Across Monetary and Social Rewards in Bipolar I Disorder

    Science.gov (United States)

    Dutra, Sunny J.; Cunningham, William A.; Kober, Hedy; Gruber, June

    2016-01-01

    Bipolar disorder (BD) is associated with increased reactivity to rewards and heightened positive affectivity. It is less clear to what extent this heightened reward sensitivity is evident across contexts and what the associated neural mechanisms might be. The present investigation employed both a monetary and social incentive delay task among adults with remitted BD type I (N=24) and a healthy non-psychiatric control group (HC; N=25) using fMRI. Both whole-brain and region-of-interest analyses revealed elevated ventral and dorsal striatal reactivity across monetary and social reward receipt, but not anticipation, in the BD group. Post-hoc analyses further suggested that greater striatal reactivity to reward receipt across monetary and social reward tasks predicted decreased self-reported positive affect when anticipating subsequent rewards in the HC, but not BD, group. Results point toward elevated striatal reactivity to reward receipt as a potential neural mechanism of reward reactivity. PMID:26390194

  19. Prediction beyond the borders: ERP indices of boundary extension-related error.

    Science.gov (United States)

    Czigler, István; Intraub, Helene; Stefanics, Gábor

    2013-01-01

    Boundary extension (BE) is a rapidly occurring memory error in which participants incorrectly remember having seen beyond the boundaries of a view. However, behavioral data has provided no insight into how quickly after the onset of a test picture the effect is detected. To determine the time course of BE from neural responses we conducted a BE experiment while recording EEG. We exploited a diagnostic response asymmetry to mismatched views (a closer and wider view of the same scene) in which the same pair of views is rated as more similar when the closer item is shown first than vice versa. On each trial, a closer or wider view was presented for 250 ms followed by a 250-ms mask and either the identical view or a mismatched view. Boundary ratings replicated the typical asymmetry. We found a similar asymmetry in ERP responses in the 265-285 ms interval where the second member of the close-then-wide pairs evoked less negative responses at left parieto-temporal sites compared to the wide-then-close condition. We also found diagnostic ERP effects in the 500-560 ms range, where ERPs to wide-then-close pairs were more positive at centro-parietal sites than in the other three conditions, which is thought to be related to participants' confidence in their perceptual decision. The ERP effect in the 265-285 ms range suggests the falsely remembered region beyond the view-boundaries of S1 is rapidly available and impacts assessment of the test picture within the first 265 ms of viewing, suggesting that extrapolated scene structure may be computed rapidly enough to play a role in the integration of successive views during visual scanning.

  20. The disparity mutagenesis model predicts rescue of living things from catastrophic errors

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    Mitsuru eFurusawa

    2014-12-01

    Full Text Available In animals including humans, mutation rates per generation will exceed a perceived threshold, which should result in an excessive genetic load. Despite this, they have survived without extinction. This is a perplexing problem for human genetics, arising at the end of the last century, and to date still does not have a fully satisfactory explanation. Shortly after we proposed the disparity theory of evolution in 1992, the disparity mutagenesis model was proposed, which forms the basis for an explanation for an acceleration of evolution and species survival. This model predicts a significant increase of the mutation threshold values if there is a high enough fidelity difference in replication between the lagging and leading strands. When applied to biological evolution, the model predicts that living things, including humans, might overcome the lethal effect of accumulated deleterious mutations and be able to survive. Artificially-prepared mutator strains of microorganisms, in which an enhanced lagging-strand-biased mutagenesis was introduced, showed unexpectedly high adaptability to severe environments. The implications of the striking behaviors shown by these disparity mutators will be discussed in relation to how living things with high mutation rates can avoid the self-defeating risk of excess mutations.

  1. The information value of early career productivity in mathematics: a ROC analysis of prediction errors in bibliometricly informed decision making.

    Science.gov (United States)

    Lindahl, Jonas; Danell, Rickard

    The aim of this study was to provide a framework to evaluate bibliometric indicators as decision support tools from a decision making perspective and to examine the information value of early career publication rate as a predictor of future productivity. We used ROC analysis to evaluate a bibliometric indicator as a tool for binary decision making. The dataset consisted of 451 early career researchers in the mathematical sub-field of number theory. We investigated the effect of three different definitions of top performance groups-top 10, top 25, and top 50 %; the consequences of using different thresholds in the prediction models; and the added prediction value of information on early career research collaboration and publications in prestige journals. We conclude that early career performance productivity has an information value in all tested decision scenarios, but future performance is more predictable if the definition of a high performance group is more exclusive. Estimated optimal decision thresholds using the Youden index indicated that the top 10 % decision scenario should use 7 articles, the top 25 % scenario should use 7 articles, and the top 50 % should use 5 articles to minimize prediction errors. A comparative analysis between the decision thresholds provided by the Youden index which take consequences into consideration and a method commonly used in evaluative bibliometrics which do not take consequences into consideration when determining decision thresholds, indicated that differences are trivial for the top 25 and the 50 % groups. However, a statistically significant difference between the methods was found for the top 10 % group. Information on early career collaboration and publication strategies did not add any prediction value to the bibliometric indicator publication rate in any of the models. The key contributions of this research is the focus on consequences in terms of prediction errors and the notion of transforming uncertainty

  2. Mechanisms mediating parallel action monitoring in fronto-striatal circuits.

    Science.gov (United States)

    Beste, Christian; Ness, Vanessa; Lukas, Carsten; Hoffmann, Rainer; Stüwe, Sven; Falkenstein, Michael; Saft, Carsten

    2012-08-01

    Flexible response adaptation and the control of conflicting information play a pivotal role in daily life. Yet, little is known about the neuronal mechanisms mediating parallel control of these processes. We examined these mechanisms using a multi-methodological approach that integrated data from event-related potentials (ERPs) with structural MRI data and source localisation using sLORETA. Moreover, we calculated evoked wavelet oscillations. We applied this multi-methodological approach in healthy subjects and patients in a prodromal phase of a major basal ganglia disorder (i.e., Huntington's disease), to directly focus on fronto-striatal networks. Behavioural data indicated, especially the parallel execution of conflict monitoring and flexible response adaptation was modulated across the examined cohorts. When both processes do not co-incide a high integrity of fronto-striatal loops seems to be dispensable. The neurophysiological data suggests that conflict monitoring (reflected by the N2 ERP) and working memory processes (reflected by the P3 ERP) differentially contribute to this pattern of results. Flexible response adaptation under the constraint of high conflict processing affected the N2 and P3 ERP, as well as their delta frequency band oscillations. Yet, modulatory effects were strongest for the N2 ERP and evoked wavelet oscillations in this time range. The N2 ERPs were localized in the anterior cingulate cortex (BA32, BA24). Modulations of the P3 ERP were localized in parietal areas (BA7). In addition, MRI-determined caudate head volume predicted modulations in conflict monitoring, but not working memory processes. The results show how parallel conflict monitoring and flexible adaptation of action is mediated via fronto-striatal networks. While both, response monitoring and working memory processes seem to play a role, especially response selection processes and ACC-basal ganglia networks seem to be the driving force in mediating parallel conflict

  3. A Real-Time Accurate Model and Its Predictive Fuzzy PID Controller for Pumped Storage Unit via Error Compensation

    Directory of Open Access Journals (Sweden)

    Jianzhong Zhou

    2017-12-01

    Full Text Available Model simulation and control of pumped storage unit (PSU are essential to improve the dynamic quality of power station. Only under the premise of the PSU models reflecting the actual transient process, the novel control method can be properly applied in the engineering. The contributions of this paper are that (1 a real-time accurate equivalent circuit model (RAECM of PSU via error compensation is proposed to reconcile the conflict between real-time online simulation and accuracy under various operating conditions, and (2 an adaptive predicted fuzzy PID controller (APFPID based on RAECM is put forward to overcome the instability of conventional control under no-load conditions with low water head. Respectively, all hydraulic factors in pipeline system are fully considered based on equivalent lumped-circuits theorem. The pretreatment, which consists of improved Suter-transformation and BP neural network, and online simulation method featured by two iterative loops are synthetically proposed to improve the solving accuracy of the pump-turbine. Moreover, the modified formulas for compensating error are derived with variable-spatial discretization to improve the accuracy of the real-time simulation further. The implicit RadauIIA method is verified to be more suitable for PSUGS owing to wider stable domain. Then, APFPID controller is constructed based on the integration of fuzzy PID and the model predictive control. Rolling prediction by RAECM is proposed to replace rolling optimization with its computational speed guaranteed. Finally, the simulation and on-site measurements are compared to prove trustworthy of RAECM under various running conditions. Comparative experiments also indicate that APFPID controller outperforms other controllers in most cases, especially low water head conditions. Satisfying results of RAECM have been achieved in engineering and it provides a novel model reference for PSUGS.

  4. A Physiologically Based Pharmacokinetic Model to Predict the Pharmacokinetics of Highly Protein-Bound Drugs and Impact of Errors in Plasma Protein Binding

    Science.gov (United States)

    Ye, Min; Nagar, Swati; Korzekwa, Ken

    2015-01-01

    Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data was often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding, and blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for terminal elimination half-life (t1/2, 100% of drugs), peak plasma concentration (Cmax, 100%), area under the plasma concentration-time curve (AUC0–t, 95.4%), clearance (CLh, 95.4%), mean retention time (MRT, 95.4%), and steady state volume (Vss, 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. PMID:26531057

  5. A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

    Science.gov (United States)

    Ye, Min; Nagar, Swati; Korzekwa, Ken

    2016-04-01

    Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  6. Addressing Common Cloud-Radiation Errors from 4-hour to 4-week Model Prediction

    Science.gov (United States)

    Benjamin, S.; Sun, S.; Grell, G. A.; Green, B.; Olson, J.; Kenyon, J.; James, E.; Smirnova, T. G.; Brown, J. M.

    2017-12-01

    Cloud-radiation representation in models for subgrid-scale clouds is a known gap from subseasonal-to-seasonal models down to storm-scale models applied for forecast duration of only a few hours. NOAA/ESRL has been applying common physical parameterizations for scale-aware deep/shallow convection and boundary-layer mixing over this wide range of time and spatial scales, with some progress to be reported in this presentation. The Grell-Freitas scheme (2014, Atmos. Chem. Phys.) and MYNN boundary-layer EDMF scheme (Olson / Benjamin et al. 2016 Mon. Wea. Rev.) have been applied and tested extensively for the NOAA hourly updated 3-km High-Resolution Rapid Refresh (HRRR) and 13-km Rapid Refresh (RAP) model/assimilation systems over the United States and North America, with targeting toward improvement to boundary-layer evolution and cloud-radiation representation in all seasons. This representation is critical for both warm-season severe convective storm forecasting and for winter-storm prediction of snow and mixed precipitation. At the same time the Grell-Freitas scheme has been applied also as an option for subseasonal forecasting toward improved US week 3-4 prediction with the FIM-HYCOM coupled model (Green et al 2017, MWR). Cloud/radiation evaluation using CERES satellite-based estimates have been applied to both 12-h RAP (13km) and also during Weeks 1-4 from 32-day FIM-HYCOM (60km) forecasts. Initial results reveal that improved cloud representation is needed for both resolutions and now is guiding further refinement for cloud representation including with the Grell-Freitas scheme and with the updated MYNN-EDMF scheme (both now also in global testing as well as with the 3km HRRR and 13km RAP models).

  7. From prediction error to incentive salience: mesolimbic computation of reward motivation

    Science.gov (United States)

    Berridge, Kent C.

    2011-01-01

    Reward contains separable psychological components of learning, incentive motivation and pleasure. Most computational models have focused only on the learning component of reward, but the motivational component is equally important in reward circuitry, and even more directly controls behavior. Modeling the motivational component requires recognition of additional control factors besides learning. Here I will discuss how mesocorticolimbic mechanisms generate the motivation component of incentive salience. Incentive salience takes Pavlovian learning and memory as one input and as an equally important input takes neurobiological state factors (e.g., drug states, appetite states, satiety states) that can vary independently of learning. Neurobiological state changes can produce unlearned fluctuations or even reversals in the ability of a previously-learned reward cue to trigger motivation. Such fluctuations in cue-triggered motivation can dramatically depart from all previously learned values about the associated reward outcome. Thus a consequence of the difference between incentive salience and learning can be to decouple cue-triggered motivation of the moment from previously learned values of how good the associated reward has been in the past. Another consequence can be to produce irrationally strong motivation urges that are not justified by any memories of previous reward values (and without distorting associative predictions of future reward value). Such irrationally strong motivation may be especially problematic in addiction. To comprehend these phenomena, future models of mesocorticolimbic reward function should address the neurobiological state factors that participate to control generation of incentive salience. PMID:22487042

  8. Cloud Condensation Nuclei Prediction Error from Application of Kohler Theory: Importance for the Aerosol Indirect Effect

    Science.gov (United States)

    Sotiropoulou, Rafaella-Eleni P.; Nenes, Athanasios; Adams, Peter J.; Seinfeld, John H.

    2007-01-01

    In situ observations of aerosol and cloud condensation nuclei (CCN) and the GISS GCM Model II' with an online aerosol simulation and explicit aerosol-cloud interactions are used to quantify the uncertainty in radiative forcing and autoconversion rate from application of Kohler theory. Simulations suggest that application of Koehler theory introduces a 10-20% uncertainty in global average indirect forcing and 2-11% uncertainty in autoconversion. Regionally, the uncertainty in indirect forcing ranges between 10-20%, and 5-50% for autoconversion. These results are insensitive to the range of updraft velocity and water vapor uptake coefficient considered. This study suggests that Koehler theory (as implemented in climate models) is not a significant source of uncertainty for aerosol indirect forcing but can be substantial for assessments of aerosol effects on the hydrological cycle in climatically sensitive regions of the globe. This implies that improvements in the representation of GCM subgrid processes and aerosol size distribution will mostly benefit indirect forcing assessments. Predictions of autoconversion, by nature, will be subject to considerable uncertainty; its reduction may require explicit representation of size-resolved aerosol composition and mixing state.

  9. Cognitive tests predict real-world errors: the relationship between drug name confusion rates in laboratory-based memory and perception tests and corresponding error rates in large pharmacy chains.

    Science.gov (United States)

    Schroeder, Scott R; Salomon, Meghan M; Galanter, William L; Schiff, Gordon D; Vaida, Allen J; Gaunt, Michael J; Bryson, Michelle L; Rash, Christine; Falck, Suzanne; Lambert, Bruce L

    2017-05-01

    Drug name confusion is a common type of medication error and a persistent threat to patient safety. In the USA, roughly one per thousand prescriptions results in the wrong drug being filled, and most of these errors involve drug names that look or sound alike. Prior to approval, drug names undergo a variety of tests to assess their potential for confusability, but none of these preapproval tests has been shown to predict real-world error rates. We conducted a study to assess the association between error rates in laboratory-based tests of drug name memory and perception and real-world drug name confusion error rates. Eighty participants, comprising doctors, nurses, pharmacists, technicians and lay people, completed a battery of laboratory tests assessing visual perception, auditory perception and short-term memory of look-alike and sound-alike drug name pairs (eg, hydroxyzine/hydralazine). Laboratory test error rates (and other metrics) significantly predicted real-world error rates obtained from a large, outpatient pharmacy chain, with the best-fitting model accounting for 37% of the variance in real-world error rates. Cross-validation analyses confirmed these results, showing that the laboratory tests also predicted errors from a second pharmacy chain, with 45% of the variance being explained by the laboratory test data. Across two distinct pharmacy chains, there is a strong and significant association between drug name confusion error rates observed in the real world and those observed in laboratory-based tests of memory and perception. Regulators and drug companies seeking a validated preapproval method for identifying confusing drug names ought to consider using these simple tests. By using a standard battery of memory and perception tests, it should be possible to reduce the number of confusing look-alike and sound-alike drug name pairs that reach the market, which will help protect patients from potentially harmful medication errors. Published by the BMJ

  10. A Post-Harvest Prediction Mass Loss Model for Tomato Fruit Using A Numerical Methodology Centered on Approximation Error Minimization

    Directory of Open Access Journals (Sweden)

    Francisco Javier Bucio

    2017-10-01

    Full Text Available Due to its nutritional and economic value, the tomato is considered one of the main vegetables in terms of production and consumption in the world. For this reason, an important case study is the fruit maturation parametrized by its mass loss in this study. This process develops in the fruit mainly after harvest. Since that parameter affects the economic value of the crop, the scientific community has been progressively approaching the issue. However, there is no a state-of-the-art practical model allowing the prediction of the tomato fruit mass loss yet. This study proposes a prediction model for tomato mass loss in a continuous and definite time-frame using regression methods. The model is based on a combination of adjustment methods such as least squares polynomial regression leading to error estimation, and cross validation techniques. Experimental results from a 50 fruit of tomato sample studied over a 54 days period were compared to results from the model using a second-order polynomial approach found to provide optimal data fit with a resulting efficiency of ~97%. The model also allows the design of precise logistic strategies centered on post-harvest tomato mass loss prediction usable by producers, distributors, and consumers.

  11. Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error

    Science.gov (United States)

    Christensen, N. K.; Minsley, B. J.; Christensen, S.

    2017-02-01

    We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.

  12. Using the area under the curve to reduce measurement error in predicting young adult blood pressure from childhood measures.

    Science.gov (United States)

    Cook, Nancy R; Rosner, Bernard A; Chen, Wei; Srinivasan, Sathanur R; Berenson, Gerald S

    2004-11-30

    Tracking correlations of blood pressure, particularly childhood measures, may be attenuated by within-person variability. Combining multiple measurements can reduce this error substantially. The area under the curve (AUC) computed from longitudinal growth curve models can be used to improve the prediction of young adult blood pressure from childhood measures. Quadratic random-effects models over unequally spaced repeated measures were used to compute the area under the curve separately within the age periods 5-14 and 20-34 years in the Bogalusa Heart Study. This method adjusts for the uneven age distribution and captures the underlying or average blood pressure, leading to improved estimates of correlation and risk prediction. Tracking correlations were computed by race and gender, and were approximately 0.6 for systolic, 0.5-0.6 for K4 diastolic, and 0.4-0.6 for K5 diastolic blood pressure. The AUC can also be used to regress young adult blood pressure on childhood blood pressure and childhood and young adult body mass index (BMI). In these data, while childhood blood pressure and young adult BMI were generally directly predictive of young adult blood pressure, childhood BMI was negatively correlated with young adult blood pressure when childhood blood pressure was in the model. In addition, racial differences in young adult blood pressure were reduced, but not eliminated, after controlling for childhood blood pressure, childhood BMI, and young adult BMI, suggesting that other genetic or lifestyle factors contribute to this difference. 2004 John Wiley & Sons, Ltd.

  13. Generation of 3-D hydrostratigraphic zones from dense airborne electromagnetic data to assess groundwater model prediction error

    Science.gov (United States)

    Christensen, Nikolaj K; Minsley, Burke J.; Christensen, Steen

    2017-01-01

    We present a new methodology to combine spatially dense high-resolution airborne electromagnetic (AEM) data and sparse borehole information to construct multiple plausible geological structures using a stochastic approach. The method developed allows for quantification of the performance of groundwater models built from different geological realizations of structure. Multiple structural realizations are generated using geostatistical Monte Carlo simulations that treat sparse borehole lithological observations as hard data and dense geophysically derived structural probabilities as soft data. Each structural model is used to define 3-D hydrostratigraphical zones of a groundwater model, and the hydraulic parameter values of the zones are estimated by using nonlinear regression to fit hydrological data (hydraulic head and river discharge measurements). Use of the methodology is demonstrated for a synthetic domain having structures of categorical deposits consisting of sand, silt, or clay. It is shown that using dense AEM data with the methodology can significantly improve the estimated accuracy of the sediment distribution as compared to when borehole data are used alone. It is also shown that this use of AEM data can improve the predictive capability of a calibrated groundwater model that uses the geological structures as zones. However, such structural models will always contain errors because even with dense AEM data it is not possible to perfectly resolve the structures of a groundwater system. It is shown that when using such erroneous structures in a groundwater model, they can lead to biased parameter estimates and biased model predictions, therefore impairing the model's predictive capability.

  14. From prediction error to incentive salience: mesolimbic computation of reward motivation.

    Science.gov (United States)

    Berridge, Kent C

    2012-04-01

    Reward contains separable psychological components of learning, incentive motivation and pleasure. Most computational models have focused only on the learning component of reward, but the motivational component is equally important in reward circuitry, and even more directly controls behavior. Modeling the motivational component requires recognition of additional control factors besides learning. Here I discuss how mesocorticolimbic mechanisms generate the motivation component of incentive salience. Incentive salience takes Pavlovian learning and memory as one input and as an equally important input takes neurobiological state factors (e.g. drug states, appetite states, satiety states) that can vary independently of learning. Neurobiological state changes can produce unlearned fluctuations or even reversals in the ability of a previously learned reward cue to trigger motivation. Such fluctuations in cue-triggered motivation can dramatically depart from all previously learned values about the associated reward outcome. Thus, one consequence of the difference between incentive salience and learning can be to decouple cue-triggered motivation of the moment from previously learned values of how good the associated reward has been in the past. Another consequence can be to produce irrationally strong motivation urges that are not justified by any memories of previous reward values (and without distorting associative predictions of future reward value). Such irrationally strong motivation may be especially problematic in addiction. To understand these phenomena, future models of mesocorticolimbic reward function should address the neurobiological state factors that participate to control generation of incentive salience. © 2012 The Author. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

  15. Behavioral sensitivity of temporally modulated striatal neurons

    Directory of Open Access Journals (Sweden)

    George ePortugal

    2011-07-01

    Full Text Available Recent investigations into the neural mechanisms that underlie temporal perception have revealed that the striatum is an important contributor to interval timing processes, and electrophysiological recording studies have shown that the firing rates of striatal neurons are modulated by the time in a trial at which an operant response is made. However, it remains unclear whether striatal firing rate modulations are related to the passage of time alone (i.e., whether temporal information is represented in an abstract manner independent of other attributes of biological importance, or whether this temporal information is embedded within striatal activity related to co-occurring contextual information, such as motor behaviors. This study evaluated these two hypotheses by recording from striatal neurons while rats performed a temporal production task. Rats were trained to respond at different nosepoke apertures for food reward under two simultaneously active reinforcement schedules: a variable-interval (VI-15 sec schedule and a fixed-interval (FI-15 sec schedule of reinforcement. Responding during a trial occurred in a sequential manner composing 3 phases; VI responding, FI responding, VI responding. The vast majority of task-sensitive striatal neurons (95% varied their firing rates associated with equivalent behaviors (e.g., periods in which their snout was held within the nosepoke across these behavioral phases, and 96% of cells varied their firing rates for the same behavior within a phase, thereby demonstrating their sensitivity to time. However, in a direct test of the abstract timing hypothesis, 91% of temporally modulated hold cells were further modulated by the overt motor behaviors associated with transitioning between nosepokes. As such, these data are inconsistent with the striatum representing time in an abstract’ manner, but support the hypothesis that temporal information is embedded within contextual and motor functions of the

  16. A Frequency-Domain Adaptive Filter (FDAF) Prediction Error Method (PEM) Framework for Double-Talk-Robust Acoustic Echo Cancellation

    DEFF Research Database (Denmark)

    Gil-Cacho, Jose M.; van Waterschoot, Toon; Moonen, Marc

    2014-01-01

    to the FDAF-PEM-AFROW algorithm. We show that FDAF-PEM-AFROW is by construction related to the best linear unbiased estimate (BLUE) of the echo path. We depart from this framework to show an improvement in performance with respect to other adaptive filters minimizing the BLUE criterion, namely the PEM......In this paper, we propose a new framework to tackle the double-talk (DT) problem in acoustic echo cancellation (AEC). It is based on a frequency-domain adaptive filter (FDAF) implementation of the so-called prediction error method adaptive filtering using row operations (PEM-AFROW) leading...... regularization (VR) algorithms. The FDAF-PEM-AFROW versions significantly outperform the original versions in every simulation. In terms of computational complexity, the FDAF-PEM-AFROW versions are themselves about two orders of magnitude cheaper than the original versions....

  17. Forensic comparison and matching of fingerprints: using quantitative image measures for estimating error rates through understanding and predicting difficulty.

    Directory of Open Access Journals (Sweden)

    Philip J Kellman

    Full Text Available Latent fingerprint examination is a complex task that, despite advances in image processing, still fundamentally depends on the visual judgments of highly trained human examiners. Fingerprints collected from crime scenes typically contain less information than fingerprints collected under controlled conditions. Specifically, they are often noisy and distorted and may contain only a portion of the total fingerprint area. Expertise in fingerprint comparison, like other forms of perceptual expertise, such as face recognition or aircraft identification, depends on perceptual learning processes that lead to the discovery of features and relations that matter in comparing prints. Relatively little is known about the perceptual processes involved in making comparisons, and even less is known about what characteristics of fingerprint pairs make particular comparisons easy or difficult. We measured expert examiner performance and judgments of difficulty and confidence on a new fingerprint database. We developed a number of quantitative measures of image characteristics and used multiple regression techniques to discover objective predictors of error as well as perceived difficulty and confidence. A number of useful predictors emerged, and these included variables related to image quality metrics, such as intensity and contrast information, as well as measures of information quantity, such as the total fingerprint area. Also included were configural features that fingerprint experts have noted, such as the presence and clarity of global features and fingerprint ridges. Within the constraints of the overall low error rates of experts, a regression model incorporating the derived predictors demonstrated reasonable success in predicting objective difficulty for print pairs, as shown both in goodness of fit measures to the original data set and in a cross validation test. The results indicate the plausibility of using objective image metrics to predict expert

  18. Forensic comparison and matching of fingerprints: using quantitative image measures for estimating error rates through understanding and predicting difficulty.

    Science.gov (United States)

    Kellman, Philip J; Mnookin, Jennifer L; Erlikhman, Gennady; Garrigan, Patrick; Ghose, Tandra; Mettler, Everett; Charlton, David; Dror, Itiel E

    2014-01-01

    Latent fingerprint examination is a complex task that, despite advances in image processing, still fundamentally depends on the visual judgments of highly trained human examiners. Fingerprints collected from crime scenes typically contain less information than fingerprints collected under controlled conditions. Specifically, they are often noisy and distorted and may contain only a portion of the total fingerprint area. Expertise in fingerprint comparison, like other forms of perceptual expertise, such as face recognition or aircraft identification, depends on perceptual learning processes that lead to the discovery of features and relations that matter in comparing prints. Relatively little is known about the perceptual processes involved in making comparisons, and even less is known about what characteristics of fingerprint pairs make particular comparisons easy or difficult. We measured expert examiner performance and judgments of difficulty and confidence on a new fingerprint database. We developed a number of quantitative measures of image characteristics and used multiple regression techniques to discover objective predictors of error as well as perceived difficulty and confidence. A number of useful predictors emerged, and these included variables related to image quality metrics, such as intensity and contrast information, as well as measures of information quantity, such as the total fingerprint area. Also included were configural features that fingerprint experts have noted, such as the presence and clarity of global features and fingerprint ridges. Within the constraints of the overall low error rates of experts, a regression model incorporating the derived predictors demonstrated reasonable success in predicting objective difficulty for print pairs, as shown both in goodness of fit measures to the original data set and in a cross validation test. The results indicate the plausibility of using objective image metrics to predict expert performance and

  19. A method for predicting errors when interacting with finite state systems. How implicit learning shapes the user's knowledge of a system

    International Nuclear Information System (INIS)

    Javaux, Denis

    2002-01-01

    This paper describes a method for predicting the errors that may appear when human operators or users interact with systems behaving as finite state systems. The method is a generalization of a method used for predicting errors when interacting with autopilot modes on modern, highly computerized airliners [Proc 17th Digital Avionics Sys Conf (DASC) (1998); Proc 10th Int Symp Aviat Psychol (1999)]. A cognitive model based on spreading activation networks is used for predicting the user's model of the system and its impact on the production of errors. The model strongly posits the importance of implicit learning in user-system interaction and its possible detrimental influence on users' knowledge of the system. An experiment conducted with Airbus Industrie and a major European airline on pilots' knowledge of autopilot behavior on the A340-200/300 confirms the model predictions, and in particular the impact of the frequencies with which specific state transitions and contexts are experienced

  20. Striatal and Tegmental Neurons Code Critical Signals for Temporal-Difference Learning of State Value in Domestic Chicks

    Directory of Open Access Journals (Sweden)

    Chentao Wen

    2016-11-01

    Full Text Available To ensure survival, animals must update the internal representations of their environment in a trial-and-error fashion. Psychological studies of associative learning and neurophysiological analyses of dopaminergic neurons have suggested that this updating process involves the temporal-difference (TD method in the basal ganglia network. However, the way in which the component variables of the TD method are implemented at the neuronal level is unclear. To investigate the underlying neural mechanisms, we trained domestic chicks to associate color cues with food rewards. We recorded neuronal activities from the medial striatum or tegmentum in a freely behaving condition and examined how reward omission changed neuronal firing. To compare neuronal activities with the signals assumed in the TD method, we simulated the behavioral task in the form of a finite sequence composed of discrete steps of time. The three signals assumed in the simulated task were the prediction signal, the target signal for updating, and the TD-error signal. In both the medial striatum and tegmentum, the majority of recorded neurons were categorized into three types according to their fitness for three models, though these neurons tended to form a continuum spectrum without distinct differences in the firing rate. Specifically, two types of striatal neurons successfully mimicked the target signal and the prediction signal. A linear summation of these two types of striatum neurons was a good fit for the activity of one type of tegmental neurons mimicking the TD-error signal. The present study thus demonstrates that the striatum and tegmentum can convey the signals critically required for the TD method. Based on the theoretical and neurophysiological studies, together with tract-tracing data, we propose a novel model to explain how the convergence of signals represented in the striatum could lead to the computation of TD error in tegmental dopaminergic neurons.

  1. No unified reward prediction error in local field potentials from the human nucleus accumbens: evidence from epilepsy patients.

    Science.gov (United States)

    Stenner, Max-Philipp; Rutledge, Robb B; Zaehle, Tino; Schmitt, Friedhelm C; Kopitzki, Klaus; Kowski, Alexander B; Voges, Jürgen; Heinze, Hans-Jochen; Dolan, Raymond J

    2015-08-01

    Functional magnetic resonance imaging (fMRI), cyclic voltammetry, and single-unit electrophysiology studies suggest that signals measured in the nucleus accumbens (Nacc) during value-based decision making represent reward prediction errors (RPEs), the difference between actual and predicted rewards. Here, we studied the precise temporal and spectral pattern of reward-related signals in the human Nacc. We recorded local field potentials (LFPs) from the Nacc of six epilepsy patients during an economic decision-making task. On each trial, patients decided whether to accept or reject a gamble with equal probabilities of a monetary gain or loss. The behavior of four patients was consistent with choices being guided by value expectations. Expected value signals before outcome onset were observed in three of those patients, at varying latencies and with nonoverlapping spectral patterns. Signals after outcome onset were correlated with RPE regressors in all subjects. However, further analysis revealed that these signals were better explained as outcome valence rather than RPE signals, with gamble gains and losses differing in the power of beta oscillations and in evoked response amplitudes. Taken together, our results do not support the idea that postsynaptic potentials in the Nacc represent a RPE that unifies outcome magnitude and prior value expectation. We discuss the generalizability of our findings to healthy individuals and the relation of our results to measurements of RPE signals obtained from the Nacc with other methods. Copyright © 2015 the American Physiological Society.

  2. EEG Theta Dynamics within Frontal and Parietal Cortices for Error Processing during Reaching Movements in a Prism Adaptation Study Altering Visuo-Motor Predictive Planning.

    Science.gov (United States)

    Arrighi, Pieranna; Bonfiglio, Luca; Minichilli, Fabrizio; Cantore, Nicoletta; Carboncini, Maria Chiara; Piccotti, Emily; Rossi, Bruno; Andre, Paolo

    2016-01-01

    Modulation of frontal midline theta (fmθ) is observed during error commission, but little is known about the role of theta oscillations in correcting motor behaviours. We investigate EEG activity of healthy partipants executing a reaching task under variable degrees of prism-induced visuo-motor distortion and visual occlusion of the initial arm trajectory. This task introduces directional errors of different magnitudes. The discrepancy between predicted and actual movement directions (i.e. the error), at the time when visual feedback (hand appearance) became available, elicits a signal that triggers on-line movement correction. Analysis were performed on 25 EEG channels. For each participant, the median value of the angular error of all reaching trials was used to partition the EEG epochs into high- and low-error conditions. We computed event-related spectral perturbations (ERSP) time-locked either to visual feedback or to the onset of movement correction. ERSP time-locked to the onset of visual feedback showed that fmθ increased in the high- but not in the low-error condition with an approximate time lag of 200 ms. Moreover, when single epochs were sorted by the degree of motor error, fmθ started to increase when a certain level of error was exceeded and, then, scaled with error magnitude. When ERSP were time-locked to the onset of movement correction, the fmθ increase anticipated this event with an approximate time lead of 50 ms. During successive trials, an error reduction was observed which was associated with indices of adaptations (i.e., aftereffects) suggesting the need to explore if theta oscillations may facilitate learning. To our knowledge this is the first study where the EEG signal recorded during reaching movements was time-locked to the onset of the error visual feedback. This allowed us to conclude that theta oscillations putatively generated by anterior cingulate cortex activation are implicated in error processing in semi-naturalistic motor

  3. Detailed analysis of inversions predicted between two human genomes: errors, real polymorphisms, and their origin and population distribution.

    Science.gov (United States)

    Vicente-Salvador, David; Puig, Marta; Gayà-Vidal, Magdalena; Pacheco, Sarai; Giner-Delgado, Carla; Noguera, Isaac; Izquierdo, David; Martínez-Fundichely, Alexander; Ruiz-Herrera, Aurora; Estivill, Xavier; Aguado, Cristina; Lucas-Lledó, José Ignacio; Cáceres, Mario

    2017-02-01

    The growing catalogue of structural variants in humans often overlooks inversions as one of the most difficult types of variation to study, even though they affect phenotypic traits in diverse organisms. Here, we have analysed in detail 90 inversions predicted from the comparison of two independently assembled human genomes: the reference genome (NCBI36/HG18) and HuRef. Surprisingly, we found that two thirds of these predictions (62) represent errors either in assembly comparison or in one of the assemblies, including 27 misassembled regions in HG18. Next, we validated 22 of the remaining 28 potential polymorphic inversions using different PCR techniques and characterized their breakpoints and ancestral state. In addition, we determined experimentally the derived allele frequency in Europeans for 17 inversions (DAF = 0.01-0.80), as well as the distribution in 14 worldwide populations for 12 of them based on the 1000 Genomes Project data. Among the validated inversions, nine have inverted repeats (IRs) at their breakpoints, and two show nucleotide variation patterns consistent with a recurrent origin. Conversely, inversions without IRs have a unique origin and almost all of them show deletions or insertions at the breakpoints in the derived allele mediated by microhomology sequences, which highlights the importance of mechanisms like FoSTeS/MMBIR in the generation of complex rearrangements in the human genome. Finally, we found several inversions located within genes and at least one candidate to be positively selected in Africa. Thus, our study emphasizes the importance of careful analysis and validation of large-scale genomic predictions to extract reliable biological conclusions. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  4. Contribution of fronto-striatal regions to emotional valence and repetition under cognitive conflict.

    Science.gov (United States)

    Chun, Ji-Won; Park, Hae-Jeong; Kim, Dai Jin; Kim, Eosu; Kim, Jae-Jin

    2017-07-01

    Conflict processing mediated by fronto-striatal regions may be influenced by emotional properties of stimuli. This study aimed to examine the effects of emotion repetition on cognitive control in a conflict-provoking situation. Twenty-one healthy subjects were scanned using functional magnetic resonance imaging while performing a sequential cognitive conflict task composed of emotional stimuli. The regional effects were analyzed according to the repetition or non-repetition of cognitive congruency and emotional valence between the preceding and current trials. Post-incongruence interference in error rate and reaction time was significantly smaller than post-congruence interference, particularly under repeated positive and non-repeated positive, respectively, and post-incongruence interference, compared to post-congruence interference, increased activity in the ACC, DLPFC, and striatum. ACC and DLPFC activities were significantly correlated with error rate or reaction time in some conditions, and fronto-striatal connections were related to the conflict processing heightened by negative emotion. These findings suggest that the repetition of emotional stimuli adaptively regulates cognitive control and the fronto-striatal circuit may engage in the conflict adaptation process induced by emotion repetition. Both repetition enhancement and repetition suppression of prefrontal activity may underlie the relationship between emotion and conflict adaptation. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Why Don't We Learn to Accurately Forecast Feelings? How Misremembering Our Predictions Blinds Us to Past Forecasting Errors

    Science.gov (United States)

    Meyvis, Tom; Ratner, Rebecca K.; Levav, Jonathan

    2010-01-01

    Why do affective forecasting errors persist in the face of repeated disconfirming evidence? Five studies demonstrate that people misremember their forecasts as consistent with their experience and thus fail to perceive the extent of their forecasting error. As a result, people do not learn from past forecasting errors and fail to adjust subsequent…

  6. Is ozone model bias driven by errors in cloud predictions? A quantitative assessment using satellite cloud retrievals in WRF-Chem

    Science.gov (United States)

    Ryu, Y. H.; Hodzic, A.; Barré, J.; Descombes, G.; Minnis, P.

    2017-12-01

    Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much of the bias in O3 predictions is caused by inaccurate cloud predictions. This study quantifies the errors in surface O3 predictions associated with clouds in summertime over CONUS using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Cloud fields used for photochemistry are corrected based on satellite cloud retrievals in sensitivity simulations. It is found that the WRF-Chem model is able to detect about 60% of clouds in the right locations and generally underpredicts cloud optical depths. The errors in hourly O3 due to the errors in cloud predictions can be up to 60 ppb. On average in summertime over CONUS, the errors in 8-h average O3 of 1-6 ppb are found to be attributable to those in cloud predictions under cloudy sky conditions. The contribution of changes in photolysis rates due to clouds is found to be larger ( 80 % on average) than that of light-dependent BVOC emissions. The effects of cloud corrections on O­3 are about 2 times larger in VOC-limited than NOx-limited regimes, suggesting that the benefits of accurate cloud predictions would be greater in VOC-limited than NOx-limited regimes.

  7. Differential Dopamine Release Dynamics in the Nucleus Accumbens Core and Shell Reveal Complementary Signals for Error Prediction and Incentive Motivation.

    Science.gov (United States)

    Saddoris, Michael P; Cacciapaglia, Fabio; Wightman, R Mark; Carelli, Regina M

    2015-08-19

    Mesolimbic dopamine (DA) is phasically released during appetitive behaviors, though there is substantive disagreement about the specific purpose of these DA signals. For example, prediction error (PE) models suggest a role of learning, while incentive salience (IS) models argue that the DA signal imbues stimuli with value and thereby stimulates motivated behavior. However, within the nucleus accumbens (NAc) patterns of DA release can strikingly differ between subregions, and as such, it is possible that these patterns differentially contribute to aspects of PE and IS. To assess this, we measured DA release in subregions of the NAc during a behavioral task that spatiotemporally separated sequential goal-directed stimuli. Electrochemical methods were used to measure subsecond NAc dopamine release in the core and shell during a well learned instrumental chain schedule in which rats were trained to press one lever (seeking; SL) to gain access to a second lever (taking; TL) linked with food delivery, and again during extinction. In the core, phasic DA release was greatest following initial SL presentation, but minimal for the subsequent TL and reward events. In contrast, phasic shell DA showed robust release at all task events. Signaling decreased between the beginning and end of sessions in the shell, but not core. During extinction, peak DA release in the core showed a graded decrease for the SL and pauses in release during omitted expected rewards, whereas shell DA release decreased predominantly during the TL. These release dynamics suggest parallel DA signals capable of supporting distinct theories of appetitive behavior. Dopamine signaling in the brain is important for a variety of cognitive functions, such as learning and motivation. Typically, it is assumed that a single dopamine signal is sufficient to support these cognitive functions, though competing theories disagree on how dopamine contributes to reward-based behaviors. Here, we have found that real

  8. Striatal response to reward anticipation: evidence for a systems-level intermediate phenotype for schizophrenia.

    Science.gov (United States)

    Grimm, Oliver; Heinz, Andreas; Walter, Henrik; Kirsch, Peter; Erk, Susanne; Haddad, Leila; Plichta, Michael M; Romanczuk-Seiferth, Nina; Pöhland, Lydia; Mohnke, Sebastian; Mühleisen, Thomas W; Mattheisen, Manuel; Witt, Stephanie H; Schäfer, Axel; Cichon, Sven; Nöthen, Markus; Rietschel, Marcella; Tost, Heike; Meyer-Lindenberg, Andreas

    2014-05-01

    Attenuated ventral striatal response during reward anticipation is a core feature of schizophrenia that is seen in prodromal, drug-naive, and chronic schizophrenic patients. Schizophrenia is highly heritable, raising the possibility that this phenotype is related to the genetic risk for the disorder. To examine a large sample of healthy first-degree relatives of schizophrenic patients and compare their neural responses to reward anticipation with those of carefully matched controls without a family psychiatric history. To further support the utility of this phenotype, we studied its test-retest reliability, its potential brain structural contributions, and the effects of a protective missense variant in neuregulin 1 (NRG1) linked to schizophrenia by meta-analysis (ie, rs10503929). Examination of a well-established monetary reward anticipation paradigm during functional magnetic resonance imaging at a university hospital; voxel-based morphometry; test-retest reliability analysis of striatal activations in an independent sample of 25 healthy participants scanned twice with the same task; and imaging genetics analysis of the control group. A total of 54 healthy first-degree relatives of schizophrenic patients and 80 controls matched for demographic, psychological, clinical, and task performance characteristics were studied. Blood oxygen level-dependent response during reward anticipation, analysis of intraclass correlations of functional contrasts, and associations between striatal gray matter volume and NRG1 genotype. Compared with controls, healthy first-degree relatives showed a highly significant decrease in ventral striatal activation during reward anticipation (familywise error-corrected P systems-level functional phenotype is reliable (with intraclass correlation coefficients of 0.59-0.73), independent of local gray matter volume (with no corresponding group differences and no correlation to function, and with all uncorrected P values >.05), and affected by

  9. Modeling coherent errors in quantum error correction

    Science.gov (United States)

    Greenbaum, Daniel; Dutton, Zachary

    2018-01-01

    Analysis of quantum error correcting codes is typically done using a stochastic, Pauli channel error model for describing the noise on physical qubits. However, it was recently found that coherent errors (systematic rotations) on physical data qubits result in both physical and logical error rates that differ significantly from those predicted by a Pauli model. Here we examine the accuracy of the Pauli approximation for noise containing coherent errors (characterized by a rotation angle ɛ) under the repetition code. We derive an analytic expression for the logical error channel as a function of arbitrary code distance d and concatenation level n, in the small error limit. We find that coherent physical errors result in logical errors that are partially coherent and therefore non-Pauli. However, the coherent part of the logical error is negligible at fewer than {ε }-({dn-1)} error correction cycles when the decoder is optimized for independent Pauli errors, thus providing a regime of validity for the Pauli approximation. Above this number of correction cycles, the persistent coherent logical error will cause logical failure more quickly than the Pauli model would predict, and this may need to be combated with coherent suppression methods at the physical level or larger codes.

  10. DRD2 genotype-based variation of default mode network activity and of its relationship with striatal DAT binding.

    Science.gov (United States)

    Sambataro, Fabio; Fazio, Leonardo; Taurisano, Paolo; Gelao, Barbara; Porcelli, Annamaria; Mancini, Marina; Sinibaldi, Lorenzo; Ursini, Gianluca; Masellis, Rita; Caforio, Grazia; Di Giorgio, Annabella; Niccoli-Asabella, Artor; Popolizio, Teresa; Blasi, Giuseppe; Bertolino, Alessandro

    2013-01-01

    The default mode network (DMN) comprises a set of brain regions with "increased" activity during rest relative to cognitive processing. Activity in the DMN is associated with functional connections with the striatum and dopamine (DA) levels in this brain region. A functional single-nucleotide polymorphism within the dopamine D2 receptor gene (DRD2, rs1076560 G > T) shifts splicing of the 2 D2 isoforms, D2 short and D2 long, and has been associated with striatal DA signaling as well as with cognitive processing. However, the effects of this polymorphism on DMN have not been explored. The aim of this study was to evaluate the effects of rs1076560 on DMN and striatal connectivity and on their relationship with striatal DA signaling. Twenty-eight subjects genotyped for rs1076560 underwent functional magnetic resonance imaging during a working memory task and 123 55 I-Fluoropropyl-2-beta-carbomethoxy-3-beta(4-iodophenyl) nortropan Single Photon Emission Computed Tomography ([(123)I]-FP-CIT SPECT) imaging (a measure of dopamine transporter [DAT] binding). Spatial group-independent component (IC) analysis was used to identify DMN and striatal ICs. Within the anterior DMN IC, GG subjects had relatively greater connectivity in medial prefrontal cortex (MPFC), which was directly correlated with striatal DAT binding. Within the posterior DMN IC, GG subjects had reduced connectivity in posterior cingulate relative to T carriers. Additionally, rs1076560 genotype predicted connectivity differences within a striatal network, and these changes were correlated with connectivity in MPFC and posterior cingulate within the DMN. These results suggest that genetically determined D2 receptor signaling is associated with DMN connectivity and that these changes are correlated with striatal function and presynaptic DA signaling.

  11. How to regress and predict in a Bland-Altman plot? Review and contribution based on tolerance intervals and correlated-errors-in-variables models.

    Science.gov (United States)

    Francq, Bernard G; Govaerts, Bernadette

    2016-06-30

    Two main methodologies for assessing equivalence in method-comparison studies are presented separately in the literature. The first one is the well-known and widely applied Bland-Altman approach with its agreement intervals, where two methods are considered interchangeable if their differences are not clinically significant. The second approach is based on errors-in-variables regression in a classical (X,Y) plot and focuses on confidence intervals, whereby two methods are considered equivalent when providing similar measures notwithstanding the random measurement errors. This paper reconciles these two methodologies and shows their similarities and differences using both real data and simulations. A new consistent correlated-errors-in-variables regression is introduced as the errors are shown to be correlated in the Bland-Altman plot. Indeed, the coverage probabilities collapse and the biases soar when this correlation is ignored. Novel tolerance intervals are compared with agreement intervals with or without replicated data, and novel predictive intervals are introduced to predict a single measure in an (X,Y) plot or in a Bland-Atman plot with excellent coverage probabilities. We conclude that the (correlated)-errors-in-variables regressions should not be avoided in method comparison studies, although the Bland-Altman approach is usually applied to avert their complexity. We argue that tolerance or predictive intervals are better alternatives than agreement intervals, and we provide guidelines for practitioners regarding method comparison studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  12. Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

    Science.gov (United States)

    Duda, David P.; Minnis, Patrick

    2009-01-01

    Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

  13. An investigation into multi-dimensional prediction models to estimate the pose error of a quadcopter in a CSP plant setting

    Science.gov (United States)

    Lock, Jacobus C.; Smit, Willie J.; Treurnicht, Johann

    2016-05-01

    The Solar Thermal Energy Research Group (STERG) is investigating ways to make heliostats cheaper to reduce the total cost of a concentrating solar power (CSP) plant. One avenue of research is to use unmanned aerial vehicles (UAVs) to automate and assist with the heliostat calibration process. To do this, the pose estimation error of each UAV must be determined and integrated into a calibration procedure. A computer vision (CV) system is used to measure the pose of a quadcopter UAV. However, this CV system contains considerable measurement errors. Since this is a high-dimensional problem, a sophisticated prediction model must be used to estimate the measurement error of the CV system for any given pose measurement vector. This paper attempts to train and validate such a model with the aim of using it to determine the pose error of a quadcopter in a CSP plant setting.

  14. Combining empirical approaches and error modelling to enhance predictive uncertainty estimation in extrapolation for operational flood forecasting. Tests on flood events on the Loire basin, France.

    Science.gov (United States)

    Berthet, Lionel; Marty, Renaud; Bourgin, François; Viatgé, Julie; Piotte, Olivier; Perrin, Charles

    2017-04-01

    An increasing number of operational flood forecasting centres assess the predictive uncertainty associated with their forecasts and communicate it to the end users. This information can match the end-users needs (i.e. prove to be useful for an efficient crisis management) only if it is reliable: reliability is therefore a key quality for operational flood forecasts. In 2015, the French flood forecasting national and regional services (Vigicrues network; www.vigicrues.gouv.fr) implemented a framework to compute quantitative discharge and water level forecasts and to assess the predictive uncertainty. Among the possible technical options to achieve this goal, a statistical analysis of past forecasting errors of deterministic models has been selected (QUOIQUE method, Bourgin, 2014). It is a data-based and non-parametric approach based on as few assumptions as possible about the forecasting error mathematical structure. In particular, a very simple assumption is made regarding the predictive uncertainty distributions for large events outside the range of the calibration data: the multiplicative error distribution is assumed to be constant, whatever the magnitude of the flood. Indeed, the predictive distributions may not be reliable in extrapolation. However, estimating the predictive uncertainty for these rare events is crucial when major floods are of concern. In order to improve the forecasts reliability for major floods, an attempt at combining the operational strength of the empirical statistical analysis and a simple error modelling is done. Since the heteroscedasticity of forecast errors can considerably weaken the predictive reliability for large floods, this error modelling is based on the log-sinh transformation which proved to reduce significantly the heteroscedasticity of the transformed error in a simulation context, even for flood peaks (Wang et al., 2012). Exploratory tests on some operational forecasts issued during the recent floods experienced in

  15. How the credit assignment problems in motor control could be solved after the cerebellum predicts increases in error.

    Science.gov (United States)

    Verduzco-Flores, Sergio O; O'Reilly, Randall C

    2015-01-01

    We present a cerebellar architecture with two main characteristics. The first one is that complex spikes respond to increases in sensory errors. The second one is that cerebellar modules associate particular contexts where errors have increased in the past with corrective commands that stop the increase in error. We analyze our architecture formally and computationally for the case of reaching in a 3D environment. In the case of motor control, we show that there are synergies of this architecture with the Equilibrium-Point hypothesis, leading to novel ways to solve the motor error and distal learning problems. In particular, the presence of desired equilibrium lengths for muscles provides a way to know when the error is increasing, and which corrections to apply. In the context of Threshold Control Theory and Perceptual Control Theory we show how to extend our model so it implements anticipative corrections in cascade control systems that span from muscle contractions to cognitive operations.

  16. How the credit assignment problems in motor control could be solved after the cerebellum predicts increases in error

    Directory of Open Access Journals (Sweden)

    Sergio Oscar Verduzco-Flores

    2015-03-01

    Full Text Available We present a cerebellar architecture with two main characteristics. The first one is that complex spikes respond to increases in sensory errors. The second one is that cerebellar modules associate particular contexts where errors have increased in the past with corrective commands that stop the increase in error. We analyze our architecture formally and computationally for the case of reaching in a 3D environment. In the case of motor control, we show that there are synergies of this architecture with the Equilibrium-Point hypothesis, leading to novel ways to solve the motor error and distal learning problems. In particular, the presence of desired equilibrium lengths for muscles provides a way to know when the error is increasing, and which corrections to apply. In the context of Threshold Control Theory and Perceptual Control Theory we show how to extend our model so it implements anticipative corrections in cascade control systems that span from muscle contractions to cognitive operations.

  17. Processing of action- but not stimulus-related prediction errors differs between active and observational feedback learning.

    Science.gov (United States)

    Kobza, Stefan; Bellebaum, Christian

    2015-01-01

    Learning of stimulus-response-outcome associations is driven by outcome prediction errors (PEs). Previous studies have shown larger PE-dependent activity in the striatum for learning from own as compared to observed actions and the following outcomes despite comparable learning rates. We hypothesised that this finding relates primarily to a stronger integration of action and outcome information in active learners. Using functional magnetic resonance imaging, we investigated brain activations related to action-dependent PEs, reflecting the deviation between action values and obtained outcomes, and action-independent PEs, reflecting the deviation between subjective values of response-preceding cues and obtained outcomes. To this end, 16 active and 15 observational learners engaged in a probabilistic learning card-guessing paradigm. On each trial, active learners saw one out of five cues and pressed either a left or right response button to receive feedback (monetary win or loss). Each observational learner observed exactly those cues, responses and outcomes of one active learner. Learning performance was assessed in active test trials without feedback and did not differ between groups. For both types of PEs, activations were found in the globus pallidus, putamen, cerebellum, and insula in active learners. However, only for action-dependent PEs, activations in these structures and the anterior cingulate were increased in active relative to observational learners. Thus, PE-related activity in the reward system is not generally enhanced in active relative to observational learning but only for action-dependent PEs. For the cerebellum, additional activations were found across groups for cue-related uncertainty, thereby emphasising the cerebellum's role in stimulus-outcome learning. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Trial-by-Trial Modulation of Associative Memory Formation by Reward Prediction Error and Reward Anticipation as Revealed by a Biologically Plausible Computational Model.

    Science.gov (United States)

    Aberg, Kristoffer C; Müller, Julia; Schwartz, Sophie

    2017-01-01

    Anticipation and delivery of rewards improves memory formation, but little effort has been made to disentangle their respective contributions to memory enhancement. Moreover, it has been suggested that the effects of reward on memory are mediated by dopaminergic influences on hippocampal plasticity. Yet, evidence linking memory improvements to actual reward computations reflected in the activity of the dopaminergic system, i.e., prediction errors and expected values, is scarce and inconclusive. For example, different previous studies reported that the magnitude of prediction errors during a reinforcement learning task was a positive, negative, or non-significant predictor of successfully encoding simultaneously presented images. Individual sensitivities to reward and punishment have been found to influence the activation of the dopaminergic reward system and could therefore help explain these seemingly discrepant results. Here, we used a novel associative memory task combined with computational modeling and showed independent effects of reward-delivery and reward-anticipation on memory. Strikingly, the computational approach revealed positive influences from both reward delivery, as mediated by prediction error magnitude, and reward anticipation, as mediated by magnitude of expected value, even in the absence of behavioral effects when analyzed using standard methods, i.e., by collapsing memory performance across trials within conditions. We additionally measured trait estimates of reward and punishment sensitivity and found that individuals with increased reward (vs. punishment) sensitivity had better memory for associations encoded during positive (vs. negative) prediction errors when tested after 20 min, but a negative trend when tested after 24 h. In conclusion, modeling trial-by-trial fluctuations in the magnitude of reward, as we did here for prediction errors and expected value computations, provides a comprehensive and biologically plausible description of

  19. EEG Theta Dynamics within Frontal and Parietal Cortices for Error Processing during Reaching Movements in a Prism Adaptation Study Altering Visuo-Motor Predictive Planning.

    Directory of Open Access Journals (Sweden)

    Pieranna Arrighi

    Full Text Available Modulation of frontal midline theta (fmθ is observed during error commission, but little is known about the role of theta oscillations in correcting motor behaviours. We investigate EEG activity of healthy partipants executing a reaching task under variable degrees of prism-induced visuo-motor distortion and visual occlusion of the initial arm trajectory. This task introduces directional errors of different magnitudes. The discrepancy between predicted and actual movement directions (i.e. the error, at the time when visual feedback (hand appearance became available, elicits a signal that triggers on-line movement correction. Analysis were performed on 25 EEG channels. For each participant, the median value of the angular error of all reaching trials was used to partition the EEG epochs into high- and low-error conditions. We computed event-related spectral perturbations (ERSP time-locked either to visual feedback or to the onset of movement correction. ERSP time-locked to the onset of visual feedback showed that fmθ increased in the high- but not in the low-error condition with an approximate time lag of 200 ms. Moreover, when single epochs were sorted by the degree of motor error, fmθ started to increase when a certain level of error was exceeded and, then, scaled with error magnitude. When ERSP were time-locked to the onset of movement correction, the fmθ increase anticipated this event with an approximate time lead of 50 ms. During successive trials, an error reduction was observed which was associated with indices of adaptations (i.e., aftereffects suggesting the need to explore if theta oscillations may facilitate learning. To our knowledge this is the first study where the EEG signal recorded during reaching movements was time-locked to the onset of the error visual feedback. This allowed us to conclude that theta oscillations putatively generated by anterior cingulate cortex activation are implicated in error processing in semi

  20. Phasic dopamine as a prediction error of intrinsic and extrinsic reinforcements driving both action acquisition and reward maximization: a simulated robotic study.

    Science.gov (United States)

    Mirolli, Marco; Santucci, Vieri G; Baldassarre, Gianluca

    2013-03-01

    An important issue of recent neuroscientific research is to understand the functional role of the phasic release of dopamine in the striatum, and in particular its relation to reinforcement learning. The literature is split between two alternative hypotheses: one considers phasic dopamine as a reward prediction error similar to the computational TD-error, whose function is to guide an animal to maximize future rewards; the other holds that phasic dopamine is a sensory prediction error signal that lets the animal discover and acquire novel actions. In this paper we propose an original hypothesis that integrates these two contrasting positions: according to our view phasic dopamine represents a TD-like reinforcement prediction error learning signal determined by both unexpected changes in the environment (temporary, intrinsic reinforcements) and biological rewards (permanent, extrinsic reinforcements). Accordingly, dopamine plays the functional role of driving both the discovery and acquisition of novel actions and the maximization of future rewards. To validate our hypothesis we perform a series of experiments with a simulated robotic system that has to learn different skills in order to get rewards. We compare different versions of the system in which we vary the composition of the learning signal. The results show that only the system reinforced by both extrinsic and intrinsic reinforcements is able to reach high performance in sufficiently complex conditions. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Soil pH Errors Propagation from Measurements to Spatial Predictions - Cost Benefit Analysis and Risk Assessment Implications for Practitioners and Modelers

    Science.gov (United States)

    Owens, P. R.; Libohova, Z.; Seybold, C. A.; Wills, S. A.; Peaslee, S.; Beaudette, D.; Lindbo, D. L.

    2017-12-01

    The measurement errors and spatial prediction uncertainties of soil properties in the modeling community are usually assessed against measured values when available. However, of equal importance is the assessment of errors and uncertainty impacts on cost benefit analysis and risk assessments. Soil pH was selected as one of the most commonly measured soil properties used for liming recommendations. The objective of this study was to assess the error size from different sources and their implications with respect to management decisions. Error sources include measurement methods, laboratory sources, pedotransfer functions, database transections, spatial aggregations, etc. Several databases of measured and predicted soil pH were used for this study including the United States National Cooperative Soil Survey Characterization Database (NCSS-SCDB), the US Soil Survey Geographic (SSURGO) Database. The distribution of errors among different sources from measurement methods to spatial aggregation showed a wide range of values. The greatest RMSE of 0.79 pH units was from spatial aggregation (SSURGO vs Kriging), while the measurement methods had the lowest RMSE of 0.06 pH units. Assuming the order of data acquisition based on the transaction distance i.e. from measurement method to spatial aggregation the RMSE increased from 0.06 to 0.8 pH units suggesting an "error propagation". This has major implications for practitioners and modeling community. Most soil liming rate recommendations are based on 0.1 pH unit increments, while the desired soil pH level increments are based on 0.4 to 0.5 pH units. Thus, even when the measured and desired target soil pH are the same most guidelines recommend 1 ton ha-1 lime, which translates in 111 ha-1 that the farmer has to factor in the cost-benefit analysis. However, this analysis need to be based on uncertainty predictions (0.5-1.0 pH units) rather than measurement errors (0.1 pH units) which would translate in 555-1,111 investment that

  2. Self-Reported and Observed Punitive Parenting Prospectively Predicts Increased Error-Related Brain Activity in Six-Year-Old Children.

    Science.gov (United States)

    Meyer, Alexandria; Proudfit, Greg Hajcak; Bufferd, Sara J; Kujawa, Autumn J; Laptook, Rebecca S; Torpey, Dana C; Klein, Daniel N

    2015-07-01

    The error-related negativity (ERN) is a negative deflection in the event-related potential (ERP) occurring approximately 50 ms after error commission at fronto-central electrode sites and is thought to reflect the activation of a generic error monitoring system. Several studies have reported an increased ERN in clinically anxious children, and suggest that anxious children are more sensitive to error commission--although the mechanisms underlying this association are not clear. We have previously found that punishing errors results in a larger ERN, an effect that persists after punishment ends. It is possible that learning-related experiences that impact sensitivity to errors may lead to an increased ERN. In particular, punitive parenting might sensitize children to errors and increase their ERN. We tested this possibility in the current study by prospectively examining the relationship between parenting style during early childhood and children's ERN approximately 3 years later. Initially, 295 parents and children (approximately 3 years old) participated in a structured observational measure of parenting behavior, and parents completed a self-report measure of parenting style. At a follow-up assessment approximately 3 years later, the ERN was elicited during a Go/No-Go task, and diagnostic interviews were completed with parents to assess child psychopathology. Results suggested that both observational measures of hostile parenting and self-report measures of authoritarian parenting style uniquely predicted a larger ERN in children 3 years later. We previously reported that children in this sample with anxiety disorders were characterized by an increased ERN. A mediation analysis indicated that ERN magnitude mediated the relationship between harsh parenting and child anxiety disorder. Results suggest that parenting may shape children's error processing through environmental conditioning and thereby risk for anxiety, although future work is needed to confirm this

  3. Self-reported and observed punitive parenting prospectively predicts increased error-related brain activity in six-year-old children

    Science.gov (United States)

    Meyer, Alexandria; Proudfit, Greg Hajcak; Bufferd, Sara J.; Kujawa, Autumn J.; Laptook, Rebecca S.; Torpey, Dana C.; Klein, Daniel N.

    2017-01-01

    The error-related negativity (ERN) is a negative deflection in the event-related potential (ERP) occurring approximately 50 ms after error commission at fronto-central electrode sites and is thought to reflect the activation of a generic error monitoring system. Several studies have reported an increased ERN in clinically anxious children, and suggest that anxious children are more sensitive to error commission—although the mechanisms underlying this association are not clear. We have previously found that punishing errors results in a larger ERN, an effect that persists after punishment ends. It is possible that learning-related experiences that impact sensitivity to errors may lead to an increased ERN. In particular, punitive parenting might sensitize children to errors and increase their ERN. We tested this possibility in the current study by prospectively examining the relationship between parenting style during early childhood and children’s ERN approximately three years later. Initially, 295 parents and children (approximately 3 years old) participated in a structured observational measure of parenting behavior, and parents completed a self-report measure of parenting style. At a follow-up assessment approximately three years later, the ERN was elicited during a Go/No-Go task, and diagnostic interviews were completed with parents to assess child psychopathology. Results suggested that both observational measures of hostile parenting and self-report measures of authoritarian parenting style uniquely predicted a larger ERN in children 3 years later. We previously reported that children in this sample with anxiety disorders were characterized by an increased ERN. A mediation analysis indicated that ERN magnitude mediated the relationship between harsh parenting and child anxiety disorder. Results suggest that parenting may shape children’s error processing through environmental conditioning and thereby risk for anxiety, although future work is needed to

  4. Pauses in Striatal Cholinergic Interneurons: What is Revealed by Their Common Themes and Variations?

    Directory of Open Access Journals (Sweden)

    Yan-Feng Zhang

    2017-10-01

    Full Text Available Striatal cholinergic interneurons, the so-called tonically active neurons (TANs, pause their firing in response to sensory cues and rewards during classical conditioning and instrumental tasks. The respective pause responses observed can demonstrate many commonalities, such as constant latency and duration, synchronous occurrence in a population of cells, and coincidence with phasic activities of midbrain dopamine neurons (DANs that signal reward predictions and errors. Pauses can however also show divergent properties. Pause latencies and durations can differ in a given TAN between appetitive vs. aversive outcomes in classical conditioning, initial excitation can be present or absent, and a second pause can variably follow a rebound. Despite more than 20 years of study, the functions of these pause responses are still elusive. Our understanding of pause function is hindered by an incomplete understanding of how pauses are generated. In this mini-review article, we compare pause types, as well as current key hypotheses for inputs underlying pauses that include dopamine-induced inhibition through D2-receptors, a GABA input from ventral tegmental area, and a prolonged afterhyperpolarization induced by excitatory input from the cortex or from the thalamus. We review how each of these mechanisms alone explains some but not all aspects of pause responses. These mechanisms might need to operate in specific but variable sets of sequences to generate a full range of pause responses. Alternatively, these mechanisms might operate in conjunction with an underlying control mechanism within cholinergic interneurons which could potentially provide a framework to generate the common themes and variations seen amongst pause responses.

  5. Prediction and error growth in the daily forecast of precipitation from the NCEP CFSv2 over the subdivisions of Indian subcontinent

    Science.gov (United States)

    Pandey, Dhruva Kumar; Rai, Shailendra; Sahai, A. K.; Abhilash, S.; Shahi, N. K.

    2016-02-01

    This study investigates the forecast skill and predictability of various indices of south Asian monsoon as well as the subdivisions of the Indian subcontinent during JJAS season for the time domain of 2001-2013 using NCEP CFSv2 output. It has been observed that the daily mean climatology of precipitation over the land points of India is underestimated in the model forecast as compared to observation. The monthly model bias of precipitation shows the dry bias over the land points of India and also over the Bay of Bengal, whereas the Himalayan and Arabian Sea regions show the wet bias. We have divided the Indian landmass into five subdivisions namely central India, southern India, Western Ghat, northeast and southern Bay of Bengal regions based on the spatial variation of observed mean precipitation in JJAS season. The underestimation over the land points of India during mature phase was originated from the central India, southern Bay of Bengal, southern India and Western Ghat regions. The error growth in June forecast is slower as compared to July forecast in all the regions. The predictability error also grows slowly in June forecast as compared to July forecast in most of the regions. The doubling time of predictability error was estimated to be in the range of 3-5 days for all the regions. Southern India and Western Ghats are more predictable in the July forecast as compared to June forecast, whereas IMR, northeast, central India and southern Bay of Bengal regions have the opposite nature.

  6. ِDesigning a Model to Medical Errors Prediction for Outpatients Visits According to Rganizational Commitment and Job Involvement

    Directory of Open Access Journals (Sweden)

    SM Mirhosseini

    2015-09-01

    Full Text Available Abstract Introduction: A wide ranges of variables effect on the medical errors such as job involvement and organizational commitment. Coincidental relationship between two variables on medical errors during outpatients’ visits has been investigated to design a model. Methods: A field study with 114 physicians during outpatients’ visits revealed the mean of medical errors. Azimi and Allen-meyer questionnaires were used to measure Job involvement and organizational commitment. Physicians divided into four groups according to the Job involvement and organizational commitment in two dimensions (Zone1: high job involvement and high organizational commitment, Zone2: high job involvement and low organizational commitment, Zone3: low job involvement and high organizational commitment, Zone 4: low job involvement and low organizational commitment. ANOVA and Scheffe test were conducted to analyse the medical errors in four Zones by SPSS22. A guideline was presented according to the relationship between errors and two other variables. Results: The mean of organizational commitment was 79.50±12.30 and job involvement 12.72±3.66, medical errors in first group (0.32, second group (0.51, third group (0.41 and last one (0.50. ANOVA (F test=22.20, sig=0.00 and Scheffé were significant except for the second and forth group. The validity of the model was 73.60%. Conclusion: Applying some strategies to boost the organizational commitment and job involvement can help for diminishing the medical errors during outpatients’ visits. Thus, the investigation to comprehend the factors contributing organizational commitment and job involvement can be helpful.

  7. Patterns of poststroke brain damage that predict speech production errors in apraxia of speech and aphasia dissociate.

    Science.gov (United States)

    Basilakos, Alexandra; Rorden, Chris; Bonilha, Leonardo; Moser, Dana; Fridriksson, Julius

    2015-06-01

    Acquired apraxia of speech (AOS) is a motor speech disorder caused by brain damage. AOS often co-occurs with aphasia, a language disorder in which patients may also demonstrate speech production errors. The overlap of speech production deficits in both disorders has raised questions on whether AOS emerges from a unique pattern of brain damage or as a subelement of the aphasic syndrome. The purpose of this study was to determine whether speech production errors in AOS and aphasia are associated with distinctive patterns of brain injury. Forty-three patients with history of a single left-hemisphere stroke underwent comprehensive speech and language testing. The AOS Rating Scale was used to rate speech errors specific to AOS versus speech errors that can also be associated with both AOS and aphasia. Localized brain damage was identified using structural magnetic resonance imaging, and voxel-based lesion-impairment mapping was used to evaluate the relationship between speech errors specific to AOS, those that can occur in AOS or aphasia, and brain damage. The pattern of brain damage associated with AOS was most strongly associated with damage to cortical motor regions, with additional involvement of somatosensory areas. Speech production deficits that could be attributed to AOS or aphasia were associated with damage to the temporal lobe and the inferior precentral frontal regions. AOS likely occurs in conjunction with aphasia because of the proximity of the brain areas supporting speech and language, but the neurobiological substrate for each disorder differs. © 2015 American Heart Association, Inc.

  8. Complex terrain wind resource estimation with the wind-atlas method: Prediction errors using linearized and nonlinear CFD micro-scale models

    DEFF Research Database (Denmark)

    Troen, Ib; Bechmann, Andreas; Kelly, Mark C.

    2014-01-01

    Using the Wind Atlas methodology to predict the average wind speed at one location from measured climatological wind frequency distributions at another nearby location we analyse the relative prediction errors using a linearized flow model (IBZ) and a more physically correct fully non-linear 3D...... flow model (CFD) for a number of sites in very complex terrain (large terrain slopes). We first briefly describe the Wind Atlas methodology as implemented in WAsP and the specifics of the “classical” model setup and the new setup allowing the use of the CFD computation engine. We discuss some known...

  9. Haloperidol Selectively Remodels Striatal Indirect Pathway Circuits

    Science.gov (United States)

    Sebel, Luke E; Graves, Steven M; Chan, C Savio; Surmeier, D James

    2017-01-01

    Typical antipsychotic drugs are widely thought to alleviate the positive symptoms of schizophrenia by antagonizing dopamine D2 receptors expressed by striatal spiny projection neurons (SPNs). What is less clear is why antipsychotics have a therapeutic latency of weeks. Using a combination of physiological and anatomical approaches in ex vivo brain slices from transgenic mice, it was found that 2 weeks of haloperidol treatment induced both intrinsic and synaptic adaptations specifically within indirect pathway SPNs (iSPNs). Perphenazine treatment had similar effects. Some of these adaptations were homeostatic, including a drop in intrinsic excitability and pruning of excitatory corticostriatal glutamatergic synapses. However, haloperidol treatment also led to strengthening of a subset of excitatory corticostriatal synapses. This slow remodeling of corticostriatal iSPN circuitry is likely to play a role in mediating the delayed therapeutic action of neuroleptics. PMID:27577602

  10. Patterns of Post-Stroke Brain Damage that Predict Speech Production Errors in Apraxia of Speech and Aphasia Dissociate

    Science.gov (United States)

    Basilakos, Alexandra; Rorden, Chris; Bonilha, Leonardo; Moser, Dana; Fridriksson, Julius

    2015-01-01

    Background and Purpose Acquired apraxia of speech (AOS) is a motor speech disorder caused by brain damage. AOS often co-occurs with aphasia, a language disorder in which patients may also demonstrate speech production errors. The overlap of speech production deficits in both disorders has raised questions regarding if AOS emerges from a unique pattern of brain damage or as a sub-element of the aphasic syndrome. The purpose of this study was to determine whether speech production errors in AOS and aphasia are associated with distinctive patterns of brain injury. Methods Forty-three patients with history of a single left-hemisphere stroke underwent comprehensive speech and language testing. The Apraxia of Speech Rating Scale was used to rate speech errors specific to AOS versus speech errors that can also be associated with AOS and/or aphasia. Localized brain damage was identified using structural MRI, and voxel-based lesion-impairment mapping was used to evaluate the relationship between speech errors specific to AOS, those that can occur in AOS and/or aphasia, and brain damage. Results The pattern of brain damage associated with AOS was most strongly associated with damage to cortical motor regions, with additional involvement of somatosensory areas. Speech production deficits that could be attributed to AOS and/or aphasia were associated with damage to the temporal lobe and the inferior pre-central frontal regions. Conclusion AOS likely occurs in conjunction with aphasia due to the proximity of the brain areas supporting speech and language, but the neurobiological substrate for each disorder differs. PMID:25908457

  11. Striatal Dopamine D2/D3 Receptor Availability Is Associated with Executive Function in Healthy Controls but Not Methamphetamine Users.

    Directory of Open Access Journals (Sweden)

    Michael E Ballard

    Full Text Available Dopamine D2/D3 receptor availability in the striatum has been linked with executive function in healthy individuals, and is below control levels among drug addicts, possibly contributing to diminished executive function in the latter group. This study tested for an association of striatal D2/D3 receptor availability with a measure of executive function among research participants who met DSM-IV criteria for methamphetamine dependence.Methamphetamine users and non-user controls (n = 18 per group completed the Wisconsin Card Sorting Test and positron emission tomography with [18F]fallypride.The methamphetamine users displayed significantly lower striatal D2/D3 receptor availability on average than controls after controlling for age and education (p = 0.008, but they did not register greater proportions of either perseverative or non-perseverative errors when controlling for education (both ps ≥ 0.622. The proportion of non-perseverative, but not perseverative, errors was negatively correlated with striatal D2/D3 receptor availability among controls (r = -0.588, p = 0.010, but not methamphetamine users (r = 0.281, p = 0.258, and the group-wise interaction was significant (p = 0.030.These results suggest that cognitive flexibility, as measured by perseverative errors on the Wisconsin Card Sorting Test, is not determined by signaling through striatal D2/D3 receptors in healthy controls, and that in stimulant abusers, who have lower D2/D3 receptor availability, compensation can effectively maintain other executive functions, which are associated with D2/D3 receptor signaling in controls.

  12. Reduced amygdala and ventral striatal activity to happy faces in PTSD is associated with emotional numbing.

    Directory of Open Access Journals (Sweden)

    Kim L Felmingham

    Full Text Available There has been a growing recognition of the importance of reward processing in PTSD, yet little is known of the underlying neural networks. This study tested the predictions that (1 individuals with PTSD would display reduced responses to happy facial expressions in ventral striatal reward networks, and (2 that this reduction would be associated with emotional numbing symptoms. 23 treatment-seeking patients with Posttraumatic Stress Disorder were recruited from the treatment clinic at the Centre for Traumatic Stress Studies, Westmead Hospital, and 20 trauma-exposed controls were recruited from a community sample. We examined functional magnetic resonance imaging responses during the presentation of happy and neutral facial expressions in a passive viewing task. PTSD participants rated happy facial expression as less intense than trauma-exposed controls. Relative to controls, PTSD participants revealed lower activation to happy (-neutral faces in ventral striatum and and a trend for reduced activation in left amygdala. A significant negative correlation was found between emotional numbing symptoms in PTSD and right ventral striatal regions after controlling for depression, anxiety and PTSD severity. This study provides initial evidence that individuals with PTSD have lower reactivity to happy facial expressions, and that lower activation in ventral striatal-limbic reward networks may be associated with symptoms of emotional numbing.

  13. A simple algorithm for subregional striatal uptake analysis with partial volume correction in dopaminergic PET imaging

    International Nuclear Information System (INIS)

    Lue Kunhan; Lin Hsinhon; Chuang Kehshih; Kao Chihhao, K.; Hsieh Hungjen; Liu Shuhsin

    2014-01-01

    In positron emission tomography (PET) of the dopaminergic system, quantitative measurements of nigrostriatal dopamine function are useful for differential diagnosis. A subregional analysis of striatal uptake enables the diagnostic performance to be more powerful. However, the partial volume effect (PVE) induces an underestimation of the true radioactivity concentration in small structures. This work proposes a simple algorithm for subregional analysis of striatal uptake with partial volume correction (PVC) in dopaminergic PET imaging. The PVC algorithm analyzes the separate striatal subregions and takes into account the PVE based on the recovery coefficient (RC). The RC is defined as the ratio of the PVE-uncorrected to PVE-corrected radioactivity concentration, and is derived from a combination of the traditional volume of interest (VOI) analysis and the large VOI technique. The clinical studies, comprising 11 patients with Parkinson's disease (PD) and 6 healthy subjects, were used to assess the impact of PVC on the quantitative measurements. Simulations on a numerical phantom that mimicked realistic healthy and neurodegenerative situations were used to evaluate the performance of the proposed PVC algorithm. In both the clinical and the simulation studies, the striatal-to-occipital ratio (SOR) values for the entire striatum and its subregions were calculated with and without PVC. In the clinical studies, the SOR values in each structure (caudate, anterior putamen, posterior putamen, putamen, and striatum) were significantly higher by using PVC in contrast to those without. Among the PD patients, the SOR values in each structure and quantitative disease severity ratings were shown to be significantly related only when PVC was used. For the simulation studies, the average absolute percentage error of the SOR estimates before and after PVC were 22.74% and 1.54% in the healthy situation, respectively; those in the neurodegenerative situation were 20.69% and 2

  14. Striatal dysfunction in attention deficit and hyperkinetic disorder

    International Nuclear Information System (INIS)

    Lou, H.C.; Henriksen, L.; Bruhn, P.; Borner, H.; Nielsen, J.B.

    1989-01-01

    We have previously reported that periventricular structures are hypoperfused in attention deficit and hyperactivity disorder (ADHD). This study has expanded the number of patients, who were divided into two groups: six patients with pure ADHD, and 13 patients with ADHD in combination with other neurologic symptoms. By using xenon 133 inhalation and emission tomography, the regional cerebral blood flow distribution was determined and compared with a control group. Striatal regions were found to be hypoperfused and, by inference, hypofunctional in both groups. This hypoperfusion was statistically significant in the right striatum in ADHD, and in both striatal regions in ADHD with other neuropsychologic and neurologic symptoms. The primary sensory and sensorimotor cortical regions were highly perfused. Methylphenidate increased flow to striatal and posterior periventricular regions, and tended to decrease flow to primary sensory regions. Low striatal activity, partially reversible with methylphenidate, appears to be a cardinal feature in ADHD

  15. Assessment of striatal & postural deformities in patients with Parkinson's disease

    Directory of Open Access Journals (Sweden)

    Sanjay Pandey

    2016-01-01

    Interpretation & conclusions: Our results showed that striatal and postural deformities were common and present in about half of the patients with PD. These deformities we more common in patients with advanced stage of PD.

  16. Striatal dysfunction in attention deficit and hyperkinetic disorder

    Energy Technology Data Exchange (ETDEWEB)

    Lou, H.C.; Henriksen, L.; Bruhn, P.; Borner, H.; Nielsen, J.B.

    1989-01-01

    We have previously reported that periventricular structures are hypoperfused in attention deficit and hyperactivity disorder (ADHD). This study has expanded the number of patients, who were divided into two groups: six patients with pure ADHD, and 13 patients with ADHD in combination with other neurologic symptoms. By using xenon 133 inhalation and emission tomography, the regional cerebral blood flow distribution was determined and compared with a control group. Striatal regions were found to be hypoperfused and, by inference, hypofunctional in both groups. This hypoperfusion was statistically significant in the right striatum in ADHD, and in both striatal regions in ADHD with other neuropsychologic and neurologic symptoms. The primary sensory and sensorimotor cortical regions were highly perfused. Methylphenidate increased flow to striatal and posterior periventricular regions, and tended to decrease flow to primary sensory regions. Low striatal activity, partially reversible with methylphenidate, appears to be a cardinal feature in ADHD.

  17. Prefrontal cortex and striatal activation by feedback in Parkinson's disease

    NARCIS (Netherlands)

    Keitz, Martijn; Koerts, Janneke; Kortekaas, Rudie; Renken, Remco; de Jong, Bauke M.; Leenders, Klaus L.

    2008-01-01

    Positive feedbacks reinforce goal-directed behavior and evoke pleasure. in Parkinson's disease (PD) the striatal dysfunction impairs motor performance, but also may lead to decreased positive feedback (reward) processing. This study investigates two types of positive feedback processing (monetary

  18. Intermittently-visual Tracking Experiments Reveal the Roles of Error-correction and Predictive Mechanisms in the Human Visual-motor Control System

    Science.gov (United States)

    Hayashi, Yoshikatsu; Tamura, Yurie; Sase, Kazuya; Sugawara, Ken; Sawada, Yasuji

    Prediction mechanism is necessary for human visual motion to compensate a delay of sensory-motor system. In a previous study, “proactive control” was discussed as one example of predictive function of human beings, in which motion of hands preceded the virtual moving target in visual tracking experiments. To study the roles of the positional-error correction mechanism and the prediction mechanism, we carried out an intermittently-visual tracking experiment where a circular orbit is segmented into the target-visible regions and the target-invisible regions. Main results found in this research were following. A rhythmic component appeared in the tracer velocity when the target velocity was relatively high. The period of the rhythm in the brain obtained from environmental stimuli is shortened more than 10%. The shortening of the period of rhythm in the brain accelerates the hand motion as soon as the visual information is cut-off, and causes the precedence of hand motion to the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand motion precedes the target in average when the predictive mechanism dominates the error-corrective mechanism.

  19. Global actions of nicotine on the striatal microcircuit

    Directory of Open Access Journals (Sweden)

    Victor E Plata

    2013-11-01

    Full Text Available The question to solve in the present work is: what is the predominant action induced by the activation of cholinergic-nicotinic receptors (nAChrs in the striatal network given that nAChrs are expressed by several elements of the circuit: cortical terminals, dopamine terminals, and various striatal GABAergic interneurons. To answer this question some type of multicellular recording has to be used without losing single cell resolution. Here, we used calcium imaging and nicotine. It is known that in the presence of low micromolar N-Methyl-D-aspartate (NMDA, the striatal microcircuit exhibits neuronal activity consisting in the spontaneous synchronization of different neuron pools that interchange their activity following determined sequences. The striatal circuit also exhibits profuse spontaneous activity in pathological states (without NMDA such as dopamine depletion. However, in this case, most pathological activity is mostly generated by the same neuron pool. Here, we show that both types of activity are inhibited during the application of nicotine. Nicotine actions were blocked by mecamylamine, a non specific antagonist of nAChrs. Interestingly, inhibitory actions of nicotine were also blocked by the GABAA-receptor antagonist bicuculline, in which case, the actions of nicotine on the circuit became excitatory and facilitated neuronal synchronization. We conclude that the predominant action of nicotine in the striatal microcircuit is indirect, via the activation of networks of inhibitory interneurons. This action inhibits striatal pathological activity in early Parkinsonian animals almost as potently as L-DOPA.

  20. Global actions of nicotine on the striatal microcircuit.

    Science.gov (United States)

    Plata, Víctor; Duhne, Mariana; Pérez-Ortega, Jesús; Hernández-Martinez, Ricardo; Rueda-Orozco, Pavel; Galarraga, Elvira; Drucker-Colín, René; Bargas, José

    2013-01-01

    what is the predominant action induced by the activation of cholinergic-nicotinic receptors (nAChrs) in the striatal network given that nAChrs are expressed by several elements of the circuit: cortical terminals, dopamine terminals, and various striatal GABAergic interneurons. To answer this question some type of multicellular recording has to be used without losing single cell resolution. Here, we used calcium imaging and nicotine. It is known that in the presence of low micromolar N-Methyl-D-aspartate (NMDA), the striatal microcircuit exhibits neuronal activity consisting in the spontaneous synchronization of different neuron pools that interchange their activity following determined sequences. The striatal circuit also exhibits profuse spontaneous activity in pathological states (without NMDA) such as dopamine depletion. However, in this case, most pathological activity is mostly generated by the same neuron pool. Here, we show that both types of activity are inhibited during the application of nicotine. Nicotine actions were blocked by mecamylamine, a non-specific antagonist of nAChrs. Interestingly, inhibitory actions of nicotine were also blocked by the GABAA-receptor antagonist bicuculline, in which case, the actions of nicotine on the circuit became excitatory and facilitated neuronal synchronization. We conclude that the predominant action of nicotine in the striatal microcircuit is indirect, via the activation of networks of inhibitory interneurons. This action inhibits striatal pathological activity in early Parkinsonian animals almost as potently as L-DOPA.

  1. Genetic influences on functional connectivity associated with feedback processing and prediction error: Phase coupling of theta-band oscillations in twins.

    Science.gov (United States)

    Demiral, Şükrü Barış; Golosheykin, Simon; Anokhin, Andrey P

    2017-05-01

    Detection and evaluation of the mismatch between the intended and actually obtained result of an action (reward prediction error) is an integral component of adaptive self-regulation of behavior. Extensive human and animal research has shown that evaluation of action outcome is supported by a distributed network of brain regions in which the anterior cingulate cortex (ACC) plays a central role, and the integration of distant brain regions into a unified feedback-processing network is enabled by long-range phase synchronization of cortical oscillations in the theta band. Neural correlates of feedback processing are associated with individual differences in normal and abnormal behavior, however, little is known about the role of genetic factors in the cerebral mechanisms of feedback processing. Here we examined genetic influences on functional cortical connectivity related to prediction error in young adult twins (age 18, n=399) using event-related EEG phase coherence analysis in a monetary gambling task. To identify prediction error-specific connectivity pattern, we compared responses to loss and gain feedback. Monetary loss produced a significant increase of theta-band synchronization between the frontal midline region and widespread areas of the scalp, particularly parietal areas, whereas gain resulted in increased synchrony primarily within the posterior regions. Genetic analyses showed significant heritability of frontoparietal theta phase synchronization (24 to 46%), suggesting that individual differences in large-scale network dynamics are under substantial genetic control. We conclude that theta-band synchronization of brain oscillations related to negative feedback reflects genetically transmitted differences in the neural mechanisms of feedback processing. To our knowledge, this is the first evidence for genetic influences on task-related functional brain connectivity assessed using direct real-time measures of neuronal synchronization. Copyright © 2016

  2. Local control of striatal dopamine release

    Directory of Open Access Journals (Sweden)

    Roger eCachope

    2014-05-01

    Full Text Available The mesolimbic and nigrostriatal dopamine (DA systems play a key role in the physiology of reward seeking, motivation and motor control. Importantly, they are also involved in the pathophysiology of Parkinson’s and Huntington’s disease, schizophrenia and addiction. Control of DA release in the striatum is tightly linked to firing of DA neurons in the ventral tegmental area (VTA and the substantia nigra (SN. However, local influences in the striatum affect release by exerting their action directly on axon terminals. For example, endogenous glutamatergic and cholinergic activity is sufficient to trigger striatal DA release independently of cell body firing. Recent developments involving genetic manipulation, pharmacological selectivity or selective stimulation have allowed for better characterization of these phenomena. Such termino-terminal forms of control of DA release transform considerably our understanding of the mesolimbic and nigrostriatal systems, and have strong implications as potential mechanisms to modify impaired control of DA release in the diseased brain. Here, we review these and related mechanisms and their implications in the physiology of ascending DA systems.

  3. EVALUATING PREDICTIVE ERRORS OF A COMPLEX ENVIRONMENTAL MODEL USING A GENERAL LINEAR MODEL AND LEAST SQUARE MEANS

    Science.gov (United States)

    A General Linear Model (GLM) was used to evaluate the deviation of predicted values from expected values for a complex environmental model. For this demonstration, we used the default level interface of the Regional Mercury Cycling Model (R-MCM) to simulate epilimnetic total mer...

  4. Optogenetic stimulation in a computational model of the basal ganglia biases action selection and reward prediction error.

    Science.gov (United States)

    Berthet, Pierre; Lansner, Anders

    2014-01-01

    Optogenetic stimulation of specific types of medium spiny neurons (MSNs) in the striatum has been shown to bias the selection of mice in a two choices task. This shift is dependent on the localisation and on the intensity of the stimulation but also on the recent reward history. We have implemented a way to simulate this increased activity produced by the optical flash in our computational model of the basal ganglia (BG). This abstract model features the direct and indirect pathways commonly described in biology, and a reward prediction pathway (RP). The framework is similar to Actor-Critic methods and to the ventral/dorsal distinction in the striatum. We thus investigated the impact on the selection caused by an added stimulation in each of the three pathways. We were able to reproduce in our model the bias in action selection observed in mice. Our results also showed that biasing the reward prediction is sufficient to create a modification in the action selection. However, we had to increase the percentage of trials with stimulation relative to that in experiments in order to impact the selection. We found that increasing only the reward prediction had a different effect if the stimulation in RP was action dependent (only for a specific action) or not. We further looked at the evolution of the change in the weights depending on the stage of learning within a block. A bias in RP impacts the plasticity differently depending on that stage but also on the outcome. It remains to experimentally test how the dopaminergic neurons are affected by specific stimulations of neurons in the striatum and to relate data to predictions of our model.

  5. Error Patterns

    NARCIS (Netherlands)

    Hoede, C.; Li, Z.

    2001-01-01

    In coding theory the problem of decoding focuses on error vectors. In the simplest situation code words are $(0,1)$-vectors, as are the received messages and the error vectors. Comparison of a received word with the code words yields a set of error vectors. In deciding on the original code word,

  6. Human errors and mistakes

    International Nuclear Information System (INIS)

    Wahlstroem, B.

    1993-01-01

    Human errors have a major contribution to the risks for industrial accidents. Accidents have provided important lesson making it possible to build safer systems. In avoiding human errors it is necessary to adapt the systems to their operators. The complexity of modern industrial systems is however increasing the danger of system accidents. Models of the human operator have been proposed, but the models are not able to give accurate predictions of human performance. Human errors can never be eliminated, but their frequency can be decreased by systematic efforts. The paper gives a brief summary of research in human error and it concludes with suggestions for further work. (orig.)

  7. Statistical Analysis of NWP Prediction Errors and Their Consequences for Short-Time Photovoltaic Energy Forecasting; A Semi-Parametric Way to Prediction Quality Improvements

    Czech Academy of Sciences Publication Activity Database

    Brabec, Marek; Eben, Kryštof; Konár, Ondřej; Krč, Pavel; Pelikán, Emil; Juruš, Pavel

    2014-01-01

    Roč. 11, - (2014), EMS2014-429 [EMS Annual Meeting /14./ & European Conference on Applied Climatology (ECAC) /10./. 06.10.2014-10.10.2014, Prague] Institutional support: RVO:67985807 Keywords : prediction * mathematical modeling * renewable energies Subject RIV: JE - Non-nuclear Energetics, Energy Consumption ; Use

  8. Abnormal Striatal BOLD Responses to Reward Anticipation and Reward Delivery in ADHD

    Science.gov (United States)

    Furukawa, Emi; Bado, Patricia; Tripp, Gail; Mattos, Paulo; Wickens, Jeff R.; Bramati, Ivanei E.; Alsop, Brent; Ferreira, Fernanda Meireles; Lima, Debora; Tovar-Moll, Fernanda; Sergeant, Joseph A.; Moll, Jorge

    2014-01-01

    Altered reward processing has been proposed to contribute to the symptoms of attention deficit hyperactivity disorder (ADHD). The neurobiological mechanism underlying this alteration remains unclear. We hypothesize that the transfer of dopamine release from reward to reward-predicting cues, as normally observed in animal studies, may be deficient in ADHD. Functional magnetic resonance imaging (fMRI) was used to investigate striatal responses to reward-predicting cues and reward delivery in a classical conditioning paradigm. Data from 14 high-functioning and stimulant-naïve young adults with elevated lifetime symptoms of ADHD (8 males, 6 females) and 15 well-matched controls (8 males, 7 females) were included in the analyses. During reward anticipation, increased blood-oxygen-level-dependent (BOLD) responses in the right ventral and left dorsal striatum were observed in controls, but not in the ADHD group. The opposite pattern was observed in response to reward delivery; the ADHD group demonstrated significantly greater BOLD responses in the ventral striatum bilaterally and the left dorsal striatum relative to controls. In the ADHD group, the number of current hyperactivity/impulsivity symptoms was inversely related to ventral striatal responses during reward anticipation and positively associated with responses to reward. The BOLD response patterns observed in the striatum are consistent with impaired predictive dopamine signaling in ADHD, which may explain altered reward-contingent behaviors and symptoms of ADHD. PMID:24586543

  9. Where attention falls: Increased risk of falls from the converging impact of cortical cholinergic and midbrain dopamine loss on striatal function.

    Science.gov (United States)

    Sarter, Martin; Albin, Roger L; Kucinski, Aaron; Lustig, Cindy

    2014-07-01

    Falls are a major source of hospitalization, long-term institutionalization, and death in older adults and patients with Parkinson's disease (PD). Limited attentional resources are a major risk factor for falls. In this review, we specify cognitive-behavioral mechanisms that produce falls and map these mechanisms onto a model of multi-system degeneration. Results from PET studies in PD fallers and findings from a recently developed animal model support the hypothesis that falls result from interactions between loss of basal forebrain cholinergic projections to the cortex and striatal dopamine loss. Striatal dopamine loss produces inefficient, low-vigor gait, posture control, and movement. Cortical cholinergic deafferentation impairs a wide range of attentional processes, including monitoring of gait, posture and complex movements. Cholinergic cell loss reveals the full impact of striatal dopamine loss on motor performance, reflecting loss of compensatory attentional supervision of movement. Dysregulation of dorsomedial striatal circuitry is an essential, albeit not exclusive, mediator of falls in this dual-system model. Because cholinergic neuromodulatory activity influences cortical circuitry primarily via stimulation of α4β2* nicotinic acetylcholine receptors, and because agonists at these receptors are known to benefit attentional processes in animals and humans, treating PD fallers with such agonists, as an adjunct to dopaminergic treatment, is predicted to reduce falls. Falls are an informative behavioral endpoint to study attentional-motor integration by striatal circuitry. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. Where attention falls: Increased risk of falls from the converging impact of cortical cholinergic and midbrain dopamine loss on striatal function

    Science.gov (United States)

    Sarter, Martin; Albin, Roger L.; Kucinski, Aaron; Lustig, Cindy

    2015-01-01

    Falls are a major source of hospitalization, long-term institutionalization, and death in older adults and patients with Parkinson’s disease (PD). Limited attentional resources are a major risk factor for falls. In this review, we specify cognitive–behavioral mechanisms that produce falls and map these mechanisms onto a model of multi-system degeneration. Results from PET studies in PD fallers and findings from a recently developed animal model support the hypothesis that falls result from interactions between loss of basal forebrain cholinergic projections to the cortex and striatal dopamine loss. Striatal dopamine loss produces inefficient, low-vigor gait, posture control, and movement. Cortical cholinergic deafferentation impairs a wide range of attentional processes, including monitoring of gait, posture and complex movements. Cholinergic cell loss reveals the full impact of striatal dopamine loss on motor performance, reflecting loss of compensatory attentional supervision of movement. Dysregulation of dorsomedial striatal circuitry is an essential, albeit not exclusive, mediator of falls in this dual-system model. Because cholinergic neuromodulatory activity influences cortical circuitry primarily via stimulation of α4β2* nicotinic acetylcholine receptors, and because agonists at these receptors are known to benefit attentional processes in animals and humans, treating PD fallers with such agonists, as an adjunct to dopaminergic treatment, is predicted to reduce falls. Falls are an informative behavioral endpoint to study attentional–motor integration by striatal circuitry. PMID:24805070

  11. Reduced striatal D2 receptor binding in myoclonus-dystonia

    International Nuclear Information System (INIS)

    Beukers, R.J.; Weisscher, N.; Tijssen, M.A.J.; Booij, J.; Zijlstra, F.; Amelsvoort, T.A.M.J. van

    2009-01-01

    To study striatal dopamine D 2 receptor availability in DYT11 mutation carriers of the autosomal dominantly inherited disorder myoclonus-dystonia (M-D). Fifteen DYT11 mutation carriers (11 clinically affected) and 15 age- and sex-matched controls were studied using 123 I-IBZM SPECT. Specific striatal binding ratios were calculated using standard templates for striatum and occipital areas. Multivariate analysis with corrections for ageing and smoking showed significantly lower specific striatal to occipital IBZM uptake ratios (SORs) both in the left and right striatum in clinically affected patients and also in all DYT11 mutation carriers compared to control subjects. Our findings are consistent with the theory of reduced dopamine D 2 receptor (D2R) availability in dystonia, although the possibility of increased endogenous dopamine, and consequently, competitive D2R occupancy cannot be ruled out. (orig.)

  12. Sea surface salinity and temperature-based predictive modeling of southwestern US winter precipitation: improvements, errors, and potential mechanisms

    Science.gov (United States)

    Liu, T.; Schmitt, R. W.; Li, L.

    2017-12-01

    Using 69 years of historical data from 1948-2017, we developed a method to globally search for sea surface salinity (SSS) and temperature (SST) predictors of regional terrestrial precipitation. We then applied this method to build an autumn (SON) SSS and SST-based 3-month lead predictive model of winter (DJF) precipitation in southwestern United States. We also find that SSS-only models perform better than SST-only models. We previously used an arbitrary correlation coefficient (r) threshold, |r| > 0.25, to define SSS and SST predictor polygons for best subset regression of southwestern US winter precipitation; from preliminary sensitivity tests, we find that |r| > 0.18 yields the best models. The observed below-average precipitation (0.69 mm/day) in winter 2015-2016 falls within the 95% confidence interval of the prediction model. However, the model underestimates the anomalous high precipitation (1.78 mm/day) in winter 2016-2017 by more than three-fold. Moisture transport mainly attributed to "pineapple express" atmospheric rivers (ARs) in winter 2016-2017 suggests that the model falls short on a sub-seasonal scale, in which case storms from ARs contribute a significant portion of seasonal terrestrial precipitation. Further, we identify a potential mechanism for long-range SSS and precipitation teleconnections: standing Rossby waves. The heat applied to the atmosphere from anomalous tropical rainfall can generate standing Rossby waves that propagate to higher latitudes. SSS anomalies may be indicative of anomalous tropical rainfall, and by extension, standing Rossby waves that provide the long-range teleconnections.

  13. No association between striatal dopamine transporter binding and body mass index

    DEFF Research Database (Denmark)

    van de Giessen, Elsmarieke; Hesse, Swen; Caan, Matthan W A

    2013-01-01

    Dopamine is one among several neurotransmitters that regulate food intake and overeating. Thus, it has been linked to the pathophysiology of obesity and high body mass index (BMI). Striatal dopamine D(2) receptor availability is lower in obesity and there are indications that striatal dopamine...... transporter (DAT) availability is also decreased. In this study, we tested whether BMI and striatal DAT availability are associated....

  14. Operator errors

    International Nuclear Information System (INIS)

    Knuefer; Lindauer

    1980-01-01

    Besides that at spectacular events a combination of component failure and human error is often found. Especially the Rasmussen-Report and the German Risk Assessment Study show for pressurised water reactors that human error must not be underestimated. Although operator errors as a form of human error can never be eliminated entirely, they can be minimized and their effects kept within acceptable limits if a thorough training of personnel is combined with an adequate design of the plant against accidents. Contrary to the investigation of engineering errors, the investigation of human errors has so far been carried out with relatively small budgets. Intensified investigations in this field appear to be a worthwhile effort. (orig.)

  15. Major Source of Error in QSPR Prediction of Intrinsic Thermodynamic Solubility of Drugs: Solid vs Nonsolid State Contributions?

    Science.gov (United States)

    Abramov, Yuriy A

    2015-06-01

    The main purpose of this study is to define the major limiting factor in the accuracy of the quantitative structure-property relationship (QSPR) models of the thermodynamic intrinsic aqueous solubility of the drug-like compounds. For doing this, the thermodynamic intrinsic aqueous solubility property was suggested to be indirectly "measured" from the contributions of solid state, ΔGfus, and nonsolid state, ΔGmix, properties, which are estimated by the corresponding QSPR models. The QSPR models of ΔGfus and ΔGmix properties were built based on a set of drug-like compounds with available accurate measurements of fusion and thermodynamic solubility properties. For consistency ΔGfus and ΔGmix models were developed using similar algorithms and descriptor sets, and validated against the similar test compounds. Analysis of the relative performances of these two QSPR models clearly demonstrates that it is the solid state contribution which is the limiting factor in the accuracy and predictive power of the QSPR models of the thermodynamic intrinsic solubility. The performed analysis outlines a necessity of development of new descriptor sets for an accurate description of the long-range order (periodicity) phenomenon in the crystalline state. The proposed approach to the analysis of limitations and suggestions for improvement of QSPR-type models may be generalized to other applications in the pharmaceutical industry.

  16. Using Air Temperature to Quantitatively Predict the MODIS Fractional Snow Cover Retrieval Errors over the Continental US (CONUS)

    Science.gov (United States)

    Dong, Jiarui; Ek, Mike; Hall, Dorothy K.; Peters-Lidard, Christa; Cosgrove, Brian; Miller, Jeff; Riggs, George A.; Xia, Youlong

    2013-01-01

    In the middle to high latitude and alpine regions, the seasonal snow pack can dominate the surface energy and water budgets due to its high albedo, low thermal conductivity, high emissivity, considerable spatial and temporal variability, and ability to store and then later release a winters cumulative snowfall (Cohen, 1994; Hall, 1998). With this in mind, the snow drought across the U.S. has raised questions about impacts on water supply, ski resorts and agriculture. Knowledge of various snow pack properties is crucial for short-term weather forecasts, climate change prediction, and hydrologic forecasting for producing reliable daily to seasonal forecasts. One potential source of this information is the multi-institution North American Land Data Assimilation System (NLDAS) project (Mitchell et al., 2004). Real-time NLDAS products are used for drought monitoring to support the National Integrated Drought Information System (NIDIS) and as initial conditions for a future NCEP drought forecast system. Additionally, efforts are currently underway to assimilate remotely-sensed estimates of land-surface states such as snowpack information into NLDAS. It is believed that this assimilation will not only produce improved snowpack states that better represent snow evolving conditions, but will directly improve the monitoring of drought.

  17. Striatal fast-spiking interneurons: from firing patterns to postsynaptic impact

    Directory of Open Access Journals (Sweden)

    Andreas eKlaus

    2011-07-01

    Full Text Available In the striatal microcircuit, fast-spiking (FS interneurons have an important role in mediating inhibition onto neighboring medium spiny (MS projection neurons. In this study, we combined computational modeling with in vitro and in vivo electrophysiological measurements to investigate FS cells in terms of their discharge properties and their synaptic efficacies onto MS neurons. In vivo firing of striatal FS interneurons is characterized by a high firing variability. It is not known, however, if this variability results from the input that FS cells receive, or if it is promoted by the stuttering spike behavior of these neurons. Both our model and measurements in vitro show that FS neurons that exhibit random stuttering discharge in response to steady depolarization, do not show the typical stuttering behavior when they receive fluctuating input. Importantly, our model predicts that electrically coupled FS cells show substantial spike synchronization only when they are in the stuttering regime. Therefore, together with the lack of synchronized firing of striatal FS interneurons that has been reported in vivo, these results suggest that neighboring FS neurons are not in the stuttering regime simultaneously and that in vivo FS firing variability is more likely determined by the input fluctuations. Furthermore, the variability in FS firing is translated to variability in the postsynaptic amplitudes in MS neurons due to the strong synaptic depression of the FS-to-MS synapse. Our results support the idea that these synapses operate over a wide range from strongly depressed to almost fully recovered. The strong inhibitory effects that FS cells can impose on their postsynaptic targets, and the fact that the FS-to-MS synapse model showed substantial depression over extended periods of time might indicate the importance of cooperative effects of multiple presynaptic FS interneurons and the precise orchestration of their activity.

  18. Alterations in Striatal Circuits Underlying Addiction-Like Behaviors.

    Science.gov (United States)

    Kim, Hyun Jin; Lee, Joo Han; Yun, Kyunghwa; Kim, Joung-Hun

    2017-06-30

    Drug addiction is a severe psychiatric disorder characterized by the compulsive pursuit of drugs of abuse despite potential adverse consequences. Although several decades of studies have revealed that psychostimulant use can result in extensive alterations of neural circuits and physiology, no effective therapeutic strategies or medicines for drug addiction currently exist. Changes in neuronal connectivity and regulation occurring after repeated drug exposure contribute to addiction-like behaviors in animal models. Among the involved brain areas, including those of the reward system, the striatum is the major area of convergence for glutamate, GABA, and dopamine transmission, and this brain region potentially determines stereotyped behaviors. Although the physiological consequences of striatal neurons after drug exposure have been relatively well documented, it remains to be clarified how changes in striatal connectivity underlie and modulate the expression of addiction-like behaviors. Understanding how striatal circuits contribute to addiction-like behaviors may lead to the development of strategies that successfully attenuate drug-induced behavioral changes. In this review, we summarize the results of recent studies that have examined striatal circuitry and pathway-specific alterations leading to addiction-like behaviors to provide an updated framework for future investigations.

  19. Dysregulation of striatal projection neurons in Parkinson's disease.

    Science.gov (United States)

    Beck, Goichi; Singh, Arun; Papa, Stella M

    2018-03-01

    The loss of nigrostriatal dopamine (DA) is the primary cause of motor dysfunction in Parkinson's disease (PD), but the underlying striatal mechanisms remain unclear. In spite of abundant literature portraying structural, biochemical and plasticity changes of striatal projection neurons (SPNs), in the past there has been a data vacuum from the natural human disease and its close model in non-human primates. Recently, single-cell recordings in advanced parkinsonian primates have generated new insights into the altered function of SPNs. Currently, there are also human data that provide direct evidence of profoundly dysregulated SPN activity in PD. Here, we review primate recordings that are impacting our understanding of the striatal dysfunction after DA loss, particularly through the analysis of physiologic correlates of parkinsonian motor behaviors. In contrast to recordings in rodents, data obtained in primates and patients demonstrate similar major abnormalities of the spontaneous SPN firing in the alert parkinsonian state. Furthermore, these studies also show altered SPN responses to DA replacement in the advanced parkinsonian state. Clearly, there is yet much to learn about the striatal discharges in PD, but studies using primate models are contributing unique information to advance our understanding of pathophysiologic mechanisms.

  20. Forgetting the best when predicting the worst: Preliminary observations on neural circuit function in adolescent social anxiety

    Directory of Open Access Journals (Sweden)

    Johanna M. Jarcho

    2015-06-01

    Full Text Available Social anxiety disorder typically begins in adolescence, a sensitive period for brain development, when increased complexity and salience of peer relationships requires novel forms of social learning. Disordered social learning in adolescence may explain how brain dysfunction promotes social anxiety. Socially anxious adolescents (n = 15 and adults (n = 19 and non-anxious adolescents (n = 24 and adults (n = 32 predicted, then received, social feedback from high and low-value peers while undergoing functional magnetic resonance imaging (fMRI. A surprise recall task assessed memory biases for feedback. Neural correlates of social evaluation prediction errors (PEs were assessed by comparing engagement to expected and unexpected positive and negative feedback. For socially anxious adolescents, but not adults or healthy participants of either age group, PEs elicited heightened striatal activity and negative fronto-striatal functional connectivity. This occurred selectively to unexpected positive feedback from high-value peers and corresponded with impaired memory for social feedback. While impaired memory also occurred in socially-anxious adults, this impairment was unrelated to brain-based PE activity. Thus, social anxiety in adolescence may relate to altered neural correlates of PEs that contribute to impaired learning about social feedback. Small samples necessitate replication. Nevertheless, results suggest that the relationship between learning and fronto-striatal function may attenuate as development progresses.

  1. Error-related brain activity and error awareness in an error classification paradigm.

    Science.gov (United States)

    Di Gregorio, Francesco; Steinhauser, Marco; Maier, Martin E

    2016-10-01

    Error-related brain activity has been linked to error detection enabling adaptive behavioral adjustments. However, it is still unclear which role error awareness plays in this process. Here, we show that the error-related negativity (Ne/ERN), an event-related potential reflecting early error monitoring, is dissociable from the degree of error awareness. Participants responded to a target while ignoring two different incongruent distractors. After responding, they indicated whether they had committed an error, and if so, whether they had responded to one or to the other distractor. This error classification paradigm allowed distinguishing partially aware errors, (i.e., errors that were noticed but misclassified) and fully aware errors (i.e., errors that were correctly classified). The Ne/ERN was larger for partially aware errors than for fully aware errors. Whereas this speaks against the idea that the Ne/ERN foreshadows the degree of error awareness, it confirms the prediction of a computational model, which relates the Ne/ERN to post-response conflict. This model predicts that stronger distractor processing - a prerequisite of error classification in our paradigm - leads to lower post-response conflict and thus a smaller Ne/ERN. This implies that the relationship between Ne/ERN and error awareness depends on how error awareness is related to response conflict in a specific task. Our results further indicate that the Ne/ERN but not the degree of error awareness determines adaptive performance adjustments. Taken together, we conclude that the Ne/ERN is dissociable from error awareness and foreshadows adaptive performance adjustments. Our results suggest that the relationship between the Ne/ERN and error awareness is correlative and mediated by response conflict. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Motor and cortico-striatal-thalamic connectivity alterations in intrauterine growth restriction.

    Science.gov (United States)

    Eixarch, Elisenda; Muñoz-Moreno, Emma; Bargallo, Nuria; Batalle, Dafnis; Gratacos, Eduard

    2016-06-01

    .409 ± 0.046; P = .016) in both networks were observed in the intrauterine growth restriction group, with no differences in number of streamlines. More importantly, strong specific correlation was found between tractography-related metrics and its relative function in both networks in intrauterine growth restricted children. Motor network metrics were correlated specifically with motor scale results (fractional anisotropy: rho = 0.857; integrity: rho = 0.740); cortico-striatal-thalamic network metrics were correlated with cognitive (fractional anisotropy: rho = 0.793; integrity, rho = 0.762) and socioemotional scale (fractional anisotropy: rho = 0.850; integrity: rho = 0.877). These results support the existence of altered brain connectivity in intrauterine growth restriction demonstrated by altered connectivity in motor and cortico-striatal-thalamic networks, with reduced fractional anisotropy and integrity. The specific correlation between tractography-related metrics and neurodevelopmental outcomes in intrauterine growth restriction shows the potential to use this approach to develop imaging biomarkers to predict specific neurodevelopmental outcome in infants who are at risk because of intrauterine growth restriction and other prenatal diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

  3. Predictors of Errors of Novice Java Programmers

    Science.gov (United States)

    Bringula, Rex P.; Manabat, Geecee Maybelline A.; Tolentino, Miguel Angelo A.; Torres, Edmon L.

    2012-01-01

    This descriptive study determined which of the sources of errors would predict the errors committed by novice Java programmers. Descriptive statistics revealed that the respondents perceived that they committed the identified eighteen errors infrequently. Thought error was perceived to be the main source of error during the laboratory programming…

  4. Einstein's error

    International Nuclear Information System (INIS)

    Winterflood, A.H.

    1980-01-01

    In discussing Einstein's Special Relativity theory it is claimed that it violates the principle of relativity itself and that an anomalous sign in the mathematics is found in the factor which transforms one inertial observer's measurements into those of another inertial observer. The apparent source of this error is discussed. Having corrected the error a new theory, called Observational Kinematics, is introduced to replace Einstein's Special Relativity. (U.K.)

  5. Levodopa administration modulates striatal processing of punishment-associated items in healthy participants.

    Science.gov (United States)

    Wittmann, Bianca C; D'Esposito, Mark

    2015-01-01

    Appetitive and aversive processes share a number of features such as their relevance for action and learning. On a neural level, reward and its predictors are associated with increased firing of dopaminergic neurons, whereas punishment processing has been linked to the serotonergic system and to decreases in dopamine transmission. Recent data indicate, however, that the dopaminergic system also responds to aversive stimuli and associated actions. In this pharmacological functional magnetic resonance imaging study, we investigated the contribution of the dopaminergic system to reward and punishment processing in humans. Two groups of participants received either placebo or the dopamine precursor levodopa and were scanned during alternating reward and punishment anticipation blocks. Levodopa administration increased striatal activations for cues presented in punishment blocks. In an interaction with individual personality scores, levodopa also enhanced striatal activation for punishment-predictive compared with neutral cues in participants scoring higher on the novelty-seeking dimension. These data support recent indications that dopamine contributes to punishment processing and suggest that the novelty-seeking trait is a measure of susceptibility to drug effects on motivation. These findings are also consistent with the possibility of an inverted U-shaped response function of dopamine in the striatum, suggesting an optimal level of dopamine release for motivational processing.

  6. Altered cingulo-striatal function underlies reward drive deficits in schizophrenia.

    Science.gov (United States)

    Park, Il Ho; Chun, Ji Won; Park, Hae-Jeong; Koo, Min-Seong; Park, Sunyoung; Kim, Seok-Hyeong; Kim, Jae-Jin

    2015-02-01

    Amotivation in schizophrenia is assumed to involve dysfunctional dopaminergic signaling of reward prediction or anticipation. It is unclear, however, whether the translation of neural representation of reward value to behavioral drive is affected in schizophrenia. In order to examine how abnormal neural processing of response valuation and initiation affects incentive motivation in schizophrenia, we conducted functional MRI using a deterministic reinforcement learning task with variable intervals of contingency reversals in 20 clinically stable patients with schizophrenia and 20 healthy controls. Behaviorally, the advantage of positive over negative reinforcer in reinforcement-related responsiveness was not observed in patients. Patients showed altered response valuation and initiation-related striatal activity and deficient rostro-ventral anterior cingulate cortex activation during reward approach initiation. Among these neural abnormalities, rostro-ventral anterior cingulate cortex activation was correlated with positive reinforcement-related responsiveness in controls and social anhedonia and social amotivation subdomain scores in patients. Our findings indicate that the central role of the anterior cingulate cortex is in translating action value into driving force of action, and underscore the role of the cingulo-striatal network in amotivation in schizophrenia. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. The error in total error reduction.

    Science.gov (United States)

    Witnauer, James E; Urcelay, Gonzalo P; Miller, Ralph R

    2014-02-01

    Most models of human and animal learning assume that learning is proportional to the discrepancy between a delivered outcome and the outcome predicted by all cues present during that trial (i.e., total error across a stimulus compound). This total error reduction (TER) view has been implemented in connectionist and artificial neural network models to describe the conditions under which weights between units change. Electrophysiological work has revealed that the activity of dopamine neurons is correlated with the total error signal in models of reward learning. Similar neural mechanisms presumably support fear conditioning, human contingency learning, and other types of learning. Using a computational modeling approach, we compared several TER models of associative learning to an alternative model that rejects the TER assumption in favor of local error reduction (LER), which assumes that learning about each cue is proportional to the discrepancy between the delivered outcome and the outcome predicted by that specific cue on that trial. The LER model provided a better fit to the reviewed data than the TER models. Given the superiority of the LER model with the present data sets, acceptance of TER should be tempered. Copyright © 2013 Elsevier Inc. All rights reserved.

  8. Prefronto-striatal physiology is associated with schizotypy and is modulated by a functional variant of DRD2.

    Science.gov (United States)

    Taurisano, Paolo; Romano, Raffaella; Mancini, Marina; Giorgio, Annabella Di; Antonucci, Linda A; Fazio, Leonardo; Rampino, Antonio; Quarto, Tiziana; Gelao, Barbara; Porcelli, Annamaria; Papazacharias, Apostolos; Ursini, Gianluca; Caforio, Grazia; Masellis, Rita; Niccoli-Asabella, Artor; Todarello, Orlando; Popolizio, Teresa; Rubini, Giuseppe; Blasi, Giuseppe; Bertolino, Alessandro

    2014-01-01

    "Schizotypy" is a latent organization of personality related to the genetic risk for schizophrenia. Some evidence suggests that schizophrenia and schizotypy share some biological features, including a link to dopaminergic D2 receptor signaling. A polymorphism in the D2 gene (DRD2 rs1076560, guanine > thymine (G > T)) has been associated with the D2 short/long isoform expression ratio, as well as striatal dopamine signaling and prefrontal cortical activity during different cognitive operations, which are measures that are altered in patients with schizophrenia. Our aim is to determine the association of schizotypy scores with the DRD2 rs1076560 genotype in healthy individuals and their interaction with prefrontal activity during attention and D2 striatal signaling. A total of 83 healthy subjects were genotyped for DRD2 rs1076560 and completed the Schizotypal Personality Questionnaire (SPQ). Twenty-six participants underwent SPECT with [(123)I]IBZM D2 receptor radiotracer, while 68 performed an attentional control task during fMRI. We found that rs1076560 GT subjects had greater SPQ scores than GG individuals. Moreover, the interaction between schizotypy and the GT genotype predicted prefrontal activity and related attentional behavior, as well as striatal binding of IBZM. No interaction was found in GG individuals. These results suggest that rs1076560 GT healthy individuals are prone to higher levels of schizotypy, and that the interaction between rs1076560 and schizotypy scores modulates phenotypes related to the pathophysiology of schizophrenia, such as prefrontal activity and striatal dopamine signaling. These results provide systems-level qualitative evidence for mapping the construct of schizotypy in healthy individuals onto the schizophrenia continuum.

  9. Dopamine-signalled reward predictions generated by competitive excitation and inhibition in a spiking neural network model

    Directory of Open Access Journals (Sweden)

    Paul eChorley

    2011-05-01

    Full Text Available Dopaminergic neurons in the mammalian substantia nigra displaycharacteristic phasic responses to stimuli which reliably predict thereceipt of primary rewards. These responses have been suggested toencode reward prediction-errors similar to those used in reinforcementlearning. Here, we propose a model of dopaminergic activity in whichprediction error signals are generated by the joint action ofshort-latency excitation and long-latency inhibition, in a networkundergoing dopaminergic neuromodulation of both spike-timing dependentsynaptic plasticity and neuronal excitability. In contrast toprevious models, sensitivity to recent events is maintained by theselective modification of specific striatal synapses, efferent tocortical neurons exhibiting stimulus-specific, temporally extendedactivity patterns. Our model shows, in the presence of significantbackground activity, (i a shift in dopaminergic response from rewardto reward predicting stimuli, (ii preservation of a response tounexpected rewards, and (iii a precisely-timed below-baseline dip inactivity observed when expected rewards are omitted.

  10. Fronto-striatal atrophy in behavioural variant frontotemporal dementia & Alzheimer’s disease

    Directory of Open Access Journals (Sweden)

    Maxime eBertoux

    2015-07-01

    Full Text Available Behavioural variant frontotemporal dementia (bvFTD has only recently been associated with significant striatal atrophy, whereas the striatum appears to be relatively preserved in Alzheimer’s disease (AD. Considering the critical role the striatum has in cognition and behaviour, striatal degeneration, together with frontal atrophy, could be responsible of some characteristic symptoms in bvFTD and emerges therefore as promising novel diagnostic biomarker to distinguish bvFTD and AD. Previous studies have, however, only taken either cortical or striatal atrophy into account when comparing the two diseases. In this study, we establish for the first time a profile of fronto-striatal atrophy in 23 bvFTD and 29 AD patients at presentation, based on the structural connectivity of striatal and cortical regions. Patients are compared to 50 healthy controls by using a novel probabilistic connectivity atlas, which defines striatal regions by their cortical white matter connectivity, allowing us to explore the degeneration of the frontal and striatal regions that are functionally linked. Comparisons with controls revealed that bvFTD showed substantial fronto-striatal atrophy affecting the ventral as well as anterior and posterior dorso-lateral prefrontal cortices and the related striatal subregions. By contrast, AD showed few fronto-striatal atrophy, despite having significant posterior dorso-lateral prefrontal degeneration. Direct comparison between bvFTD and AD revealed significantly more atrophy in the ventral striatal-ventromedial prefrontal cortex regions in bvFTD. Consequently, deficits in ventral fronto-striatal regions emerge as promising novel and efficient diagnosis biomarker for bvFTD. Future investigations into the contributions of these fronto-striatal loops on bvFTD symptomology are needed to develop simple diagnostic and disease tracking algorithms.

  11. Striatal dopamine release codes uncertainty in pathological gambling

    DEFF Research Database (Denmark)

    Linnet, Jakob; Mouridsen, Kim; Peterson, Ericka

    2012-01-01

    Two mechanisms of midbrain and striatal dopaminergic projections may be involved in pathological gambling: hypersensitivity to reward and sustained activation toward uncertainty. The midbrain—striatal dopamine system distinctly codes reward and uncertainty, where dopaminergic activation is a linear...... function of expected reward and an inverse U-shaped function of uncertainty. In this study, we investigated the dopaminergic coding of reward and uncertainty in 18 pathological gambling sufferers and 16 healthy controls. We used positron emission tomography (PET) with the tracer [11C]raclopride to measure...... dopamine release, and we used performance on the Iowa Gambling Task (IGT) to determine overall reward and uncertainty. We hypothesized that we would find a linear function between dopamine release and IGT performance, if dopamine release coded reward in pathological gambling. If, on the other hand...

  12. Centrality of striatal cholinergic transmission in basal ganglia function

    Directory of Open Access Journals (Sweden)

    Paola eBonsi

    2011-02-01

    Full Text Available Work over the past two decades revealed a previously unexpected role for striatal cholinergic interneurons in the context of basal ganglia function. The recognition that these interneurons are essential in synaptic plasticity and motor learning represents a significant step ahead in deciphering how the striatum processes cortical inputs, and why pathological circumstances cause motor dysfunction.Loss of the reciprocal modulation between dopaminergic inputs and the intrinsic cholinergic innervation within the striatum appears to be the trigger for pathophysiological changes occurring in basal ganglia disorders. Accordingly, there is now compelling evidence showing profound changes in cholinergic markers in these disorders, in particular Parkinson’s disease and dystonia.Based on converging experimental and clinical evidence, we provide an overview of the role of striatal cholinergic transmission in physiological and pathological conditions, in the context of the pathogenesis of movement disorders.

  13. Distinctive striatal dopamine signaling after dieting and gastric bypass.

    Science.gov (United States)

    Hankir, Mohammed K; Ashrafian, Hutan; Hesse, Swen; Horstmann, Annette; Fenske, Wiebke K

    2015-05-01

    Highly palatable and/or calorically dense foods, such as those rich in fat, engage the striatum to govern and set complex behaviors. Striatal dopamine signaling has been implicated in hedonic feeding and the development of obesity. Dieting and bariatric surgery have markedly different outcomes on weight loss, yet how these interventions affect central homeostatic and food reward processing remains poorly understood. Here, we propose that dieting and gastric bypass produce distinct changes in peripheral factors with known roles in regulating energy homeostasis, resulting in differential modulation of nigrostriatal and mesolimbic dopaminergic reward circuits. Enhancement of intestinal fat metabolism after gastric bypass may also modify striatal dopamine signaling contributing to its unique long-term effects on feeding behavior and body weight in obese individuals. Copyright © 2015 Elsevier Ltd. All rights reserved.

  14. Striatal dopamine release codes uncertainty in pathological gambling

    DEFF Research Database (Denmark)

    Linnet, Jakob; Mouridsen, Kim; Peterson, Ericka

    2012-01-01

    Two mechanisms of midbrain and striatal dopaminergic projections may be involved in pathological gambling: hypersensitivity to reward and sustained activation toward uncertainty. The midbrain-striatal dopamine system distinctly codes reward and uncertainty, where dopaminergic activation is a linear...... function of expected reward and an inverse U-shaped function of uncertainty. In this study, we investigated the dopaminergic coding of reward and uncertainty in 18 pathological gambling sufferers and 16 healthy controls. We used positron emission tomography (PET) with the tracer [(11)C......]raclopride to measure dopamine release, and we used performance on the Iowa Gambling Task (IGT) to determine overall reward and uncertainty. We hypothesized that we would find a linear function between dopamine release and IGT performance, if dopamine release coded reward in pathological gambling. If, on the other hand...

  15. Enhanced striatal sensitivity to aversive reinforcement in adolescents versus adults.

    Science.gov (United States)

    Galván, Adriana; McGlennen, Kristine M

    2013-02-01

    Neurodevelopmental changes in mesolimbic regions are associated with adolescent risk-taking behavior. Numerous studies have shown exaggerated activation in the striatum in adolescents compared with children and adults during reward processing. However, striatal sensitivity to aversion remains elusive. Given the important role of the striatum in tracking both appetitive and aversive events, addressing this question is critical to understanding adolescent decision-making, as both positive and negative factors contribute to this behavior. In this study, human adult and adolescent participants performed a task in which they received squirts of appetitive or aversive liquid while undergoing fMRI, a novel approach in human adolescents. Compared with adults, adolescents showed greater behavioral and striatal sensitivity to both appetitive and aversive stimuli, an effect that was exaggerated in response to delivery of the aversive stimulus. Collectively, these findings contribute to understanding how neural responses to positive and negative outcomes differ between adolescents and adults and how they may influence adolescent behavior.

  16. Striatal grafts in a rat model of Huntington's disease

    DEFF Research Database (Denmark)

    Guzman, R; Meyer, M; Lövblad, K O

    1999-01-01

    Survival and integration into the host brain of grafted tissue are crucial factors in neurotransplantation approaches. The present study explored the feasibility of using a clinical MR scanner to study striatal graft development in a rat model of Huntington's disease. Rat fetal lateral ganglionic...... time-points graft location could not be further verified. Measures for graft size and ventricle size obtained from MR images highly correlated with measures obtained from histologically processed sections (R = 0.8, P fetal rat lateral ganglionic...

  17. Control of striatal signaling by G protein regulators

    Directory of Open Access Journals (Sweden)

    Keqiang eXie

    2011-08-01

    Full Text Available Signaling via heterotrimeric G proteins plays a crucial role in modulating the responses of striatal neurons that ultimately shape core behaviors mediated by the basal ganglia circuitry, such as reward valuation, habit formation and movement coordination. Activation of G-protein-coupled receptors (GPCRs by extracellular signals activates heterotrimeric G proteins by promoting the binding of GTP to their α subunits. G proteins exert their effects by influencing the activity of key effector proteins in this region, including ion channels, second messenger enzymes and protein kinases. Striatal neurons express a staggering number of GPCRs whose activation results in the engagement of downstream signaling pathways and cellular responses with unique profiles but common molecular mechanisms. Studies over the last decade have revealed that the extent and duration of GPCR signaling are controlled by a conserved protein family named Regulator of G protein Signaling (RGS. RGS proteins accelerate GTP hydrolysis by the α subunits of G proteins, thus promoting deactivation of GPCR signaling. In this review, we discuss the progress made in understanding the roles of RGS proteins in controlling striatal G protein signaling and providing integration and selectivity of signal transmission. We review evidence on the formation of a macromolecular complex between RGS proteins and other components of striatal signaling pathways, their molecular regulatory mechanisms and impacts on GPCR signaling in the striatum obtained from biochemical studies and experiments involving genetic mouse models. Special emphasis is placed on RGS9-2, a member of the RGS family that is highly enriched in the striatum and plays critical roles in drug addiction and motor control.

  18. Motor tics evoked by striatal disinhibition in the rat

    Science.gov (United States)

    Bronfeld, Maya; Yael, Dorin; Belelovsky, Katya; Bar-Gad, Izhar

    2013-01-01

    Motor tics are sudden, brief, repetitive movements that constitute the main symptom of Tourette syndrome (TS). Multiple lines of evidence suggest the involvement of the cortico-basal ganglia system, and in particular the basal ganglia input structure—the striatum in tic formation. The striatum receives somatotopically organized cortical projections and contains an internal GABAergic network of interneurons and projection neurons' collaterals. Disruption of local striatal GABAergic connectivity has been associated with TS and was found to induce abnormal movements in model animals. We have previously described the behavioral and neurophysiological characteristics of motor tics induced in monkeys by local striatal microinjections of the GABAA antagonist bicuculline. In the current study we explored the abnormal movements induced by a similar manipulation in freely moving rats. We targeted microinjections to different parts of the dorsal striatum, and examined the effects of this manipulation on the induced tic properties, such as latency, duration, and somatic localization. Tics induced by striatal disinhibition in monkeys and rats shared multiple properties: tics began within several minutes after microinjection, were expressed solely in the contralateral side, and waxed and waned around a mean inter-tic interval of 1–4 s. A clear somatotopic organization was observed only in rats, where injections to the anterior or posterior striatum led to tics in the forelimb or hindlimb areas, respectively. These results suggest that striatal disinhibition in the rat may be used to model motor tics such as observed in TS. Establishing this reliable and accessible animal model could facilitate the study of the neural mechanisms underlying motor tics, and the testing of potential therapies for tic disorders. PMID:24065893

  19. Neuroglial plasticity at striatal glutamatergic synapses in Parkinson's disease

    Directory of Open Access Journals (Sweden)

    Rosa M Villalba

    2011-08-01

    Full Text Available Striatal dopamine denervation is the pathological hallmark of Parkinson’s disease (PD. Another major pathological change described in animal models and PD patients is a significant reduction in the density of dendritic spines on medium spiny striatal projection neurons. Simultaneously, the ultrastructural features of the neuronal synaptic elements at the remaining corticostriatal and thalamostriatal glutamatergic axo-spinous synapses undergo complex ultrastructural remodeling consistent with increased synaptic activity (Villalba et al., 2011. The concept of tripartite synapses (TS was introduced a decade ago, according to which astrocytes process and exchange information with neuronal synaptic elements at glutamatergic synapses (Araque et al., 1999a. Although there has been compelling evidence that astrocytes are integral functional elements of tripartite glutamatergic synaptic complexes in the cerebral cortex and hippocampus, their exact functional role, degree of plasticity and preponderance in other CNS regions remain poorly understood. In this review, we discuss our recent findings showing that neuronal elements at cortical and thalamic glutamatergic synapses undergo significant plastic changes in the striatum of MPTP-treated parkinsonian monkeys. We also present new ultrastructural data that demonstrate a significant expansion of the astrocytic coverage of striatal TS synapses in the parkinsonian state, providing further evidence for ultrastructural compensatory changes that affect both neuronal and glial elements at TS. Together with our limited understanding of the mechanisms by which astrocytes respond to changes in neuronal activity and extracellular transmitter homeostasis, the role of both neuronal and glial components of excitatory synapses must be considered, if one hopes to take advantage of glia-neuronal communication knowledge to better understand the pathophysiology of striatal processing in parkinsonism, and develop new PD

  20. Real-time parallel processing of grammatical structure in the fronto-striatal system: a recurrent network simulation study using reservoir computing.

    Science.gov (United States)

    Hinaut, Xavier; Dominey, Peter Ford

    2013-01-01

    Sentence processing takes place in real-time. Previous words in the sentence can influence the processing of the current word in the timescale of hundreds of milliseconds. Recent neurophysiological studies in humans suggest that the fronto-striatal system (frontal cortex, and striatum--the major input locus of the basal ganglia) plays a crucial role in this process. The current research provides a possible explanation of how certain aspects of this real-time processing can occur, based on the dynamics of recurrent cortical networks, and plasticity in the cortico-striatal system. We simulate prefrontal area BA47 as a recurrent network that receives on-line input about word categories during sentence processing, with plastic connections between cortex and striatum. We exploit the homology between the cortico-striatal system and reservoir computing, where recurrent frontal cortical networks are the reservoir, and plastic cortico-striatal synapses are the readout. The system is trained on sentence-meaning pairs, where meaning is coded as activation in the striatum corresponding to the roles that different nouns and verbs play in the sentences. The model learns an extended set of grammatical constructions, and demonstrates the ability to generalize to novel constructions. It demonstrates how early in the sentence, a parallel set of predictions are made concerning the meaning, which are then confirmed or updated as the processing of the input sentence proceeds. It demonstrates how on-line responses to words are influenced by previous words in the sentence, and by previous sentences in the discourse, providing new insight into the neurophysiology of the P600 ERP scalp response to grammatical complexity. This demonstrates that a recurrent neural network can decode grammatical structure from sentences in real-time in order to generate a predictive representation of the meaning of the sentences. This can provide insight into the underlying mechanisms of human cortico-striatal

  1. Molecular substrates of action control in cortico-striatal circuits.

    Science.gov (United States)

    Shiflett, Michael W; Balleine, Bernard W

    2011-09-15

    The purpose of this review is to describe the molecular mechanisms in the striatum that mediate reward-based learning and action control during instrumental conditioning. Experiments assessing the neural bases of instrumental conditioning have uncovered functional circuits in the striatum, including dorsal and ventral striatal sub-regions, involved in action-outcome learning, stimulus-response learning, and the motivational control of action by reward-associated cues. Integration of dopamine (DA) and glutamate neurotransmission within these striatal sub-regions is hypothesized to enable learning and action control through its role in shaping synaptic plasticity and cellular excitability. The extracellular signal regulated kinase (ERK) appears to be particularly important for reward-based learning and action control due to its sensitivity to combined DA and glutamate receptor activation and its involvement in a range of cellular functions. ERK activation in striatal neurons is proposed to have a dual role in both the learning and performance factors that contribute to instrumental conditioning through its regulation of plasticity-related transcription factors and its modulation of intrinsic cellular excitability. Furthermore, perturbation of ERK activation by drugs of abuse may give rise to behavioral disorders such as addiction. Copyright © 2011 Elsevier Ltd. All rights reserved.

  2. Adrenergic receptor-mediated modulation of striatal firing patterns.

    Science.gov (United States)

    Ohta, Hiroyuki; Kohno, Yu; Arake, Masashi; Tamura, Risa; Yukawa, Suguru; Sato, Yoshiaki; Morimoto, Yuji; Nishida, Yasuhiro; Yawo, Hiromu

    2016-11-01

    Although noradrenaline and adrenaline are some of the most important neurotransmitters in the central nervous system, the effects of noradrenergic/adrenergic modulation on the striatum have not been determined. In order to explore the effects of adrenergic receptor (AR) agonists on the striatal firing patterns, we used optogenetic methods which can induce continuous firings. We employed transgenic rats expressing channelrhodopsin-2 (ChR2) in neurons. The medium spiny neuron showed a slow rising depolarization during the 1-s long optogenetic striatal photostimulation and a residual potential with 8.6-s half-life decay after the photostimulation. As a result of the residual potential, five repetitive 1-sec long photostimulations with 20-s onset intervals cumulatively increased the number of spikes. This 'firing increment', possibly relating to the timing control function of the striatum, was used to evaluate the AR modulation. The β-AR agonist isoproterenol decreased the firing increment between the 1st and 5th stimulation cycles, while the α 1 -AR agonist phenylephrine enhanced the firing increment. Isoproterenol and adrenaline increased the early phase (0-0.5s of the photostimulation) firing response. This adrenergic modulation was inhibited by the β-antagonist propranolol. Conversely, phenylephrine and noradrenaline reduced the early phase response. β-ARs and α 1 -ARs work in opposition controlling the striatal firing initiation and the firing increment. Copyright © 2016 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

  3. The role of striatal NMDA receptors in drug addiction.

    Science.gov (United States)

    Ma, Yao-Ying; Cepeda, Carlos; Cui, Cai-Lian

    2009-01-01

    The past decade has witnessed an impressive accumulation of evidence indicating that the excitatory amino acid glutamate and its receptors, in particular the N-methyl-D-aspartate (NMDA) receptor subtype, play an important role in drug addiction. Various lines of research using animal models of drug addiction have demonstrated that drug-induced craving is accompanied by significant upregulation of NR2B subunit expression. Furthermore, selective blockade of NR2B-containing NMDA receptors in the striatum, especially in the nucleus accumbens (NAc) can inhibit drug craving and reinstatement. The purpose of this review is to examine the role of striatal NMDA receptors in drug addiction. After a brief description of glutamatergic innervation and NMDA receptor subunit distribution in the striatum, we discuss potential mechanisms to explain the role of striatal NMDA receptors in drug addiction by elucidating signaling cascades involved in the regulation of subunit expression and redistribution, phosphorylation of receptor subunits, as well as activation of intracellular signals triggered by drug experience. Understanding the mechanisms regulating striatal NMDA receptor changes in drug addiction will provide more specific and rational targets to counteract the deleterious effects of drug addiction.

  4. In vivo neurochemical characterization of clothianidin induced striatal dopamine release.

    Science.gov (United States)

    Faro, L R F; Oliveira, I M; Durán, R; Alfonso, M

    2012-12-16

    Clothianidin (CLO) is a neonicotinoid insecticide with selective action on nicotinic acetylcholine receptors. The aim of this study was to determine the neurochemical basis for CLO-induced striatal dopamine release using the microdialysis technique in freely moving and conscious rats. Intrastriatal administration of CLO (3.5mM), produced an increase in both spontaneous (2462 ± 627% with respect to basal values) and KCl-evoked (4672 ± 706% with respect to basal values) dopamine release. This effect was attenuated in Ca(2+)-free medium, and was prevented in reserpine pre-treated animals or in presence of tetrodotoxin (TTX). To investigate the involvement of dopamine transporter (DAT), the effect of CLO was observed in presence of nomifensine. The coadministration of CLO and nomifensine produced an additive effect on striatal dopamine release. The results suggest that the effect of CLO on striatal dopamine release is predominantly mediated by an exocytotic mechanism, Ca(2+), vesicular and TTX-dependent and not by a mechanism mediated by dopamine transporter. Published by Elsevier Ireland Ltd.

  5. Fractal analysis of striatal dopamine re-uptake sites

    International Nuclear Information System (INIS)

    Kuikka, J.T.; Bergstroem, K.A.; Tiihonen, J.; Raesaenen, P.; Karhu, J.

    1997-01-01

    Spatial variation in regional blood flow, metabolism and receptor density within the brain and in other organs is measurable even with a low spatial resolution technique such as emission tomography. It has been previously shown that the observed variance increases with increasing number of subregions in the organ/tissue studied. This resolution-dependent variance can be described by fractal analysis. We studied striatal dopamine re-uptake sites in 39 healthy volunteers with high-resolution single-photon emission tomography using iodine-123 labelled 2β-carbomethoxy-3β-(4-iodophenyl)tropane ([ 123 I]β-CIT). The mean fractal dimension was 1.15±0.07. The results indicate that regional striatal dopamine re-uptake sites involve considerable spatial heterogeneity which is higher than the uniform density (dimension=1.00) but much lower than complete randomness (dimension=1.50). There was a gender difference, with females having a higher heterogeneity in both the left and the right striatum. In addition, we found striatal asymmetry (left-to-right heterogeneity ratio of 1.19±0.15; P<0.001), suggesting functional hemispheric lateralization consistent with the control of motor behaviour and integrative functions. (orig.). With 5 figs., 1 tab

  6. Fractal analysis of striatal dopamine re-uptake sites

    Energy Technology Data Exchange (ETDEWEB)

    Kuikka, J.T.; Bergstroem, K.A. [Department of Clinical Physiology, Kuopio University Hospital, Kuopio (Finland); Tiihonen, J.; Raesaenen, P. [Department of Forensic Psychiatry, University of Kuopio and Niuvanniemi Hospital, Kuopio (Finland); Karhu, J. [Department of Clinical Neurophysiology, Kuopio University Hospital, Kuopio (Finland)

    1997-09-01

    Spatial variation in regional blood flow, metabolism and receptor density within the brain and in other organs is measurable even with a low spatial resolution technique such as emission tomography. It has been previously shown that the observed variance increases with increasing number of subregions in the organ/tissue studied. This resolution-dependent variance can be described by fractal analysis. We studied striatal dopamine re-uptake sites in 39 healthy volunteers with high-resolution single-photon emission tomography using iodine-123 labelled 2{beta}-carbomethoxy-3{beta}-(4-iodophenyl)tropane ([{sup 123}I]{beta}-CIT). The mean fractal dimension was 1.15{+-}0.07. The results indicate that regional striatal dopamine re-uptake sites involve considerable spatial heterogeneity which is higher than the uniform density (dimension=1.00) but much lower than complete randomness (dimension=1.50). There was a gender difference, with females having a higher heterogeneity in both the left and the right striatum. In addition, we found striatal asymmetry (left-to-right heterogeneity ratio of 1.19{+-}0.15; P<0.001), suggesting functional hemispheric lateralization consistent with the control of motor behaviour and integrative functions. (orig.). With 5 figs., 1 tab.

  7. Transient and steady-state selection in the striatal microcircuit

    Directory of Open Access Journals (Sweden)

    Adam eTomkins

    2014-01-01

    Full Text Available Although the basal ganglia have been widely studied and implicated in signal processing and action selection, little information is known about the active role the striatal microcircuit plays in action selection in the basal ganglia-thalamo-cortical loops. To address this knowledge gap we use a large scale three dimensional spiking model of the striatum, combined with a rate coded model of the basal ganglia-thalamo-cortical loop, to asses the computational role the striatum plays in action selection. We identify a robust transient phenomena generated by the striatal microcircuit, which temporarily enhances the difference between two competing cortical inputs. We show that this transient is sufficient to modulate decision making in the basal ganglia-thalamo-cortical circuit. We also find that the transient selection originates from a novel adaptation effect in single striatal projection neurons, which is amenable to experimental testing. Finally, we compared transient selection with models implementing classical steady-state selection. We challenged both forms of model to account for recent reports of paradoxically enhanced response selection in Huntington's Disease patients. We found that steady-state selection was uniformly impaired under all simulated Huntington's conditions, but transient selection was enhanced given a sufficient Huntington's-like increase in NMDA receptor sensitivity. Thus our models provide an intriguing hypothesis for the mechanisms underlying the paradoxical cognitive improvements in manifest Huntington's patients.

  8. [3H]Dopamine accumulation and release from striatal slices in young, mature and senescent rats

    International Nuclear Information System (INIS)

    Thompson, J.M.

    1981-01-01

    Examinations of [ 3 H]dopamine ([ 3 H]DA) release following KCl or amphetamine administration in striatal slices from young (7 month), mature (12 month) and senescent (24 month) Wistar rats showed no age-related changes. Further, the amount of [ 3 H]DA accumulated in the striatal slices showed no changes with age. Thus, previously reported age-related deficits in motor behavior (i.e. rotational) are not produced by changes in striatal DA accumulation or release. (Auth.)

  9. Adversity in childhood linked to elevated striatal dopamine function in adulthood

    OpenAIRE

    Egerton, A.; Valmaggia, L. R.; Howes, O. D.; Day, F.; Chaddock, C. A.; Allen, P.; Winton-Brown, T. T.; Bloomfield, M. A. P.; Bhattacharyya, S.; Chilcott, J.; Lappin, J. M.; Murray, R. M.; McGuire, P.

    2016-01-01

    Childhood adversity increases the risk of psychosis in adulthood. Theoretical and animal models suggest that this effect may be mediated by increased striatal dopamine neurotransmission. The primary objective of this study was to examine the relationship between adversity in childhood and striatal dopamine function in early adulthood. Secondary objectives were to compare exposure to childhood adversity and striatal dopamine function in young people at ultra high risk (UHR) of psychosis and he...

  10. Striatal fast-spiking interneurons selectively modulate circuit output and are required for habitual behavior.

    Science.gov (United States)

    O'Hare, Justin K; Li, Haofang; Kim, Namsoo; Gaidis, Erin; Ade, Kristen; Beck, Jeff; Yin, Henry; Calakos, Nicole

    2017-09-05

    Habit formation is a behavioral adaptation that automates routine actions. Habitual behavior correlates with broad reconfigurations of dorsolateral striatal (DLS) circuit properties that increase gain and shift pathway timing. The mechanism(s) for these circuit adaptations are unknown and could be responsible for habitual behavior. Here we find that a single class of interneuron, fast-spiking interneurons (FSIs), modulates all of these habit-predictive properties. Consistent with a role in habits, FSIs are more excitable in habitual mice compared to goal-directed and acute chemogenetic inhibition of FSIs in DLS prevents the expression of habitual lever pressing. In vivo recordings further reveal a previously unappreciated selective modulation of SPNs based on their firing patterns; FSIs inhibit most SPNs but paradoxically promote the activity of a subset displaying high fractions of gamma-frequency spiking. These results establish a microcircuit mechanism for habits and provide a new example of how interneurons mediate experience-dependent behavior.

  11. Learning time-dependent noise to reduce logical errors: real time error rate estimation in quantum error correction

    Science.gov (United States)

    Huo, Ming-Xia; Li, Ying

    2017-12-01

    Quantum error correction is important to quantum information processing, which allows us to reliably process information encoded in quantum error correction codes. Efficient quantum error correction benefits from the knowledge of error rates. We propose a protocol for monitoring error rates in real time without interrupting the quantum error correction. Any adaptation of the quantum error correction code or its implementation circuit is not required. The protocol can be directly applied to the most advanced quantum error correction techniques, e.g. surface code. A Gaussian processes algorithm is used to estimate and predict error rates based on error correction data in the past. We find that using these estimated error rates, the probability of error correction failures can be significantly reduced by a factor increasing with the code distance.

  12. The U.S. Navy's Global Wind-Wave Models: An Investigation into Sources of Errors in Low-Frequency Energy Predictions

    National Research Council Canada - National Science Library

    Rogers, W

    2002-01-01

    This report describes an investigation to determine the relative importance of various sources of error in the two global-scale models of wind-generated surface waves used operationally by the U.S. Navy...

  13. Impaired striatal Akt signaling disrupts dopamine homeostasis and increases feeding.

    Directory of Open Access Journals (Sweden)

    Nicole Speed

    Full Text Available The prevalence of obesity has increased dramatically worldwide. The obesity epidemic begs for novel concepts and therapeutic targets that cohesively address "food-abuse" disorders. We demonstrate a molecular link between impairment of a central kinase (Akt involved in insulin signaling induced by exposure to a high-fat (HF diet and dysregulation of higher order circuitry involved in feeding. Dopamine (DA rich brain structures, such as striatum, provide motivation stimuli for feeding. In these central circuitries, DA dysfunction is posited to contribute to obesity pathogenesis. We identified a mechanistic link between metabolic dysregulation and the maladaptive behaviors that potentiate weight gain. Insulin, a hormone in the periphery, also acts centrally to regulate both homeostatic and reward-based HF feeding. It regulates DA homeostasis, in part, by controlling a key element in DA clearance, the DA transporter (DAT. Upon HF feeding, nigro-striatal neurons rapidly develop insulin signaling deficiencies, causing increased HF calorie intake.We show that consumption of fat-rich food impairs striatal activation of the insulin-activated signaling kinase, Akt. HF-induced Akt impairment, in turn, reduces DAT cell surface expression and function, thereby decreasing DA homeostasis and amphetamine (AMPH-induced DA efflux. In addition, HF-mediated dysregulation of Akt signaling impairs DA-related behaviors such as (AMPH-induced locomotion and increased caloric intake. We restored nigro-striatal Akt phosphorylation using recombinant viral vector expression technology. We observed a rescue of DAT expression in HF fed rats, which was associated with a return of locomotor responses to AMPH and normalization of HF diet-induced hyperphagia.Acquired disruption of brain insulin action may confer risk for and/or underlie "food-abuse" disorders and the recalcitrance of obesity. This molecular model, thus, explains how even short-term exposure to "the fast food

  14. Neuroinflammation alters voltage-dependent conductance in striatal astrocytes.

    Science.gov (United States)

    Karpuk, Nikolay; Burkovetskaya, Maria; Kielian, Tammy

    2012-07-01

    Neuroinflammation has the capacity to alter normal central nervous system (CNS) homeostasis and function. The objective of the present study was to examine the effects of an inflammatory milieu on the electrophysiological properties of striatal astrocyte subpopulations with a mouse bacterial brain abscess model. Whole cell patch-clamp recordings were performed in striatal glial fibrillary acidic protein (GFAP)-green fluorescent protein (GFP)(+) astrocytes neighboring abscesses at postinfection days 3 or 7 in adult mice. Cell input conductance (G(i)) measurements spanning a membrane potential (V(m)) surrounding resting membrane potential (RMP) revealed two prevalent astrocyte subsets. A1 and A2 astrocytes were identified by negative and positive G(i) increments vs. V(m), respectively. A1 and A2 astrocytes displayed significantly different RMP, G(i), and cell membrane capacitance that were influenced by both time after bacterial exposure and astrocyte proximity to the inflammatory site. Specifically, the percentage of A1 astrocytes was decreased immediately surrounding the inflammatory lesion, whereas A2 cells were increased. These changes were particularly evident at postinfection day 7, revealing increased cell numbers with an outward current component. Furthermore, RMP was inversely modified in A1 and A2 astrocytes during neuroinflammation, and resting G(i) was increased from 21 to 30 nS in the latter. In contrast, gap junction communication was significantly decreased in all astrocyte populations associated with inflamed tissues. Collectively, these findings demonstrate the heterogeneity of striatal astrocyte populations, which experience distinct electrophysiological modifications in response to CNS inflammation.

  15. HIV infection results in ventral-striatal reward system hypo-activation during cue processing

    NARCIS (Netherlands)

    Plessis, Stéfan du; Vink, Matthijs; Joska, John A; Koutsilieri, Eleni; Bagadia, Asif; Stein, Dan J; Emsley, Robin

    2015-01-01

    OBJECTIVE: Functional MRI has thus far demonstrated that HIV has an impact on frontal-striatal systems involved in executive functioning. The potential impact of HIV on frontal-striatal systems involved in reward processing has yet to be examined by functional MRI. This study therefore aims to

  16. Fronto-striatal atrophy correlates of neuropsychiatric dysfunction in frontotemporal dementia (FTD and Alzheimer's disease (AD

    Directory of Open Access Journals (Sweden)

    Dong Seok Yi

    Full Text Available ABSTRACT Behavioural disturbances in frontotemporal dementia (FTD are thought to reflect mainly atrophy of cortical regions. Recent studies suggest that subcortical brain regions, in particular the striatum, are also significantly affected and this pathology might play a role in the generation of behavioural symptoms. Objective: To investigate prefrontal cortical and striatal atrophy contributions to behavioural symptoms in FTD. Methods: One hundred and eighty-two participants (87 FTD patients, 39 AD patients and 56 controls were included. Behavioural profiles were established using the Cambridge Behavioural Inventory Revised (CBI-R and Frontal System Behaviour Scale (FrSBe. Atrophy in prefrontal (VMPFC, DLPFC and striatal (caudate, putamen regions was established via a 5-point visual rating scale of the MRI scans. Behavioural scores were correlated with atrophy rating scores. Results: Behavioural and atrophy ratings demonstrated that patients were significantly impaired compared to controls, with bvFTD being most severely affected. Behavioural-anatomical correlations revealed that VMPFC atrophy was closely related to abnormal behaviour and motivation disturbances. Stereotypical behaviours were associated with both VMPFC and striatal atrophy. By contrast, disturbance of eating was found to be related to striatal atrophy only. Conclusion: Frontal and striatal atrophy contributed to the behavioural disturbances seen in FTD, with some behaviours related to frontal, striatal or combined fronto-striatal pathology. Consideration of striatal contributions to the generation of behavioural disturbances should be taken into account when assessing patients with potential FTD.

  17. Medication Errors - A Review

    OpenAIRE

    Vinay BC; Nikhitha MK; Patel Sunil B

    2015-01-01

    In this present review article, regarding medication errors its definition, medication error problem, types of medication errors, common causes of medication errors, monitoring medication errors, consequences of medication errors, prevention of medication error and managing medication errors have been explained neatly and legibly with proper tables which is easy to understand.

  18. Error Covariance Estimation of Mesoscale Data Assimilation

    National Research Council Canada - National Science Library

    Xu, Qin

    2005-01-01

    The goal of this project is to explore and develop new methods of error covariance estimation that will provide necessary statistical descriptions of prediction and observation errors for mesoscale data assimilation...

  19. Quantification and handling of sampling errors in instrumental measurements: a case study

    DEFF Research Database (Denmark)

    Andersen, Charlotte Møller; Bro, R.

    2004-01-01

    in certain situations, the effect of systematic errors is also considerable. The relevant errors contributing to the prediction error are: error in instrumental measurements (x-error), error in reference measurements (y-error), error in the estimated calibration model (regression coefficient error) and model...

  20. Adenosine Receptor Heteromers and their Integrative Role in Striatal Function

    Directory of Open Access Journals (Sweden)

    Sergi Ferré

    2007-01-01

    Full Text Available By analyzing the functional role of adenosine receptor heteromers, we review a series of new concepts that should modify our classical views of neurotransmission in the central nervous system (CNS. Neurotransmitter receptors cannot be considered as single functional units anymore. Heteromerization of neurotransmitter receptors confers functional entities that possess different biochemical characteristics with respect to the individual components of the heteromer. Some of these characteristics can be used as a “biochemical fingerprint” to identify neurotransmitter receptor heteromers in the CNS. This is exemplified by changes in binding characteristics that are dependent on coactivation of the receptor units of different adenosine receptor heteromers. Neurotransmitter receptor heteromers can act as “processors” of computations that modulate cell signaling, sometimes critically involved in the control of pre- and postsynaptic neurotransmission. For instance, the adenosine A1-A2A receptor heteromer acts as a concentration-dependent switch that controls striatal glutamatergic neurotransmission. Neurotransmitter receptor heteromers play a particularly important integrative role in the “local module” (the minimal portion of one or more neurons and/or one or more glial cells that operates as an independent integrative unit, where they act as processors mediating computations that convey information from diverse volume-transmitted signals. For instance, the adenosine A2A-dopamine D2 receptor heteromers work as integrators of two different neurotransmitters in the striatal spine module.

  1. Pyrethroid insecticides evoke neurotransmitter release from rabbit striatal slices

    International Nuclear Information System (INIS)

    Eells, J.T.; Dubocovich, M.L.

    1988-01-01

    The effects of the synthetic pyrethroid insecticide fenvalerate ([R,S]-alpha-cyano-3-phenoxybenzyl[R,S]-2-(4-chlorophenyl)-3- methylbutyrate) on neurotransmitter release in rabbit brain slices were investigated. Fenvalerate evoked a calcium-dependent release of [ 3 H]dopamine and [ 3 H]acetylcholine from rabbit striatal slices that was concentration-dependent and specific for the toxic stereoisomer of the insecticide. The release of [ 3 H]dopamine and [ 3 H]acetylcholine by fenvalerate was modulated by D2 dopamine receptor activation and antagonized completely by the sodium channel blocker, tetrodotoxin. These findings are consistent with an action of fenvalerate on the voltage-dependent sodium channels of the presynaptic membrane resulting in membrane depolarization, and the release of dopamine and acetylcholine by a calcium-dependent exocytotic process. In contrast to results obtained in striatal slices, fenvalerate did not elicit the release of [ 3 H]norepinephrine or [ 3 H]acetylcholine from rabbit hippocampal slices indicative of regional differences in sensitivity to type II pyrethroid actions

  2. Clock error models for simulation and estimation

    International Nuclear Information System (INIS)

    Meditch, J.S.

    1981-10-01

    Mathematical models for the simulation and estimation of errors in precision oscillators used as time references in satellite navigation systems are developed. The results, based on all currently known oscillator error sources, are directly implementable on a digital computer. The simulation formulation is sufficiently flexible to allow for the inclusion or exclusion of individual error sources as desired. The estimation algorithms, following from Kalman filter theory, provide directly for the error analysis of clock errors in both filtering and prediction

  3. Error Budgeting

    Energy Technology Data Exchange (ETDEWEB)

    Vinyard, Natalia Sergeevna [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Perry, Theodore Sonne [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Usov, Igor Olegovich [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-10-04

    We calculate opacity from k (hn)=-ln[T(hv)]/pL, where T(hv) is the transmission for photon energy hv, p is sample density, and L is path length through the sample. The density and path length are measured together by Rutherford backscatter. Δk = $\\partial k$\\ $\\partial T$ ΔT + $\\partial k$\\ $\\partial (pL)$. We can re-write this in terms of fractional error as Δk/k = Δ1n(T)/T + Δ(pL)/(pL). Transmission itself is calculated from T=(U-E)/(V-E)=B/B0, where B is transmitted backlighter (BL) signal and B0 is unattenuated backlighter signal. Then ΔT/T=Δln(T)=ΔB/B+ΔB0/B0, and consequently Δk/k = 1/T (ΔB/B + ΔB$_0$/B$_0$ + Δ(pL)/(pL). Transmission is measured in the range of 0.2

  4. Measurement of striatal dopamine metabolism with 6-[18F]-fluoro-L-dopa and PET

    International Nuclear Information System (INIS)

    Kuwabara, Y.; Otsuka, M.; Ichiya, Y.; Yoshikai, T.; Fukumura, T.; Masuda, K.; Kato, M.; Taniwaki, T.

    1992-01-01

    Striatal dopamine metabolism was studied with 6-[ 18 F]-fluoro-L-dopa ( 18 F-DOPA) and PET. The subjects were normal controls, and patients with Parkinson's disease (PD), parkinsonism, multiple system atrophy (MSA), progressive supranuclear palsy (PSP), Alzheimer's disease (AD), Huntington's disease (HD) and other cerebral disorders. Cerebral glucose metabolism (CMRGlc) was also measured in these patients. Striatal dopamine metabolism was evaluated by the relative striatal uptake of 18 F-DOPA referring cerebellum (S/C ratio). In normal controls, the S/C ratio was 2.82 ± 0.32 (n = 6, mean ± SD) at 120 min after injection of 18 F-DOPA. The S/C ratio was low in patients with PD, parkinsonism, MSA and PSP compared to the normal controls and thus coincident with the symptoms of parkinsonism due to decrease in striatal dopamine concentration. The decrease in the striatal CMRGlc was also observed in patients with parkinsonism and PSP, and it was preserved in patients with PD, thus representing that more neurons were damaged in patients with parkinsonism and PSP than in patients with PD. A patient with AD having symptoms of parkinsonism also showed a decrease in S/C ratio. In a patient with HD, the striatal CMRGlc sharply decreased, but the S/C ratio was normal. The measurements of striatal dopamine and glucose metabolism with PET may be useful for studying the pathophysiological mechanism in patients with cerebral disorders. (author)

  5. Evaluation of errors and limits of the 63-μm house-dust-fraction method, a surrogate to predict hidden moisture damage

    Directory of Open Access Journals (Sweden)

    Assadian Ojan

    2009-10-01

    Full Text Available Abstract Background The aim of this study is to analyze possible random and systematic measurement errors and to detect methodological limits of the previously established method. Findings To examine the distribution of random errors (repeatability standard deviation of the detection procedure, collective samples were taken from two uncontaminated rooms using a sampling vacuum cleaner, and 10 sub-samples each were examined with 3 parallel cultivation plates (DG18. In this two collective samples of new dust, the total counts of Aspergillus spp. varied moderately by 25 and 29% (both 9 cfu per plate. At an average of 28 cfu/plate, the total number varied only by 13%. For the evaluation of the influence of old dust, old and fresh dust samples were examined. In both cases with old dust, the old dust influenced the results indicating false positive results, where hidden moist was indicated but was not present. To quantify the influence of sand and sieving, 13 sites were sampled in parallel using the 63-μm- and total dust collection approaches. Sieving to 63-μm resulted in a more then 10-fold enrichment, due to the different quantity of inert sand in each total dust sample. Conclusion The major errors during the quantitative evaluation from house dust samples for mould fungi as reference values for assessment resulted from missing filtration, contamination with old dust and the massive influence of soil. If the assessment is guided by indicator genera, the percentage standard deviation lies in a moderate range.

  6. Model-based mean square error estimators for k-nearest neighbour predictions and applications using remotely sensed data for forest inventories

    Science.gov (United States)

    Steen Magnussen; Ronald E. McRoberts; Erkki O. Tomppo

    2009-01-01

    New model-based estimators of the uncertainty of pixel-level and areal k-nearest neighbour (knn) predictions of attribute Y from remotely-sensed ancillary data X are presented. Non-parametric functions predict Y from scalar 'Single Index Model' transformations of X. Variance functions generated...

  7. Striatal dopamine release induced by repetitive transcranial magnetic stimulation over dorsolateral prefrontal cortex: effect of aging

    International Nuclear Information System (INIS)

    Bang, Seong Ae; Cho, Sang Soo; Yoon, Eun Jin; Kim, Ji Sun; Lee, Byung Chul; Kim, Yu Kyeong; Kim, Sang Eun

    2007-01-01

    We previously demonstrated dopamine (DA) release in the bilateral striatal regions following prefrontal repetitive transcranial magnetic stimulation (rTMS) in young subjects. Several lines of evidence support substantial age-related changes in human dopaminergic neurotransmission. One possible explanation is alteration of cortico striatal neural connection with aging. Therefore, we investigated how frontal activation by rTMS influences striatal DA release in the elderly with SPECT measurements of striatal binding of [123I]iodobenzamide (lBZM), a DA D2 receptor radioligand that is sensitive to endogenous DA. Five healthy elderly male subjects (age, 64 3 y) were studied with brain [123I]IBZM SPECT under three conditions (resting, sham stimulation, and active rTMS over left dorsolateral prefrontal cortex (DLPFC)), while receiving a bolus plus constant infusion of [123I]IBZM. rTMS session consisted of three blocks. In each block, 15 trains of 2 sec duration were delivered with 10 Hz stimulation frequency and 100% motor threshold. Striatal V3', calculated as (striatal - occipital)/occipital radioactivity, was measured under equilibrium condition at baseline and after sham and active rTMS. Sham stimulation did not affect striatal V3'. rTMS over left DLPFC induced no significant change in V3' in the right striatum compared with baseline condition (0.91 0.25 vs. 0.96 0.25, P = NS). Interestingly, left striatal V3' showed a significant increase after rTMS over left DLPFC compared with sham condition (1.09 0.33 vs. 0.93 0.27, P < 0.05; 17.0 11.1% increase). These results are discrepant from previous ones from young subjects, who showed frontal rTMS-induced reduction of striatal V3', indicating rTMS-induced striatal DA release. We found no significant striatal DA release induced by rTMS over DLPFC in healthy elderly subjects using in vivo binding competition techniques. These results may support an altered cortico striatal circuit in normal aging

  8. Striatal dopamine release induced by repetitive transcranial magnetic stimulation over dorsolateral prefrontal cortex: effect of aging

    Energy Technology Data Exchange (ETDEWEB)

    Bang, Seong Ae; Cho, Sang Soo; Yoon, Eun Jin; Kim, Ji Sun; Lee, Byung Chul; Kim, Yu Kyeong; Kim, Sang Eun [Seoul National Univ. College of Medicine, Seoul (Korea, Republic of)

    2007-07-01

    We previously demonstrated dopamine (DA) release in the bilateral striatal regions following prefrontal repetitive transcranial magnetic stimulation (rTMS) in young subjects. Several lines of evidence support substantial age-related changes in human dopaminergic neurotransmission. One possible explanation is alteration of cortico striatal neural connection with aging. Therefore, we investigated how frontal activation by rTMS influences striatal DA release in the elderly with SPECT measurements of striatal binding of [123I]iodobenzamide (lBZM), a DA D2 receptor radioligand that is sensitive to endogenous DA. Five healthy elderly male subjects (age, 64 3 y) were studied with brain [123I]IBZM SPECT under three conditions (resting, sham stimulation, and active rTMS over left dorsolateral prefrontal cortex (DLPFC)), while receiving a bolus plus constant infusion of [123I]IBZM. rTMS session consisted of three blocks. In each block, 15 trains of 2 sec duration were delivered with 10 Hz stimulation frequency and 100% motor threshold. Striatal V3', calculated as (striatal - occipital)/occipital radioactivity, was measured under equilibrium condition at baseline and after sham and active rTMS. Sham stimulation did not affect striatal V3'. rTMS over left DLPFC induced no significant change in V3' in the right striatum compared with baseline condition (0.91 0.25 vs. 0.96 0.25, P = NS). Interestingly, left striatal V3' showed a significant increase after rTMS over left DLPFC compared with sham condition (1.09 0.33 vs. 0.93 0.27, P < 0.05; 17.0 11.1% increase). These results are discrepant from previous ones from young subjects, who showed frontal rTMS-induced reduction of striatal V3', indicating rTMS-induced striatal DA release. We found no significant striatal DA release induced by rTMS over DLPFC in healthy elderly subjects using in vivo binding competition techniques. These results may support an altered cortico striatal circuit in normal aging.

  9. Ventral striatal activity links adversity and reward processing in children.

    Science.gov (United States)

    Kamkar, Niki H; Lewis, Daniel J; van den Bos, Wouter; Morton, J Bruce

    2017-08-01

    Adversity impacts many aspects of psychological and physical development including reward-based learning and decision-making. Mechanisms relating adversity and reward processing in children, however, remain unclear. Here, we show that adversity is associated with potentiated learning from positive outcomes and impulsive decision-making, but unrelated to learning from negative outcomes. We then show via functional magnetic resonance imaging that the link between adversity and reward processing is partially mediated by differences in ventral striatal response to rewards. The findings suggest that early-life adversity is associated with alterations in the brain's sensitivity to rewards accounting, in part, for the link between adversity and altered reward processing in children. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  10. Striatal activation reflects urgency in perceptual decision making.

    Science.gov (United States)

    van Maanen, Leendert; Fontanesi, Laura; Hawkins, Guy E; Forstmann, Birte U

    2016-10-01

    Deciding between multiple courses of action often entails an increasing need to do something as time passes - a sense of urgency. This notion of urgency is not incorporated in standard theories of speeded decision making that assume information is accumulated until a critical fixed threshold is reached. Yet, it is hypothesized in novel theoretical models of decision making. In two experiments, we investigated the behavioral and neural evidence for an "urgency signal" in human perceptual decision making. Experiment 1 found that as the duration of the decision making process increased, participants made a choice based on less evidence for the selected option. Experiment 2 replicated this finding, and additionally found that variability in this effect across participants covaried with activation in the striatum. We conclude that individual differences in susceptibility to urgency are reflected by striatal activation. By dynamically updating a response threshold, the striatum is involved in signaling urgency in humans. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Regulation of drugs affecting striatal cholinergic activity by corticostriatal projections

    International Nuclear Information System (INIS)

    Ladinsky, H.

    1986-01-01

    Research demonstrates that the chronic degeneration of the corticostriatal excitatory pathway makes the cholinergic neurons of the striatum insensitive to the neuropharmacological action of a number of different drugs. Female rats were used; they were killed and after the i.v. infusion of tritium-choline precursor, choline acetyltransferase activity was measured. Striatal noradrenaline, dopamine and serotonin content was measured by electrochemical detection coupled with high pressure liquid chromatography. Uptake of tritium-glutamic acid was estimated. The data were analyzed statistically. It is shown that there is evidence that the effects of a number of drugs capable of depressing cholinergic activity through receptor-mediated responses are operative only if the corticostriatal pathway is integral. Neuropharmacological responses in the brain appear to be the result of an interaction between several major neurotransmitter systems

  12. Ventral striatal activity links adversity and reward processing in children

    Directory of Open Access Journals (Sweden)

    Niki H. Kamkar

    2017-08-01

    Full Text Available Adversity impacts many aspects of psychological and physical development including reward-based learning and decision-making. Mechanisms relating adversity and reward processing in children, however, remain unclear. Here, we show that adversity is associated with potentiated learning from positive outcomes and impulsive decision-making, but unrelated to learning from negative outcomes. We then show via functional magnetic resonance imaging that the link between adversity and reward processing is partially mediated by differences in ventral striatal response to rewards. The findings suggest that early-life adversity is associated with alterations in the brain’s sensitivity to rewards accounting, in part, for the link between adversity and altered reward processing in children.

  13. Association Between Peripheral Inflammation and DATSCAN Data of the Striatal Nuclei in Different Motor Subtypes of Parkinson Disease

    Directory of Open Access Journals (Sweden)

    Hossein Sanjari Moghaddam

    2018-04-01

    Full Text Available The interplay between peripheral and central inflammation has a significant role in dopaminergic neural death in nigrostriatal pathway, although no direct assessment of inflammation has been performed in relation to dopaminergic neuronal loss in striatal nuclei. In this study, the correlation of neutrophil to lymphocyte ratio (NLR as a marker of peripheral inflammation to striatal binding ratios (SBRs of DAT SPECT images in bilateral caudate and putamen nuclei was calculated in 388 drug-naïve early PD patients [288 tremor dominant (TD, 73 postural instability and gait difficulty (PIGD, and 27 indeterminate] and 148 controls. NLR was significantly higher in PD patients than in age- and sex-matched healthy controls, and showed a negative correlation to SBR in bilateral putamen and ipsilateral caudate in all PD subjects. Among our three subgroups, only TD patients showed remarkable results. A positive association between NLR and motor severity was observed in TD subgroup. Besides, NLR could negatively predict the SBR in ipsilateral and contralateral putamen and caudate nuclei in tremulous phenotype. Nonetheless, we found no significant association between NLR and other clinical and imaging findings in PIGD and indeterminate subgroups, supporting the presence of distinct underlying pathologic mechanisms between tremor and non-tremor predominant PD at early stages of the disease.

  14. Speech-induced striatal dopamine release is left lateralized and coupled to functional striatal circuits in healthy humans: A combined PET, fMRI and DTI study

    Science.gov (United States)

    Simonyan, Kristina; Herscovitch, Peter; Horwitz, Barry

    2013-01-01

    Considerable progress has been recently made in understanding the brain mechanisms underlying speech and language control. However, the neurochemical underpinnings of normal speech production remain largely unknown. We investigated the extent of striatal endogenous dopamine release and its influences on the organization of functional striatal speech networks during production of meaningful English sentences using a combination of positron emission tomography (PET) with the dopamine D2/D3 receptor radioligand [11C]raclopride and functional MRI (fMRI). In addition, we used diffusion tensor tractography (DTI) to examine the extent of dopaminergic modulatory influences on striatal structural network organization. We found that, during sentence production, endogenous dopamine was released in the ventromedial portion of the dorsal striatum, in its both associative and sensorimotor functional divisions. In the associative striatum, speech-induced dopamine release established a significant relationship with neural activity and influenced the left-hemispheric lateralization of striatal functional networks. In contrast, there were no significant effects of endogenous dopamine release on the lateralization of striatal structural networks. Our data provide the first evidence for endogenous dopamine release in the dorsal striatum during normal speaking and point to the possible mechanisms behind the modulatory influences of dopamine on the organization of functional brain circuits controlling normal human speech. PMID:23277111

  15. Ability of 18F-DOPA PET/CT and fused 18F-DOPA PET/MRI to assess striatal involvement in paediatric glioma

    International Nuclear Information System (INIS)

    Morana, Giovanni; Severino, Mariasavina; Tortora, Domenico; Rossi, Andrea; Puntoni, Matteo; Garre, Maria Luisa; Massollo, Michela; Naseri, Merhdad; Piccardo, Arnoldo; Lopci, Egesta

    2016-01-01

    To assess the diagnostic performance of 18 F-DOPA PET/CT and fused 18 F-DOPA PET/MRI in detecting striatal involvement in children with gliomas. This retrospective study included 28 paediatric patients referred to our institution for the presence of primary, residual or recurrent glioma (12 boys, 16 girls; mean age 10.7 years) and investigated with 18 F-DOPA PET/CT and brain MRI. Fused 18 F-DOPA PET/MR images were obtained and compared with PET/CT and MRI images. Accuracy, sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV) for striatal involvement were calculated for each diagnostic tool. Univariate and multivariate logistic analyses were applied to evaluate the associations between 18 F-DOPA PET/CT and fused 18 F-DOPA PET/MRI diagnostic results and tumour uptake outside the striatum, grade, dimension and site of striatal involvement (ventral and/or dorsal). Accuracy, sensitivity, specificity, PPV, and NPV were 100 % for MRI, 93 %, 89 %, 100 %, 100 % and 82 % for 18 F-DOPA PET/MRI, and 75 %, 74 %, 78 %, 88 % and 58 % for 18 F-DOPA PET/CT, respectively. 18 F-DOPA PET/MRI showed a trend towards higher accuracy compared with 18 F-DOPA PET/CT (p = 0.06). MRI showed significantly higher accuracy compared with 18 F-DOPA PET/CT (p = 0.01), but there was no significant difference between MRI and 18 F-DOPA PET/MRI. Both univariate and multivariate logistic analyses showed a significant association (OR 8.0 and 7.7, respectively) between the tumour-to-normal striatal uptake (T/S) ratio and the diagnostic ability of 18 F-DOPA PET/CT (p = 0.03). A strong significant association was also found between involvement of the dorsal striatum and the 18 F-DOPA PET/CT results (p = 0.001), with a perfect prediction of involvement of the dorsal striatum by 18 F-DOPA PET/MRI. Physiological striatal 18 F-DOPA uptake does not appear to be a main limitation in the evaluation of basal ganglia involvement. 18 F-DOPA PET/CT correctly detected

  16. Behavioural inflexibility in a comorbid rat model of striatal ischemic injury and mutant hAPP overexpression.

    Science.gov (United States)

    Levit, Alexander; Regis, Aaron M; Garabon, Jessica R; Oh, Seung-Hun; Desai, Sagar J; Rajakumar, Nagalingam; Hachinski, Vladimir; Agca, Yuksel; Agca, Cansu; Whitehead, Shawn N; Allman, Brian L

    2017-08-30

    Alzheimer disease (AD) and stroke coexist and interact; yet how they interact is not sufficiently understood. Both AD and basal ganglia stroke can impair behavioural flexibility, which can be reliably modeled in rats using an established operant based set-shifting test. Transgenic Fischer 344-APP21 rats (TgF344) overexpress pathogenic human amyloid precursor protein (hAPP) but do not spontaneously develop overt pathology, hence TgF344 rats can be used to model the effect of vascular injury in the prodromal stages of Alzheimer disease. We demonstrate that the injection of endothelin-1 (ET1) into the dorsal striatum of TgF344 rats (Tg-ET1) produced an exacerbation of behavioural inflexibility with a behavioural phenotype that was distinct from saline-injected wildtype & TgF344 rats as well as ET1-injected wildtype rats (Wt-ET1). In addition to profiling the types of errors made, interpolative modeling using logistic exposure-response regression provided an informative analysis of the timing and efficiency of behavioural flexibility. During set-shifting, Tg-ET1 committed fewer perseverative errors than Wt-ET1. However, Tg-ET1 committed significantly more regressive errors and had a less efficient strategy change than all other groups. Thus, behavioural flexibility was more vulnerable to striatal ischemic injury in TgF344 rats. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Value of dual biometry in the detection and investigation of error in the preoperative prediction of refractive status following cataract surgery.

    LENUS (Irish Health Repository)

    Charalampidou, Sofia

    2012-02-01

    PURPOSE: To report the value of dual biometry in the detection of biometry errors. METHODS: Study 1: retrospective study of 224 consecutive cataract operations. The intraocular lens power calculation was based on immersion biometry. Study 2: immersion biometry was compared with optical coherence biometry (OCB) in terms of axial length, anterior chamber depth, keratometry readings and the recommended lens power to achieve emmetropia. Study 3: prospective study of 61 consecutive cataract operations. Both immersion and OCB were performed, but lens power calculation was based on the latter. RESULTS: Study 1: 115 (86%), 101 (75.4%), 90 (67.2%) and 50 (37.3%) of postoperative spherical equivalents were within +\\/-1.5 dioptres (D), +\\/-1.25 D, +\\/-1 D and +\\/-0.5 D of the target, respectively. Study 2: excellent agreement between axial length readings, anterior chamber depth readings and keratometry readings by immersion biometry and OCB was observed (reflected in a mean bias of -0.065 mm, -0.048 mm and +0.1803 D, respectively, in association with OCB). Agreement between the lens power recommended by each technique to achieve emmetropia was poor (mean bias of +1.16 D in association with OCB), but improved following appropriate modification of lens constants in the Accutome A-scan software (mean bias with OCB = -0.4 D). Study 3: 37 (92.5%) and 23 (57.5%) of operated eyes achieved a postoperative refraction within +\\/-1 D and +\\/-0.5 D of target, respectively. CONCLUSION: Systematic errors in biometry can exist, in the presence of acceptable postoperative refractive results. Dual biometry allows each biometric parameter to be scrutinized in isolation, and identify sources of error that may otherwise go undetected.

  18. Striatal and extra-striatal dopamine transporter in cannabis and tobacco addiction: a high resolution PET study

    International Nuclear Information System (INIS)

    Leroy, C.; Martinot, J.L.; Duchesnay, E.; Artiges, E.; Ribeiro, M.J.; Trichard, Ch.; Karila, L.; Lukasiewicz, M.; Benyamina, A.; Reynaud, M.; Martinot, J.L.; Duchesnay, E.; Artiges, E.; Comtat, C.; Artiges, E.; Trichard, Ch.

    2011-01-01

    The dopamine (DA) system is known to be involved in the reward and dependence mechanisms of addiction. However, modifications in dopaminergic neurotransmission associated with long-term tobacco and cannabis use have been poorly documented in vivo. In order to assess striatal and extra-striatal dopamine transporter (DAT) availability in tobacco and cannabis addiction, three groups of male age-matched subjects were compared: 11 healthy non-smoker subjects, 14 tobacco-dependent smokers (17.6 ± 5.3 cigarettes/day for 12.1 ± 8.5 years) and 13 cannabis and tobacco smokers (CTS) (4.8 ± 5.3 cannabis joints/day for 8.7 ± 3.9 years). DAT availability was examined in positron emission tomography (HRRT) with a high resolution research tomograph after injection of [ 11 C]PE2I, a selective DAT radioligand. Region of interest and voxel-by-voxel approaches using a simplified reference tissue model were performed for the between-group comparison of DAT availability. Measurements in the dorsal striatum from both analyses were concordant and showed a mean 20% lower DAT availability in drug users compared with controls. Whole-brain analysis also revealed lower DAT availability in the ventral striatum, the midbrain, the middle cingulate and the thalamus (ranging from -15 to -30%). The DAT availability was slightly lower in all regions in CTS than in subjects who smoke tobacco only, but the difference does not reach a significant level. These results support the existence of a decrease in DAT availability associated with tobacco and cannabis addictions involving all dopaminergic brain circuits. These findings are consistent with the idea of a global decrease in cerebral DA activity in dependent subjects. (authors)

  19. Statistical errors in Monte Carlo estimates of systematic errors

    Science.gov (United States)

    Roe, Byron P.

    2007-01-01

    For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k2. The specific terms unisim and multisim were coined by Peter Meyers and Steve Brice, respectively, for the MiniBooNE experiment. However, the concepts have been developed over time and have been in general use for some time.

  20. Statistical errors in Monte Carlo estimates of systematic errors

    Energy Technology Data Exchange (ETDEWEB)

    Roe, Byron P. [Department of Physics, University of Michigan, Ann Arbor, MI 48109 (United States)]. E-mail: byronroe@umich.edu

    2007-01-01

    For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k{sup 2}.

  1. Statistical errors in Monte Carlo estimates of systematic errors

    International Nuclear Information System (INIS)

    Roe, Byron P.

    2007-01-01

    For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k 2

  2. Effects of postnatal anoxia on striatal dopamine metabolism and prepulse inhibition in rats

    DEFF Research Database (Denmark)

    Sandager-Nielsen, Karin; Andersen, Maibritt B; Sager, Thomas N

    2004-01-01

    (DOPAC) and homovanillic acid (HVA) concentrations. Furthermore, in the anoxic group only, striatal HVA concentrations were negatively correlated to prefrontal cortical N-acetylaspartate (NAA) levels. Similar findings of distorted prefrontal-subcortical interactions have recently been reported...

  3. Effect of in vitro gamma exposure on rat mesencephalic and striatal cellular types and processes length

    International Nuclear Information System (INIS)

    Coffigny, H.; Court, L.

    1994-01-01

    The isolated mesencephalic and striatal cells were irradiated in a dose-range of 0.25 to 3 Gy followed by 3 day of culture. The proportion of monopolar, bipolar, tripolar and multipolar cell population was not obviously modified by irradiation. The processes length was similar to controls, except after 3 Gy exposure, for monopolar and bipolar mesencephalic cells and the tripolar striatal cells where it was increased. In these populations, only cells with long processes seemed to survive. (author)

  4. Elevated Striatal Dopamine Function in Immigrants and Their Children: A Risk Mechanism for Psychosis

    OpenAIRE

    Egerton, A.; Howes, O. D.; Houle, S.; McKenzie, K.; Valmaggia, L. R.; Bagby, M. R.; Tseng, H-H; Bloomfield, M. A. P.; Kenk, M.; Bhattacharyya, S.; Suridjan, I.; Chaddock, C. A.; Winton-Brown, T. T.; Allen, P.; Rusjan, P.

    2017-01-01

    Migration is a major risk factor for schizophrenia but the neurochemical processes involved are unknown. One candidate mechanism is through elevations in striatal dopamine synthesis and release. The objective of this research was to determine whether striatal dopamine function is elevated in immigrants compared to nonimmigrants and the relationship with psychosis. Two complementary case–control studies of in vivo dopamine function (stress-induced dopamine release and dopamine synthesis capaci...

  5. Opposite Effects of Stimulant and Antipsychotic Drugs on Striatal Fast-Spiking Interneurons

    OpenAIRE

    Wiltschko, Alexander B; Pettibone, Jeffrey R; Berke, Joshua D

    2010-01-01

    Psychomotor stimulants and typical antipsychotic drugs have powerful but opposite effects on mood and behavior, largely through alterations in striatal dopamine signaling. Exactly how these drug actions lead to behavioral change is not well understood, as previous electrophysiological studies have found highly heterogeneous changes in striatal neuron firing. In this study, we examined whether part of this heterogeneity reflects the mixture of distinct cell types present in the striatum, by di...

  6. The pan-Kv7 (KCNQ) Channel Opener Retigabine Inhibits Striatal Excitability by Direct Action on Striatal Neurons In Vivo

    DEFF Research Database (Denmark)

    Hansen, Henrik H; Weikop, Pia; Mikkelsen, Maria D

    2017-01-01

    Central Kv7 (KCNQ) channels are voltage-dependent potassium channels composed of different combinations of four Kv7 subunits, being differently expressed in the brain. Notably, striatal dopaminergic neurotransmission is strongly suppressed by systemic administration of the pan-Kv7 channel opener ...... by acute systemic haloperidol administration in the rat. The relative mRNA levels of Kv7 subunits in the rat striatum were found to be Kv7.2 = Kv7.3 = Kv7.5 > >Kv7.4. These data suggest that intrastriatal Kv7 channels play a direct role in regulating striatal excitability in vivo....

  7. Drifting from Slow to "D'oh!": Working Memory Capacity and Mind Wandering Predict Extreme Reaction Times and Executive Control Errors

    Science.gov (United States)

    McVay, Jennifer C.; Kane, Michael J.

    2012-01-01

    A combined experimental, individual-differences, and thought-sampling study tested the predictions of executive attention (e.g., Engle & Kane, 2004) and coordinative binding (e.g., Oberauer, Suss, Wilhelm, & Sander, 2007) theories of working memory capacity (WMC). We assessed 288 subjects' WMC and their performance and mind-wandering rates…

  8. Drifting from Slow to “D’oh!” Working Memory Capacity and Mind Wandering Predict Extreme Reaction Times and Executive-Control Errors

    Science.gov (United States)

    McVay, Jennifer C.; Kane, Michael J.

    2012-01-01

    A combined experimental, individual-differences, and thought-sampling study tested the predictions of executive attention (e.g., Engle & Kane, 2004) and coordinative binding (e.g., Oberauer, Süß, Wilhelm, & Sander, 2007) theories of working memory capacity (WMC). We assessed 288 subjects’ WMC and their performance and mind-wandering rates during a sustained-attention task; subjects completed either a go/no-go version requiring executive control over habit, or a vigilance version that did not. We further combined the data with those from McVay and Kane (2009) to: (1) gauge the contributions of WMC and attentional lapses to the worst-performance rule and the tail, or τ parameter, of response time (RT) distributions; (2) assess which parameters from a quantitative evidence-accumulation RT model were predicted by WMC and mind-wandering reports, and (3) consider intra-subject RT patterns – particularly, speeding – as potential objective markers of mind wandering. We found that WMC predicted action and thought control in only some conditions, that attentional lapses (indicated by TUT reports and drift-rate variability in evidence accumulation) contributed to τ, performance accuracy, and WMC’s association with them, and that mind-wandering experiences were not predicted by trial-to-trial RT changes, and so they cannot always be inferred from objective performance measures. PMID:22004270

  9. Common Variation in the DOPA Decarboxylase (DDC) Gene and Human Striatal DDC Activity In Vivo.

    Science.gov (United States)

    Eisenberg, Daniel P; Kohn, Philip D; Hegarty, Catherine E; Ianni, Angela M; Kolachana, Bhaskar; Gregory, Michael D; Masdeu, Joseph C; Berman, Karen F

    2016-08-01

    The synthesis of multiple amine neurotransmitters, such as dopamine, norepinephrine, serotonin, and trace amines, relies in part on DOPA decarboxylase (DDC, AADC), an enzyme that is required for normative neural operations. Because rare, loss-of-function mutations in the DDC gene result in severe enzymatic deficiency and devastating autonomic, motor, and cognitive impairment, DDC common genetic polymorphisms have been proposed as a source of more moderate, but clinically important, alterations in DDC function that may contribute to risk, course, or treatment response in complex, heritable neuropsychiatric illnesses. However, a direct link between common genetic variation in DDC and DDC activity in the living human brain has never been established. We therefore tested for this association by conducting extensive genotyping across the DDC gene in a large cohort of 120 healthy individuals, for whom DDC activity was then quantified with [(18)F]-FDOPA positron emission tomography (PET). The specific uptake constant, Ki, a measure of DDC activity, was estimated for striatal regions of interest and found to be predicted by one of five tested haplotypes, particularly in the ventral striatum. These data provide evidence for cis-acting, functional common polymorphisms in the DDC gene and support future work to determine whether such variation might meaningfully contribute to DDC-mediated neural processes relevant to neuropsychiatric illness and treatment.

  10. Striatal D1- and D2-type dopamine receptors are linked to motor response inhibition in human subjects.

    Science.gov (United States)

    Robertson, Chelsea L; Ishibashi, Kenji; Mandelkern, Mark A; Brown, Amira K; Ghahremani, Dara G; Sabb, Fred; Bilder, Robert; Cannon, Tyrone; Borg, Jacqueline; London, Edythe D

    2015-04-15

    Motor response inhibition is mediated by neural circuits involving dopaminergic transmission; however, the relative contributions of dopaminergic signaling via D1- and D2-type receptors are unclear. Although evidence supports dissociable contributions of D1- and D2-type receptors to response inhibition in rats and associations of D2-type receptors to response inhibition in humans, the relationship between D1-type receptors and response inhibition has not been evaluated in humans. Here, we tested whether individual differences in striatal D1- and D2-type receptors are related to response inhibition in human subjects, possibly in opposing ways. Thirty-one volunteers participated. Response inhibition was indexed by stop-signal reaction time on the stop-signal task and commission errors on the continuous performance task, and tested for association with striatal D1- and D2-type receptor availability [binding potential referred to nondisplaceable uptake (BPND)], measured using positron emission tomography with [(11)C]NNC-112 and [(18)F]fallypride, respectively. Stop-signal reaction time was negatively correlated with D1- and D2-type BPND in whole striatum, with significant relationships involving the dorsal striatum, but not the ventral striatum, and no significant correlations involving the continuous performance task. The results indicate that dopamine D1- and D2-type receptors are associated with response inhibition, and identify the dorsal striatum as an important locus of dopaminergic control in stopping. Moreover, the similar contribution of both receptor subtypes suggests the importance of a relative balance between phasic and tonic dopaminergic activity subserved by D1- and D2-type receptors, respectively, in support of response inhibition. The results also suggest that the stop-signal task and the continuous performance task use different neurochemical mechanisms subserving motor response inhibition. Copyright © 2015 the authors 0270-6474/15/355990-08$15.00/0.

  11. An adaptive orienting theory of error processing.

    Science.gov (United States)

    Wessel, Jan R

    2018-03-01

    The ability to detect and correct action errors is paramount to safe and efficient goal-directed behaviors. Existing work on the neural underpinnings of error processing and post-error behavioral adaptations has led to the development of several mechanistic theories of error processing. These theories can be roughly grouped into adaptive and maladaptive theories. While adaptive theories propose that errors trigger a cascade of processes that will result in improved behavior after error commission, maladaptive theories hold that error commission momentarily impairs behavior. Neither group of theories can account for all available data, as different empirical studies find both impaired and improved post-error behavior. This article attempts a synthesis between the predictions made by prominent adaptive and maladaptive theories. Specifically, it is proposed that errors invoke a nonspecific cascade of processing that will rapidly interrupt and inhibit ongoing behavior and cognition, as well as orient attention toward the source of the error. It is proposed that this cascade follows all unexpected action outcomes, not just errors. In the case of errors, this cascade is followed by error-specific, controlled processing, which is specifically aimed at (re)tuning the existing task set. This theory combines existing predictions from maladaptive orienting and bottleneck theories with specific neural mechanisms from the wider field of cognitive control, including from error-specific theories of adaptive post-error processing. The article aims to describe the proposed framework and its implications for post-error slowing and post-error accuracy, propose mechanistic neural circuitry for post-error processing, and derive specific hypotheses for future empirical investigations. © 2017 Society for Psychophysiological Research.

  12. [Development of a Striatal and Skull Phantom for Quantitative 123I-FP-CIT SPECT].

    Science.gov (United States)

    Ishiguro, Masanobu; Uno, Masaki; Miyazaki, Takuma; Kataoka, Yumi; Toyama, Hiroshi; Ichihara, Takashi

    123 Iodine-labelled N-(3-fluoropropyl) -2β-carbomethoxy-3β-(4-iodophenyl) nortropane ( 123 I-FP-CIT) single photon emission computerized tomography (SPECT) images are used for differential diagnosis such as Parkinson's disease (PD). Specific binding ratio (SBR) is affected by scattering and attenuation in SPECT imaging, because gender and age lead to changes in skull density. It is necessary to clarify and correct the influence of the phantom simulating the the skull. The purpose of this study was to develop phantoms that can evaluate scattering and attenuation correction. Skull phantoms were prepared based on the measuring the results of the average computed tomography (CT) value, average skull thickness of 12 males and 16 females. 123 I-FP-CIT SPECT imaging of striatal phantom was performed with these skull phantoms, which reproduced normal and PD. SPECT images, were reconstructed with scattering and attenuation correction. SBR with partial volume effect corrected (SBR act ) and conventional SBR (SBR Bolt ) were measured and compared. The striatum and the skull phantoms along with 123 I-FP-CIT were able to reproduce the normal accumulation and disease state of PD and further those reproduced the influence of skull density on SPECT imaging. The error rate with the true SBR, SBR act was much smaller than SBR Bolt . The effect on SBR could be corrected by scattering and attenuation correction even if the skull density changes with 123 I-FP-CIT on SPECT imaging. The combination of triple energy window method and CT-attenuation correction method would be the best correction method for SBR act .

  13. Striatal [[sup 11]C]-N-methyl-spiperone binding in patients with focal dystonia (torticollis) using positron emission tomography

    Energy Technology Data Exchange (ETDEWEB)

    Leenders, K [Paul Scherrer Inst. (PSI), Villigen (Switzerland); Hartvig, P [Hospital Pharmacy, Univ. Hospital, Uppsala (Sweden); Forsgren, L; Holmgren, G; Almay, B [Dept. of Neurology, Umeaa Univ., Umeaa (Sweden); Eckernaes, S A [Dept. of Neurology, Univ. Hospital, Uppsala (Sweden); Lundqvist, H; Laangstroem, B [Uppsala Univ. PET-Center, Uppsala (Sweden)

    1993-01-01

    Specific binding of [[sup 11]C]-N-methyl-spiperone to striatal dopamine D2 receptors was assessed using positron emission tomography (PET) in 6 patients with adult-onset focal dystonia (predominantly spasmodic torticollis) and in 5 healthy subjects. No significant difference in average specific striatal tracer uptake between patients and healthy subjects was found. However, in the 5 patients showing lateralisation of clinical signs a trend to higher striatal tracer uptake in the contralateral hemisphere was observed. (authors).

  14. Free radical production induced by methamphetamine in rat striatal synaptosomes

    International Nuclear Information System (INIS)

    Pubill, David; Chipana, Carlos; Camins, Antonio; Pallas, Merce; Camarasa, Jordi; Escubedo, Elena

    2005-01-01

    The pro-oxidative effect of methamphetamine (METH) in dopamine terminals was studied in rat striatal synaptosomes. Flow cytometry analysis showed increased production of reactive oxygen species (ROS) in METH-treated synaptosomes, without reduction in the density of dopamine transporters. In synaptosomes from dopamine (DA)-depleted animals, METH did not induce ROS production. Reserpine, in vitro, completely inhibited METH-induced ROS production. These results point to endogenous DA as the main source of ROS induced by METH. Antioxidants and inhibitors of neuronal nitric oxide synthase and protein kinase C (PKC) prevented the METH-induced oxidative effect. EGTA and the specific antagonist methyllycaconitine (MLA, 50 μM) prevented METH-induced ROS production, thus implicating calcium and α7 nicotinic receptors in such effect. Higher concentrations of MLA (>100 μM) showed nonspecific antioxidant effect. Preincubation of synaptosomes with METH (1 μM) for 30 min reduced [ 3 H]DA uptake by 60%. The METH effect was attenuated by MLA and EGTA and potentiated by nicotine, indicating that activation of α 7 nicotinic receptors and Ca 2+ entry are necessary and take place before DAT inhibition. From these findings, it can be postulated that, in our model, METH induces DA release from synaptic vesicles to the cytosol. Simultaneously, METH activates α 7 nicotinic receptors, probably inducing depolarization and an increase in intrasynaptosomal Ca 2+ . This would lead to DAT inhibition and NOS and PKC activation, initiating oxidation of cytosolic DA

  15. Reduced Striatal Dopamine Transporters in People with Internet Addiction Disorder

    Directory of Open Access Journals (Sweden)

    Haifeng Hou

    2012-01-01

    Full Text Available In recent years, internet addiction disorder (IAD has become more prevalent worldwide and the recognition of its devastating impact on the users and society has rapidly increased. However, the neurobiological mechanism of IAD has not bee fully expressed. The present study was designed to determine if the striatal dopamine transporter (DAT levels measured by T99mc-TRODAT-1 single photon emission computed tomography (SPECT brain scans were altered in individuals with IAD. SPECT brain scans were acquired on 5 male IAD subjects and 9 healthy age-matched controls. The volume (V and weight (W of bilateral corpus striatum as well as the T99mc-TRODAT-1 uptake ratio of corpus striatum/the whole brain (Ra were calculated using mathematical models. It was displayed that DAT expression level of striatum was significantly decreased and the V, W, and Ra were greatly reduced in the individuals with IAD compared to controls. Taken together, these results suggest that IAD may cause serious damages to the brain and the neuroimaging findings further illustrate IAD is associated with dysfunctions in the dopaminergic brain systems. Our findings also support the claim that IAD may share similar neurobiological abnormalities with other addictive disorders.

  16. Learning from prescribing errors

    OpenAIRE

    Dean, B

    2002-01-01

    

 The importance of learning from medical error has recently received increasing emphasis. This paper focuses on prescribing errors and argues that, while learning from prescribing errors is a laudable goal, there are currently barriers that can prevent this occurring. Learning from errors can take place on an individual level, at a team level, and across an organisation. Barriers to learning from prescribing errors include the non-discovery of many prescribing errors, lack of feedback to th...

  17. β1-adrenergic receptors activate two distinct signaling pathways in striatal neurons

    Science.gov (United States)

    Meitzen, John; Luoma, Jessie I.; Stern, Christopher M.; Mermelstein, Paul G.

    2010-01-01

    Monoamine action in the dorsal striatum and nucleus accumbens plays essential roles in striatal physiology. Although research often focuses on dopamine and its receptors, norepinephrine and adrenergic receptors are also crucial in regulating striatal function. While noradrenergic neurotransmission has been identified in the striatum, little is known regarding the signaling pathways activated by β-adrenergic receptors in this brain region. Using cultured striatal neurons, we characterized a novel signaling pathway by which activation of β1-adrenergic receptors leads to the rapid phosphorylation of cAMP Response Element Binding Protein (CREB), a transcription-factor implicated as a molecular switch underlying long-term changes in brain function. Norepinephrine-mediated CREB phosphorylation requires β1-adrenergic receptor stimulation of a receptor tyrosine kinase, ultimately leading to the activation of a Ras/Raf/MEK/MAPK/MSK signaling pathway. Activation of β1-adrenergic receptors also induces CRE-dependent transcription and increased c-fos expression. In addition, stimulation of β1-adrenergic receptors produces cAMP production, but surprisingly, β1-adrenergic receptor activation of adenylyl cyclase was not functionally linked to rapid CREB phosphorylation. These findings demonstrate that activation of β1-adrenergic receptors on striatal neurons can stimulate two distinct signaling pathways. These adrenergic actions can produce long-term changes in gene expression, as well as rapidly modulate cellular physiology. By elucidating the mechanisms by which norepinephrine and β1-adrenergic receptor activation affects striatal physiology, we provide the means to more fully understand the role of monoamines in modulating striatal function, specifically how norepinephrine and β1-adrenergic receptors may affect striatal physiology. PMID:21143600

  18. Beyond the Classic VTA: Extended Amygdala Projections to DA-Striatal Paths in the Primate.

    Science.gov (United States)

    Fudge, Julie L; Kelly, Emily A; Pal, Ria; Bedont, Joseph L; Park, Lydia; Ho, Brian

    2017-07-01

    The central extended amygdala (CEA) has been conceptualized as a 'macrosystem' that regulates various stress-induced behaviors. Consistent with this, the CEA highly expresses corticotropin-releasing factor (CRF), an important modulator of stress responses. Stress alters goal-directed responses associated with striatal paths, including maladaptive responses such as drug seeking, social withdrawal, and compulsive behavior. CEA inputs to the midbrain dopamine (DA) system are positioned to influence striatal functions through mesolimbic DA-striatal pathways. However, the structure of this amygdala-CEA-DA neuron path to the striatum has been poorly characterized in primates. In primates, we combined neuronal tracer injections into various arms of the circuit through specific DA subpopulations to assess: (1) whether the circuit connecting amygdala, CEA, and DA cells follows CEA intrinsic organization, or a more direct topography involving bed nucleus vs central nucleus divisions; (2) CRF content of the CEA-DA path; and (3) striatal subregions specifically involved in CEA-DA-striatal loops. We found that the amygdala-CEA-DA path follows macrostructural subdivisions, with the majority of input/outputs converging in the medial central nucleus, the sublenticular extended amygdala, and the posterior lateral bed nucleus of the stria terminalis. The proportion of CRF+ outputs is >50%, and mainly targets the A10 parabrachial pigmented nucleus (PBP) and A8 (retrorubal field, RRF) neuronal subpopulations, with additional inputs to the dorsal A9 neurons. CRF-enriched CEA-DA projections are positioned to influence outputs to the 'limbic-associative' striatum, which is distinct from striatal regions targeted by DA cells lacking CEA input. We conclude that the concept of the CEA is supported on connectional grounds, and that CEA termination over the PBP and RRF neuronal populations can influence striatal circuits involved in associative learning.

  19. Inhibition of the striatal specific phosphodiesterase PDE10A ameliorates striatal and cortical pathology in R6/2 mouse model of Huntington's disease.

    Directory of Open Access Journals (Sweden)

    Carmela Giampà

    2010-10-01

    Full Text Available Huntington's disease is a devastating neurodegenerative condition for which there is no therapy to slow disease progression. The particular vulnerability of striatal medium spiny neurons to Huntington's pathology is hypothesized to result from transcriptional dysregulation within the cAMP and CREB signaling cascades in these neurons. To test this hypothesis, and a potential therapeutic approach, we investigated whether inhibition of the striatal-specific cyclic nucleotide phosphodiesterase PDE10A would alleviate neurological deficits and brain pathology in a highly utilized model system, the R6/2 mouse.R6/2 mice were treated with the highly selective PDE10A inhibitor TP-10 from 4 weeks of age until euthanasia. TP-10 treatment significantly reduced and delayed the development of the hind paw clasping response during tail suspension, deficits in rotarod performance, and decrease in locomotor activity in an open field. Treatment prolonged time to loss of righting reflex. These effects of PDE10A inhibition on neurological function were reflected in a significant amelioration in brain pathology, including reduction in striatal and cortical cell loss, the formation of striatal neuronal intranuclear inclusions, and the degree of microglial activation that occurs in response to the mutant huntingtin-induced brain damage. Striatal and cortical levels of phosphorylated CREB and BDNF were significantly elevated.Our findings provide experimental support for targeting the cAMP and CREB signaling pathways and more broadly transcriptional dysregulation as a therapeutic approach to Huntington's disease. It is noteworthy that PDE10A inhibition in the R6/2 mice reduces striatal pathology, consistent with the localization of the enzyme in medium spiny neurons, and also cortical pathology and the formation of neuronal nuclear inclusions. These latter findings suggest that striatal pathology may be a primary driver of these secondary pathological events. More

  20. Errors, error detection, error correction and hippocampal-region damage: data and theories.

    Science.gov (United States)

    MacKay, Donald G; Johnson, Laura W

    2013-11-01

    This review and perspective article outlines 15 observational constraints on theories of errors, error detection, and error correction, and their relation to hippocampal-region (HR) damage. The core observations come from 10 studies with H.M., an amnesic with cerebellar and HR damage but virtually no neocortical damage. Three studies examined the detection of errors planted in visual scenes (e.g., a bird flying in a fish bowl in a school classroom) and sentences (e.g., I helped themselves to the birthday cake). In all three experiments, H.M. detected reliably fewer errors than carefully matched memory-normal controls. Other studies examined the detection and correction of self-produced errors, with controls for comprehension of the instructions, impaired visual acuity, temporal factors, motoric slowing, forgetting, excessive memory load, lack of motivation, and deficits in visual scanning or attention. In these studies, H.M. corrected reliably fewer errors than memory-normal and cerebellar controls, and his uncorrected errors in speech, object naming, and reading aloud exhibited two consistent features: omission and anomaly. For example, in sentence production tasks, H.M. omitted one or more words in uncorrected encoding errors that rendered his sentences anomalous (incoherent, incomplete, or ungrammatical) reliably more often than controls. Besides explaining these core findings, the theoretical principles discussed here explain H.M.'s retrograde amnesia for once familiar episodic and semantic information; his anterograde amnesia for novel information; his deficits in visual cognition, sentence comprehension, sentence production, sentence reading, and object naming; and effects of aging on his ability to read isolated low frequency words aloud. These theoretical principles also explain a wide range of other data on error detection and correction and generate new predictions for future test. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Intrastriatal administration of botulinum neurotoxin A normalizes striatal D2 R binding and reduces striatal D1 R binding in male hemiparkinsonian rats.

    Science.gov (United States)

    Wedekind, Franziska; Oskamp, Angela; Lang, Markus; Hawlitschka, Alexander; Zilles, Karl; Wree, Andreas; Bauer, Andreas

    2018-01-01

    Cerebral administration of botulinum neurotoxin A (BoNT-A) has been shown to improve disease-specific motor behavior in a rat model of Parkinson disease (PD). Since the dopaminergic system of the basal ganglia fundamentally contributes to motor function, we investigated the impact of BoNT-A on striatal dopamine receptor expression using in vitro and in vivo imaging techniques (positron emission tomography and quantitative autoradiography, respectively). Seventeen male Wistar rats were unilaterally lesioned with 6-hydroxydopamine (6-OHDA) and assigned to two treatment groups 7 weeks later: 10 rats were treated ipsilaterally with an intrastriatal injection of 1 ng BoNT-A, while the others received vehicle (n = 7). All animals were tested for asymmetric motor behavior (apomorphine-induced rotations and forelimb usage) and for striatal expression of dopamine receptors and transporters (D 1 R, D 2 R, and DAT). The striatal D 2 R availability was also quantified longitudinally (1.5, 3, and 5 months after intervention) in 5 animals per treatment group. The 6-OHDA lesion alone induced a unilateral PD-like phenotype and a 13% increase of striatal D 2 R. BoNT-A treatment reduced the asymmetry in both apomorphine-induced rotational behavior and D 2 R expression, with the latter returning to normal values 5 months after intervention. D 1 R expression was significantly reduced, while DAT concentrations showed no alteration. Independent of the treatment, higher interhemispheric symmetry in raclopride binding to D 2 R was generally associated with reduced forelimb akinesia. Our findings indicate that striatal BoNT-A treatment diminishes motor impairment and induces changes in D 1 and D 2 binding site density in the 6-OHDA rat model of PD. © 2017 Wiley Periodicals, Inc.

  2. Game Design Principles based on Human Error

    Directory of Open Access Journals (Sweden)

    Guilherme Zaffari

    2016-03-01

    Full Text Available This paper displays the result of the authors’ research regarding to the incorporation of Human Error, through design principles, to video game design. In a general way, designers must consider Human Error factors throughout video game interface development; however, when related to its core design, adaptations are in need, since challenge is an important factor for fun and under the perspective of Human Error, challenge can be considered as a flaw in the system. The research utilized Human Error classifications, data triangulation via predictive human error analysis, and the expanded flow theory to allow the design of a set of principles in order to match the design of playful challenges with the principles of Human Error. From the results, it was possible to conclude that the application of Human Error in game design has a positive effect on player experience, allowing it to interact only with errors associated with the intended aesthetics of the game.

  3. The Errors of Our Ways: Understanding Error Representations in Cerebellar-Dependent Motor Learning.

    Science.gov (United States)

    Popa, Laurentiu S; Streng, Martha L; Hewitt, Angela L; Ebner, Timothy J

    2016-04-01

    The cerebellum is essential for error-driven motor learning and is strongly implicated in detecting and correcting for motor errors. Therefore, elucidating how motor errors are represented in the cerebellum is essential in understanding cerebellar function, in general, and its role in motor learning, in particular. This review examines how motor errors are encoded in the cerebellar cortex in the context of a forward internal model that generates predictions about the upcoming movement and drives learning and adaptation. In this framework, sensory prediction errors, defined as the discrepancy between the predicted consequences of motor commands and the sensory feedback, are crucial for both on-line movement control and motor learning. While many studies support the dominant view that motor errors are encoded in the complex spike discharge of Purkinje cells, others have failed to relate complex spike activity with errors. Given these limitations, we review recent findings in the monkey showing that complex spike modulation is not necessarily required for motor learning or for simple spike adaptation. Also, new results demonstrate that the simple spike discharge provides continuous error signals that both lead and lag the actual movements in time, suggesting errors are encoded as both an internal prediction of motor commands and the actual sensory feedback. These dual error representations have opposing effects on simple spike discharge, consistent with the signals needed to generate sensory prediction errors used to update a forward internal model.

  4. Deficits in Attention and Visual Processing but not Global Cognition Predict Simulated Driving Errors in Drivers Diagnosed With Mild Alzheimer's Disease.

    Science.gov (United States)

    Yamin, Stephanie; Stinchcombe, Arne; Gagnon, Sylvain

    2016-06-01

    This study sought to predict driving performance of drivers with Alzheimer's disease (AD) using measures of attention, visual processing, and global cognition. Simulated driving performance of individuals with mild AD (n = 20) was contrasted with performance of a group of healthy controls (n = 21). Performance on measures of global cognitive function and specific tests of attention and visual processing were examined in relation to simulated driving performance. Strong associations were observed between measures of attention, notably the Test of Everyday Attention (sustained attention; r = -.651, P = .002) and the Useful Field of View (r = .563, P = .010), and driving performance among drivers with mild AD. The Visual Object and Space Perception Test-object was significantly correlated with the occurrence of crashes (r = .652, P = .002). Tests of global cognition did not correlate with simulated driving outcomes. The results suggest that professionals exercise caution when extrapolating driving performance based on global cognitive indicators. © The Author(s) 2015.

  5. Gender Differences in Age-Related Striatal Dopamine Depletion in Parkinson’s Disease

    Directory of Open Access Journals (Sweden)

    Jae Jung Lee

    2015-09-01

    Full Text Available Objective Gender differences are a well-known clinical characteristic of Parkinson’s disease (PD. In-vivo imaging studies demonstrated that women have greater striatal dopamine transporter (DAT activity than do men, both in the normal population and in PD patients. We hypothesize that women exhibit more rapid aging-related striatal DAT reduction than do men, as the potential neuroprotective effect of estrogen wanes with age. Methods This study included 307 de novo PD patients (152 men and 155 women who underwent DAT scans for an initial diagnostic work-up. Gender differences in age-related DAT decline were assessed in striatal sub-regions using linear regression analysis. Results Female patients exhibited greater DAT activity compared with male patients in all striatal sub-regions. The linear regression analysis revealed that age-related DAT decline was greater in the anterior and posterior caudate, and the anterior putamen in women compared with men; we did not observe this difference in other sub-regions. Conclusions This study demonstrated the presence of gender differences in age-related DAT decline in striatal sub-regions, particularly in the antero-dorsal striatum, in patients with PD, presumably due to aging-related decrease in estrogen. Because this difference was not observed in the sensorimotor striatum, this finding also suggests that women may not have a greater capacity to tolerate PD pathogenesis than do men.

  6. Striatal lesions produce distinctive impairments in reaction time performance in two different operant chambers.

    Science.gov (United States)

    Brasted, P J; Döbrössy, M D; Robbins, T W; Dunnett, S B

    1998-08-01

    The dorsal striatum plays a crucial role in mediating voluntary movement. Excitotoxic striatal lesions in rats have previously been shown to impair the initiation but not the execution of movement in a choice reaction time task in an automated lateralised nose-poke apparatus (the "nine-hole box"). Conversely, when a conceptually similar reaction time task has been applied in a conventional operant chamber (or "Skinner box"), striatal lesions have been seen to impair the execution rather than the initiation of the lateralised movement. The present study was undertaken to compare directly these two results by training the same group of rats to perform a choice reaction time task in the two chambers and then comparing the effects of a unilateral excitotoxic striatal lesion in both chambers in parallel. Particular attention was paid to adopting similar parameters and contingencies in the control of the task in the two test chambers. After striatal lesions, the rats showed predominantly contralateral impairments in both tasks. However, they showed a deficit in reaction time in the nine-hole box but an apparent deficit in response execution in the Skinner box. This finding confirms the previous studies and indicates that differences in outcome are not simply attributable to procedural differences in the lesions, training conditions or tasks parameters. Rather, the pattern of reaction time deficit after striatal lesions depends critically on the apparatus used and the precise response requirements for each task.

  7. Altered resting state cortico-striatal connectivity in mild to moderate stage Parkinson’s disease

    Directory of Open Access Journals (Sweden)

    Youngbin Kwak

    2010-09-01

    Full Text Available Parkinson’s disease (PD is a progressive neurodegenerative disorder that is characterized by dopamine depletion in the striatum. One consistent pathophysiological hallmark of PD is an increase in spontaneous oscillatory activity in the basal ganglia thalamocortical networks. We evaluated these effects using resting state functional connectivity MRI (fcMRI in mild to moderate stage Parkinson’s patients on and off L-DOPA and age-matched controls using six different striatal seed regions. We observed an overall increase in the strength of cortico-striatal functional connectivity in PD patients off L-DOPA compared to controls. This enhanced connectivity was down-regulated by L-DOPA as shown by an overall decrease in connectivity strength, particularly within motor cortical regions. We also performed a frequency content analysis of the BOLD signal time course extracted from the six striatal seed regions. PD off L-DOPA exhibited increased power in the frequency band 0.02 – 0.05 Hz compared to controls and to PD on L-DOPA. The L-DOPA associated decrease in the power of this frequency range modulated the L-DOPA associated decrease in connectivity strength between striatal seeds and the thalamus. In addition, the L-DOPA associated decrease in power in this frequency band also correlated with the L-DOPA associated improvement in cognitive performance. Our results demonstrate that PD and L-DOPA modulate striatal resting state BOLD signal oscillations and corticostriatal network coherence.

  8. Regulation of dopamine synthesis and release in striatal and prefrontal cortical brain slices

    International Nuclear Information System (INIS)

    Wolf, M.E.

    1986-01-01

    Brain slices were used to investigate the role of nerve terminal autoreceptors in modulating dopamine (DA) synthesis and release in striatum and prefrontal cortex. Accumulation of dihydroxyphenylalanine (DOPA) was used as an index of tyrosine hydroxylation in vitro. Nomifensine, a DA uptake blocker, inhibited DOPA synthesis in striatal but not prefrontal slices. This effect was reversed by the DA antagonist sulpiride, suggesting it involved activation of DA receptors by elevated synaptic levels of DA. The autoreceptor-selective agonist EMD-23-448 also inhibited striatal but not prefrontal DOPA synthesis. DOPA synthesis was stimulated in both brain regions by elevated K + , however only striatal synthesis could be further enhanced by sulpiride. DA release was measured by following the efflux of radioactivity from brain slices prelabeled with [ 3 H]-DA. EMD-23-448 and apomorphine inhibited, while sulpiride enhanced, the K + -evoked overflow of radioactivity from both striatal and prefrontal cortical slices. These findings suggest that striatal DA nerve terminals possess autoreceptors which modulate tyrosine hydroxylation as well as autoreceptors which modulate release. Alternatively, one site may be coupled to both functions through distinct transduction mechanisms. In contrast, autoreceptors on prefrontal cortical terminals appear to regulate DA release but not DA synthesis

  9. An inquiry into the semiquantitative parameters of striatal dopamine receptor imaging

    International Nuclear Information System (INIS)

    Cao Guoxiang; Tan Tianzhi; Kuang Anren; Liang Zhenglu

    1998-01-01

    Purpose: To inquire into the optimal striatal reference region for nonspecific IBZM uptake in brain dopamine receptor imaging. Methods: Using in vivo data from rats, the authors compared the results of 125 I-iodobenzamide ( 125 I-IBZM) striatal specific binding that were respectively obtained taking cerebellum and frontal cortex as striatal reference region of nonspecific uptake of ligand. Results: Radioiodination labelled IBZM bound stereoselectively and reversibly to striatal D2 receptors. Frontal cortex and cerebellum showed rapid uptake and rapid washout of ligand. When cerebellar uptake was used as a reference of nonspecific uptake in striatum, IBZM saturation could not be demonstrated. But when the frontal cortex was used as reference region, saturation could be demonstrated with B max = 44 pmol/g striatum tissue. The percentage of haloperidol replacement and the percentage of uptake difference between striatum and other brain regions which were derived from competitive inhibition experiments with a large does of spiperone or haloperidol, suggested that the cerebellar uptake underestimated nonspecific uptake in the striatum while frontal cortex was an appropriate reference region for nonspecific uptake of ligand in striatum. Conclusions: For the calculation of specific IBZM binding and other semiquantitative parameters of striatal dopamine D2 receptor imaging, frontal cortex would be the nonspecific reference region of choice

  10. Two-dimensional errors

    International Nuclear Information System (INIS)

    Anon.

    1991-01-01

    This chapter addresses the extension of previous work in one-dimensional (linear) error theory to two-dimensional error analysis. The topics of the chapter include the definition of two-dimensional error, the probability ellipse, the probability circle, elliptical (circular) error evaluation, the application to position accuracy, and the use of control systems (points) in measurements

  11. Part two: Error propagation

    International Nuclear Information System (INIS)

    Picard, R.R.

    1989-01-01

    Topics covered in this chapter include a discussion of exact results as related to nuclear materials management and accounting in nuclear facilities; propagation of error for a single measured value; propagation of error for several measured values; error propagation for materials balances; and an application of error propagation to an example of uranium hexafluoride conversion process

  12. Learning from Errors

    OpenAIRE

    Martínez-Legaz, Juan Enrique; Soubeyran, Antoine

    2003-01-01

    We present a model of learning in which agents learn from errors. If an action turns out to be an error, the agent rejects not only that action but also neighboring actions. We find that, keeping memory of his errors, under mild assumptions an acceptable solution is asymptotically reached. Moreover, one can take advantage of big errors for a faster learning.

  13. Generalized Gaussian Error Calculus

    CERN Document Server

    Grabe, Michael

    2010-01-01

    For the first time in 200 years Generalized Gaussian Error Calculus addresses a rigorous, complete and self-consistent revision of the Gaussian error calculus. Since experimentalists realized that measurements in general are burdened by unknown systematic errors, the classical, widespread used evaluation procedures scrutinizing the consequences of random errors alone turned out to be obsolete. As a matter of course, the error calculus to-be, treating random and unknown systematic errors side by side, should ensure the consistency and traceability of physical units, physical constants and physical quantities at large. The generalized Gaussian error calculus considers unknown systematic errors to spawn biased estimators. Beyond, random errors are asked to conform to the idea of what the author calls well-defined measuring conditions. The approach features the properties of a building kit: any overall uncertainty turns out to be the sum of a contribution due to random errors, to be taken from a confidence inter...

  14. An imperfect dopaminergic error signal can drive temporal-difference learning.

    Directory of Open Access Journals (Sweden)

    Wiebke Potjans

    2011-05-01

    Full Text Available An open problem in the field of computational neuroscience is how to link synaptic plasticity to system-level learning. A promising framework in this context is temporal-difference (TD learning. Experimental evidence that supports the hypothesis that the mammalian brain performs temporal-difference learning includes the resemblance of the phasic activity of the midbrain dopaminergic neurons to the TD error and the discovery that cortico-striatal synaptic plasticity is modulated by dopamine. However, as the phasic dopaminergic signal does not reproduce all the properties of the theoretical TD error, it is unclear whether it is capable of driving behavior adaptation in complex tasks. Here, we present a spiking temporal-difference learning model based on the actor-critic architecture. The model dynamically generates a dopaminergic signal with realistic firing rates and exploits this signal to modulate the plasticity of synapses as a third factor. The predictions of our proposed plasticity dynamics are in good agreement with experimental results with respect to dopamine, pre- and post-synaptic activity. An analytical mapping from the parameters of our proposed plasticity dynamics to those of the classical discrete-time TD algorithm reveals that the biological constraints of the dopaminergic signal entail a modified TD algorithm with self-adapting learning parameters and an adapting offset. We show that the neuronal network is able to learn a task with sparse positive rewards as fast as the corresponding classical discrete-time TD algorithm. However, the performance of the neuronal network is impaired with respect to the traditional algorithm on a task with both positive and negative rewards and breaks down entirely on a task with purely negative rewards. Our model demonstrates that the asymmetry of a realistic dopaminergic signal enables TD learning when learning is driven by positive rewards but not when driven by negative rewards.

  15. Medication errors: prescribing faults and prescription errors.

    Science.gov (United States)

    Velo, Giampaolo P; Minuz, Pietro

    2009-06-01

    1. Medication errors are common in general practice and in hospitals. Both errors in the act of writing (prescription errors) and prescribing faults due to erroneous medical decisions can result in harm to patients. 2. Any step in the prescribing process can generate errors. Slips, lapses, or mistakes are sources of errors, as in unintended omissions in the transcription of drugs. Faults in dose selection, omitted transcription, and poor handwriting are common. 3. Inadequate knowledge or competence and incomplete information about clinical characteristics and previous treatment of individual patients can result in prescribing faults, including the use of potentially inappropriate medications. 4. An unsafe working environment, complex or undefined procedures, and inadequate communication among health-care personnel, particularly between doctors and nurses, have been identified as important underlying factors that contribute to prescription errors and prescribing faults. 5. Active interventions aimed at reducing prescription errors and prescribing faults are strongly recommended. These should be focused on the education and training of prescribers and the use of on-line aids. The complexity of the prescribing procedure should be reduced by introducing automated systems or uniform prescribing charts, in order to avoid transcription and omission errors. Feedback control systems and immediate review of prescriptions, which can be performed with the assistance of a hospital pharmacist, are also helpful. Audits should be performed periodically.

  16. Prediction error variance and expected response to selection, when selection is based on the best predictor - for Gaussian and threshold characters, traits following a Poisson mixed model and survival traits

    DEFF Research Database (Denmark)

    Andersen, Anders Holst; Korsgaard, Inge Riis; Jensen, Just

    2002-01-01

    In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed...... or random effects). In the different models, expressions are given (when these can be found - otherwise unbiased estimates are given) for prediction error variance, accuracy of selection and expected response to selection on the additive genetic scale and on the observed scale. The expressions given for non...... Gaussian traits are generalisations of the well-known formulas for Gaussian traits - and reflect, for Poisson mixed models and frailty models for survival data, the hierarchal structure of the models. In general the ratio of the additive genetic variance to the total variance in the Gaussian part...

  17. Mitochondrial fragmentation in neuronal degeneration: Toward an understanding of HD striatal susceptibility

    International Nuclear Information System (INIS)

    Cherubini, Marta; Ginés, Silvia

    2017-01-01

    Huntington's disease (HD) is an autosomal-dominant progressive neurodegenerative disorder that primarily affects medium spiny neurons within the striatum. HD is caused by inheritance of an expanded CAG repeat in the HTT gene, resulting in a mutant huntingtin (mHtt) protein containing extra glutamine residues. Despite the advances in understanding the molecular mechanisms involved in HD the preferential vulnerability of the striatum remains an intriguing question. This review discusses current knowledge that links altered mitochondrial dynamics with striatal susceptibility in HD. We also highlight how the modulation of mitochondrial function may constitute an attractive therapeutic approach to reduce mHtt-induced toxicity and therefore prevent the selective striatal neurodegeneration. - Highlights: • Mitochondrial dynamics is unbalanced towards fission in HD. • Excessive mitochondrial fragmentation plays a critical role in the selective vulnerability of the striatum in HD. • Therapeutic approaches aimed to inhibit mitochondrial fission could contribute to prevent striatal neurodegeneration in HD.

  18. Decreased spontaneous eye blink rates in chronic cannabis users: evidence for striatal cannabinoid-dopamine interactions.

    Directory of Open Access Journals (Sweden)

    Mikael A Kowal

    Full Text Available Chronic cannabis use has been shown to block long-term depression of GABA-glutamate synapses in the striatum, which is likely to reduce the extent to which endogenous cannabinoids modulate GABA- and glutamate-related neuronal activity. The current study aimed at investigating the effect of this process on striatal dopamine levels by studying the spontaneous eye blink rate (EBR, a clinical marker of dopamine level in the striatum. 25 adult regular cannabis users and 25 non-user controls matched for age, gender, race, and IQ were compared. Results show a significant reduction in EBR in chronic users as compared to non-users, suggesting an indirect detrimental effect of chronic cannabis use on striatal dopaminergic functioning. Additionally, EBR correlated negatively with years of cannabis exposure, monthly peak cannabis consumption, and lifetime cannabis consumption, pointing to a relationship between the degree of impairment of striatal dopaminergic transmission and cannabis consumption history.

  19. Dopamine-Related Disruption of Functional Topography of Striatal Connections in Unmedicated Patients With Schizophrenia.

    Science.gov (United States)

    Horga, Guillermo; Cassidy, Clifford M; Xu, Xiaoyan; Moore, Holly; Slifstein, Mark; Van Snellenberg, Jared X; Abi-Dargham, Anissa

    2016-08-01

    Despite the well-established role of striatal dopamine in psychosis, current views generally agree that cortical dysfunction is likely necessary for the emergence of psychotic symptoms. The topographic organization of striatal-cortical connections is central to gating and integration of higher-order information, so a disruption of such topography via dysregulated dopamine could lead to cortical dysfunction in schizophrenia. However, this hypothesis remains to be tested using multivariate methods ascertaining the global pattern of striatal connectivity and without the confounding effects of antidopaminergic medication. To examine whether the pattern of brain connectivity across striatal subregions is abnormal in unmedicated patients with schizophrenia and whether this abnormality relates to psychotic symptoms and extrastriatal dopaminergic transmission. In this multimodal, case-control study, we obtained resting-state functional magnetic resonance imaging data from 18 unmedicated patients with schizophrenia and 24 matched healthy controls from the New York State Psychiatric Institute. A subset of these (12 and 17, respectively) underwent positron emission tomography with the dopamine D2 receptor radiotracer carbon 11-labeled FLB457 before and after amphetamine administration. Data were acquired between June 16, 2011, and February 25, 2014. Data analysis was performed from September 1, 2014, to January 11, 2016. Group differences in the striatal connectivity pattern (assessed via multivariable logistic regression) across striatal subregions, the association between the multivariate striatal connectivity pattern and extrastriatal baseline D2 receptor binding potential and its change after amphetamine administration, and the association between the multivariate connectivity pattern and the severity of positive symptoms evaluated with the Positive and Negative Syndrome Scale. Of the patients with schizophrenia (mean [SEM] age, 35.6 [11.8] years), 9 (50%) were male and 9

  20. Striatal structure and its association with N-Acetylaspartate and glutamate in autism spectrum disorder and obsessive compulsive disorder

    NARCIS (Netherlands)

    Naaijen, Jilly; Zwiers, Marcel P.; Forde, Natalie J.; Williams, Steven C. R.; Durston, Sarah; Brandeis, Daniel; Glennon, Jeffrey C.; Franke, Barbara; Lythgoe, David J.; Buitelaar, Jan K.

    Autism spectrum disorders (ASD) and obsessive compulsive disorder (OCD) are often comorbid and are associated with changes in striatal volumes and N-Acetylaspartate (NAA) and glutamate levels. Here, we investigated the relation between dorsal striatal volume and NAA and glutamate levels. We

  1. Contribution of vesicular and cytosolic dopamine to the increased striatal dopamine efflux elicited by intrastriatal injection of SKF38393.

    NARCIS (Netherlands)

    Saigusa, T.; Aono, Y.; Sekino, R.; Uchida, T.; Takada, K.; Oi, Y.; Koshikawa, N.; Cools, A.R.

    2009-01-01

    Like dexamphetamine, SKF38393 induces an increase in striatal dopamine efflux which is insensitive for tetrodotoxin, Ca(2+) independent and prevented by a dopamine transporter inhibitor. The dexamphetamine-induced striatal dopamine efflux originates from both the reserpine-sensitive vesicular

  2. Striatal dopamine in Parkinson disease: A meta-analysis of imaging studies.

    Science.gov (United States)

    Kaasinen, Valtteri; Vahlberg, Tero

    2017-12-01

    A meta-analysis of 142 positron emission tomography and single photon emission computed tomography studies that have investigated striatal presynaptic dopamine function in Parkinson disease (PD) was performed. Subregional estimates of striatal dopamine metabolism are presented. The aromatic L-amino-acid decarboxylase (AADC) defect appears to be consistently smaller than the dopamine transporter and vesicular monoamine transporter 2 defects, suggesting upregulation of AADC function in PD. The correlation between disease severity and dopamine loss appears linear, but the majority of longitudinal studies point to a negative exponential progression pattern of dopamine loss in PD. Ann Neurol 2017;82:873-882. © 2017 American Neurological Association.

  3. Position Error Covariance Matrix Validation and Correction

    Science.gov (United States)

    Frisbee, Joe, Jr.

    2016-01-01

    In order to calculate operationally accurate collision probabilities, the position error covariance matrices predicted at times of closest approach must be sufficiently accurate representations of the position uncertainties. This presentation will discuss why the Gaussian distribution is a reasonable expectation for the position uncertainty and how this assumed distribution type is used in the validation and correction of position error covariance matrices.

  4. Field error lottery

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, C.J.; McVey, B. (Los Alamos National Lab., NM (USA)); Quimby, D.C. (Spectra Technology, Inc., Bellevue, WA (USA))

    1990-01-01

    The level of field errors in an FEL is an important determinant of its performance. We have computed 3D performance of a large laser subsystem subjected to field errors of various types. These calculations have been guided by simple models such as SWOOP. The technique of choice is utilization of the FELEX free electron laser code that now possesses extensive engineering capabilities. Modeling includes the ability to establish tolerances of various types: fast and slow scale field bowing, field error level, beam position monitor error level, gap errors, defocusing errors, energy slew, displacement and pointing errors. Many effects of these errors on relative gain and relative power extraction are displayed and are the essential elements of determining an error budget. The random errors also depend on the particular random number seed used in the calculation. The simultaneous display of the performance versus error level of cases with multiple seeds illustrates the variations attributable to stochasticity of this model. All these errors are evaluated numerically for comprehensive engineering of the system. In particular, gap errors are found to place requirements beyond mechanical tolerances of {plus minus}25{mu}m, and amelioration of these may occur by a procedure utilizing direct measurement of the magnetic fields at assembly time. 4 refs., 12 figs.

  5. Prescription Errors in Psychiatry

    African Journals Online (AJOL)

    Arun Kumar Agnihotri

    clinical pharmacists in detecting errors before they have a (sometimes serious) clinical impact should not be underestimated. Research on medication error in mental health care is limited. .... participation in ward rounds and adverse drug.

  6. A theory of cross-validation error

    OpenAIRE

    Turney, Peter D.

    1994-01-01

    This paper presents a theory of error in cross-validation testing of algorithms for predicting real-valued attributes. The theory justifies the claim that predicting real-valued attributes requires balancing the conflicting demands of simplicity and accuracy. Furthermore, the theory indicates precisely how these conflicting demands must be balanced, in order to minimize cross-validation error. A general theory is presented, then it is developed in detail for linear regression and instance-bas...

  7. Robot learning and error correction

    Science.gov (United States)

    Friedman, L.

    1977-01-01

    A model of robot learning is described that associates previously unknown perceptions with the sensed known consequences of robot actions. For these actions, both the categories of outcomes and the corresponding sensory patterns are incorporated in a knowledge base by the system designer. Thus the robot is able to predict the outcome of an action and compare the expectation with the experience. New knowledge about what to expect in the world may then be incorporated by the robot in a pre-existing structure whether it detects accordance or discrepancy between a predicted consequence and experience. Errors committed during plan execution are detected by the same type of comparison process and learning may be applied to avoiding the errors.

  8. Errors in otology.

    Science.gov (United States)

    Kartush, J M

    1996-11-01

    Practicing medicine successfully requires that errors in diagnosis and treatment be minimized. Malpractice laws encourage litigators to ascribe all medical errors to incompetence and negligence. There are, however, many other causes of unintended outcomes. This article describes common causes of errors and suggests ways to minimize mistakes in otologic practice. Widespread dissemination of knowledge about common errors and their precursors can reduce the incidence of their occurrence. Consequently, laws should be passed to allow for a system of non-punitive, confidential reporting of errors and "near misses" that can be shared by physicians nationwide.

  9. Repeated cocaine administration results in supersensitivity of striatal D-2 dopamine autoreceptors to pergolide

    International Nuclear Information System (INIS)

    Dwoskin, L.P.; Peris, J.; Yasuda, R.P.; Philpott, K.; Zahniser, N.R.

    1988-01-01

    Groups of rats administered cocaine-HCl (10 mg/kg, i.p.) or saline either acutely or once daily for 8 or 14 days were killed 24 hrs after the last dose. In striatal slices prelabelled with [ 3 H]DA, modulation of [ 3 H]-overflow by pergolide was used to measure D-2 autoreceptor activity. Compared to the contemporaneous control group pergolide produced a greater inhibition only in striatal slices from rats treated repeatedly with cocaine. In radioligand binding studies using striatal membranes from control rats, pergolide had a 500-fold greater affinity for the D-2, as opposed to the D-1, dopamine (DA) receptor subtype. These results indicate that repeated treatment with cocaine produces supersensitive striatal D-2 release-modulating autoreceptors consistent with a compensatory change to diminish the effect of elevated synaptic concentrations of DA produced by cocaine. In contrast, supersensitivity of D-2 receptors was not detected in [ 3 H]spiperone binding assays. 31 references, 2 figures, 1 table

  10. De Novo Mutations in PDE10A Cause Childhood-Onset Chorea with Bilateral Striatal Lesions

    NARCIS (Netherlands)

    Mencacci, N.E.; Kamsteeg, E.J.; Nakashima, K.; R'Bibo, L.; Lynch, D.S.; Balint, B.; Willemsen, M.A.A.P.; Adams, M.E.; Wiethoff, S.; Suzuki, K.; Davies, C.H.; Ng, J.; Meyer, E.; Veneziano, L.; Giunti, P.; Hughes, D.; Raymond, F.L.; Carecchio, M.; Zorzi, G.; Nardocci, N.; Barzaghi, C.; Garavaglia, B.; Salpietro, V.; Hardy, J.; Pittman, A.M.; Houlden, H.; Kurian, M.A.; Kimura, H.; Vissers, L.E.L.M.; Wood, N.W.; Bhatia, K.P.

    2016-01-01

    Chorea is a hyperkinetic movement disorder resulting from dysfunction of striatal medium spiny neurons (MSNs), which form the main output projections from the basal ganglia. Here, we used whole-exome sequencing to unravel the underlying genetic cause in three unrelated individuals with a very

  11. Striatal dopamine D2 receptors, metabolism, and volume in preclinical Huntington disease

    NARCIS (Netherlands)

    van Oostrom, JCH; Maguire, RP; Verschuuren-Bemelmans, CC; van der Duin, LV; Pruim, J; Roos, RAC; Leenders, KL

    2005-01-01

    Among 27 preclinical carriers of the Huntington disease mutation (PMC), the authors found normal striatal values for MRI volumetry in 88% and for fluorodesoxyglucose PET metabolic index in 67%. Raclopride PET binding potential (RAC-BP) was decreased in 50% and correlated with increases in the

  12. Abnormal fronto-striatal activation as a marker of threshold and subthreshold Bulimia Nervosa.

    Science.gov (United States)

    Cyr, Marilyn; Yang, Xiao; Horga, Guillermo; Marsh, Rachel

    2018-04-01

    This study aimed to determine whether functional disturbances in fronto-striatal control circuits characterize adolescents with Bulimia Nervosa (BN) spectrum eating disorders regardless of clinical severity. FMRI was used to assess conflict-related brain activations during performance of a Simon task in two samples of adolescents with BN symptoms compared with healthy adolescents. The BN samples differed in the severity of their clinical presentation, illness duration and age. Multi-voxel pattern analyses (MVPAs) based on machine learning were used to determine whether patterns of fronto-striatal activation characterized adolescents with BN spectrum disorders regardless of clinical severity, and whether accurate classification of less symptomatic adolescents (subthreshold BN; SBN) could be achieved based on patterns of activation in adolescents who met DSM5 criteria for BN. MVPA classification analyses revealed that both BN and SBN adolescents could be accurately discriminated from healthy adolescents based on fronto-striatal activation. Notably, the patterns detected in more severely ill BN compared with healthy adolescents accurately discriminated less symptomatic SBN from healthy adolescents. Deficient activation of fronto-striatal circuits can characterize BN early in its course, when clinical presentations are less severe, perhaps pointing to circuit-based disturbances as useful biomarker or risk factor for the disorder, and a tool for understanding its developmental trajectory, as well as the development of early interventions. © 2018 Wiley Periodicals, Inc.

  13. Synthesis and binding to striatal membranes of non carrier added I-123 labeled 4'-iodococaine

    International Nuclear Information System (INIS)

    Metwally, S.A.M.; Gatley, S.J.; Wolf, A.P.; Yu, D.-W.

    1992-01-01

    An 123 I labeled cocaine analog, 4'-[ 123 I]iodococaine, has been prepared by oxidative destannylation of the tributyltin analog and shown to interact with cocaine binding sites in rat brain striatal membranes. It may thus be a suitable SPECT radiotracer for studies of the dopamine reuptake site in neurodegenerative diseases. (Author)

  14. Human striatal recordings reveal abnormal discharge of projection neurons in Parkinson's disease.

    Science.gov (United States)

    Singh, Arun; Mewes, Klaus; Gross, Robert E; DeLong, Mahlon R; Obeso, José A; Papa, Stella M

    2016-08-23

    Circuitry models of Parkinson's disease (PD) are based on striatal dopamine loss and aberrant striatal inputs into the basal ganglia network. However, extrastriatal mechanisms have increasingly been the focus of attention, whereas the status of striatal discharges in the parkinsonian human brain remains conjectural. We now report the activity pattern of striatal projection neurons (SPNs) in patients with PD undergoing deep brain stimulation surgery, compared with patients with essential tremor (ET) and isolated dystonia (ID). The SPN activity in ET was very low (2.1 ± 0.1 Hz) and reminiscent of that found in normal animals. In contrast, SPNs in PD fired at much higher frequency (30.2 ± 1.2 Hz) and with abundant spike bursts. The difference between PD and ET was reproduced between 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine-treated and normal nonhuman primates. The SPN activity was also increased in ID, but to a lower level compared with the hyperactivity observed in PD. These results provide direct evidence that the striatum contributes significantly altered signals to the network in patients with PD.

  15. Diversity in Long-Term Synaptic Plasticity at Inhibitory Synapses of Striatal Spiny Neurons

    Science.gov (United States)

    Rueda-Orozco, Pavel E.; Mendoza, Ernesto; Hernandez, Ricardo; Aceves, Jose J.; Ibanez-Sandoval, Osvaldo; Galarraga, Elvira; Bargas, Jose

    2009-01-01

    Procedural memories and habits are posited to be stored in the basal ganglia, whose intrinsic circuitries possess important inhibitory connections arising from striatal spiny neurons. However, no information about long-term plasticity at these synapses is available. Therefore, this work describes a novel postsynaptically dependent long-term…

  16. Fronto-striatal glutamate in children with Tourette's disorder and attention-deficit/hyperactivity disorder

    Directory of Open Access Journals (Sweden)

    Jilly Naaijen

    2017-01-01

    Conclusion: We found no evidence for glutamatergic neuropathology in TD or ADHD within the fronto-striatal circuits. However, the correlation of OC-symptoms with ACC glutamate concentrations suggests that altered glutamatergic transmission is involved in OC-symptoms within TD, but this needs further investigation.

  17. Fronto-striatal glutamate in children with Tourette's disorder and attention-deficit/hyperactivity disorder

    NARCIS (Netherlands)

    Naaijen, Jilly; Forde, Natalie J.; Lythgoe, David J.; Akkermans, Sophie E. A.; Openneer, Thaira J. C.; Dietrich, Andrea; Zwiers, Marcel P.; Hoekstra, Pieter J.; Buitelaar, Jan K.

    2017-01-01

    Objective: Both Tourette's disorder (TD) and attention-deficit/hyperactivity disorder (ADHD) have been related to abnormalities in glutamatergic neurochemistry in the fronto-striatal circuitry. TD and ADHD often co-occur and the neural underpinnings of this co-occurrence have been insufficiently

  18. Adversity in childhood linked to elevated striatal dopamine function in adulthood.

    Science.gov (United States)

    Egerton, Alice; Valmaggia, Lucia R; Howes, Oliver D; Day, Fern; Chaddock, Christopher A; Allen, Paul; Winton-Brown, Toby T; Bloomfield, Michael A P; Bhattacharyya, Sagnik; Chilcott, Jack; Lappin, Julia M; Murray, Robin M; McGuire, Philip

    2016-10-01

    Childhood adversity increases the risk of psychosis in adulthood. Theoretical and animal models suggest that this effect may be mediated by increased striatal dopamine neurotransmission. The primary objective of this study was to examine the relationship between adversity in childhood and striatal dopamine function in early adulthood. Secondary objectives were to compare exposure to childhood adversity and striatal dopamine function in young people at ultra high risk (UHR) of psychosis and healthy volunteers. Sixty-seven young adults, comprising 47 individuals at UHR for psychosis and 20 healthy volunteers were recruited from the same geographic area and were matched for age, gender and substance use. Presynaptic dopamine function in the associative striatum was assessed using 18F-DOPA positron emission tomography. Childhood adversity was assessed using the Childhood Experience of Care and Abuse questionnaire. Within the sample as a whole, both severe physical or sexual abuse (T63=2.92; P=0.005), and unstable family arrangements (T57=2.80; P=0.007) in childhood were associated with elevated dopamine function in the associative striatum in adulthood. Comparison of the UHR and volunteer subgroups revealed similar incidence of childhood adverse experiences, and there was no significant group difference in dopamine function. This study provides evidence that childhood adversity is linked to elevated striatal dopamine function in adulthood. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  19. Striatal Dopamine Transporter Binding Does Not Correlate with Clinical Severity in Dementia with Lewy Bodies

    DEFF Research Database (Denmark)

    Ziebell, Morten; Andersen, Birgitte B; Pinborg, Lars H

    2013-01-01

    cognitively evaluated with the Mini Mental State Examination. RESULTS: There was no correlation between Mini Mental State Examination, Hoehn and Yahr score, fluctuations or hallucinations, and striatal DAT availability as measured with (123)I-PE2I and SPECT. CONCLUSION: In patients with newly diagnosed DLB...

  20. Functional connectivity modeling of consistent cortico-striatal degeneration in Huntington's disease

    Directory of Open Access Journals (Sweden)

    Imis Dogan

    2015-01-01

    Full Text Available Huntington's disease (HD is a progressive neurodegenerative disorder characterized by a complex neuropsychiatric phenotype. In a recent meta-analysis we identified core regions of consistent neurodegeneration in premanifest HD in the striatum and middle occipital gyrus (MOG. For early manifest HD convergent evidence of atrophy was most prominent in the striatum, motor cortex (M1 and inferior frontal junction (IFJ. The aim of the present study was to functionally characterize this topography of brain atrophy and to investigate differential connectivity patterns formed by consistent cortico-striatal atrophy regions in HD. Using areas of striatal and cortical atrophy at different disease stages as seeds, we performed task-free resting-state and task-based meta-analytic connectivity modeling (MACM. MACM utilizes the large data source of the BrainMap database and identifies significant areas of above-chance co-activation with the seed-region via the activation-likelihood-estimation approach. In order to delineate functional networks formed by cortical as well as striatal atrophy regions we computed the conjunction between the co-activation profiles of striatal and cortical seeds in the premanifest and manifest stages of HD, respectively. Functional characterization of the seeds was obtained using the behavioral meta-data of BrainMap. Cortico-striatal atrophy seeds of the premanifest stage of HD showed common co-activation with a rather cognitive network including the striatum, anterior insula, lateral prefrontal, premotor, supplementary motor and parietal regions. A similar but more pronounced co-activation pattern, additionally including the medial prefrontal cortex and thalamic nuclei was found with striatal and IFJ seeds at the manifest HD stage. The striatum and M1 were functionally connected mainly to premotor and sensorimotor areas, posterior insula, putamen and thalamus. Behavioral characterization of the seeds confirmed that experiments

  1. Role of contingency in striatal response to incentive in adolescents with anxiety.

    Science.gov (United States)

    Benson, Brenda E; Guyer, Amanda E; Nelson, Eric E; Pine, Daniel S; Ernst, Monique

    2015-03-01

    This study examines the effect of contingency on reward function in anxiety. We define contingency as the aspect of a situation in which the outcome is determined by one's action-that is, when there is a direct link between one's action and the outcome of the action. Past findings in adolescents with anxiety or at risk for anxiety have revealed hypersensitive behavioral and neural responses to higher value rewards with correct performance. This hypersensitivity to highly valued (salient) actions suggests that the value of actions is determined not only by outcome magnitude, but also by the degree to which the outcome is contingent on correct performance. Thus, contingency and incentive value might each modulate reward responses in unique ways in anxiety. Using fMRI with a monetary reward task, striatal response to cue anticipation is compared in 18 clinically anxious and 20 healthy adolescents. This task manipulates orthogonally reward contingency and incentive value. Findings suggest that contingency modulates the neural response to incentive magnitude differently in the two groups. Specifically, during the contingent condition, right-striatal response tracks incentive value in anxious, but not healthy, adolescents. During the noncontingent condition, striatal response is bilaterally stronger to low than to high incentive in anxious adolescents, while healthy adolescents exhibit the expected opposite pattern. Both contingency and reward magnitude differentiate striatal activation in anxious versus healthy adolescents. These findings may reflect exaggerated concern about performance and/or alterations of striatal coding of reward value in anxious adolescents. Abnormalities in reward function in anxiety may have treatment implications.

  2. Striatal dopamine transmission is subtly modified in human A53Tα-synuclein overexpressing mice.

    Directory of Open Access Journals (Sweden)

    Nicola J Platt

    Full Text Available Mutations in, or elevated dosage of, SNCA, the gene for α-synuclein (α-syn, cause familial Parkinson's disease (PD. Mouse lines overexpressing the mutant human A53Tα-syn may represent a model of early PD. They display progressive motor deficits, abnormal cellular accumulation of α-syn, and deficits in dopamine-dependent corticostriatal plasticity, which, in the absence of overt nigrostriatal degeneration, suggest there are age-related deficits in striatal dopamine (DA signalling. In addition A53Tα-syn overexpression in cultured rodent neurons has been reported to inhibit transmitter release. Therefore here we have characterized for the first time DA release in the striatum of mice overexpressing human A53Tα-syn, and explored whether A53Tα-syn overexpression causes deficits in the release of DA. We used fast-scan cyclic voltammetry to detect DA release at carbon-fibre microelectrodes in acute striatal slices from two different lines of A53Tα-syn-overexpressing mice, at up to 24 months. In A53Tα-syn overexpressors, mean DA release evoked by a single stimulus pulse was not different from wild-types, in either dorsal striatum or nucleus accumbens. However the frequency responsiveness of DA release was slightly modified in A53Tα-syn overexpressors, and in particular showed slight deficiency when the confounding effects of striatal ACh acting at presynaptic nicotinic receptors (nAChRs were antagonized. The re-release of DA was unmodified after single-pulse stimuli, but after prolonged stimulation trains, A53Tα-syn overexpressors showed enhanced recovery of DA release at old age, in keeping with elevated striatal DA content. In summary, A53Tα-syn overexpression in mice causes subtle changes in the regulation of DA release in the striatum. While modest, these modifications may indicate or contribute to striatal dysfunction.

  3. The basal ganglia matching tools package for striatal uptake semi-quantification: description and validation

    International Nuclear Information System (INIS)

    Calvini, Piero; Rodriguez, Guido; Nobili, Flavio; Inguglia, Fabrizio; Mignone, Alessandro; Guerra, Ugo P.

    2007-01-01

    To design a novel algorithm (BasGan) for automatic segmentation of striatal 123 I-FP-CIT SPECT. The BasGan algorithm is based on a high-definition, three-dimensional (3D) striatal template, derived from Talairach's atlas. A blurred template, obtained by convolving the former with a 3D Gaussian kernel (FWHM = 10 mm), approximates striatal activity distribution. The algorithm performs translations and scale transformation on the bicommissural aligned image to set the striatal templates with standard size in an appropriate initial position. An optimization protocol automatically performs fine adjustments in the positioning of blurred templates to best match the radioactive counts, and locates an occipital ROI for background evaluation. Partial volume effect correction is included in the process of uptake computation of caudate, putamen and background. Experimental validation was carried out by means of six acquisitions of an anthropomorphic striatal phantom. The BasGan software was applied to a first set of patients with Parkinson's disease (PD) versus patients affected by essential tremor. A highly significant correlation was achieved between true binding potential and measured 123 I activity from the phantom. 123 I-FP-CIT uptake was significantly lower in all basal ganglia in the PD group versus controls with both BasGan and a conventional ROI method used for comparison, but particularly with the former. Correlations with the motor UPDRS score were far more significant with the BasGan. The novel BasGan algorithm automatically performs the 3D segmentation of striata. Because co-registered MRI is not needed, it can be used by all nuclear medicine departments, since it is freely available on the Web. (orig.)

  4. Striatal cholinergic interneurons and D2 receptor-expressing GABAergic medium spiny neurons regulate tardive dyskinesia.

    Science.gov (United States)

    Bordia, Tanuja; Zhang, Danhui; Perez, Xiomara A; Quik, Maryka

    2016-12-01

    Tardive dyskinesia (TD) is a drug-induced movement disorder that arises with antipsychotics. These drugs are the mainstay of treatment for schizophrenia and bipolar disorder, and are also prescribed for major depression, autism, attention deficit hyperactivity, obsessive compulsive and post-traumatic stress disorder. There is thus a need for therapies to reduce TD. The present studies and our previous work show that nicotine administration decreases haloperidol-induced vacuous chewing movements (VCMs) in rodent TD models, suggesting a role for the nicotinic cholinergic system. Extensive studies also show that D2 dopamine receptors are critical to TD. However, the precise involvement of striatal cholinergic interneurons and D2 medium spiny neurons (MSNs) in TD is uncertain. To elucidate their role, we used optogenetics with a focus on the striatum because of its close links to TD. Optical stimulation of striatal cholinergic interneurons using cholineacetyltransferase (ChAT)-Cre mice expressing channelrhodopsin2-eYFP decreased haloperidol-induced VCMs (~50%), with no effect in control-eYFP mice. Activation of striatal D2 MSNs using Adora2a-Cre mice expressing channelrhodopsin2-eYFP also diminished antipsychotic-induced VCMs, with no change in control-eYFP mice. In both ChAT-Cre and Adora2a-Cre mice, stimulation or mecamylamine alone similarly decreased VCMs with no further decline with combined treatment, suggesting nAChRs are involved. Striatal D2 MSN activation in haloperidol-treated Adora2a-Cre mice increased c-Fos + D2 MSNs and decreased c-Fos + non-D2 MSNs, suggesting a role for c-Fos. These studies provide the first evidence that optogenetic stimulation of striatal cholinergic interneurons and GABAergic MSNs modulates VCMs, and thus possibly TD. Moreover, they suggest nicotinic receptor drugs may reduce antipsychotic-induced TD. Copyright © 2016 Elsevier Inc. All rights reserved.

  5. Nature or Nurture? Determining the Heritability of Human Striatal Dopamine Function: an [18F]-DOPA PET Study

    Science.gov (United States)

    Stokes, Paul R A; Shotbolt, Paul; Mehta, Mitul A; Turkheimer, Eric; Benecke, Aaf; Copeland, Caroline; Turkheimer, Federico E; Lingford-Hughes, Anne R; Howes, Oliver D

    2013-01-01

    Striatal dopamine function is important for normal personality, cognitive processes and behavior, and abnormalities are linked to a number of neuropsychiatric disorders. However, no studies have examined the relative influence of genetic inheritance and environmental factors in determining striatal dopamine function. Using [18F]-DOPA positron emission tomography (PET), we sought to determine the heritability of presynaptic striatal dopamine function by comparing variability in uptake values in same sex monozygotic (MZ) twins to dizygotic (DZ) twins. Nine MZ and 10 DZ twin pairs underwent high-resolution [18F]-DOPA PET to assess presynaptic striatal dopamine function. Uptake values for the overall striatum and functional striatal subdivisions were determined by a Patlak analysis using a cerebellar reference region. Heritability, shared environmental effects and non-shared individual-specific effects were estimated using a region of interest (ROI) analysis and a confirmatory parametric analysis. Overall striatal heritability estimates from the ROI and parametric analyses were 0.44 and 0.33, respectively. We found a distinction between striatal heritability in the functional subdivisions, with the greatest heritability estimates occurring in the sensorimotor striatum and the greatest effect of individual-specific environmental factors in the limbic striatum. Our results indicate that variation in overall presynaptic striatal dopamine function is determined by a combination of genetic factors and individual-specific environmental factors, with familial environmental effects having no effect. These findings underline the importance of individual-specific environmental factors for striatal dopaminergic function, particularly in the limbic striatum, with implications for understanding neuropsychiatric disorders such as schizophrenia and addictions. PMID:23093224

  6. Collection of offshore human error probability data

    International Nuclear Information System (INIS)

    Basra, Gurpreet; Kirwan, Barry

    1998-01-01

    Accidents such as Piper Alpha have increased concern about the effects of human errors in complex systems. Such accidents can in theory be predicted and prevented by risk assessment, and in particular human reliability assessment (HRA), but HRA ideally requires qualitative and quantitative human error data. A research initiative at the University of Birmingham led to the development of CORE-DATA, a Computerised Human Error Data Base. This system currently contains a reasonably large number of human error data points, collected from a variety of mainly nuclear-power related sources. This article outlines a recent offshore data collection study, concerned with collecting lifeboat evacuation data. Data collection methods are outlined and a selection of human error probabilities generated as a result of the study are provided. These data give insights into the type of errors and human failure rates that could be utilised to support offshore risk analyses

  7. Analysis of error patterns in clinical radiotherapy

    International Nuclear Information System (INIS)

    Macklis, Roger; Meier, Tim; Barrett, Patricia; Weinhous, Martin

    1996-01-01

    individual disease sites although this relationship was confounded by treatment complexity issues. Most brachytherapy discrepancies were related to unanticipated patient intervention or movement. Minor blocking errors were the most common category of error ((21(59)) total external beam incidents) followed by field size discrepancies ((8(59))) and prescription mistakes ((6(59))). There were no adverse medical outcomes of any sort associated with the errors. Conclusions: We conclude that error rates in large tertiary care radiation oncology practices may be very low, and appear to compare quite favorably with reported error rates in other branches of medicine. Increases in patient volume requiring extended hours (12-14 hours per day of operating time) do not necessarily cause increased error rates or error severity. Error analysis can serve to predict error-prone components of the clinical operation that may lend themselves to additional automated or administrative safeguards as practice volumes change

  8. Quantifying and handling errors in instrumental measurements using the measurement error theory

    DEFF Research Database (Denmark)

    Andersen, Charlotte Møller; Bro, R.; Brockhoff, P.B.

    2003-01-01

    . This is a new way of using the measurement error theory. Reliability ratios illustrate that the models for the two fish species are influenced differently by the error. However, the error seems to influence the predictions of the two reference measures in the same way. The effect of using replicated x...... measurements. A new general formula is given for how to correct the least squares regression coefficient when a different number of replicated x-measurements is used for prediction than for calibration. It is shown that the correction should be applied when the number of replicates in prediction is less than...

  9. Error Modeling and Design Optimization of Parallel Manipulators

    DEFF Research Database (Denmark)

    Wu, Guanglei

    /backlash, manufacturing and assembly errors and joint clearances. From the error prediction model, the distributions of the pose errors due to joint clearances are mapped within its constant-orientation workspace and the correctness of the developed model is validated experimentally. ix Additionally, using the screw......, dynamic modeling etc. Next, the rst-order dierential equation of the kinematic closure equation of planar parallel manipulator is obtained to develop its error model both in Polar and Cartesian coordinate systems. The established error model contains the error sources of actuation error...

  10. Applying Intelligent Algorithms to Automate the Identification of Error Factors.

    Science.gov (United States)

    Jin, Haizhe; Qu, Qingxing; Munechika, Masahiko; Sano, Masataka; Kajihara, Chisato; Duffy, Vincent G; Chen, Han

    2018-05-03

    Medical errors are the manifestation of the defects occurring in medical processes. Extracting and identifying defects as medical error factors from these processes are an effective approach to prevent medical errors. However, it is a difficult and time-consuming task and requires an analyst with a professional medical background. The issues of identifying a method to extract medical error factors and reduce the extraction difficulty need to be resolved. In this research, a systematic methodology to extract and identify error factors in the medical administration process was proposed. The design of the error report, extraction of the error factors, and identification of the error factors were analyzed. Based on 624 medical error cases across four medical institutes in both Japan and China, 19 error-related items and their levels were extracted. After which, they were closely related to 12 error factors. The relational model between the error-related items and error factors was established based on a genetic algorithm (GA)-back-propagation neural network (BPNN) model. Additionally, compared to GA-BPNN, BPNN, partial least squares regression and support vector regression, GA-BPNN exhibited a higher overall prediction accuracy, being able to promptly identify the error factors from the error-related items. The combination of "error-related items, their different levels, and the GA-BPNN model" was proposed as an error-factor identification technology, which could automatically identify medical error factors.

  11. Prediction error variance and expected response to selection, when selection is based on the best predictor – for Gaussian and threshold characters, traits following a Poisson mixed model and survival traits

    Directory of Open Access Journals (Sweden)

    Jensen Just

    2002-05-01

    Full Text Available Abstract In this paper, we consider selection based on the best predictor of animal additive genetic values in Gaussian linear mixed models, threshold models, Poisson mixed models, and log normal frailty models for survival data (including models with time-dependent covariates with associated fixed or random effects. In the different models, expressions are given (when these can be found – otherwise unbiased estimates are given for prediction error variance, accuracy of selection and expected response to selection on the additive genetic scale and on the observed scale. The expressions given for non Gaussian traits are generalisations of the well-known formulas for Gaussian traits – and reflect, for Poisson mixed models and frailty models for survival data, the hierarchal structure of the models. In general the ratio of the additive genetic variance to the total variance in the Gaussian part of the model (heritability on the normally distributed level of the model or a generalised version of heritability plays a central role in these formulas.

  12. Errors in Neonatology

    OpenAIRE

    Antonio Boldrini; Rosa T. Scaramuzzo; Armando Cuttano

    2013-01-01

    Introduction: Danger and errors are inherent in human activities. In medical practice errors can lean to adverse events for patients. Mass media echo the whole scenario. Methods: We reviewed recent published papers in PubMed database to focus on the evidence and management of errors in medical practice in general and in Neonatology in particular. We compared the results of the literature with our specific experience in Nina Simulation Centre (Pisa, Italy). Results: In Neonatology the main err...

  13. Systematic Procedural Error

    National Research Council Canada - National Science Library

    Byrne, Michael D

    2006-01-01

    .... This problem has received surprisingly little attention from cognitive psychologists. The research summarized here examines such errors in some detail both empirically and through computational cognitive modeling...

  14. Clinical errors and medical negligence.

    Science.gov (United States)

    Oyebode, Femi

    2013-01-01

    This paper discusses the definition, nature and origins of clinical errors including their prevention. The relationship between clinical errors and medical negligence is examined as are the characteristics of litigants and events that are the source of litigation. The pattern of malpractice claims in different specialties and settings is examined. Among hospitalized patients worldwide, 3-16% suffer injury as a result of medical intervention, the most common being the adverse effects of drugs. The frequency of adverse drug effects appears superficially to be higher in intensive care units and emergency departments but once rates have been corrected for volume of patients, comorbidity of conditions and number of drugs prescribed, the difference is not significant. It is concluded that probably no more than 1 in 7 adverse events in medicine result in a malpractice claim and the factors that predict that a patient will resort to litigation include a prior poor relationship with the clinician and the feeling that the patient is not being kept informed. Methods for preventing clinical errors are still in their infancy. The most promising include new technologies such as electronic prescribing systems, diagnostic and clinical decision-making aids and error-resistant systems. Copyright © 2013 S. Karger AG, Basel.

  15. Reward Inference by Primate Prefrontal and Striatal Neurons

    OpenAIRE

    Pan, Xiaochuan; Fan, Hongwei; Sawa, Kosuke; Tsuda, Ichiro; Tsukada, Minoru; Sakagami, Masamichi

    2014-01-01

    The brain contains multiple yet distinct systems involved in reward prediction. To understand the nature of these processes, we recorded single-unit activity from the lateral prefrontal cortex (LPFC) and the striatum in monkeys performing a reward inference task using an asymmetric reward schedule. We found that neurons both in the LPFC and in the striatum predicted reward values for stimuli that had been previously well experienced with set reward quantities in the asymmetric reward task. Im...

  16. Imaging of striatal dopamine transporters in rat brain with single pinhole SPECT and co-aligned MRI is highly reproducible

    International Nuclear Information System (INIS)

    Booij, Jan; Bruin, Kora de; Win, Maartje M.L. de; Lavini, Cristina Mphil; Heeten, Gerard J. den; Habraken, Jan

    2003-01-01

    A recently developed pinhole high-resolution SPECT system was used to measure striatal to non-specific binding ratios in rats (n = 9), after injection of the dopamine transporter ligand 123 I-FP-CIT, and to assess its test/retest reproducibility. For co-alignment purposes, the rat brain was imaged on a 1.5 Tesla clinical MRI scanner using a specially developed surface coil. The SPECT images showed clear striatal uptake. On the MR images, cerebral and extra-cerebral structures could be easily delineated. The mean striatal to non-specific [ 123 I]FP-CIT binding ratios of the test/retest studies were 1.7 ± 0.2 and 1.6 ± 0.2, respectively. The test/retest variability was approximately 9%. We conclude that the assessment of striatal [ 123 I]FP-CIT binding ratios in rats is highly reproducible

  17. Pre-pulse inhibition and striatal dopamine in subjects at an ultra-high risk for psychosis

    NARCIS (Netherlands)

    de Koning, Mariken B.; Bloemen, Oswald J. N.; van Duin, Esther D. A.; Booij, Jan; Abel, Kathryn M.; de Haan, Lieuwe; Linszen, Don H.; van Amelsvoort, Thérèse A. M. J.

    2014-01-01

    Reduced prepulse inhibition (PPI) of the acoustic startle response is thought to represent a robust biomarker in schizophrenia. Reduced PPI has been demonstrated in subjects at ultra high risk (UHR) for developing psychosis. Imaging studies report disruption of striatal dopaminergic

  18. Learning from Errors

    Science.gov (United States)

    Metcalfe, Janet

    2017-01-01

    Although error avoidance during learning appears to be the rule in American classrooms, laboratory studies suggest that it may be a counterproductive strategy, at least for neurologically typical students. Experimental investigations indicate that errorful learning followed by corrective feedback is beneficial to learning. Interestingly, the…

  19. HdhQ111 Mice Exhibit Tissue Specific Metabolite Profiles that Include Striatal Lipid Accumulation

    Science.gov (United States)

    Carroll, Jeffrey B.; Deik, Amy; Fossale, Elisa; Weston, Rory M.; Guide, Jolene R.; Arjomand, Jamshid; Kwak, Seung; Clish, Clary B.; MacDonald, Marcy E.

    2015-01-01

    The HTT CAG expansion mutation causes Huntington’s Disease and is associated with a wide range of cellular consequences, including altered metabolism. The mutant allele is expressed widely, in all tissues, but the striatum and cortex are especially vulnerable to its effects. To more fully understand this tissue-specificity, early in the disease process, we asked whether the metabolic impact of the mutant CAG expanded allele in heterozygous B6.HdhQ111/+ mice would be common across tissues, or whether tissues would have tissue-specific responses and whether such changes may be affected by diet. Specifically, we cross-sectionally examined steady state metabolite concentrations from a range of tissues (plasma, brown adipose tissue, cerebellum, striatum, liver, white adipose tissue), using an established liquid chromatography-mass spectrometry pipeline, from cohorts of 8 month old mutant and wild-type littermate mice that were fed one of two different high-fat diets. The differential response to diet highlighted a proportion of metabolites in all tissues, ranging from 3% (7/219) in the striatum to 12% (25/212) in white adipose tissue. By contrast, the mutant CAG-expanded allele primarily affected brain metabolites, with 14% (30/219) of metabolites significantly altered, compared to wild-type, in striatum and 11% (25/224) in the cerebellum. In general, diet and the CAG-expanded allele both elicited metabolite changes that were predominantly tissue-specific and non-overlapping, with evidence for mutation-by-diet interaction in peripheral tissues most affected by diet. Machine-learning approaches highlighted the accumulation of diverse lipid species as the most genotype-predictive metabolite