Discriminative learning for speech recognition

CERN Document Server

He, Xiadong

2008-01-01

In this book, we introduce the background and mainstream methods of probabilistic modeling and discriminative parameter optimization for speech recognition. The specific models treated in depth include the widely used exponential-family distributions and the hidden Markov model. A detailed study is presented on unifying the common objective functions for discriminative learning in speech recognition, namely maximum mutual information (MMI), minimum classification error, and minimum phone/word error. The unification is presented, with rigorous mathematical analysis, in a common rational-functio

Picture-Word Differences in Discrimination Learning: II. Effects of Conceptual Categories.

Science.gov (United States)

Bourne, Lyle E., Jr.; And Others

A well established finding in the discrimination learning literature is that pictures are learned more rapidly than their associated verbal labels. It was hypothesized in this study that the usual superiority of pictures over words in a discrimination list containing same-instance repetitions would disappear in a discrimination list containing…

Pigeons can discriminate "good" and "bad" paintings by children.

Science.gov (United States)

Watanabe, Shigeru

2010-01-01

Humans have the unique ability to create art, but non-human animals may be able to discriminate "good" art from "bad" art. In this study, I investigated whether pigeons could be trained to discriminate between paintings that had been judged by humans as either "bad" or "good". To do this, adult human observers first classified several children's paintings as either "good" (beautiful) or "bad" (ugly). Using operant conditioning procedures, pigeons were then reinforced for pecking at "good" paintings. After the pigeons learned the discrimination task, they were presented with novel pictures of both "good" and "bad" children's paintings to test whether they had successfully learned to discriminate between these two stimulus categories. The results showed that pigeons could discriminate novel "good" and "bad" paintings. Then, to determine which cues the subjects used for the discrimination, I conducted tests of the stimuli when the paintings were of reduced size or grayscale. In addition, I tested their ability to discriminate when the painting stimuli were mosaic and partial occluded. The pigeons maintained discrimination performance when the paintings were reduced in size. However, discrimination performance decreased when stimuli were presented as grayscale images or when a mosaic effect was applied to the original stimuli in order to disrupt spatial frequency. Thus, the pigeons used both color and pattern cues for their discrimination. The partial occlusion did not disrupt the discriminative behavior suggesting that the pigeons did not attend to particular parts, namely upper, lower, left or right half, of the paintings. These results suggest that the pigeons are capable of learning the concept of a stimulus class that humans name "good" pictures. The second experiment showed that pigeons learned to discriminate watercolor paintings from pastel paintings. The subjects showed generalization to novel paintings. Then, as the first experiment, size reduction test

Polarimetric SAR image classification based on discriminative dictionary learning model

Science.gov (United States)

Sang, Cheng Wei; Sun, Hong

2018-03-01

Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

Dorsolateral Striatum Engagement Interferes with Early Discrimination Learning

Directory of Open Access Journals (Sweden)

Hadley C. Bergstrom

2018-05-01

Full Text Available Summary: In current models, learning the relationship between environmental stimuli and the outcomes of actions involves both stimulus-driven and goal-directed systems, mediated in part by the DLS and DMS, respectively. However, though these models emphasize the importance of the DLS in governing actions after extensive experience has accumulated, there is growing evidence of DLS engagement from the onset of training. Here, we used in vivo photosilencing to reveal that DLS recruitment interferes with early touchscreen discrimination learning. We also show that the direct output pathway of the DLS is preferentially recruited and causally involved in early learning and find that silencing the normal contribution of the DLS produces plasticity-related alterations in a PL-DMS circuit. These data provide further evidence suggesting that the DLS is recruited in the construction of stimulus-elicited actions that ultimately automate behavior and liberate cognitive resources for other demands, but with a cost to performance at the outset of learning. : What is the contribution of the DLS in early discrimination learning? Bergstrom et al. show using in vivo optogenetics, fluorescence in situ hybridization, and brain-wide activity mapping that silencing the DLS facilitates early discrimination learning, drives activity in a parallel PL-DMS circuit, and preferentially recruits the DLS “direct” output pathway. Keywords: striatum, reward, goal-directed, habit, optogenetics, plasticity, cognition, Arc

Conditional discrimination learning: A critique and amplification

OpenAIRE

Schrier, Allan M.; Thompson, Claudia R.

1980-01-01

Carter and Werner recently reviewed the literature on conditional discrimination learning by pigeons, which consists of studies of matching-to-sample and oddity-from-sample. They also discussed three models of such learning: the “multiple-rule” model (learning of stimulus-specific relations), the “configuration” model, and the “single-rule” model (concept learning). Although their treatment of the multiple-rule model, which seems most applicable to the pigeon data, is generally excellent, the...

Dynamic functional brain networks involved in simple visual discrimination learning.

Science.gov (United States)

Fidalgo, Camino; Conejo, Nélida María; González-Pardo, Héctor; Arias, Jorge Luis

2014-10-01

Visual discrimination tasks have been widely used to evaluate many types of learning and memory processes. However, little is known about the brain regions involved at different stages of visual discrimination learning. We used cytochrome c oxidase histochemistry to evaluate changes in regional brain oxidative metabolism during visual discrimination learning in a water-T maze at different time points during training. As compared with control groups, the results of the present study reveal the gradual activation of cortical (prefrontal and temporal cortices) and subcortical brain regions (including the striatum and the hippocampus) associated to the mastery of a simple visual discrimination task. On the other hand, the brain regions involved and their functional interactions changed progressively over days of training. Regions associated with novelty, emotion, visuo-spatial orientation and motor aspects of the behavioral task seem to be relevant during the earlier phase of training, whereas a brain network comprising the prefrontal cortex was found along the whole learning process. This study highlights the relevance of functional interactions among brain regions to investigate learning and memory processes. Copyright © 2014 Elsevier Inc. All rights reserved.

Perceptual Learning: 12-Month-Olds' Discrimination of Monkey Faces

Science.gov (United States)

Fair, Joseph; Flom, Ross; Jones, Jacob; Martin, Justin

2012-01-01

Six-month-olds reliably discriminate different monkey and human faces whereas 9-month-olds only discriminate different human faces. It is often falsely assumed that perceptual narrowing reflects a permanent change in perceptual abilities. In 3 experiments, ninety-six 12-month-olds' discrimination of unfamiliar monkey faces was examined. Following…

Interaction between age and perceptual similarity in olfactory discrimination learning in F344 rats: relationships with spatial learning

Science.gov (United States)

Yoder, Wendy M.; Gaynor, Leslie S.; Burke, Sara N.; Setlow, Barry; Smith, David W.; Bizon, Jennifer L.

2017-01-01

Emerging evidence suggests that aging is associated with a reduced ability to distinguish perceptually similar stimuli in one’s environment. As the ability to accurately perceive and encode sensory information is foundational for explicit memory, understanding the neurobiological underpinnings of discrimination impairments that emerge with advancing age could help elucidate the mechanisms of mnemonic decline. To this end, there is a need for preclinical approaches that robustly and reliably model age-associated perceptual discrimination deficits. Taking advantage of rodents’ exceptional olfactory abilities, the present study applied rigorous psychophysical techniques to the evaluation of discrimination learning in young and aged F344 rats. Aging did not influence odor detection thresholds or the ability to discriminate between perceptually distinct odorants. In contrast, aged rats were disproportionately impaired relative to young on problems that required discriminations between perceptually similar olfactory stimuli. Importantly, these disproportionate impairments in discrimination learning did not simply reflect a global learning impairment in aged rats, as they performed other types of difficult discriminations on par with young rats. Among aged rats, discrimination deficits were strongly associated with spatial learning deficits. These findings reveal a new, sensitive behavioral approach for elucidating the neural mechanisms of cognitive decline associated with normal aging. PMID:28259065

Spatial discrimination and visual discrimination

DEFF Research Database (Denmark)

Haagensen, Annika M. J.; Grand, Nanna; Klastrup, Signe

2013-01-01

Two methods investigating learning and memory in juvenile Gottingen minipigs were evaluated for potential use in preclinical toxicity testing. Twelve minipigs were tested using a spatial hole-board discrimination test including a learning phase and two memory phases. Five minipigs were tested...... in a visual discrimination test. The juvenile minipigs were able to learn the spatial hole-board discrimination test and showed improved working and reference memory during the learning phase. Performance in the memory phases was affected by the retention intervals, but the minipigs were able to remember...... the concept of the test in both memory phases. Working memory and reference memory were significantly improved in the last trials of the memory phases. In the visual discrimination test, the minipigs learned to discriminate between the three figures presented to them within 9-14 sessions. For the memory test...

Learning for pitch and melody discrimination in congenital amusia.

Science.gov (United States)

Whiteford, Kelly L; Oxenham, Andrew J

2018-03-23

Congenital amusia is currently thought to be a life-long neurogenetic disorder in music perception, impervious to training in pitch or melody discrimination. This study provides an explicit test of whether amusic deficits can be reduced with training. Twenty amusics and 20 matched controls participated in four sessions of psychophysical training involving either pure-tone (500 Hz) pitch discrimination or a control task of lateralization (interaural level differences for bandpass white noise). Pure-tone pitch discrimination at low, medium, and high frequencies (500, 2000, and 8000 Hz) was measured before and after training (pretest and posttest) to determine the specificity of learning. Melody discrimination was also assessed before and after training using the full Montreal Battery of Evaluation of Amusia, the most widely used standardized test to diagnose amusia. Amusics performed more poorly than controls in pitch but not localization discrimination, but both groups improved with practice on the trained stimuli. Learning was broad, occurring across all three frequencies and melody discrimination for all groups, including those who trained on the non-pitch control task. Following training, 11 of 20 amusics no longer met the global diagnostic criteria for amusia. A separate group of untrained controls (n = 20), who also completed melody discrimination and pretest, improved by an equal amount as trained controls on all measures, suggesting that the bulk of learning for the control group occurred very rapidly from the pretest. Thirty-one trained participants (13 amusics) returned one year later to assess long-term maintenance of pitch and melody discrimination. On average, there was no change in performance between posttest and one-year follow-up, demonstrating that improvements on pitch- and melody-related tasks in amusics and controls can be maintained. The findings indicate that amusia is not always a life-long deficit when using the current standard

Discrimination learning and attentional set formation in a mouse model of Fragile X.

Science.gov (United States)

Casten, Kimberly S; Gray, Annette C; Burwell, Rebecca D

2011-06-01

Fragile X Syndrome is the most prevalent genetic cause of mental retardation. Selective deficits in executive function, including inhibitory control and attention, are core features of the disorder. In humans, Fragile X results from a trinucleotide repeat in the Fmr1 gene that renders it functionally silent and has been modeled in mice by targeted deletion of the Fmr1 gene. Fmr1 knockout (KO) mice recapitulate many features of Fragile X syndrome, but evidence for deficits in executive function is inconsistent. To address this issue, we trained wild-type and Fmr1 KO mice on an experimental paradigm that assesses attentional set-shifting. Mice learned to discriminate between stimuli differing in two of three perceptual dimensions. Successful discrimination required attending only to the relevant dimension, while ignoring irrelevant dimensions. Mice were trained on three discriminations in the same perceptual dimension, each followed by a reversal. This procedure normally results in the formation of an attentional set to the relevant dimension. Mice were then required to shift attention and discriminate based on a previously irrelevant perceptual dimension. Wild-type mice exhibited the increase in trials to criterion expected when shifting attention from one perceptual dimension to another. In contrast, the Fmr1 KO group failed to show the expected increase, suggesting impairment in forming an attentional set. Fmr1 KO mice also exhibited a general impairment in learning discriminations and reversals. This is the first demonstration that Fmr1 KO mice show a deficit in attentional set formation.

Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning.

Science.gov (United States)

Wang, Jinhua; Yang, Xi; Cai, Hongmin; Tan, Wanchang; Jin, Cangzheng; Li, Li

2016-06-07

Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer.

Discriminative object tracking via sparse representation and online dictionary learning.

Science.gov (United States)

Xie, Yuan; Zhang, Wensheng; Li, Cuihua; Lin, Shuyang; Qu, Yanyun; Zhang, Yinghua

2014-04-01

We propose a robust tracking algorithm based on local sparse coding with discriminative dictionary learning and new keypoint matching schema. This algorithm consists of two parts: the local sparse coding with online updated discriminative dictionary for tracking (SOD part), and the keypoint matching refinement for enhancing the tracking performance (KP part). In the SOD part, the local image patches of the target object and background are represented by their sparse codes using an over-complete discriminative dictionary. Such discriminative dictionary, which encodes the information of both the foreground and the background, may provide more discriminative power. Furthermore, in order to adapt the dictionary to the variation of the foreground and background during the tracking, an online learning method is employed to update the dictionary. The KP part utilizes refined keypoint matching schema to improve the performance of the SOD. With the help of sparse representation and online updated discriminative dictionary, the KP part are more robust than the traditional method to reject the incorrect matches and eliminate the outliers. The proposed method is embedded into a Bayesian inference framework for visual tracking. Experimental results on several challenging video sequences demonstrate the effectiveness and robustness of our approach.

Human Drug Discrimination: Elucidating the Neuropharmacology of Commonly Abused Illicit Drugs.

Science.gov (United States)

Bolin, B Levi; Alcorn, Joseph L; Reynolds, Anna R; Lile, Joshua A; Stoops, William W; Rush, Craig R

2016-06-07

Drug-discrimination procedures empirically evaluate the control that internal drug states have over behavior. They provide a highly selective method to investigate the neuropharmacological underpinnings of the interoceptive effects of drugs in vivo. As a result, drug discrimination has been one of the most widely used assays in the field of behavioral pharmacology. Drug-discrimination procedures have been adapted for use with humans and are conceptually similar to preclinical drug-discrimination techniques in that a behavior is differentially reinforced contingent on the presence or absence of a specific interoceptive drug stimulus. This chapter provides a basic overview of human drug-discrimination procedures and reviews the extant literature concerning the use of these procedures to elucidate the underlying neuropharmacological mechanisms of commonly abused illicit drugs (i.e., stimulants, opioids, and cannabis) in humans. This chapter is not intended to review every available study that used drug-discrimination procedures in humans. Instead, when possible, exemplary studies that used a stimulant, opioid, or Δ 9 -tetrahydrocannabinol (the primary psychoactive constituent of cannabis) to assess the discriminative-stimulus effects of drugs in humans are reviewed for illustrative purposes. We conclude by commenting on the current state and future of human drug-discrimination research.

Dog's discrimination of human selfish and generous attitudes: the role of individual recognition, experience, and experimenters' gender.

Science.gov (United States)

Carballo, Fabricio; Freidin, Esteban; Putrino, Natalia; Shimabukuro, Carolina; Casanave, Emma; Bentosela, Mariana

2015-01-01

Discrimination of and memory for others' generous and selfish behaviors could be adaptive abilities in social animals. Dogs have seemingly expressed such skills in both direct and indirect interactions with humans. However, recent studies suggest that their capacity may rely on cues other than people's individual characteristics, such as the place where the person stands. Thus, the conditions under which dogs recognize individual humans when solving cooperative tasks still remains unclear. With the aim of contributing to this problem, we made dogs interact with two human experimenters, one generous (pointed towards the food, gave ostensive cues, and allowed the dog to eat it) and the other selfish (pointed towards the food, but ate it before the dog could have it). Then subjects could choose between them (studies 1-3). In study 1, dogs took several training trials to learn the discrimination between the generous and the selfish experimenters when both were of the same gender. In study 2, the discrimination was learned faster when the experimenters were of different gender as evidenced both by dogs' latencies to approach the bowl in training trials as well as by their choices in preference tests. Nevertheless, dogs did not get confused by gender when the experimenters were changed in between the training and the choice phase in study 3. We conclude that dogs spontaneously used human gender as a cue to discriminate between more and less cooperative experimenters. They also relied on some other personal feature which let them avoid being confused by gender when demonstrators were changed. We discuss these results in terms of dogs' ability to recognize individuals and the potential advantage of this skill for their lives in human environments.

Dog's discrimination of human selfish and generous attitudes: the role of individual recognition, experience, and experimenters' gender.

Directory of Open Access Journals (Sweden)

Fabricio Carballo

Full Text Available Discrimination of and memory for others' generous and selfish behaviors could be adaptive abilities in social animals. Dogs have seemingly expressed such skills in both direct and indirect interactions with humans. However, recent studies suggest that their capacity may rely on cues other than people's individual characteristics, such as the place where the person stands. Thus, the conditions under which dogs recognize individual humans when solving cooperative tasks still remains unclear. With the aim of contributing to this problem, we made dogs interact with two human experimenters, one generous (pointed towards the food, gave ostensive cues, and allowed the dog to eat it and the other selfish (pointed towards the food, but ate it before the dog could have it. Then subjects could choose between them (studies 1-3. In study 1, dogs took several training trials to learn the discrimination between the generous and the selfish experimenters when both were of the same gender. In study 2, the discrimination was learned faster when the experimenters were of different gender as evidenced both by dogs' latencies to approach the bowl in training trials as well as by their choices in preference tests. Nevertheless, dogs did not get confused by gender when the experimenters were changed in between the training and the choice phase in study 3. We conclude that dogs spontaneously used human gender as a cue to discriminate between more and less cooperative experimenters. They also relied on some other personal feature which let them avoid being confused by gender when demonstrators were changed. We discuss these results in terms of dogs' ability to recognize individuals and the potential advantage of this skill for their lives in human environments.

Weighted Discriminative Dictionary Learning based on Low-rank Representation

International Nuclear Information System (INIS)

Chang, Heyou; Zheng, Hao

2017-01-01

Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods. (paper)

Valence of Facial Cues Influences Sheep Learning in a Visual Discrimination Task

Directory of Open Access Journals (Sweden)

Lucille G. A. Bellegarde

2017-11-01

Full Text Available Sheep are one of the most studied farm species in terms of their ability to process information from faces, but little is known about their face-based emotion recognition abilities. We investigated (a whether sheep could use images of sheep faces taken in situation of varying valence as cues in a simultaneous discrimination task and (b whether the valence of the situation affects their learning performance. To accomplish this, we photographed faces of sheep in three situations inducing emotional states of neutral (ruminating in the home pen or negative valence (social isolation or aggressive interaction. Sheep (n = 35 first had to learn a discrimination task with colored cards. Animals that reached the learning criterion (n = 16 were then presented with pairs of images of the face of a single individual taken in the neutral situation and in one of the negative situations. Finally, sheep had to generalize what they had learned to new pairs of images of faces taken in the same situation, but of a different conspecific. All sheep that learned the discrimination task with colored cards reached the learning criterion with images of faces. Sheep that had to associate a negative image with a food reward learned faster than sheep that had to associate a neutral image with a reward. With the exception of sheep from the aggression-rewarded group, sheep generalized this discrimination to images of faces of different individuals. Our results suggest that sheep can perceive the emotional valence displayed on faces of conspecifics and that this valence affects learning processes.

Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning.

Science.gov (United States)

Zhou, Tao; Liu, Fanghui; Bhaskar, Harish; Yang, Jie

2017-09-12

In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can provide good discriminative representations of both target and background. We accomplish this by exploiting the recovery ability of low-rank matrices. That is if we assume that the data from the same class are linearly correlated, then the corresponding basis vectors learned from the training set of each class shall render the dictionary to become approximately low-rank. The proposed dictionary learning technique incorporates a reconstruction error that improves the reliability of classification. Also, a multiconstraint objective function is designed to enable active learning of a discriminative and robust dictionary. Further, an optimal solution is obtained by iteratively computing the dictionary, coefficients, and by simultaneously learning the classifier parameters. Finally, a simple yet effective likelihood function is implemented to estimate the optimal state of the target during tracking. Moreover, to make the dictionary adaptive to the variations of the target and background during tracking, an online update criterion is employed while learning the new dictionary. Experimental results on a publicly available benchmark dataset have demonstrated that the proposed tracking algorithm performs better than other state-of-the-art trackers.

Discrimination between smiling faces: Human observers vs. automated face analysis.

Science.gov (United States)

Del Líbano, Mario; Calvo, Manuel G; Fernández-Martín, Andrés; Recio, Guillermo

2018-05-11

This study investigated (a) how prototypical happy faces (with happy eyes and a smile) can be discriminated from blended expressions with a smile but non-happy eyes, depending on type and intensity of the eye expression; and (b) how smile discrimination differs for human perceivers versus automated face analysis, depending on affective valence and morphological facial features. Human observers categorized faces as happy or non-happy, or rated their valence. Automated analysis (FACET software) computed seven expressions (including joy/happiness) and 20 facial action units (AUs). Physical properties (low-level image statistics and visual saliency) of the face stimuli were controlled. Results revealed, first, that some blended expressions (especially, with angry eyes) had lower discrimination thresholds (i.e., they were identified as "non-happy" at lower non-happy eye intensities) than others (especially, with neutral eyes). Second, discrimination sensitivity was better for human perceivers than for automated FACET analysis. As an additional finding, affective valence predicted human discrimination performance, whereas morphological AUs predicted FACET discrimination. FACET can be a valid tool for categorizing prototypical expressions, but is currently more limited than human observers for discrimination of blended expressions. Configural processing facilitates detection of in/congruence(s) across regions, and thus detection of non-genuine smiling faces (due to non-happy eyes). Copyright © 2018 Elsevier B.V. All rights reserved.

Post-training depletions of basolateral amygdala serotonin fail to disrupt discrimination, retention, or reversal learning

Directory of Open Access Journals (Sweden)

G. Jesus eOchoa

2015-05-01

Full Text Available In goal-directed pursuits, the basolateral amygdala (BLA is critical in learning about changes in the value of rewards. BLA-lesioned rats show enhanced reversal learning, a task employed to measure the flexibility of response to changes in reward. Similarly, there is a trend for enhanced discrimination learning, suggesting that BLA may modulate formation of stimulus-reward associations. There is a parallel literature on the importance of serotonin (5HT in new stimulus-reward and reversal learning. Recent postulations implicate 5HT in learning from punishment. Whereas dopaminergic involvement is critical in behavioral activation and reinforcement, 5HT may be most critical for aversive processing and behavioral inhibition, complementary cognitive processes. Given these findings, a 5HT-mediated mechanism in BLA may mediate the facilitated learning observed previously. The present study investigated the effects of selective 5HT lesions in BLA using 5,7-dihydroxytryptamine (5,7-DHT versus infusions of saline (Sham on discrimination, retention, and deterministic reversal learning. Rats were required to reach an 85% correct pairwise discrimination and single reversal criterion prior to surgery. Postoperatively, rats were then tested on the 1 retention of the pretreatment discrimination pair 2 discrimination of a novel pair and 3 reversal learning performance. We found statistically comparable preoperative learning rates between groups, intact postoperative retention, and unaltered novel discrimination and reversal learning in 5,7-DHT rats. These findings suggest that 5HT in BLA is not required for formation and flexible adjustment of new stimulus-reward associations when the strategy to efficiently solve the task has already been learned. Given the complementary role of orbitofrontal cortex in reward learning and its interconnectivity with BLA, these findings add to the list of dissociable mechanisms for BLA and orbitofrontal cortex in reward learning.

Reduced autobiographical memory specificity is associated with impaired discrimination learning in anxiety disorder patients

Science.gov (United States)

Lenaert, Bert; Boddez, Yannick; Vervliet, Bram; Schruers, Koen; Hermans, Dirk

2015-01-01

Associative learning plays an important role in the development of anxiety disorders, but a thorough understanding of the variables that impact such learning is still lacking. We investigated whether individual differences in autobiographical memory specificity are related to discrimination learning and generalization. In an associative learning task, participants learned the association between two pictures of female faces and a non-aversive outcome. Subsequently, six morphed pictures functioning as generalization stimuli (GSs) were introduced. In a sample of healthy participants (Study 1), we did not find evidence for differences in discrimination learning as a function of memory specificity. In a sample of anxiety disorder patients (Study 2), individuals who were characterized by low memory specificity showed deficient discrimination learning relative to high specific individuals. In contrast to previous findings, results revealed no effect of memory specificity on generalization. These results indicate that impaired discrimination learning, previously shown in patients suffering from an anxiety disorder, may be—in part—due to limited memory specificity. Together, these studies emphasize the importance of incorporating cognitive variables in associative learning theories and their implications for the development of anxiety disorders. In addition, re-analyses of the data (Study 3) showed that patients suffering from panic disorder showed higher outcome expectancies in the presence of the stimulus that was never followed by an outcome during discrimination training, relative to patients suffering from other anxiety disorders and healthy participants. Because we used a neutral, non-aversive outcome (i.e., drawing of a lightning bolt), these data suggest that learning abnormalities in panic disorder may not be restricted to fear learning, but rather reflect a more general associative learning deficit that also manifests in fear irrelevant contexts. PMID

Semi-supervised learning for ordinal Kernel Discriminant Analysis.

Science.gov (United States)

Pérez-Ortiz, M; Gutiérrez, P A; Carbonero-Ruz, M; Hervás-Martínez, C

2016-12-01

Ordinal classification considers those classification problems where the labels of the variable to predict follow a given order. Naturally, labelled data is scarce or difficult to obtain in this type of problems because, in many cases, ordinal labels are given by a user or expert (e.g. in recommendation systems). Firstly, this paper develops a new strategy for ordinal classification where both labelled and unlabelled data are used in the model construction step (a scheme which is referred to as semi-supervised learning). More specifically, the ordinal version of kernel discriminant learning is extended for this setting considering the neighbourhood information of unlabelled data, which is proposed to be computed in the feature space induced by the kernel function. Secondly, a new method for semi-supervised kernel learning is devised in the context of ordinal classification, which is combined with our developed classification strategy to optimise the kernel parameters. The experiments conducted compare 6 different approaches for semi-supervised learning in the context of ordinal classification in a battery of 30 datasets, showing (1) the good synergy of the ordinal version of discriminant analysis and the use of unlabelled data and (2) the advantage of computing distances in the feature space induced by the kernel function. Copyright © 2016 Elsevier Ltd. All rights reserved.

Hyperspectral Image Classification Using Discriminative Dictionary Learning

International Nuclear Information System (INIS)

Zongze, Y; Hao, S; Kefeng, J; Huanxin, Z

2014-01-01

The hyperspectral image (HSI) processing community has witnessed a surge of papers focusing on the utilization of sparse prior for effective HSI classification. In sparse representation based HSI classification, there are two phases: sparse coding with an over-complete dictionary and classification. In this paper, we first apply a novel fisher discriminative dictionary learning method, which capture the relative difference in different classes. The competitive selection strategy ensures that atoms in the resulting over-complete dictionary are the most discriminative. Secondly, motivated by the assumption that spatially adjacent samples are statistically related and even belong to the same materials (same class), we propose a majority voting scheme incorporating contextual information to predict the category label. Experiment results show that the proposed method can effectively strengthen relative discrimination of the constructed dictionary, and incorporating with the majority voting scheme achieve generally an improved prediction performance

Comparing statistical and machine learning classifiers: alternatives for predictive modeling in human factors research.

Science.gov (United States)

Carnahan, Brian; Meyer, Gérard; Kuntz, Lois-Ann

2003-01-01

Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches--genetic programming and decision tree induction--were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.

Neighbors Based Discriminative Feature Difference Learning for Kinship Verification

DEFF Research Database (Denmark)

Duan, Xiaodong; Tan, Zheng-Hua

2015-01-01

In this paper, we present a discriminative feature difference learning method for facial image based kinship verification. To transform feature difference of an image pair to be discriminative for kinship verification, a linear transformation matrix for feature difference between an image pair...... than the commonly used feature concatenation, leading to a low complexity. Furthermore, there is no positive semi-definitive constrain on the transformation matrix while there is in metric learning methods, leading to an easy solution for the transformation matrix. Experimental results on two public...... databases show that the proposed method combined with a SVM classification method outperforms or is comparable to state-of-the-art kinship verification methods. © Springer International Publishing AG, Part of Springer Science+Business Media...

Effects of X-ray radiation on complex visual discrimination learning and social recognition memory in rats.

Directory of Open Access Journals (Sweden)

Catherine M Davis

Full Text Available The present report describes an animal model for examining the effects of radiation on a range of neurocognitive functions in rodents that are similar to a number of basic human cognitive functions. Fourteen male Long-Evans rats were trained to perform an automated intra-dimensional set shifting task that consisted of their learning a basic discrimination between two stimulus shapes followed by more complex discrimination stages (e.g., a discrimination reversal, a compound discrimination, a compound reversal, a new shape discrimination, and an intra-dimensional stimulus discrimination reversal. One group of rats was exposed to head-only X-ray radiation (2.3 Gy at a dose rate of 1.9 Gy/min, while a second group received a sham-radiation exposure using the same anesthesia protocol. The irradiated group responded less, had elevated numbers of omitted trials, increased errors, and greater response latencies compared to the sham-irradiated control group. Additionally, social odor recognition memory was tested after radiation exposure by assessing the degree to which rats explored wooden beads impregnated with either their own odors or with the odors of novel, unfamiliar rats; however, no significant effects of radiation on social odor recognition memory were observed. These data suggest that rodent tasks assessing higher-level human cognitive domains are useful in examining the effects of radiation on the CNS, and may be applicable in approximating CNS risks from radiation exposure in clinical populations receiving whole brain irradiation.

Effects of X-ray radiation on complex visual discrimination learning and social recognition memory in rats.

Science.gov (United States)

Davis, Catherine M; Roma, Peter G; Armour, Elwood; Gooden, Virginia L; Brady, Joseph V; Weed, Michael R; Hienz, Robert D

2014-01-01

The present report describes an animal model for examining the effects of radiation on a range of neurocognitive functions in rodents that are similar to a number of basic human cognitive functions. Fourteen male Long-Evans rats were trained to perform an automated intra-dimensional set shifting task that consisted of their learning a basic discrimination between two stimulus shapes followed by more complex discrimination stages (e.g., a discrimination reversal, a compound discrimination, a compound reversal, a new shape discrimination, and an intra-dimensional stimulus discrimination reversal). One group of rats was exposed to head-only X-ray radiation (2.3 Gy at a dose rate of 1.9 Gy/min), while a second group received a sham-radiation exposure using the same anesthesia protocol. The irradiated group responded less, had elevated numbers of omitted trials, increased errors, and greater response latencies compared to the sham-irradiated control group. Additionally, social odor recognition memory was tested after radiation exposure by assessing the degree to which rats explored wooden beads impregnated with either their own odors or with the odors of novel, unfamiliar rats; however, no significant effects of radiation on social odor recognition memory were observed. These data suggest that rodent tasks assessing higher-level human cognitive domains are useful in examining the effects of radiation on the CNS, and may be applicable in approximating CNS risks from radiation exposure in clinical populations receiving whole brain irradiation.

Effects of X-Ray Radiation on Complex Visual Discrimination Learning and Social Recognition Memory in Rats

Science.gov (United States)

Davis, Catherine M.; Roma, Peter G.; Armour, Elwood; Gooden, Virginia L.; Brady, Joseph V.; Weed, Michael R.; Hienz, Robert D.

2014-01-01

The present report describes an animal model for examining the effects of radiation on a range of neurocognitive functions in rodents that are similar to a number of basic human cognitive functions. Fourteen male Long-Evans rats were trained to perform an automated intra-dimensional set shifting task that consisted of their learning a basic discrimination between two stimulus shapes followed by more complex discrimination stages (e.g., a discrimination reversal, a compound discrimination, a compound reversal, a new shape discrimination, and an intra-dimensional stimulus discrimination reversal). One group of rats was exposed to head-only X-ray radiation (2.3 Gy at a dose rate of 1.9 Gy/min), while a second group received a sham-radiation exposure using the same anesthesia protocol. The irradiated group responded less, had elevated numbers of omitted trials, increased errors, and greater response latencies compared to the sham-irradiated control group. Additionally, social odor recognition memory was tested after radiation exposure by assessing the degree to which rats explored wooden beads impregnated with either their own odors or with the odors of novel, unfamiliar rats; however, no significant effects of radiation on social odor recognition memory were observed. These data suggest that rodent tasks assessing higher-level human cognitive domains are useful in examining the effects of radiation on the CNS, and may be applicable in approximating CNS risks from radiation exposure in clinical populations receiving whole brain irradiation. PMID:25099152

Multi-level discriminative dictionary learning with application to large scale image classification.

Science.gov (United States)

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination.

Science.gov (United States)

De Meo, Rosanna; Bourquin, Nathalie M-P; Knebel, Jean-François; Murray, Micah M; Clarke, Stephanie

2015-09-01

Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra

Fronto-striatal grey matter contributions to discrimination learning in Parkinson's disease

NARCIS (Netherlands)

O'Callaghan, C.; Moustafa, A.A.; de Wit, S.; Shine, J.M.; Robbins, T.W.; Lewis, S.J.G.; Hornberger, M.

2013-01-01

Discrimination learning deficits in Parkinson's disease (PD) have been well-established. Using both behavioral patient studies and computational approaches, these deficits have typically been attributed to dopamine imbalance across the basal ganglia. However, this explanation of impaired learning in

Pitch discrimination learning: specificity for pitch and harmonic resolvability, and electrophysiological correlates.

Science.gov (United States)

Carcagno, Samuele; Plack, Christopher J

2011-08-01

Multiple-hour training on a pitch discrimination task dramatically decreases the threshold for detecting a pitch difference between two harmonic complexes. Here, we investigated the specificity of this perceptual learning with respect to the pitch and the resolvability of the trained harmonic complex, as well as its cortical electrophysiological correlates. We trained 24 participants for 12 h on a pitch discrimination task using one of four different harmonic complexes. The complexes differed in pitch and/or spectral resolvability of their components by the cochlea, but were filtered into the same spectral region. Cortical-evoked potentials and a behavioral measure of pitch discrimination were assessed before and after training for all the four complexes. The change in these measures was compared to that of two control groups: one trained on a level discrimination task and one without any training. The behavioral results showed that learning was partly specific to both pitch and resolvability. Training with a resolved-harmonic complex improved pitch discrimination for resolved complexes more than training with an unresolved complex. However, we did not find evidence that training with an unresolved complex leads to specific learning for unresolved complexes. Training affected the P2 component of the cortical-evoked potentials, as well as a later component (250-400 ms). No significant changes were found on the mismatch negativity (MMN) component, although a separate experiment showed that this measure was sensitive to pitch changes equivalent to the pitch discriminability changes induced by training. This result suggests that pitch discrimination training affects processes not measured by the MMN, for example, processes higher in level or parallel to those involved in MMN generation.

Perceptual learning and human expertise.

Science.gov (United States)

Kellman, Philip J; Garrigan, Patrick

2009-06-01

We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual

Perceptual learning and human expertise

Science.gov (United States)

Kellman, Philip J.; Garrigan, Patrick

2009-06-01

We consider perceptual learning: experience-induced changes in the way perceivers extract information. Often neglected in scientific accounts of learning and in instruction, perceptual learning is a fundamental contributor to human expertise and is crucial in domains where humans show remarkable levels of attainment, such as language, chess, music, and mathematics. In Section 2, we give a brief history and discuss the relation of perceptual learning to other forms of learning. We consider in Section 3 several specific phenomena, illustrating the scope and characteristics of perceptual learning, including both discovery and fluency effects. We describe abstract perceptual learning, in which structural relationships are discovered and recognized in novel instances that do not share constituent elements or basic features. In Section 4, we consider primary concepts that have been used to explain and model perceptual learning, including receptive field change, selection, and relational recoding. In Section 5, we consider the scope of perceptual learning, contrasting recent research, focused on simple sensory discriminations, with earlier work that emphasized extraction of invariance from varied instances in more complex tasks. Contrary to some recent views, we argue that perceptual learning should not be confined to changes in early sensory analyzers. Phenomena at various levels, we suggest, can be unified by models that emphasize discovery and selection of relevant information. In a final section, we consider the potential role of perceptual learning in educational settings. Most instruction emphasizes facts and procedures that can be verbalized, whereas expertise depends heavily on implicit pattern recognition and selective extraction skills acquired through perceptual learning. We consider reasons why perceptual learning has not been systematically addressed in traditional instruction, and we describe recent successful efforts to create a technology of perceptual

Vicarious trial-and-error behavior and hippocampal cytochrome oxidase activity during Y-maze discrimination learning in the rat.

Science.gov (United States)

Hu, Dan; Xu, Xiaojuan; Gonzalez-Lima, Francisco

2006-03-01

The present study investigated whether more vicarious trial-and-error (VTE) behavior, defined by head movement from one stimulus to another at a choice point during simultaneous discriminations, led to better visual discrimination learning in a Y-maze, and whether VTE behavior was a function of the hippocampus by measuring regional brain cytochrome oxidase (C.O.) activity, an index of neuronal metabolic activity. The results showed that the more VTEs a rat made, the better the rat learned the visual discrimination. Furthermore, both learning and VTE behavior during learning were correlated to C.O. activity in the hippocampus, suggesting that the hippocampus plays a role in VTE behavior during discrimination learning.

Aversive reinforcement improves visual discrimination learning in free-flying honeybees.

Directory of Open Access Journals (Sweden)

Aurore Avarguès-Weber

Full Text Available BACKGROUND: Learning and perception of visual stimuli by free-flying honeybees has been shown to vary dramatically depending on the way insects are trained. Fine color discrimination is achieved when both a target and a distractor are present during training (differential conditioning, whilst if the same target is learnt in isolation (absolute conditioning, discrimination is coarse and limited to perceptually dissimilar alternatives. Another way to potentially enhance discrimination is to increase the penalty associated with the distractor. Here we studied whether coupling the distractor with a highly concentrated quinine solution improves color discrimination of both similar and dissimilar colors by free-flying honeybees. As we assumed that quinine acts as an aversive stimulus, we analyzed whether aversion, if any, is based on an aversive sensory input at the gustatory level or on a post-ingestional malaise following quinine feeding. METHODOLOGY/PRINCIPAL FINDINGS: We show that the presence of a highly concentrated quinine solution (60 mM acts as an aversive reinforcer promoting rejection of the target associated with it, and improving discrimination of perceptually similar stimuli but not of dissimilar stimuli. Free-flying bees did not use remote cues to detect the presence of quinine solution; the aversive effect exerted by this substance was mediated via a gustatory input, i.e. via a distasteful sensory experience, rather than via a post-ingestional malaise. CONCLUSION: The present study supports the hypothesis that aversion conditioning is important for understanding how and what animals perceive and learn. By using this form of conditioning coupled with appetitive conditioning in the framework of a differential conditioning procedure, it is possible to uncover discrimination capabilities that may remain otherwise unsuspected. We show, therefore, that visual discrimination is not an absolute phenomenon but can be modulated by experience.

Effects of Learning about Historical Gender Discrimination on Early Adolescents' Occupational Judgments and Aspirations

Science.gov (United States)

Pahlke, Erin; Bigler, Rebecca S.; Green, Vanessa A.

2010-01-01

To examine the consequences of learning about gender discrimination, early adolescents (n = 121, aged 10-14) were randomly assigned to receive either (a) standard biographical lessons about historical figures (standard condition) or (b) nearly identical lessons that included information about gender discrimination (discrimination condition).…

Discrimination against women and the human rights of women

OpenAIRE

Žunić Natalija

2014-01-01

This paper investigates the concept of the human rights of women and its connection with the phenomenon and the instances of discrimination against women. Discrimination against women, its social visibility and the fight against it, within the idea of the rights and the equality of women, are a source of many theoretical debates. Academic discussions and a powerful influence of the women's movement have brought about the establishment and the exercise of the human rights of women at different...

Discrimination against women and the human rights of women

Directory of Open Access Journals (Sweden)

Žunić Natalija

2014-01-01

Full Text Available This paper investigates the concept of the human rights of women and its connection with the phenomenon and the instances of discrimination against women. Discrimination against women, its social visibility and the fight against it, within the idea of the rights and the equality of women, are a source of many theoretical debates. Academic discussions and a powerful influence of the women's movement have brought about the establishment and the exercise of the human rights of women at different levels of the public and the private spheres of society, as a substantial part of the universal regime of human rights.

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI

Directory of Open Access Journals (Sweden)

Ling-Li Zeng

2018-04-01

Full Text Available Background: A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. Methods: A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Findings: Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. Interpretation: The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the “disconnectivity” model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Keywords: Schizophrenia, Deep learning, Connectome, f

Multi-Site Diagnostic Classification of Schizophrenia Using Discriminant Deep Learning with Functional Connectivity MRI.

Science.gov (United States)

Zeng, Ling-Li; Wang, Huaning; Hu, Panpan; Yang, Bo; Pu, Weidan; Shen, Hui; Chen, Xingui; Liu, Zhening; Yin, Hong; Tan, Qingrong; Wang, Kai; Hu, Dewen

2018-04-01

A lack of a sufficiently large sample at single sites causes poor generalizability in automatic diagnosis classification of heterogeneous psychiatric disorders such as schizophrenia based on brain imaging scans. Advanced deep learning methods may be capable of learning subtle hidden patterns from high dimensional imaging data, overcome potential site-related variation, and achieve reproducible cross-site classification. However, deep learning-based cross-site transfer classification, despite less imaging site-specificity and more generalizability of diagnostic models, has not been investigated in schizophrenia. A large multi-site functional MRI sample (n = 734, including 357 schizophrenic patients from seven imaging resources) was collected, and a deep discriminant autoencoder network, aimed at learning imaging site-shared functional connectivity features, was developed to discriminate schizophrenic individuals from healthy controls. Accuracies of approximately 85·0% and 81·0% were obtained in multi-site pooling classification and leave-site-out transfer classification, respectively. The learned functional connectivity features revealed dysregulation of the cortical-striatal-cerebellar circuit in schizophrenia, and the most discriminating functional connections were primarily located within and across the default, salience, and control networks. The findings imply that dysfunctional integration of the cortical-striatal-cerebellar circuit across the default, salience, and control networks may play an important role in the "disconnectivity" model underlying the pathophysiology of schizophrenia. The proposed discriminant deep learning method may be capable of learning reliable connectome patterns and help in understanding the pathophysiology and achieving accurate prediction of schizophrenia across multiple independent imaging sites. Copyright © 2018 German Center for Neurodegenerative Diseases (DZNE). Published by Elsevier B.V. All rights reserved.

Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification.

Science.gov (United States)

Wen, Zaidao; Hou, Biao; Jiao, Licheng

2017-05-03

Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

Training haptic stiffness discrimination: time course of learning with or without visual information and knowledge of results.

Science.gov (United States)

Teodorescu, Kinneret; Bouchigny, Sylvain; Korman, Maria

2013-08-01

In this study, we explored the time course of haptic stiffness discrimination learning and how it was affected by two experimental factors, the addition of visual information and/or knowledge of results (KR) during training. Stiffness perception may integrate both haptic and visual modalities. However, in many tasks, the visual field is typically occluded, forcing stiffness perception to be dependent exclusively on haptic information. No studies to date addressed the time course of haptic stiffness perceptual learning. Using a virtual environment (VE) haptic interface and a two-alternative forced-choice discrimination task, the haptic stiffness discrimination ability of 48 participants was tested across 2 days. Each day included two haptic test blocks separated by a training block Additional visual information and/or KR were manipulated between participants during training blocks. Practice repetitions alone induced significant improvement in haptic stiffness discrimination. Between days, accuracy was slightly improved, but decision time performance was deteriorated. The addition of visual information and/or KR had only temporary effects on decision time, without affecting the time course of haptic discrimination learning. Learning in haptic stiffness discrimination appears to evolve through at least two distinctive phases: A single training session resulted in both immediate and latent learning. This learning was not affected by the training manipulations inspected. Training skills in VE in spaced sessions can be beneficial for tasks in which haptic perception is critical, such as surgery procedures, when the visual field is occluded. However, training protocols for such tasks should account for low impact of multisensory information and KR.

Effects of Learning about Gender Discrimination on Adolescent Girls' Attitudes toward and Interest in Science

Science.gov (United States)

Weisgram, Erica S.; Bigler, Rebecca S.

2007-01-01

Gender discrimination has contributed to the gender imbalance in scientific fields. However, research on the effects of informing adolescent girls about gender discrimination in these fields is rare and controversial. To examine the consequences of learning about gender-based occupational discrimination, adolescent girls (n= 158, ages 11 to 14)…

Enhanced attentional gain as a mechanism for generalized perceptual learning in human visual cortex.

Science.gov (United States)

Byers, Anna; Serences, John T

2014-09-01

Learning to better discriminate a specific visual feature (i.e., a specific orientation in a specific region of space) has been associated with plasticity in early visual areas (sensory modulation) and with improvements in the transmission of sensory information from early visual areas to downstream sensorimotor and decision regions (enhanced readout). However, in many real-world scenarios that require perceptual expertise, observers need to efficiently process numerous exemplars from a broad stimulus class as opposed to just a single stimulus feature. Some previous data suggest that perceptual learning leads to highly specific neural modulations that support the discrimination of specific trained features. However, the extent to which perceptual learning acts to improve the discriminability of a broad class of stimuli via the modulation of sensory responses in human visual cortex remains largely unknown. Here, we used functional MRI and a multivariate analysis method to reconstruct orientation-selective response profiles based on activation patterns in the early visual cortex before and after subjects learned to discriminate small offsets in a set of grating stimuli that were rendered in one of nine possible orientations. Behavioral performance improved across 10 training sessions, and there was a training-related increase in the amplitude of orientation-selective response profiles in V1, V2, and V3 when orientation was task relevant compared with when it was task irrelevant. These results suggest that generalized perceptual learning can lead to modified responses in the early visual cortex in a manner that is suitable for supporting improved discriminability of stimuli drawn from a large set of exemplars. Copyright © 2014 the American Physiological Society.

Braille character discrimination in blindfolded human subjects.

Science.gov (United States)

Kauffman, Thomas; Théoret, Hugo; Pascual-Leone, Alvaro

2002-04-16

Visual deprivation may lead to enhanced performance in other sensory modalities. Whether this is the case in the tactile modality is controversial and may depend upon specific training and experience. We compared the performance of sighted subjects on a Braille character discrimination task to that of normal individuals blindfolded for a period of five days. Some participants in each group (blindfolded and sighted) received intensive Braille training to offset the effects of experience. Blindfolded subjects performed better than sighted subjects in the Braille discrimination task, irrespective of tactile training. For the left index finger, which had not been used in the formal Braille classes, blindfolding had no effect on performance while subjects who underwent tactile training outperformed non-stimulated participants. These results suggest that visual deprivation speeds up Braille learning and may be associated with behaviorally relevant neuroplastic changes.

Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data

Directory of Open Access Journals (Sweden)

Michael Veale

2017-11-01

Full Text Available Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining (DADM and fairness, accountability and transparency machine learning (FATML, their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data on sensitive attributes such as gender, ethnicity, sexuality or disability needed to diagnose and mitigate emergent indirect discrimination-by-proxy, such as redlining. Such organisations might also lack the knowledge and capacity to identify and manage fairness issues that are emergent properties of complex sociotechnical systems. This paper presents and discusses three potential approaches to deal with such knowledge and information deficits in the context of fairer machine learning. Trusted third parties could selectively store data necessary for performing discrimination discovery and incorporating fairness constraints into model-building in a privacy-preserving manner. Collaborative online platforms would allow diverse organisations to record, share and access contextual and experiential knowledge to promote fairness in machine learning systems. Finally, unsupervised learning and pedagogically interpretable algorithms might allow fairness hypotheses to be built for further selective testing and exploration. Real-world fairness challenges in machine learning are not abstract, constrained optimisation problems, but are institutionally and contextually grounded. Computational fairness tools are useful, but must be researched and developed in and with the messy contexts that will shape their deployment, rather than just for imagined situations. Not doing so risks real, near-term algorithmic harm.

Can machine learning explain human learning?

NARCIS (Netherlands)

Vahdat, M.; Oneto, L.; Anguita, D.; Funk, M.; Rauterberg, G.W.M.

2016-01-01

Learning Analytics (LA) has a major interest in exploring and understanding the learning process of humans and, for this purpose, benefits from both Cognitive Science, which studies how humans learn, and Machine Learning, which studies how algorithms learn from data. Usually, Machine Learning is

Food approach conditioning and discrimination learning using sound cues in benthic sharks.

Science.gov (United States)

Vila Pouca, Catarina; Brown, Culum

2018-07-01

The marine environment is filled with biotic and abiotic sounds. Some of these sounds predict important events that influence fitness while others are unimportant. Individuals can learn specific sound cues and 'soundscapes' and use them for vital activities such as foraging, predator avoidance, communication and orientation. Most research with sounds in elasmobranchs has focused on hearing thresholds and attractiveness to sound sources, but very little is known about their abilities to learn about sounds, especially in benthic species. Here we investigated if juvenile Port Jackson sharks could learn to associate a musical stimulus with a food reward, discriminate between two distinct musical stimuli, and whether individual personality traits were linked to cognitive performance. Five out of eight sharks were successfully conditioned to associate a jazz song with a food reward delivered in a specific corner of the tank. We observed repeatable individual differences in activity and boldness in all eight sharks, but these personality traits were not linked to the learning performance assays we examined. These sharks were later trained in a discrimination task, where they had to distinguish between the same jazz and a novel classical music song, and swim to opposite corners of the tank according to the stimulus played. The sharks' performance to the jazz stimulus declined to chance levels in the discrimination task. Interestingly, some sharks developed a strong side bias to the right, which in some cases was not the correct side for the jazz stimulus.

Functional discrimination of membrane proteins using machine learning techniques

Directory of Open Access Journals (Sweden)

Yabuki Yukimitsu

2008-03-01

Full Text Available Abstract Background Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amino acid residues in membrane proteins that perform major functions, such as channels/pores, electrochemical potential-driven transporters and primary active transporters. Results We observed that the residues Asp, Asn and Tyr are dominant in channels/pores whereas the composition of hydrophobic residues, Phe, Gly, Ile, Leu and Val is high in electrochemical potential-driven transporters. The composition of all the amino acids in primary active transporters lies in between other two classes of proteins. We have utilized different machine learning algorithms, such as, Bayes rule, Logistic function, Neural network, Support vector machine, Decision tree etc. for discriminating these classes of proteins. We observed that most of the algorithms have discriminated them with similar accuracy. The neural network method discriminated the channels/pores, electrochemical potential-driven transporters and active transporters with the 5-fold cross validation accuracy of 64% in a data set of 1718 membrane proteins. The application of amino acid occurrence improved the overall accuracy to 68%. In addition, we have discriminated transporters from other α-helical and β-barrel membrane proteins with the accuracy of 85% using k-nearest neighbor method. The classification of transporters and all other proteins (globular and membrane showed the accuracy of 82%. Conclusion The performance of discrimination with amino acid occurrence is better than that with amino acid composition. We suggest that this method could be effectively used to discriminate transporters from all other globular and membrane proteins, and classify them into channels/pores, electrochemical and active transporters.

Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses

OpenAIRE

Bisele, M; Bencsik, M; Lewis, MGC; Barnett, CT

2017-01-01

Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a ...

Active Discriminative Dictionary Learning for Weather Recognition

Directory of Open Access Journals (Sweden)

Caixia Zheng

2016-01-01

Full Text Available Weather recognition based on outdoor images is a brand-new and challenging subject, which is widely required in many fields. This paper presents a novel framework for recognizing different weather conditions. Compared with other algorithms, the proposed method possesses the following advantages. Firstly, our method extracts both visual appearance features of the sky region and physical characteristics features of the nonsky region in images. Thus, the extracted features are more comprehensive than some of the existing methods in which only the features of sky region are considered. Secondly, unlike other methods which used the traditional classifiers (e.g., SVM and K-NN, we use discriminative dictionary learning as the classification model for weather, which could address the limitations of previous works. Moreover, the active learning procedure is introduced into dictionary learning to avoid requiring a large number of labeled samples to train the classification model for achieving good performance of weather recognition. Experiments and comparisons are performed on two datasets to verify the effectiveness of the proposed method.

Effects of MK-801 on vicarious trial-and-error and reversal of olfactory discrimination learning in weanling rats.

Science.gov (United States)

Griesbach, G S; Hu, D; Amsel, A

1998-12-01

The effects of dizocilpine maleate (MK-801) on vicarious trial-and-error (VTE), and on simultaneous olfactory discrimination learning and its reversal, were observed in weanling rats. The term VTE was used by Tolman (The determiners of behavior at a choice point. Psychol. Rev. 1938;46:318-336), who described it as conflict-like behavior at a choice-point in simultaneous discrimination learning. It takes the form of head movements from one stimulus to the other, and has recently been proposed by Amsel (Hippocampal function in the rat: cognitive mapping or vicarious trial-and-error? Hippocampus, 1993;3:251-256) as related to hippocampal, nonspatial function during this learning. Weanling male rats received systemic MK-801 either 30 min before the onset of olfactory discrimination training and its reversal, or only before its reversal. The MK-801-treated animals needed significantly more sessions to acquire the discrimination and showed significantly fewer VTEs in the acquisition phase of learning. Impaired reversal learning was shown only when MK-801 was administered during the reversal-learning phase, itself, and not when it was administered throughout both phases.

Abnormality detection of mammograms by discriminative dictionary learning on DSIFT descriptors.

Science.gov (United States)

Tavakoli, Nasrin; Karimi, Maryam; Nejati, Mansour; Karimi, Nader; Reza Soroushmehr, S M; Samavi, Shadrokh; Najarian, Kayvan

2017-07-01

Detection and classification of breast lesions using mammographic images are one of the most difficult studies in medical image processing. A number of learning and non-learning methods have been proposed for detecting and classifying these lesions. However, the accuracy of the detection/classification still needs improvement. In this paper we propose a powerful classification method based on sparse learning to diagnose breast cancer in mammograms. For this purpose, a supervised discriminative dictionary learning approach is applied on dense scale invariant feature transform (DSIFT) features. A linear classifier is also simultaneously learned with the dictionary which can effectively classify the sparse representations. Our experimental results show the superior performance of our method compared to existing approaches.

Pitch Discrimination Learning: Specificity for Pitch and Harmonic Resolvability, and Electrophysiological Correlates

OpenAIRE

Carcagno, Samuele; Plack, Christopher J.

2011-01-01

Multiple-hour training on a pitch discrimination task dramatically decreases the threshold for detecting a pitch difference between two harmonic complexes. Here, we investigated the specificity of this perceptual learning with respect to the pitch and the resolvability of the trained harmonic complex, as well as its cortical electrophysiological correlates. We trained 24 participants for 12 h on a pitch discrimination task using one of four different harmonic complexes. The complexes differed...

Brightness discrimination learning in a Skinner box in prenatally X-irradiated rats

International Nuclear Information System (INIS)

Tamaki, Y.; Inouye, M.

1976-01-01

Male MP 1 albino rats were exposed to x-irradiation in utero at a single dose of 200 R on day 17 of gestation. The light-dark discrimination training in a Skinner box was continued until the animals attained a learning criterion of 0.80 correct response ratio for 3 consecutive days. Although during the unreinforced baseline sessions the total number of bar pressings in the irradiated animals was superior to that in the controls, performance between the control and the irradiated animals did not differ significantly in (a) the number of training days required to attain the learning criterion, (b) the total number of days on which the animals produced a correct response ratio more than 0.80, and (c) the number of consecutive days during which the correct response ratio was more than 0.75. The results obtained suggest that the irradiated animals were able to discriminate in brightness cues as well, or nearly as well, as the controls. The cortical-subcortical system mediating brightness discrimination in the irradiated animals is discussed. (author)

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

Science.gov (United States)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

Science.gov (United States)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Training with Differential Outcomes Enhances Discriminative Learning and Visuospatial Recognition Memory in Children Born Prematurely

Science.gov (United States)

Martinez, Lourdes; Mari-Beffa, Paloma; Roldan-Tapia, Dolores; Ramos-Lizana, Julio; Fuentes, Luis J.; Estevez, Angeles F.

2012-01-01

Previous studies have demonstrated that discriminative learning is facilitated when a particular outcome is associated with each relation to be learned. When this training procedure is applied (the differential outcome procedure; DOP), learning is faster and more accurate than when the more common non-differential outcome procedure is used. This…

Dopamine modulates memory consolidation of discrimination learning in the auditory cortex.

Science.gov (United States)

Schicknick, Horst; Reichenbach, Nicole; Smalla, Karl-Heinz; Scheich, Henning; Gundelfinger, Eckart D; Tischmeyer, Wolfgang

2012-03-01

In Mongolian gerbils, the auditory cortex is critical for discriminating rising vs. falling frequency-modulated tones. Based on our previous studies, we hypothesized that dopaminergic inputs to the auditory cortex during and shortly after acquisition of the discrimination strategy control long-term memory formation. To test this hypothesis, we studied frequency-modulated tone discrimination learning of gerbils in a shuttle box GO/NO-GO procedure following differential treatments. (i) Pre-exposure of gerbils to the frequency-modulated tones at 1 day before the first discrimination training session severely impaired the accuracy of the discrimination acquired in that session during the initial trials of a second training session, performed 1 day later. (ii) Local injection of the D1/D5 dopamine receptor antagonist SCH-23390 into the auditory cortex after task acquisition caused a discrimination deficit of similar extent and time course as with pre-exposure. This effect was dependent on the dose and time point of injection. (iii) Injection of the D1/D5 dopamine receptor agonist SKF-38393 into the auditory cortex after retraining caused a further discrimination improvement at the beginning of subsequent sessions. All three treatments, which supposedly interfered with dopamine signalling during conditioning and/or retraining, had a substantial impact on the dynamics of the discrimination performance particularly at the beginning of subsequent training sessions. These findings suggest that auditory-cortical dopamine activity after acquisition of a discrimination of complex sounds and after retrieval of weak frequency-modulated tone discrimination memory further improves memory consolidation, i.e. the correct association of two sounds with their respective GO/NO-GO meaning, in support of future memory recall. © 2012 The Authors. European Journal of Neuroscience © 2012 Federation of European Neuroscience Societies and Blackwell Publishing Ltd.

Global discriminative learning for higher-accuracy computational gene prediction.

Directory of Open Access Journals (Sweden)

Axel Bernal

2007-03-01

Full Text Available Most ab initio gene predictors use a probabilistic sequence model, typically a hidden Markov model, to combine separately trained models of genomic signals and content. By combining separate models of relevant genomic features, such gene predictors can exploit small training sets and incomplete annotations, and can be trained fairly efficiently. However, that type of piecewise training does not optimize prediction accuracy and has difficulty in accounting for statistical dependencies among different parts of the gene model. With genomic information being created at an ever-increasing rate, it is worth investigating alternative approaches in which many different types of genomic evidence, with complex statistical dependencies, can be integrated by discriminative learning to maximize annotation accuracy. Among discriminative learning methods, large-margin classifiers have become prominent because of the success of support vector machines (SVM in many classification tasks. We describe CRAIG, a new program for ab initio gene prediction based on a conditional random field model with semi-Markov structure that is trained with an online large-margin algorithm related to multiclass SVMs. Our experiments on benchmark vertebrate datasets and on regions from the ENCODE project show significant improvements in prediction accuracy over published gene predictors that use intrinsic features only, particularly at the gene level and on genes with long introns.

Human Machine Learning Symbiosis

Science.gov (United States)

Walsh, Kenneth R.; Hoque, Md Tamjidul; Williams, Kim H.

2017-01-01

Human Machine Learning Symbiosis is a cooperative system where both the human learner and the machine learner learn from each other to create an effective and efficient learning environment adapted to the needs of the human learner. Such a system can be used in online learning modules so that the modules adapt to each learner's learning state both…

Performance and strategy comparisons of human listeners and logistic regression in discriminating underwater targets.

Science.gov (United States)

Yang, Lixue; Chen, Kean

2015-11-01

To improve the design of underwater target recognition systems based on auditory perception, this study compared human listeners with automatic classifiers. Performances measures and strategies in three discrimination experiments, including discriminations between man-made and natural targets, between ships and submarines, and among three types of ships, were used. In the experiments, the subjects were asked to assign a score to each sound based on how confident they were about the category to which it belonged, and logistic regression, which represents linear discriminative models, also completed three similar tasks by utilizing many auditory features. The results indicated that the performances of logistic regression improved as the ratio between inter- and intra-class differences became larger, whereas the performances of the human subjects were limited by their unfamiliarity with the targets. Logistic regression performed better than the human subjects in all tasks but the discrimination between man-made and natural targets, and the strategies employed by excellent human subjects were similar to that of logistic regression. Logistic regression and several human subjects demonstrated similar performances when discriminating man-made and natural targets, but in this case, their strategies were not similar. An appropriate fusion of their strategies led to further improvement in recognition accuracy.

Development of vicarious trial-and-error behavior in odor discrimination learning in the rat: relation to hippocampal function?

Science.gov (United States)

Hu, D; Griesbach, G; Amsel, A

1997-06-01

Previous work from our laboratory has suggested that hippocampal electrolytic lesions result in a deficit in simultaneous, black-white discrimination learning and reduce the frequency of vicarious trial-and-error (VTE) at a choice-point. VTE is a term Tolman used to describe the rat's conflict-like behavior, moving its head from one stimulus to the other at a choice point, and has been proposed as a major nonspatial feature of hippocampal function in both visual and olfactory discrimination learning. Simultaneous odor discrimination and VTE behavior were examined at three different ages. The results were that 16-day-old pups made fewer VTEs and learned much more slowly than 30- and 60-day-olds, a finding in accord with levels of hippocampal maturity in the rat.

Quantifying explainable discrimination and removing illegal discrimination in automated decision making

NARCIS (Netherlands)

Kamiran, F.; Zliobaite, I.; Calders, T.G.K.

2013-01-01

Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train

Perceptual learning of motion direction discrimination with suppressed and unsuppressed MT in humans: an fMRI study.

Directory of Open Access Journals (Sweden)

Benjamin Thompson

Full Text Available The middle temporal area of the extrastriate visual cortex (area MT is integral to motion perception and is thought to play a key role in the perceptual learning of motion tasks. We have previously found, however, that perceptual learning of a motion discrimination task is possible even when the training stimulus contains locally balanced, motion opponent signals that putatively suppress the response of MT. Assuming at least partial suppression of MT, possible explanations for this learning are that 1 training made MT more responsive by reducing motion opponency, 2 MT remained suppressed and alternative visual areas such as V1 enabled learning and/or 3 suppression of MT increased with training, possibly to reduce noise. Here we used fMRI to test these possibilities. We first confirmed that the motion opponent stimulus did indeed suppress the BOLD response within hMT+ compared to an almost identical stimulus without locally balanced motion signals. We then trained participants on motion opponent or non-opponent stimuli. Training with the motion opponent stimulus reduced the BOLD response within hMT+ and greater reductions in BOLD response were correlated with greater amounts of learning. The opposite relationship between BOLD and behaviour was found at V1 for the group trained on the motion-opponent stimulus and at both V1 and hMT+ for the group trained on the non-opponent motion stimulus. As the average response of many cells within MT to motion opponent stimuli is the same as their response to non-directional flickering noise, the reduced activation of hMT+ after training may reflect noise reduction.

Human semi-supervised learning.

Science.gov (United States)

Gibson, Bryan R; Rogers, Timothy T; Zhu, Xiaojin

2013-01-01

Most empirical work in human categorization has studied learning in either fully supervised or fully unsupervised scenarios. Most real-world learning scenarios, however, are semi-supervised: Learners receive a great deal of unlabeled information from the world, coupled with occasional experiences in which items are directly labeled by a knowledgeable source. A large body of work in machine learning has investigated how learning can exploit both labeled and unlabeled data provided to a learner. Using equivalences between models found in human categorization and machine learning research, we explain how these semi-supervised techniques can be applied to human learning. A series of experiments are described which show that semi-supervised learning models prove useful for explaining human behavior when exposed to both labeled and unlabeled data. We then discuss some machine learning models that do not have familiar human categorization counterparts. Finally, we discuss some challenges yet to be addressed in the use of semi-supervised models for modeling human categorization. Copyright © 2013 Cognitive Science Society, Inc.

Sampling capacity underlies individual differences in human associative learning.

Science.gov (United States)

Byrom, Nicola C; Murphy, Robin A

2014-04-01

Though much work has studied how external factors, such as stimulus properties, influence generalization of associative strength, there has been limited exploration of the influence that internal dispositions may contribute to stimulus processing. Here we report 2 studies using a modified negative patterning discrimination to test the relationship between global processing and generalization. Global processing was associated with stronger negative patterning discrimination, indicative of limited generalization between distinct stimulus compounds and their constituent elements. In Experiment 2, participants pretrained to adopt global processing similarly showed strong negative patterning discrimination. These results demonstrate considerable individual difference in capacity to engage in negative patterning discrimination and suggest that the tendency toward global processing may be one factor explaining this variability. The need for models of learning to account for this variability in learning is discussed.

A perceptual learning deficit in Chinese developmental dyslexia as revealed by visual texture discrimination training.

Science.gov (United States)

Wang, Zhengke; Cheng-Lai, Alice; Song, Yan; Cutting, Laurie; Jiang, Yuzheng; Lin, Ou; Meng, Xiangzhi; Zhou, Xiaolin

2014-08-01

Learning to read involves discriminating between different written forms and establishing connections with phonology and semantics. This process may be partially built upon visual perceptual learning, during which the ability to process the attributes of visual stimuli progressively improves with practice. The present study investigated to what extent Chinese children with developmental dyslexia have deficits in perceptual learning by using a texture discrimination task, in which participants were asked to discriminate the orientation of target bars. Experiment l demonstrated that, when all of the participants started with the same initial stimulus-to-mask onset asynchrony (SOA) at 300 ms, the threshold SOA, adjusted according to response accuracy for reaching 80% accuracy, did not show a decrement over 5 days of training for children with dyslexia, whereas this threshold SOA steadily decreased over the training for the control group. Experiment 2 used an adaptive procedure to determine the threshold SOA for each participant during training. Results showed that both the group of dyslexia and the control group attained perceptual learning over the sessions in 5 days, although the threshold SOAs were significantly higher for the group of dyslexia than for the control group; moreover, over individual participants, the threshold SOA negatively correlated with their performance in Chinese character recognition. These findings suggest that deficits in visual perceptual processing and learning might, in part, underpin difficulty in reading Chinese. Copyright © 2014 John Wiley & Sons, Ltd.

Fairer machine learning in the real world: Mitigating discrimination without collecting sensitive data

OpenAIRE

Veale, M; Binns, RDP

2017-01-01

Decisions based on algorithmic, machine learning models can be unfair, reproducing biases in historical data used to train them. While computational techniques are emerging to address aspects of these concerns through communities such as discrimination-aware data mining (DADM) and fairness, accountability and transparency machine learning (FATML), their practical implementation faces real-world challenges. For legal, institutional or commercial reasons, organisations might not hold the data o...

Handling conditional discrimination

NARCIS (Netherlands)

Zliobaite, I.; Kamiran, F.; Calders, T.G.K.

2011-01-01

Historical data used for supervised learning may contain discrimination. We study how to train classifiers on such data, so that they are discrimination free with respect to a given sensitive attribute, e.g., gender. Existing techniques that deal with this problem aim at removing all discrimination

Selective increase of auditory cortico-striatal coherence during auditory-cued Go/NoGo discrimination learning.

Directory of Open Access Journals (Sweden)

Andreas L. Schulz

2016-01-01

Full Text Available Goal directed behavior and associated learning processes are tightly linked to neuronal activity in the ventral striatum. Mechanisms that integrate task relevant sensory information into striatal processing during decision making and learning are implicitly assumed in current reinforcementmodels, yet they are still weakly understood. To identify the functional activation of cortico-striatal subpopulations of connections during auditory discrimination learning, we trained Mongolian gerbils in a two-way active avoidance task in a shuttlebox to discriminate between falling and rising frequency modulated tones with identical spectral properties. We assessed functional coupling by analyzing the field-field coherence between the auditory cortex and the ventral striatum of animals performing the task. During the course of training, we observed a selective increase of functionalcoupling during Go-stimulus presentations. These results suggest that the auditory cortex functionally interacts with the ventral striatum during auditory learning and that the strengthening of these functional connections is selectively goal-directed.

[Discrimination and homophobia associated to the human immunodeficiency virus epidemic].

Science.gov (United States)

Orozco-Núñez, Emanuel; Alcalde-Rabanal, Jacqueline Elizabeth; Ruiz-Larios, José Arturo; Sucilla-Pérez, Héctor; García-Cerde, Rodrigo

2015-01-01

To describe a political mapping on discrimination and homophobia associated to human immunodeficiency virus (HIV) in the context of public institutions in Mexico. The political mapping was conducted in six Mexican states. Stakeholders who were involved in HIV actions from public and private sectors were included. Semistructured interviews were applied to explore homophobia and discrimination associated with HIV. Information was systematized using the Policy Maker software, which is a good support for analyzing health policies. Discriminatory and homophobic practices in the public domain occurred, damaging people´s integrity via insults, derision and hate crimes. Most stakeholders expressed a supportive position to prevent discrimination and homophobia and some of them had great influence on policy-making decisions. It was found that state policy frameworks are less specific in addressing these issues. Homophobia and discrimination associated to HIV are still considered problematic in Mexico. Homophobia is a very sensitive issue that requires further attention. Also, an actual execution of governmental authority requires greater enforcement of laws against discrimination and homophobia.

Pharmacological evidence that both cognitive memory and habit formation contribute to within-session learning of concurrent visual discriminations.

Science.gov (United States)

Turchi, Janita; Devan, Bryan; Yin, Pingbo; Sigrist, Emmalynn; Mishkin, Mortimer

2010-07-01

The monkey's ability to learn a set of visual discriminations presented concurrently just once a day on successive days (24-h ITI task) is based on habit formation, which is known to rely on a visuo-striatal circuit and to be independent of visuo-rhinal circuits that support one-trial memory. Consistent with this dissociation, we recently reported that performance on the 24-h ITI task is impaired by a striatal-function blocking agent, the dopaminergic antagonist haloperidol, and not by a rhinal-function blocking agent, the muscarinic cholinergic antagonist scopolamine. In the present study, monkeys were trained on a short-ITI form of concurrent visual discrimination learning, one in which a set of stimulus pairs is repeated not only across daily sessions but also several times within each session (in this case, at about 4-min ITIs). Asymptotic discrimination learning rates in the non-drug condition were reduced by half, from approximately 11 trials/pair on the 24-h ITI task to approximately 5 trials/pair on the 4-min ITI task, and this faster learning was impaired by systemic injections of either haloperidol or scopolamine. The results suggest that in the version of concurrent discrimination learning used here, the short ITIs within a session recruit both visuo-rhinal and visuo-striatal circuits, and that the final performance level is driven by both cognitive memory and habit formation working in concert.

Songbirds and humans apply different strategies in a sound sequence discrimination task

Directory of Open Access Journals (Sweden)

Yoshimasa eSeki

2013-07-01

Full Text Available The abilities of animals and humans to extract rules from sound sequences have previously been compared using observation of spontaneous responses and conditioning techniques. However, the results were inconsistently interpreted across studies possibly due to methodological and/or species differences. Therefore, we examined the strategies for discrimination of sound sequences in Bengalese finches and humans using the same protocol. Birds were trained on a GO/NOGO task to discriminate between two categories of sound stimulus generated based on an AAB or ABB rule. The sound elements used were taken from a variety of male (M and female (F calls, such that the sequences could be represented as MMF and MFF. In test sessions, FFM and FMM sequences, which were never presented in the training sessions but conformed to the rule, were presented as probe stimuli. The results suggested two discriminative strategies were being applied: 1 memorizing sound patterns of either GO or NOGO stimuli and generating the appropriate responses for only those sounds; and 2 using the repeated element as a cue. There was no evidence that the birds successfully extracted the abstract rule (i.e. AAB and ABB; MMF-GO subjects did not produce a GO response for FFM and vice versa. Next we examined whether those strategies were also applicable for human participants on the same task. The results and questionnaires revealed that participants extracted the abstract rule, and most of them employed it to discriminate the sequences. This strategy was never observed in bird subjects, although some participants used strategies similar to the birds when responding to the probe stimuli. Our results showed that the human participants applied the abstract rule in the task even without instruction but Bengalese finches did not, thereby reconfirming that humans have to extract abstract rules from sound sequences that is distinct from non-human animals.

Songbirds and humans apply different strategies in a sound sequence discrimination task.

Science.gov (United States)

Seki, Yoshimasa; Suzuki, Kenta; Osawa, Ayumi M; Okanoya, Kazuo

2013-01-01

The abilities of animals and humans to extract rules from sound sequences have previously been compared using observation of spontaneous responses and conditioning techniques. However, the results were inconsistently interpreted across studies possibly due to methodological and/or species differences. Therefore, we examined the strategies for discrimination of sound sequences in Bengalese finches and humans using the same protocol. Birds were trained on a GO/NOGO task to discriminate between two categories of sound stimulus generated based on an "AAB" or "ABB" rule. The sound elements used were taken from a variety of male (M) and female (F) calls, such that the sequences could be represented as MMF and MFF. In test sessions, FFM and FMM sequences, which were never presented in the training sessions but conformed to the rule, were presented as probe stimuli. The results suggested two discriminative strategies were being applied: (1) memorizing sound patterns of either GO or NOGO stimuli and generating the appropriate responses for only those sounds; and (2) using the repeated element as a cue. There was no evidence that the birds successfully extracted the abstract rule (i.e., AAB and ABB); MMF-GO subjects did not produce a GO response for FFM and vice versa. Next we examined whether those strategies were also applicable for human participants on the same task. The results and questionnaires revealed that participants extracted the abstract rule, and most of them employed it to discriminate the sequences. This strategy was never observed in bird subjects, although some participants used strategies similar to the birds when responding to the probe stimuli. Our results showed that the human participants applied the abstract rule in the task even without instruction but Bengalese finches did not, thereby reconfirming that humans have to extract abstract rules from sound sequences that is distinct from non-human animals.

Discourses of Roma Anti-Discrimination in Reports on Human Rights Violations

Directory of Open Access Journals (Sweden)

Chloë Delcour

2015-09-01

Full Text Available In an effort to understand the paradox between the expansion of inclusion projects for the Roma and their persisting exclusion, this article explores human rights practice in order to grasp the complexity of meanings of inclusion negotiated in this practice. In this way, we scrutinize whether there are limiting factors within the inclusionary discourse itself. Specifically, we analyze the discourse in transnational judicial, political and civil society actors’ reports on violations of human rights against Roma. A strong shared tendency to frame the violations in terms of discrimination can be discerned in the reports, demonstrating a dominant concept in the human rights discourse for Roma. However, a framing analysis of the underlying assumptions of this concept shows that not all three actors offer the same solutions for obtaining non-discrimination, which can partly explain the limited impact of the ostensibly strong and inclusive anti-discrimination discourse. In contrast, the actors do share a negative attribution of responsibility to the nation states, but the effectiveness of this shared discursive claim can be questioned. This article illustrates how inclusion discourses are actually quite complex to grasp and so it substantiates the need for greater critical understanding of such discourses in further research.

Discrimination aware decision tree learning

NARCIS (Netherlands)

Kamiran, F.; Calders, T.G.K.; Pechenizkiy, M.

2010-01-01

Recently, the following discrimination aware classification problem was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B. This problem is motivated by the fact

Long term effects of aversive reinforcement on colour discrimination learning in free-flying bumblebees.

Directory of Open Access Journals (Sweden)

Miguel A Rodríguez-Gironés

Full Text Available The results of behavioural experiments provide important information about the structure and information-processing abilities of the visual system. Nevertheless, if we want to infer from behavioural data how the visual system operates, it is important to know how different learning protocols affect performance and to devise protocols that minimise noise in the response of experimental subjects. The purpose of this work was to investigate how reinforcement schedule and individual variability affect the learning process in a colour discrimination task. Free-flying bumblebees were trained to discriminate between two perceptually similar colours. The target colour was associated with sucrose solution, and the distractor could be associated with water or quinine solution throughout the experiment, or with one substance during the first half of the experiment and the other during the second half. Both acquisition and final performance of the discrimination task (measured as proportion of correct choices were determined by the choice of reinforcer during the first half of the experiment: regardless of whether bees were trained with water or quinine during the second half of the experiment, bees trained with quinine during the first half learned the task faster and performed better during the whole experiment. Our results confirm that the choice of stimuli used during training affects the rate at which colour discrimination tasks are acquired and show that early contact with a strongly aversive stimulus can be sufficient to maintain high levels of attention during several hours. On the other hand, bees which took more time to decide on which flower to alight were more likely to make correct choices than bees which made fast decisions. This result supports the existence of a trade-off between foraging speed and accuracy, and highlights the importance of measuring choice latencies during behavioural experiments focusing on cognitive abilities.

Discrimination aware decision tree learning

NARCIS (Netherlands)

Kamiran, F.; Calders, T.G.K.; Pechenizkiy, M.

2010-01-01

Recently, the following problem of discrimination aware classification was introduced: given a labeled dataset and an attribute B, find a classifier with high predictive accuracy that at the same time does not discriminate on the basis of the given attribute B. This problem is motivated by the fact

Discrimination of Rock Fracture and Blast Events Based on Signal Complexity and Machine Learning

Directory of Open Access Journals (Sweden)

Zilong Zhou

2018-01-01

Full Text Available The automatic discrimination of rock fracture and blast events is complex and challenging due to the similar waveform characteristics. To solve this problem, a new method based on the signal complexity analysis and machine learning has been proposed in this paper. First, the permutation entropy values of signals at different scale factors are calculated to reflect complexity of signals and constructed into a feature vector set. Secondly, based on the feature vector set, back-propagation neural network (BPNN as a means of machine learning is applied to establish a discriminator for rock fracture and blast events. Then to evaluate the classification performances of the new method, the classifying accuracies of support vector machine (SVM, naive Bayes classifier, and the new method are compared, and the receiver operating characteristic (ROC curves are also analyzed. The results show the new method obtains the best classification performances. In addition, the influence of different scale factor q and number of training samples n on discrimination results is discussed. It is found that the classifying accuracy of the new method reaches the highest value when q = 8–15 or 8–20 and n=140.

Semi-Supervised Tensor-Based Graph Embedding Learning and Its Application to Visual Discriminant Tracking.

Science.gov (United States)

Hu, Weiming; Gao, Jin; Xing, Junliang; Zhang, Chao; Maybank, Stephen

2017-01-01

An appearance model adaptable to changes in object appearance is critical in visual object tracking. In this paper, we treat an image patch as a two-order tensor which preserves the original image structure. We design two graphs for characterizing the intrinsic local geometrical structure of the tensor samples of the object and the background. Graph embedding is used to reduce the dimensions of the tensors while preserving the structure of the graphs. Then, a discriminant embedding space is constructed. We prove two propositions for finding the transformation matrices which are used to map the original tensor samples to the tensor-based graph embedding space. In order to encode more discriminant information in the embedding space, we propose a transfer-learning- based semi-supervised strategy to iteratively adjust the embedding space into which discriminative information obtained from earlier times is transferred. We apply the proposed semi-supervised tensor-based graph embedding learning algorithm to visual tracking. The new tracking algorithm captures an object's appearance characteristics during tracking and uses a particle filter to estimate the optimal object state. Experimental results on the CVPR 2013 benchmark dataset demonstrate the effectiveness of the proposed tracking algorithm.

Varieties of perceptual learning.

Science.gov (United States)

Mackintosh, N J

2009-05-01

Although most studies of perceptual learning in human participants have concentrated on the changes in perception assumed to be occurring, studies of nonhuman animals necessarily measure discrimination learning and generalization and remain agnostic on the question of whether changes in behavior reflect changes in perception. On the other hand, animal studies do make it easier to draw a distinction between supervised and unsupervised learning. Differential reinforcement will surely teach animals to attend to some features of a stimulus array rather than to others. But it is an open question as to whether such changes in attention underlie the enhanced discrimination seen after unreinforced exposure to such an array. I argue that most instances of unsupervised perceptual learning observed in animals (and at least some in human animals) are better explained by appeal to well-established principles and phenomena of associative learning theory: excitatory and inhibitory associations between stimulus elements, latent inhibition, and habituation.

An Information Analysis of 2-, 3-, and 4-Word Verbal Discrimination Learning.

Science.gov (United States)

Arima, James K.; Gray, Francis D.

Information theory was used to qualify the difficulty of verbal discrimination (VD) learning tasks and to measure VD performance. Words for VD items were selected with high background frequency and equal a priori probabilities of being selected as a first response. Three VD lists containing only 2-, 3-, or 4-word items were created and equated for…

Confidence-Based Data Association and Discriminative Deep Appearance Learning for Robust Online Multi-Object Tracking.

Science.gov (United States)

Bae, Seung-Hwan; Yoon, Kuk-Jin

2018-03-01

Online multi-object tracking aims at estimating the tracks of multiple objects instantly with each incoming frame and the information provided up to the moment. It still remains a difficult problem in complex scenes, because of the large ambiguity in associating multiple objects in consecutive frames and the low discriminability between objects appearances. In this paper, we propose a robust online multi-object tracking method that can handle these difficulties effectively. We first define the tracklet confidence using the detectability and continuity of a tracklet, and decompose a multi-object tracking problem into small subproblems based on the tracklet confidence. We then solve the online multi-object tracking problem by associating tracklets and detections in different ways according to their confidence values. Based on this strategy, tracklets sequentially grow with online-provided detections, and fragmented tracklets are linked up with others without any iterative and expensive association steps. For more reliable association between tracklets and detections, we also propose a deep appearance learning method to learn a discriminative appearance model from large training datasets, since the conventional appearance learning methods do not provide rich representation that can distinguish multiple objects with large appearance variations. In addition, we combine online transfer learning for improving appearance discriminability by adapting the pre-trained deep model during online tracking. Experiments with challenging public datasets show distinct performance improvement over other state-of-the-arts batch and online tracking methods, and prove the effect and usefulness of the proposed methods for online multi-object tracking.

Roles of Approval Motivation and Generalized Expectancy for Reinforcement in Children's Conceptual Discrimination Learning

Science.gov (United States)

Nyce, Peggy A.; And Others

1977-01-01

Forty-four third graders were given a two-choice conceptual discrimination learning task. The two major factors were (1) four treatment groups varying at the extremes on two personality measures, approval motivation and locus of control and (2) sex. (MS)

Dissociable Hippocampal and Amygdalar D1-like receptor contribution to Discriminated Pavlovian conditioned approach learning

Science.gov (United States)

Andrzejewski, Matthew E; Ryals, Curtis

2016-01-01

Pavlovian conditioning is an elementary form of reward-related behavioral adaptation. The mesolimbic dopamine system is widely considered to mediate critical aspects of reward-related learning. For example, initial acquisition of positively-reinforced operant behavior requires dopamine (DA) D1 receptor (D1R) activation in the basolateral amygdala (BLA), central nucleus of the amygdala (CeA), and the ventral subiculum (vSUB). However, the role of D1R activation in these areas on appetitive, non-drug-related, Pavlovian learning is not currently known. In separate experiments, microinfusions of the D1-like receptor antagonist SCH-23390 (3.0 nmol/0.5 μL per side) into the amygdala and subiculum preceded discriminated Pavlovian conditioned approach (dPCA) training sessions. D1-like antagonism in all three structures impaired the acquisition of discriminated approach, but had no effect on performance after conditioning was asymptotic. Moreover, dissociable effects of D1-like antagonism in the three structures on components of discriminated responding were obtained. Lastly, the lack of latent inhibition in drug-treated groups may elucidate the role of D1-like in reward-related Pavlovian conditioning. The present data suggest a role for the D1 receptors in the amygdala and hippocampus in learning the significance of conditional stimuli, but not in the expression of conditional responses. PMID:26632336

Mechanisms underlying speech sound discrimination and categorization in humans and zebra finches

NARCIS (Netherlands)

Burgering, Merel A.; ten Cate, Carel; Vroomen, Jean

Speech sound categorization in birds seems in many ways comparable to that by humans, but it is unclear what mechanisms underlie such categorization. To examine this, we trained zebra finches and humans to discriminate two pairs of edited speech sounds that varied either along one dimension (vowel

Discrimination of holograms and real objects by pigeons (Columba livia) and humans (Homo sapiens).

Science.gov (United States)

Stephan, Claudia; Steurer, Michael M; Aust, Ulrike

2014-08-01

The type of stimulus material employed in visual tasks is crucial to all comparative cognition research that involves object recognition. There is considerable controversy about the use of 2-dimensional stimuli and the impact that the lack of the 3rd dimension (i.e., depth) may have on animals' performance in tests for their visual and cognitive abilities. We report evidence of discrimination learning using a completely novel type of stimuli, namely, holograms. Like real objects, holograms provide full 3-dimensional shape information but they also offer many possibilities for systematically modifying the appearance of a stimulus. Hence, they provide a promising means for investigating visual perception and cognition of different species in a comparative way. We trained pigeons and humans to discriminate either between 2 real objects or between holograms of the same 2 objects, and we subsequently tested both species for the transfer of discrimination to the other presentation mode. The lack of any decrements in accuracy suggests that real objects and holograms were perceived as equivalent in both species and shows the general appropriateness of holograms as stimuli in visual tasks. A follow-up experiment involving the presentation of novel views of the training objects and holograms revealed some interspecies differences in rotational invariance, thereby confirming and extending the results of previous studies. Taken together, these results suggest that holograms may not only provide a promising tool for investigating yet unexplored issues, but their use may also lead to novel insights into some crucial aspects of comparative visual perception and categorization.

Dissociable contributions of the orbitofrontal and infralimbic cortex to pavlovian autoshaping and discrimination reversal learning: further evidence for the functional heterogeneity of the rodent frontal cortex.

Science.gov (United States)

Chudasama, Y; Robbins, Trevor W

2003-09-24

To examine possible heterogeneity of function within the ventral regions of the rodent frontal cortex, the present study compared the effects of excitotoxic lesions of the orbitofrontal cortex (OFC) and the infralimbic cortex (ILC) on pavlovian autoshaping and discrimination reversal learning. During the pavlovian autoshaping task, in which rats learn to approach a stimulus predictive of reward [conditional stimulus (CS+)], only the OFC group failed to acquire discriminated approach but was unimpaired when preoperatively trained. In the visual discrimination learning and reversal task, rats were initially required to discriminate a stimulus positively associated with reward. There was no effect of either OFC or ILC lesions on discrimination learning. When the stimulus-reward contingencies were reversed, both groups of animals committed more errors, but only the OFC-lesioned animals were unable to suppress the previously rewarded stimulus-reward association, committing more "stimulus perseverative" errors. In contrast, the ILC group showed a pattern of errors that was more attributable to "learning" than perseveration. These findings suggest two types of dissociation between the effects of OFC and ILC lesions: (1) OFC lesions impaired the learning processes implicated in pavlovian autoshaping but not instrumental simultaneous discrimination learning, whereas ILC lesions were unimpaired at autoshaping and their reversal learning deficit did not reflect perseveration, and (2) OFC lesions induced perseverative responding in reversal learning but did not disinhibit responses to pavlovian CS-. In contrast, the ILC lesion had no effect on response inhibitory control in either of these settings. The findings are discussed in the context of dissociable executive functions in ventral sectors of the rat prefrontal cortex.

Artificial Skin Ridges Enhance Local Tactile Shape Discrimination

Directory of Open Access Journals (Sweden)

Shuzhi Sam Ge

2011-09-01

Full Text Available One of the fundamental requirements for an artificial hand to successfully grasp and manipulate an object is to be able to distinguish different objects’ shapes and, more specifically, the objects’ surface curvatures. In this study, we investigate the possibility of enhancing the curvature detection of embedded tactile sensors by proposing a ridged fingertip structure, simulating human fingerprints. In addition, a curvature detection approach based on machine learning methods is proposed to provide the embedded sensors with the ability to discriminate the surface curvature of different objects. For this purpose, a set of experiments were carried out to collect tactile signals from a 2 × 2 tactile sensor array, then the signals were processed and used for learning algorithms. To achieve the best possible performance for our machine learning approach, three different learning algorithms of Naïve Bayes (NB, Artificial Neural Networks (ANN, and Support Vector Machines (SVM were implemented and compared for various parameters. Finally, the most accurate method was selected to evaluate the proposed skin structure in recognition of three different curvatures. The results showed an accuracy rate of 97.5% in surface curvature discrimination.

Human listeners provide insights into echo features used by dolphins (Tursiops truncatus) to discriminate among objects.

Science.gov (United States)

Delong, Caroline M; Au, Whitlow W L; Harley, Heidi E; Roitblat, Herbert L; Pytka, Lisa

2007-08-01

Echolocating bottlenose dolphins (Tursiops truncatus) discriminate between objects on the basis of the echoes reflected by the objects. However, it is not clear which echo features are important for object discrimination. To gain insight into the salient features, the authors had a dolphin perform a match-to-sample task and then presented human listeners with echoes from the same objects used in the dolphin's task. In 2 experiments, human listeners performed as well or better than the dolphin at discriminating objects, and they reported the salient acoustic cues. The error patterns of the humans and the dolphin were compared to determine which acoustic features were likely to have been used by the dolphin. The results indicate that the dolphin did not appear to use overall echo amplitude, but that it attended to the pattern of changes in the echoes across different object orientations. Human listeners can quickly identify salient combinations of echo features that permit object discrimination, which can be used to generate hypotheses that can be tested using dolphins as subjects.

Combining generative and discriminative representation learning for lung CT analysis with convolutional restricted Boltzmann machines

DEFF Research Database (Denmark)

van Tulder, Gijs; de Bruijne, Marleen

2016-01-01

The choice of features greatly influences the performance of a tissue classification system. Despite this, many systems are built with standard, predefined filter banks that are not optimized for that particular application. Representation learning methods such as restricted Boltzmann machines may...... outperform these standard filter banks because they learn a feature description directly from the training data. Like many other representation learning methods, restricted Boltzmann machines are unsupervised and are trained with a generative learning objective; this allows them to learn representations from...... unlabeled data, but does not necessarily produce features that are optimal for classification. In this paper we propose the convolutional classification restricted Boltzmann machine, which combines a generative and a discriminative learning objective. This allows it to learn filters that are good both...

Discriminating Drivers through Human Factor and Behavioral Difference

Directory of Open Access Journals (Sweden)

Ju Seok Oh

2011-05-01

Full Text Available Since Greenwood and Woods' (1919 study in tendency of accident, many researchers have insisted that various human factors (sensation seeking, anger, anxiety are highly correlated with reckless driving and traffic accidents. Oh and Lee (2011 designed the Driving Behavior Determinants Questionnaire, a psychological tool to predict danger level of drivers and discriminate them into three groups (normal, unintentionally reckless, and intentionally reckless by their characteristics, attitude, and expected reckless behavior level. This tool's overall accuracy of discrimination was 70%. This study aimed to prove that the discrimination reflects the behavioral difference of drivers. Twenty-four young drivers were requested to react to the visual stimuli (tests for subjective speed sense, simple visual reaction time, and left turning at own risk. The results showed no differences in subjective speed sense among the driver groups, which means drivers' excessive speeding behaviors occur due to intention based on personality and attitude, not because of sensory disorders. In addition, there were no differences in simple reaction time among driver groups. However, the results of the ‘Left turning at drivers’ own risk task” revealed significant group differences. All reckless drivers showed a greater degree of dangerous left turning behaviors than the normal group did.

Enhanced discriminative fear learning of phobia-irrelevant stimuli in spider-fearful individuals

Directory of Open Access Journals (Sweden)

Carina eMosig

2014-10-01

Full Text Available Avoidance is considered as a central hallmark of all anxiety disorders. The acquisition and expression of avoidance which leads to the maintenance and exacerbation of pathological fear is closely linked to Pavlovian and operant conditioning processes. Changes in conditionability might represent a key feature of all anxiety disorders but the exact nature of these alterations might vary across different disorders. To date, no information is available on specific changes in conditionability for disorder-irrelevant stimuli in specific phobia (SP. The first aim of this study was to investigate changes in fear acquisition and extinction in spider-fearful individuals as compared to non-fearful participants by using the de novo fear conditioning paradigm. Secondly, we aimed to determine whether differences in the magnitude of context-dependent fear retrieval exist between spider-fearful and non-fearful individuals. Our findings point to an enhanced fear discrimination in spider-fearful individuals as compared to non-fearful individuals at both the physiological and subjective level. The enhanced fear discrimination in spider-fearful individuals was neither mediated by increased state anxiety, depression, nor stress tension. Spider-fearful individuals displayed no changes in extinction learning and/or fear retrieval. Surprisingly, we found no evidence for context-dependent modulation of fear retrieval in either group. Here we provide first evidence that spider-fearful individuals show an enhanced discriminative fear learning of phobia-irrelevant (de novo stimuli. Our findings provide novel insights into the role of fear acquisition and expression for the development and maintenance of maladaptive responses in the course of SP.

Machinery fault diagnosis using joint global and local/nonlocal discriminant analysis with selective ensemble learning

Science.gov (United States)

Yu, Jianbo

2016-11-01

The vibration signals of faulty machine are generally non-stationary and nonlinear under those complicated working conditions. Thus, it is a big challenge to extract and select the effective features from vibration signals for machinery fault diagnosis. This paper proposes a new manifold learning algorithm, joint global and local/nonlocal discriminant analysis (GLNDA), which aims to extract effective intrinsic geometrical information from the given vibration data. Comparisons with other regular methods, principal component analysis (PCA), local preserving projection (LPP), linear discriminant analysis (LDA) and local LDA (LLDA), illustrate the superiority of GLNDA in machinery fault diagnosis. Based on the extracted information by GLNDA, a GLNDA-based Fisher discriminant rule (FDR) is put forward and applied to machinery fault diagnosis without additional recognizer construction procedure. By importing Bagging into GLNDA score-based feature selection and FDR, a novel manifold ensemble method (selective GLNDA ensemble, SE-GLNDA) is investigated for machinery fault diagnosis. The motivation for developing ensemble of manifold learning components is that it can achieve higher accuracy and applicability than single component in machinery fault diagnosis. The effectiveness of the SE-GLNDA-based fault diagnosis method has been verified by experimental results from bearing full life testers.

A multiplicative reinforcement learning model capturing learning dynamics and interindividual variability in mice

OpenAIRE

Bathellier, Brice; Tee, Sui Poh; Hrovat, Christina; Rumpel, Simon

2013-01-01

Learning speed can strongly differ across individuals. This is seen in humans and animals. Here, we measured learning speed in mice performing a discrimination task and developed a theoretical model based on the reinforcement learning framework to account for differences between individual mice. We found that, when using a multiplicative learning rule, the starting connectivity values of the model strongly determine the shape of learning curves. This is in contrast to current learning models ...

Transfer of Perceptual Learning of Depth Discrimination Between Local and Global Stereograms

OpenAIRE

Gantz, Liat; Bedell, Harold

2010-01-01

Several previous studies reported differences when stereothresholds are assessed with local-contour stereograms vs. complex random-dot stereograms (RDSs). Dissimilar thresholds may be due to differences in the properties of the stereograms (e.g., spatial frequency content, contrast, inter-element separation, area) or to different underlying processing mechanisms. This study examined the transfer of perceptual learning of depth discrimination between local and global RDSs with similar properti...

Hippocampal-cortical contributions to strategic exploration during perceptual discrimination.

Science.gov (United States)

Voss, Joel L; Cohen, Neal J

2017-06-01

The hippocampus is crucial for long-term memory; its involvement in short-term or immediate expressions of memory is more controversial. Rodent hippocampus has been implicated in an expression of memory that occurs on-line during exploration termed "vicarious trial-and-error" (VTE) behavior. VTE occurs when rodents iteratively explore options during perceptual discrimination or at choice points. It is strategic in that it accelerates learning and improves later memory. VTE has been associated with activity of rodent hippocampal neurons, and lesions of hippocampus disrupt VTE and associated learning and memory advantages. Analogous findings of VTE in humans would support the role of hippocampus in active use of short-term memory to guide strategic behavior. We therefore measured VTE using eye-movement tracking during perceptual discrimination and identified relevant neural correlates with functional magnetic resonance imaging. A difficult perceptual-discrimination task was used that required visual information to be maintained during a several second trial, but with no long-term memory component. VTE accelerated discrimination. Neural correlates of VTE included robust activity of hippocampus and activity of a network of medial prefrontal and lateral parietal regions involved in memory-guided behavior. This VTE-related activity was distinct from activity associated with simply viewing visual stimuli and making eye movements during the discrimination task, which occurred in regions frequently associated with visual processing and eye-movement control. Subjects were mostly unaware of performing VTE, thus further distancing VTE from explicit long-term memory processing. These findings bridge the rodent and human literatures on neural substrates of memory-guided behavior, and provide further support for the role of hippocampus and a hippocampal-centered network of cortical regions in the immediate use of memory in on-line processing and the guidance of behavior. © 2017

Kennard-Stone combined with least square support vector machine method for noncontact discriminating human blood species

Science.gov (United States)

Zhang, Linna; Li, Gang; Sun, Meixiu; Li, Hongxiao; Wang, Zhennan; Li, Yingxin; Lin, Ling

2017-11-01

Identifying whole bloods to be either human or nonhuman is an important responsibility for import-export ports and inspection and quarantine departments. Analytical methods and DNA testing methods are usually destructive. Previous studies demonstrated that visible diffuse reflectance spectroscopy method can realize noncontact human and nonhuman blood discrimination. An appropriate method for calibration set selection was very important for a robust quantitative model. In this paper, Random Selection (RS) method and Kennard-Stone (KS) method was applied in selecting samples for calibration set. Moreover, proper stoichiometry method can be greatly beneficial for improving the performance of classification model or quantification model. Partial Least Square Discrimination Analysis (PLSDA) method was commonly used in identification of blood species with spectroscopy methods. Least Square Support Vector Machine (LSSVM) was proved to be perfect for discrimination analysis. In this research, PLSDA method and LSSVM method was used for human blood discrimination. Compared with the results of PLSDA method, this method could enhance the performance of identified models. The overall results convinced that LSSVM method was more feasible for identifying human and animal blood species, and sufficiently demonstrated LSSVM method was a reliable and robust method for human blood identification, and can be more effective and accurate.

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning.

Science.gov (United States)

Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

2014-07-01

Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different patches of the

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

Science.gov (United States)

Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

2014-01-01

Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

International Nuclear Information System (INIS)

Guo, Yanrong; Shao, Yeqin; Gao, Yaozong; Price, True; Oto, Aytekin; Shen, Dinggang

2014-01-01

Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

Energy Technology Data Exchange (ETDEWEB)

Guo, Yanrong; Shao, Yeqin [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Gao, Yaozong; Price, True [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Computer Science, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Oto, Aytekin [Department of Radiology, Section of Urology, University of Chicago, Illinois 60637 (United States); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul 136-713 (Korea, Republic of)

2014-07-15

Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on

Segmentation of MR images via discriminative dictionary learning and sparse coding: Application to hippocampus labeling

OpenAIRE

Tong, Tong; Wolz, Robin; Coupe, Pierrick; Hajnal, Joseph V.; Rueckert, Daniel

2013-01-01

International audience; We propose a novel method for the automatic segmentation of brain MRI images by using discriminative dictionary learning and sparse coding techniques. In the proposed method, dictionaries and classifiers are learned simultaneously from a set of brain atlases, which can then be used for the reconstruction and segmentation of an unseen target image. The proposed segmentation strategy is based on image reconstruction, which is in contrast to most existing atlas-based labe...

Differential effects of visual context on pattern discrimination by pigeons (Columba livia) and humans (Homo sapiens).

Science.gov (United States)

Kelly, Debbie M; Cook, Robert G

2003-06-01

Three experiment examined the role of contextual information during line orientation and line position discriminations by pigeons (Columba livia) and humans (Homo sapiens). Experiment 1 tested pigeons' performance with these stimuli in a target localization task using texture displays. Experiments 2 and 3 tested pigeons and humans, respectively, with small and large variations of these stimuli in a same-different task. Humans showed a configural superiority effect when tested with displays constructed from large elements but not when tested with the smaller, more densely packed texture displays. The pigeons, in contrast, exhibited a configural inferiority effect when required to discriminate line orientation, regardless of stimulus size. These contrasting results suggest a species difference in the perceptionand use of features and contextual information in the discrimination of line information.

Dopamine D2 receptors mediate two-odor discrimination and reversal learning in C57BL/6 mice

Directory of Open Access Journals (Sweden)

Grandy David K

2004-04-01

Full Text Available Abstract Background Dopamine modulation of neuronal signaling in the frontal cortex, midbrain, and striatum is essential for processing and integrating diverse external sensory stimuli and attaching salience to environmental cues that signal causal relationships, thereby guiding goal-directed, adaptable behaviors. At the cellular level, dopamine signaling is mediated through D1-like or D2-like receptors. Although a role for D1-like receptors in a variety of goal-directed behaviors has been identified, an explicit involvement of D2 receptors has not been clearly established. To determine whether dopamine D2 receptor-mediated signaling contributes to associative and reversal learning, we compared C57Bl/6J mice that completely lack functional dopamine D2 receptors to wild-type mice with respect to their ability to attach appropriate salience to external stimuli (stimulus discrimination and disengage from inappropriate behavioral strategies when reinforcement contingencies change (e.g. reversal learning. Results Mildly food-deprived female wild-type and dopamine D2 receptor deficient mice rapidly learned to retrieve and consume visible food reinforcers from a small plastic dish. Furthermore, both genotypes readily learned to dig through the same dish filled with sterile sand in order to locate a buried food pellet. However, the dopamine D2 receptor deficient mice required significantly more trials than wild-type mice to discriminate between two dishes, each filled with a different scented sand, and to associate one of the two odors with the presence of a reinforcer (food. In addition, the dopamine D2 receptor deficient mice repeatedly fail to alter their response patterns during reversal trials where the reinforcement rules were inverted. Conclusions Inbred C57Bl/6J mice that develop in the complete absence of functional dopamine D2 receptors are capable of olfaction but display an impaired ability to acquire odor-driven reinforcement contingencies

Discriminative stimuli that control instrumental tobacco-seeking by human smokers also command selective attention.

Science.gov (United States)

Hogarth, Lee; Dickinson, Anthony; Duka, Theodora

2003-08-01

Incentive salience theory states that acquired bias in selective attention for stimuli associated with tobacco-smoke reinforcement controls the selective performance of tobacco-seeking and tobacco-taking behaviour. To support this theory, we assessed whether a stimulus that had acquired control of a tobacco-seeking response in a discrimination procedure would command the focus of visual attention in a subsequent test phase. Smokers received discrimination training in which an instrumental key-press response was followed by tobacco-smoke reinforcement when one visual discriminative stimulus (S+) was present, but not when another stimulus (S-) was present. The skin conductance response to the S+ and S- assessed whether Pavlovian conditioning to the S+ had taken place. In a subsequent test phase, the S+ and S- were presented in the dot-probe task and the allocation of the focus of visual attention to these stimuli was measured. Participants learned to perform the instrumental tobacco-seeking response selectively in the presence of the S+ relative to the S-, and showed a greater skin conductance response to the S+ than the S-. In the subsequent test phase, participants allocated the focus of visual attention to the S+ in preference to the S-. Correlation analysis revealed that the visual attentional bias for the S+ was positively associated with the number of times the S+ had been paired with tobacco-smoke in training, the skin conductance response to the S+ and with subjective craving to smoke. Furthermore, increased exposure to tobacco-smoke in the natural environment was associated with reduced discrimination learning. These data demonstrate that discriminative stimuli that signal that tobacco-smoke reinforcement is available acquire the capacity to command selective attentional and elicit instrumental tobacco-seeking behaviour.

Learning and Recognition of a Non-conscious Sequence of Events in Human Primary Visual Cortex.

Science.gov (United States)

Rosenthal, Clive R; Andrews, Samantha K; Antoniades, Chrystalina A; Kennard, Christopher; Soto, David

2016-03-21

Human primary visual cortex (V1) has long been associated with learning simple low-level visual discriminations [1] and is classically considered outside of neural systems that support high-level cognitive behavior in contexts that differ from the original conditions of learning, such as recognition memory [2, 3]. Here, we used a novel fMRI-based dichoptic masking protocol-designed to induce activity in V1, without modulation from visual awareness-to test whether human V1 is implicated in human observers rapidly learning and then later (15-20 min) recognizing a non-conscious and complex (second-order) visuospatial sequence. Learning was associated with a change in V1 activity, as part of a temporo-occipital and basal ganglia network, which is at variance with the cortico-cerebellar network identified in prior studies of "implicit" sequence learning that involved motor responses and visible stimuli (e.g., [4]). Recognition memory was associated with V1 activity, as part of a temporo-occipital network involving the hippocampus, under conditions that were not imputable to mechanisms associated with conscious retrieval. Notably, the V1 responses during learning and recognition separately predicted non-conscious recognition memory, and functional coupling between V1 and the hippocampus was enhanced for old retrieval cues. The results provide a basis for novel hypotheses about the signals that can drive recognition memory, because these data (1) identify human V1 with a memory network that can code complex associative serial visuospatial information and support later non-conscious recognition memory-guided behavior (cf. [5]) and (2) align with mouse models of experience-dependent V1 plasticity in learning and memory [6]. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pigeons learn stimulus identity and stimulus relations when both serve as redundant, relevant cues during same-different discrimination training.

Science.gov (United States)

Gibson, Brett M; Wasserman, Edward A

2003-01-01

The authors taught pigeons to discriminate displays of 16 identical items from displays of 16 nonidentical items. Unlike most same-different discrimination studies--where only stimulus relations could serve a discriminative function--both the identity of the items and the relations among the items were discriminative features of the displays. The pigeons learned about both stimulus identity and stimulus relations when these 2 sources of information served as redundant, relevant cues. In tests of associative competition, identity cues exerted greater stimulus control than relational cues. These results suggest that the pigeon can respond to both specific stimuli and general relations in the environment.

Does Fine Color Discrimination Learning in Free-Flying Honeybees Change Mushroom-Body Calyx Neuroarchitecture?

Science.gov (United States)

Sommerlandt, Frank M J; Spaethe, Johannes; Rössler, Wolfgang; Dyer, Adrian G

2016-01-01

Honeybees learn color information of rewarding flowers and recall these memories in future decisions. For fine color discrimination, bees require differential conditioning with a concurrent presentation of target and distractor stimuli to form a long-term memory. Here we investigated whether the long-term storage of color information shapes the neural network of microglomeruli in the mushroom body calyces and if this depends on the type of conditioning. Free-flying honeybees were individually trained to a pair of perceptually similar colors in either absolute conditioning towards one of the colors or in differential conditioning with both colors. Subsequently, bees of either conditioning groups were tested in non-rewarded discrimination tests with the two colors. Only bees trained with differential conditioning preferred the previously learned color, whereas bees of the absolute conditioning group, and a stimuli-naïve group, chose randomly among color stimuli. All bees were then kept individually for three days in the dark to allow for complete long-term memory formation. Whole-mount immunostaining was subsequently used to quantify variation of microglomeruli number and density in the mushroom-body lip and collar. We found no significant differences among groups in neuropil volumes and total microglomeruli numbers, but learning performance was negatively correlated with microglomeruli density in the absolute conditioning group. Based on these findings we aim to promote future research approaches combining behaviorally relevant color learning tests in honeybees under free-flight conditions with neuroimaging analysis; we also discuss possible limitations of this approach.

Learning Auditory Discrimination with Computer-Assisted Instruction: A Comparison of Two Different Performance Objectives.

Science.gov (United States)

Steinhaus, Kurt A.

A 12-week study of two groups of 14 college freshmen music majors was conducted to determine which group demonstrated greater achievement in learning auditory discrimination using computer-assisted instruction (CAI). The method employed was a pre-/post-test experimental design using subjects randomly assigned to a control group or an experimental…

Learning temporal context shapes prestimulus alpha oscillations and improves visual discrimination performance.

Science.gov (United States)

Toosi, Tahereh; K Tousi, Ehsan; Esteky, Hossein

2017-08-01

Time is an inseparable component of every physical event that we perceive, yet it is not clear how the brain processes time or how the neuronal representation of time affects our perception of events. Here we asked subjects to perform a visual discrimination task while we changed the temporal context in which the stimuli were presented. We collected electroencephalography (EEG) signals in two temporal contexts. In predictable blocks stimuli were presented after a constant delay relative to a visual cue, and in unpredictable blocks stimuli were presented after variable delays relative to the visual cue. Four subsecond delays of 83, 150, 400, and 800 ms were used in the predictable and unpredictable blocks. We observed that predictability modulated the power of prestimulus alpha oscillations in the parieto-occipital sites: alpha power increased in the 300-ms window before stimulus onset in the predictable blocks compared with the unpredictable blocks. This modulation only occurred in the longest delay period, 800 ms, in which predictability also improved the behavioral performance of the subjects. Moreover, learning the temporal context shaped the prestimulus alpha power: modulation of prestimulus alpha power grew during the predictable block and correlated with performance enhancement. These results suggest that the brain is able to learn the subsecond temporal context of stimuli and use this to enhance sensory processing. Furthermore, the neural correlate of this temporal prediction is reflected in the alpha oscillations. NEW & NOTEWORTHY It is not well understood how the uncertainty in the timing of an external event affects its processing, particularly at subsecond scales. Here we demonstrate how a predictable timing scheme improves visual processing. We found that learning the predictable scheme gradually shaped the prestimulus alpha power. These findings indicate that the human brain is able to extract implicit subsecond patterns in the temporal context of

Gender Discrimination, Education and Economic Growth in a Generalized Uzawa-Lucas Two-Sector Model

Directory of Open Access Journals (Sweden)

Zhang Wei-Bin

2014-06-01

Full Text Available This paper is mainly concerned with relationships between economic growth and gender discrimination in labor markets and education. Although discrimination in different fields has well been addresses and modelled in the economic literature, there are only a few growth models with endogenous wealth and human capital accumulation, gender time distribution between work, leisure and education under gender (positive or negative discrimination. The production and economic structures, human capital accumulation are based on the Uzawa-Lucas model, while the utility function and gender division of labor, leisure time and study time are based on the model by Zhang. The model takes account of learning by education in modeling human capital accumulation. We simulate the model to demonstrate the existence of equilibrium points and motion of the national economy. We also conduct a comparative dynamic analysis in regard to changes in discrimination in the education sector, women’s propensity to stay at home, women’s propensity to receive education, women’s knowledge utilization efficiency, and the propensity to save.

Label-Driven Learning Framework: Towards More Accurate Bayesian Network Classifiers through Discrimination of High-Confidence Labels

Directory of Open Access Journals (Sweden)

Yi Sun

2017-12-01

Full Text Available Bayesian network classifiers (BNCs have demonstrated competitive classification accuracy in a variety of real-world applications. However, it is error-prone for BNCs to discriminate among high-confidence labels. To address this issue, we propose the label-driven learning framework, which incorporates instance-based learning and ensemble learning. For each testing instance, high-confidence labels are first selected by a generalist classifier, e.g., the tree-augmented naive Bayes (TAN classifier. Then, by focusing on these labels, conditional mutual information is redefined to more precisely measure mutual dependence between attributes, thus leading to a refined generalist with a more reasonable network structure. To enable finer discrimination, an expert classifier is tailored for each high-confidence label. Finally, the predictions of the refined generalist and the experts are aggregated. We extend TAN to LTAN (Label-driven TAN by applying the proposed framework. Extensive experimental results demonstrate that LTAN delivers superior classification accuracy to not only several state-of-the-art single-structure BNCs but also some established ensemble BNCs at the expense of reasonable computation overhead.

Not All Same-Different Discriminations Are Created Equal: Evidence Contrary to a Unidimensional Account of Same-Different Learning

Science.gov (United States)

Gibson, Brett M.; Wasserman, Edward A.; Cook, Robert G.

2006-01-01

In Experiment 1, we trained four pigeons to concurrently discriminate displays of 16 same icons (16S) from displays of 16 different icons (16D) as well as between displays of same icons (16S) from displays that contained 15 same icons and one different icon (15S:1D). The birds rapidly learned to discriminate 16S vs. 16D displays, but they failed…

Separate and combined effects of the GABAA positive allosteric modulator diazepam and Δ⁹-THC in humans discriminating Δ⁹-THC.

Science.gov (United States)

Lile, Joshua A; Kelly, Thomas H; Hays, Lon R

2014-10-01

Our previous research suggested the involvement of γ-aminobutyric acid (GABA), in particular the GABAB receptor subtype, in the interoceptive effects of Δ(9)-tetrahydrocannabinol (Δ(9)-THC). The aim of the present study was to determine the potential involvement of the GABAA receptor subtype by assessing the separate and combined effects of the GABAA positive allosteric modulator diazepam and Δ(9)-THC using pharmacologically selective drug-discrimination procedures. Ten cannabis users learned to discriminate 30 mg oral Δ(9)-THC from placebo and then received diazepam (5 and 10mg), Δ(9)-THC (5, 15 and 30 mg) and placebo, alone and in combination. Self-report, task performance and physiological measures were also collected. Δ(9)-THC functioned as a discriminative stimulus, produced subjective effects typically associated with cannabinoids (e.g., High, Stoned, Like Drug) and elevated heart rate. Diazepam alone impaired performance on psychomotor performance tasks and increased ratings on a limited number of self-report questionnaire items (e.g., Any Effect, Sedated), but did not substitute for the Δ(9)-THC discriminative stimulus or alter the Δ(9)-THC discrimination dose-response function. Similarly, diazepam had limited impact on the other behavioral effects of Δ(9)-THC. These results suggest that the GABAA receptor subtype has minimal involvement in the interoceptive effects of Δ(9)-THC, and by extension cannabis, in humans. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Visual artificial grammar learning: comparative research on humans, kea (Nestor notabilis) and pigeons (Columba livia)

Science.gov (United States)

Stobbe, Nina; Westphal-Fitch, Gesche; Aust, Ulrike; Fitch, W. Tecumseh

2012-01-01

Artificial grammar learning (AGL) provides a useful tool for exploring rule learning strategies linked to general purpose pattern perception. To be able to directly compare performance of humans with other species with different memory capacities, we developed an AGL task in the visual domain. Presenting entire visual patterns simultaneously instead of sequentially minimizes the amount of required working memory. This approach allowed us to evaluate performance levels of two bird species, kea (Nestor notabilis) and pigeons (Columba livia), in direct comparison to human participants. After being trained to discriminate between two types of visual patterns generated by rules at different levels of computational complexity and presented on a computer screen, birds and humans received further training with a series of novel stimuli that followed the same rules, but differed in various visual features from the training stimuli. Most avian and all human subjects continued to perform well above chance during this initial generalization phase, suggesting that they were able to generalize learned rules to novel stimuli. However, detailed testing with stimuli that violated the intended rules regarding the exact number of stimulus elements indicates that neither bird species was able to successfully acquire the intended pattern rule. Our data suggest that, in contrast to humans, these birds were unable to master a simple rule above the finite-state level, even with simultaneous item presentation and despite intensive training. PMID:22688635

Sex differences in conditioned stimulus discrimination during context-dependent fear learning and its retrieval in humans: the role of biological sex, contraceptives and menstrual cycle phases.

Science.gov (United States)

Lonsdorf, Tina B; Haaker, Jan; Schümann, Dirk; Sommer, Tobias; Bayer, Janine; Brassen, Stefanie; Bunzeck, Nico; Gamer, Matthias; Kalisch, Raffael

2015-11-01

Anxiety disorders are more prevalent in women than in men. Despite this sexual dimorphism, most experimental studies are conducted in male participants and studies focusing on sex differences are sparse. In addition, the role of hormonal contraceptives and menstrual cycle phase in fear conditioning and extinction processes remain largely unknown. We investigated sex differences in context-dependent fear acquisition and extinction (day 1) and their retrieval/expression (day 2). Skin conductance responses (SCRs), fear and unconditioned stimulus expectancy ratings were obtained. We included 377 individuals (261 women) in our study. Robust sex differences were observed in all dependent measures. Women generally displayed higher subjective ratings but smaller SCRs than men and showed reduced excitatory/inhibitory conditioned stimulus (CS+/CS-) discrimination in all dependent measures. Furthermore, women using hormonal contraceptives showed reduced SCR CS discrimination on day 2 than men and free-cycling women, while menstrual cycle phase had no effect. Possible limitations include the simultaneous testing of up to 4 participants in cubicles, which might have introduced a social component, and not assessing postexperimental contingency awareness. The response pattern in women shows striking similarity to previously reported sex differences in patients with anxiety. Our results suggest that pronounced deficits in associative discrimination learning and subjective expression of safety information (CS- responses) might underlie higher prevalence and higher symptom rates seen in women with anxiety disorders. The data call for consideration of biological sex and hormonal contraceptive use in future studies and may suggest that targeting inhibitory learning during therapy might aid precision medicine.

Narrowing down the conditions for extinction of Pavlovian feature-positive discriminations in humans.

Science.gov (United States)

van Vooren, Priya R; Franssen, Mathijs; Beckers, Tom; Hermans, Dirk; Baeyens, Frank

2012-12-01

The aim of this study was to delineate the minimal conditions for extinction of Pavlovian modulation in humans. Previous experiments at our lab showed that, after X-- A+/A- acquisition training, X- trials did not extinguish differential X-- A+/A- responding, while X-- A- trials did. Additionally, X-- A- extinction training seemed only to extinguish differential X-- A+/A- responding, while leaving differential responding on a concurrently trained Y [Symbol: see text] B+/B- discrimination intact. It thus seemed that the X-- A+/A- discrimination can only be extinguished by X-- A- extinction trials. (Rescorla, Journal of Experimental Psychology: Animal Behavior Processes 12, 16-24, 1986), on the other hand, found that the minimal conditions for extinction were broader in pigeons: Namely, he found that an acquired X-- A+/A- discrimination could be extinguished by presenting the original feature X in combination with a different target (B) that was minimally trained as an exciter. We thus wanted to examine whether this was also the case in humans. We found that nonreinforced X-- B- presentations did not abolish discriminative X-- A/A responding when target B was a nonreinforced stimulus. Nonreinforced X-- B- trials did extinguish the X-- A+/A- discrimination when target B had previously been trained as a target for modulation (X-- B+/B- or Y [Symbol: see text] B+/B- training) or as a reinforced exciter (B+). Our results thusf parallel and extend those in nonhuman animals (Rescorla, Journal of Experimental Psychology: Animal Behavior Processes 12, 16-24, 1986).

Go/no-go discriminated avoidance learning in prenatally x-irradiated rats

International Nuclear Information System (INIS)

Tamaki, Y.; Inouye, M.

1988-01-01

Male Fischer344 rats were exposed to x-irradiation at a dose of 200 rad on Day 17 of gestation. Irradiated and control rats were tested at 10-13 weeks of age with the paradigm of go/no-go (active-passive) discriminated avoidance conditioning for three consecutive daily sessions. During the first conditioning session, they learned only active avoidance responses to two different warning signals. During the second and third sessions, they learned active and passive avoidance responses: in response to one warning signal, rats were required to make an active response to avoid a shock, but not to run in response to the other signal in order to avoid a shock. Prenatally irradiated rats made more active avoidance responses to both warning signals than controls (first session). In the early training phase of the go/no-go task, irradiated rats performed significantly higher active and lower passive avoidance responses than controls. Irradiated rats established a strong tendency to respond actively to the no-go signal, but eventually learned to respond to it

Valence of facial cues influences sheep learning in a visual discrimination task

OpenAIRE

Bellegarde, Lucille; Erhard, Hans; Weiss, A.; Boissy, Alain; Haskell, M.J.

2017-01-01

Sheep are one of the most studied farm species in terms of their ability to process information from faces, but little is known about their face-based emotion recognition abilities. We investigated (a) whether sheep could use images of sheep faces taken in situation of varying valence as cues in a simultaneous discrimination task and (b) whether the valence of the situation affects their learning performance. To accomplish this, we photographed faces of sheep in three situations inducing emot...

Valence of Facial Cues Influences Sheep Learning in a Visual Discrimination Task

OpenAIRE

Lucille G. A. Bellegarde; Lucille G. A. Bellegarde; Lucille G. A. Bellegarde; Hans W. Erhard; Alexander Weiss; Alain Boissy; Marie J. Haskell

2017-01-01

Sheep are one of the most studied farm species in terms of their ability to process information from faces, but little is known about their face-based emotion recognition abilities. We investigated (a) whether sheep could use images of sheep faces taken in situation of varying valence as cues in a simultaneous discrimination task and (b) whether the valence of the situation affects their learning performance. To accomplish this, we photographed faces of sheep in three situations inducing emot...

Vicarious learning from human models in monkeys.

Science.gov (United States)

Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

2012-01-01

We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

Derivation of Human Chromatic Discrimination Ability from an Information-Theoretical Notion of Distance in Color Space.

Science.gov (United States)

da Fonseca, María; Samengo, Inés

2016-12-01

The accuracy with which humans detect chromatic differences varies throughout color space. For example, we are far more precise when discriminating two similar orange stimuli than two similar green stimuli. In order for two colors to be perceived as different, the neurons representing chromatic information must respond differently, and the difference must be larger than the trial-to-trial variability of the response to each separate color. Photoreceptors constitute the first stage in the processing of color information; many more stages are required before humans can consciously report whether two stimuli are perceived as chromatically distinguishable. Therefore, although photoreceptor absorption curves are expected to influence the accuracy of conscious discriminability, there is no reason to believe that they should suffice to explain it. Here we develop information-theoretical tools based on the Fisher metric that demonstrate that photoreceptor absorption properties explain about 87% of the variance of human color discrimination ability, as tested by previous behavioral experiments. In the context of this theory, the bottleneck in chromatic information processing is determined by photoreceptor absorption characteristics. Subsequent encoding stages modify only marginally the chromatic discriminability at the photoreceptor level.

Managing Human Resource Learning for Innovation

DEFF Research Database (Denmark)

Nielsen, Peter

Managing human resource learning for innovation develops a systemic understanding of building innovative capabilities. Building innovative capabilities require active creation, coordination and absorption of useful knowledge and thus a cohesive management approach to learning. Often learning...... in organizations and work is approached without considerations on how to integrate it in the management of human resources. The book investigates the empirical conditions for managing human resources learning for innovation. With focus on innovative performance the importance of modes of innovation, clues...

Does Fine Color Discrimination Learning in Free-Flying Honeybees Change Mushroom-Body Calyx Neuroarchitecture?

Directory of Open Access Journals (Sweden)

Frank M J Sommerlandt

Full Text Available Honeybees learn color information of rewarding flowers and recall these memories in future decisions. For fine color discrimination, bees require differential conditioning with a concurrent presentation of target and distractor stimuli to form a long-term memory. Here we investigated whether the long-term storage of color information shapes the neural network of microglomeruli in the mushroom body calyces and if this depends on the type of conditioning. Free-flying honeybees were individually trained to a pair of perceptually similar colors in either absolute conditioning towards one of the colors or in differential conditioning with both colors. Subsequently, bees of either conditioning groups were tested in non-rewarded discrimination tests with the two colors. Only bees trained with differential conditioning preferred the previously learned color, whereas bees of the absolute conditioning group, and a stimuli-naïve group, chose randomly among color stimuli. All bees were then kept individually for three days in the dark to allow for complete long-term memory formation. Whole-mount immunostaining was subsequently used to quantify variation of microglomeruli number and density in the mushroom-body lip and collar. We found no significant differences among groups in neuropil volumes and total microglomeruli numbers, but learning performance was negatively correlated with microglomeruli density in the absolute conditioning group. Based on these findings we aim to promote future research approaches combining behaviorally relevant color learning tests in honeybees under free-flight conditions with neuroimaging analysis; we also discuss possible limitations of this approach.

Patterns of Learning in Verbal Discrimination as an Interaction of Social Reinforcement and Sex Combinations

Science.gov (United States)

Ratliff, Richard G.; And Others

1976-01-01

A total of 540 college students were run in two verbal discrimination learning studies (the second, a replication of the first) with one of three verbal reward conditions. In both studies, equal numbers of male and female subjects were run in each reward condition by each male and female experimenter. (MS)

Vicarious learning from human models in monkeys.

Directory of Open Access Journals (Sweden)

Rossella Falcone

Full Text Available We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was apparent from the first trial of the test phase, confirming the ability of monkeys to learn by vicarious observation of human models.

Sparse representation for infrared Dim target detection via a discriminative over-complete dictionary learned online.

Science.gov (United States)

Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju

2014-05-27

It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

Sparse Representation for Infrared Dim Target Detection via a Discriminative Over-Complete Dictionary Learned Online

Directory of Open Access Journals (Sweden)

Zheng-Zhou Li

2014-05-01

Full Text Available It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn’t be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.

A possible structural correlate of learning performance on a colour discrimination task in the brain of the bumblebee

Science.gov (United States)

Li, Li; MaBouDi, HaDi; Egertová, Michaela; Elphick, Maurice R.

2017-01-01

Synaptic plasticity is considered to be a basis for learning and memory. However, the relationship between synaptic arrangements and individual differences in learning and memory is poorly understood. Here, we explored how the density of microglomeruli (synaptic complexes) within specific regions of the bumblebee (Bombus terrestris) brain relates to both visual learning and inter-individual differences in learning and memory performance on a visual discrimination task. Using whole-brain immunolabelling, we measured the density of microglomeruli in the collar region (visual association areas) of the mushroom bodies of the bumblebee brain. We found that bumblebees which made fewer errors during training in a visual discrimination task had higher microglomerular density. Similarly, bumblebees that had better retention of the learned colour-reward associations two days after training had higher microglomerular density. Further experiments indicated experience-dependent changes in neural circuitry: learning a colour-reward contingency with 10 colours (but not two colours) does result, and exposure to many different colours may result, in changes to microglomerular density in the collar region of the mushroom bodies. These results reveal the varying roles that visual experience, visual learning and foraging activity have on neural structure. Although our study does not provide a causal link between microglomerular density and performance, the observed positive correlations provide new insights for future studies into how neural structure may relate to inter-individual differences in learning and memory. PMID:28978727

A possible structural correlate of learning performance on a colour discrimination task in the brain of the bumblebee.

Science.gov (United States)

Li, Li; MaBouDi, HaDi; Egertová, Michaela; Elphick, Maurice R; Chittka, Lars; Perry, Clint J

2017-10-11

Synaptic plasticity is considered to be a basis for learning and memory. However, the relationship between synaptic arrangements and individual differences in learning and memory is poorly understood. Here, we explored how the density of microglomeruli (synaptic complexes) within specific regions of the bumblebee ( Bombus terrestris ) brain relates to both visual learning and inter-individual differences in learning and memory performance on a visual discrimination task. Using whole-brain immunolabelling, we measured the density of microglomeruli in the collar region (visual association areas) of the mushroom bodies of the bumblebee brain. We found that bumblebees which made fewer errors during training in a visual discrimination task had higher microglomerular density. Similarly, bumblebees that had better retention of the learned colour-reward associations two days after training had higher microglomerular density. Further experiments indicated experience-dependent changes in neural circuitry: learning a colour-reward contingency with 10 colours (but not two colours) does result, and exposure to many different colours may result, in changes to microglomerular density in the collar region of the mushroom bodies. These results reveal the varying roles that visual experience, visual learning and foraging activity have on neural structure. Although our study does not provide a causal link between microglomerular density and performance, the observed positive correlations provide new insights for future studies into how neural structure may relate to inter-individual differences in learning and memory. © 2017 The Authors.

Hippocampus, Perirhinal Cortex, and Complex Visual Discriminations in Rats and Humans

Science.gov (United States)

Hales, Jena B.; Broadbent, Nicola J.; Velu, Priya D.; Squire, Larry R.; Clark, Robert E.

2015-01-01

Structures in the medial temporal lobe, including the hippocampus and perirhinal cortex, are known to be essential for the formation of long-term memory. Recent animal and human studies have investigated whether perirhinal cortex might also be important for visual perception. In our study, using a simultaneous oddity discrimination task, rats with…

Robot learning from human teachers

CERN Document Server

Chernova, Sonia

2014-01-01

Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn f

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data.

Science.gov (United States)

Tomazzoli, Maíra M; Pai Neto, Remi D; Moresco, Rodolfo; Westphal, Larissa; Zeggio, Amelia R S; Specht, Leandro; Costa, Christopher; Rocha, Miguel; Maraschin, Marcelo

2015-12-01

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plant's resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( λ= 280-400 ηm), suggesting that besides the biological activities of those

Faster native vowel discrimination learning in musicians is mediated by an optimization of mnemonic functions.

Science.gov (United States)

Elmer, Stefan; Greber, Marielle; Pushparaj, Arethy; Kühnis, Jürg; Jäncke, Lutz

2017-09-01

The ability to discriminate phonemes varying in spectral and temporal attributes constitutes one of the most basic intrinsic elements underlying language learning mechanisms. Since previous work has consistently shown that professional musicians are characterized by perceptual and cognitive advantages in a variety of language-related tasks, and since vowels can be considered musical sounds within the domain of speech, here we investigated the behavioral and electrophysiological correlates of native vowel discrimination learning in a sample of professional musicians and non-musicians. We evaluated the contribution of both the neurophysiological underpinnings of perceptual (i.e., N1/P2 complex) and mnemonic functions (i.e., N400 and P600 responses) while the participants were instructed to judge whether pairs of native consonant-vowel (CV) syllables manipulated in the first formant transition of the vowel (i.e., from /tu/ to /to/) were identical or not. Results clearly demonstrated faster learning in musicians, compared to non-musicians, as reflected by shorter reaction times and higher accuracy. Most notably, in terms of morphology, time course, and voltage strength, this steeper learning curve was accompanied by distinctive N400 and P600 manifestations between the two groups. In contrast, we did not reveal any group differences during the early stages of auditory processing (i.e., N1/P2 complex), suggesting that faster learning was mediated by an optimization of mnemonic but not perceptual functions. Based on a clear taxonomy of the mnemonic functions involved in the task, results are interpreted as pointing to a relationship between faster learning mechanisms in musicians and an optimization of echoic (i.e., N400 component) and working memory (i.e., P600 component) functions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Vicarious Learning from Human Models in Monkeys

OpenAIRE

Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

2012-01-01

We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was app...

Separate and combined effects of the GABAB agonist baclofen and Δ9-THC in humans discriminating Δ9-THC

Science.gov (United States)

Lile, Joshua A.; Kelly, Thomas H.; Hays, Lon R.

2012-01-01

Background Our previous research with the GABA reuptake inhibitor tiagabine suggested the involvement GABA in the interoceptive effects of Δ9-THC. The aim of the present study was to determine the potential involvement of the GABAB receptor subtype by assessing the separate and combined effects of the GABAB-selective agonist baclofen and Δ9-THC using pharmacologically specific drug-discrimination procedures. Methods Eight cannabis users learned to discriminate 30 mg oral Δ9-THC from placebo and then received baclofen (25 and 50 mg), Δ9-THC (5, 15 and 30 mg) and placebo, alone and in combination. Self-report, task performance and physiological measures were also collected. Results Δ9-THC functioned as a discriminative stimulus, produced subjective effects typically associated with cannabinoids (e.g., High, Stoned, Like Drug), elevated heart rate and impaired rate and accuracy on a psychomotor performance task. Baclofen alone (50 mg) substituted for the Δ9-THC discriminative stimulus, and both baclofen doses shifted the discriminative-stimulus effects of Δ9-THC leftward/upward. Similar results were observed on other cannabinoid-sensitive outcomes, although baclofen generally did not engender Δ9-THC-like subjective responses when administered alone. Conclusions These results suggest that the GABAB receptor subtype is involved in the abuse-related effects of Δ9-THC, and that GABAB receptors were responsible, at least in part, for the effects of tiagabine-induced elevated GABA on cannabinoid-related behaviors in our previous study. Future research should test GABAergic compounds selective for other GABA receptor subtypes (i.e., GABAA) to determine the contribution of the different GABA receptors in the effects of Δ9-THC, and by extension cannabis, in humans. PMID:22699093

Attentional Bias in Human Category Learning: The Case of Deep Learning.

Science.gov (United States)

Hanson, Catherine; Caglar, Leyla Roskan; Hanson, Stephen José

2018-01-01

Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987) showed that stimuli can have structures with features that are statistically uncorrelated (separable) or statistically correlated (integral) within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974). In contrast to humans, a single hidden layer backpropagation (BP) neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993). This "failure" to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1) by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2) by investigating whether a Deep Learning (DL) network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc.), would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993). Second, we show that using the same low dimensional stimuli, Deep Learning (DL), unlike BP but similar to humans, learns separable category structures more quickly than integral category structures

Attentional Bias in Human Category Learning: The Case of Deep Learning

Directory of Open Access Journals (Sweden)

Catherine Hanson

2018-04-01

Full Text Available Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987 showed that stimuli can have structures with features that are statistically uncorrelated (separable or statistically correlated (integral within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974. In contrast to humans, a single hidden layer backpropagation (BP neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993. This “failure” to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1 by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2 by investigating whether a Deep Learning (DL network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc., would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993. Second, we show that using the same low dimensional stimuli, Deep Learning (DL, unlike BP but similar to humans, learns separable category structures more quickly than integral category

Accounting for individual differences in human associative learning.

Science.gov (United States)

Byrom, Nicola C

2013-09-04

Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility in learning caused by external factors, there has been limited work considering how to model the influence of dispositional factors. This review looks at the range of individual differences in human associative learning that have been explored and the attempts to account for, and model, this flexibility. To fully understand human associative learning, further research needs to attend to the causes of variation in human learning.

Accounting for Individual Differences in Human Associative Learning.

Directory of Open Access Journals (Sweden)

Nicola C Byrom

2013-09-01

Full Text Available Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility in learning caused by external factors, there has been limited work considering how to model the influence of dispositional factors. This review looks at the range of individual differences in human associative learning that have been explored and the attempts to account for, and model, this flexibility. To fully understand human associative learning, further research needs to attend to the causes of variation in human learning.

Non-discrimination and equality of women

NARCIS (Netherlands)

Oostland, Rolanda Carina

2006-01-01

Non-discrimination is considered to be a cornerstone of the human rights framework of the United Nations. Already in the UN Charter of 1945 it is stated that human rights should be promoted without discrimination as to, amongst other things, sex. This principle of non-discrimination on the ground of

Discriminative Multi-View Interactive Image Re-Ranking.

Science.gov (United States)

Li, Jun; Xu, Chang; Yang, Wankou; Sun, Changyin; Tao, Dacheng

2017-07-01

Given an unreliable visual patterns and insufficient query information, content-based image retrieval is often suboptimal and requires image re-ranking using auxiliary information. In this paper, we propose a discriminative multi-view interactive image re-ranking (DMINTIR), which integrates user relevance feedback capturing users' intentions and multiple features that sufficiently describe the images. In DMINTIR, heterogeneous property features are incorporated in the multi-view learning scheme to exploit their complementarities. In addition, a discriminatively learned weight vector is obtained to reassign updated scores and target images for re-ranking. Compared with other multi-view learning techniques, our scheme not only generates a compact representation in the latent space from the redundant multi-view features but also maximally preserves the discriminative information in feature encoding by the large-margin principle. Furthermore, the generalization error bound of the proposed algorithm is theoretically analyzed and shown to be improved by the interactions between the latent space and discriminant function learning. Experimental results on two benchmark data sets demonstrate that our approach boosts baseline retrieval quality and is competitive with the other state-of-the-art re-ranking strategies.

Modification method to reduce the impact of blood vessel on noncontact discrimination of human blood based on ;M+N; theory

Science.gov (United States)

Zhang, Linna; Ding, Hongyan; Lin, Ling; Wang, Yimin; Guo, Xin

2018-01-01

Noncontact discriminating human blood is significantly crucial for import-export ports and inspection and quarantine departments. We had already demonstrated that visible diffuse reflectance spectroscopy combining PLS-DA method can successfully realize noncontact human blood discrimination. However, the circulated blood vessels may be produced with different materials. The use of various kinds of blood tubes may have a negative effect on the discrimination, based on ;M+N; theory (Li et al., 2016). In this research, we explored the impact of different material of blood vessels, such as glass tube and plastic tube, on the prediction ability of the discrimination model. Furthermore, we searched for the modification method to reduce the influence from the blood tubes. Our work indicated that generalized diffuse reflectance method can greatly improve the discrimination accuracy. This research can greatly facilitate the application of noncontact discrimination method based on visible and near-infrared diffuse reflectance spectroscopy.

Pattern recognition in bees : orientation discrimination

NARCIS (Netherlands)

Hateren, J.H. van; Srinivasan, M.V.; Wait, P.B.

1990-01-01

Honey bees (Apis mellifera, worker) were trained to discriminate between two random gratings oriented perpendicularly to each other. This task was quickly learned with vertical, horizontal, and oblique gratings. After being trained on perpendicularly-oriented random gratings, bees could discriminate

Human Activity Recognition from Body Sensor Data using Deep Learning.

Science.gov (United States)

Hassan, Mohammad Mehedi; Huda, Shamsul; Uddin, Md Zia; Almogren, Ahmad; Alrubaian, Majed

2018-04-16

In recent years, human activity recognition from body sensor data or wearable sensor data has become a considerable research attention from academia and health industry. This research can be useful for various e-health applications such as monitoring elderly and physical impaired people at Smart home to improve their rehabilitation processes. However, it is not easy to accurately and automatically recognize physical human activity through wearable sensors due to the complexity and variety of body activities. In this paper, we address the human activity recognition problem as a classification problem using wearable body sensor data. In particular, we propose to utilize a Deep Belief Network (DBN) model for successful human activity recognition. First, we extract the important initial features from the raw body sensor data. Then, a kernel principal component analysis (KPCA) and linear discriminant analysis (LDA) are performed to further process the features and make them more robust to be useful for fast activity recognition. Finally, the DBN is trained by these features. Various experiments were performed on a real-world wearable sensor dataset to verify the effectiveness of the deep learning algorithm. The results show that the proposed DBN outperformed other algorithms and achieves satisfactory activity recognition performance.

PROCEDURE OF THE INSTITUTION OF HUMAN RIGHTS OMBUDSMAN OF BOSNIA AND HERZEGOVINA IN CASES OF DISCRIMINATION

Directory of Open Access Journals (Sweden)

Ljubinko Mitrović

2017-12-01

Full Text Available Human Rights Ombudspersons or national institutions for the protection of human rights in most of modern countries today are independent institutions established with the aim of promoting good governance and the rule of law, as well as protection of human rights and fundamental freedoms. Their jurisdiction includes, as a rule, protection and promotion of human rights and freedoms, as well as the functioning of the national preventive mechanisms for the prevention and the prevention of torture and other cruel, inhuman or degrading treatment or punishment. In addition, the powers of these institutions also cover procedures to be applied in cases involving freedom of access to information, and ministerial, governmental and other appointments. An important segment in functioning of the Ombudsman is the prevention or elimination of discrimination. Discrimination (originating from the Latin word discriminare: separate, distinguish, unwarranted discrimination or unequal treatment, or illegal distinction is a negative and socially dangerous phenomenon which in a nutshell means any unequal or different treatment including every exclusion, restriction or preference based on real or assumed grounds against any person or group of persons, and their blood relatives or otherwise related to them, on the basis of their race, color, language, religion, ethnicity, disability, age, national or social origin, political or other opinion, property, membership in a trade union or any other association, education, social status and sex, sexual expression or sexual orientation, and any other circumstance with a purpose or a consequence to disable or endanger recognition, enjoyment or exercise on an equal basis, rights and freedoms in all spheres of life. The methods applied in operation of the national bodies for the protection of equality, primarily the Institution of Human Rights Ombudsman of Bosnia and Herzegovina in discrimination cases are subject of this paper.

Paintings discrimination by mice: Different strategies for different paintings.

Science.gov (United States)

Watanabe, Shigeru

2017-09-01

C57BL/6 mice were trained on simultaneous discrimination of paintings with multiple exemplars, using an operant chamber with a touch screen. The number of exemplars was successively increased up to six. Those mice trained in Kandinsky/Mondrian discrimination showed improved learning and generalization, whereas those trained in Picasso/Renoir discrimination showed no improvements in learning or generalization. These results suggest category-like discrimination in the Kandinsky/Mondrian task, but item-to-item discrimination in the Picasso/Renoir task. Mice maintained their discriminative behavior in a pixelization test with various paintings; however, mice in the Picasso/Renoir task showed poor performance in a test that employed scrambling processing. These results do not indicate that discrimination strategy for any Kandinsky/Mondrian combinations differed from that for any Picasso/Monet combinations but suggest the mice employed different strategies of discrimination tasks depending upon stimuli. Copyright © 2017 Elsevier B.V. All rights reserved.

The time course of shape discrimination in the human brain.

Science.gov (United States)

Ales, Justin M; Appelbaum, L Gregory; Cottereau, Benoit R; Norcia, Anthony M

2013-02-15

The lateral occipital cortex (LOC) activates selectively to images of intact objects versus scrambled controls, is selective for the figure-ground relationship of a scene, and exhibits at least some degree of invariance for size and position. Because of these attributes, it is considered to be a crucial part of the object recognition pathway. Here we show that human LOC is critically involved in perceptual decisions about object shape. High-density EEG was recorded while subjects performed a threshold-level shape discrimination task on texture-defined figures segmented by either phase or orientation cues. The appearance or disappearance of a figure region from a uniform background generated robust visual evoked potentials throughout retinotopic cortex as determined by inverse modeling of the scalp voltage distribution. Contrasting responses from trials containing shape changes that were correctly detected (hits) with trials in which no change occurred (correct rejects) revealed stimulus-locked, target-selective activity in the occipital visual areas LOC and V4 preceding the subject's response. Activity that was locked to the subjects' reaction time was present in the LOC. Response-locked activity in the LOC was determined to be related to shape discrimination for several reasons: shape-selective responses were silenced when subjects viewed identical stimuli but their attention was directed away from the shapes to a demanding letter discrimination task; shape-selectivity was present across four different stimulus configurations used to define the figure; LOC responses correlated with participants' reaction times. These results indicate that decision-related activity is present in the LOC when subjects are engaged in threshold-level shape discriminations. Copyright © 2012 Elsevier Inc. All rights reserved.

Statistics that learn: can logistic discriminant analysis improve diagnosis in brain SPECT?

International Nuclear Information System (INIS)

Behin-Ain, S.; Barnden, L.; Kwiatek, R.; Del Fante, P.; Casse, R.; Burnet, R.; Chew, G.; Kitchener, M.; Boundy, K.; Unger, S.

2002-01-01

Full text: Logistic discriminant analysis (LDA) is a statistical technique capable of discriminating individuals within a diseased group against normals. It also enables classification of various diseases within a group of patients. This technique provides a quantitative, automated and non-subjective clinical diagnostic tool. Based on a population known to have the disease and a normal control group, an algorithm was developed and trained to identify regions in the human brain responsible for the disease in question. The algorithm outputs a statistical map representing diseased or normal probability on a voxel or cluster basis from which an index is generated for each subject. The algorithm also generates a set of coefficients which is used to generate an index for the purpose of classification of new subjects. The results are comparable and complement those of Statistical Parametric Mapping (SPM) which employs a more common linear discriminant technique. The results are presented for brain SPECT studies of two diseases: chronic fatigue syndrome (CFS) and fibromyalgia (FM). A 100% specificity and 94% sensitivity is achieved for the CFS study (similar to SPM results) and for the FM study 82% specificity and 94% sensitivity is achieved with corresponding SPM results showing 90% specificity and 82% sensitivity. The results encourages application of LDA for discrimination of new single subjects as well as of diseased and normal groups. Copyright (2002) The Australian and New Zealand Society of Nuclear Medicine Inc

Learning discriminative distance functions for valve retrieval and improved decision support in valvular heart disease

Science.gov (United States)

Voigt, Ingmar; Vitanovski, Dime; Ionasec, Razvan I.; Tsymal, Alexey; Georgescu, Bogdan; Zhou, Shaohua K.; Huber, Martin; Navab, Nassir; Hornegger, Joachim; Comaniciu, Dorin

2010-03-01

Disorders of the heart valves constitute a considerable health problem and often require surgical intervention. Recently various approaches were published seeking to overcome the shortcomings of current clinical practice,that still relies on manually performed measurements for performance assessment. Clinical decisions are still based on generic information from clinical guidelines and publications and personal experience of clinicians. We present a framework for retrieval and decision support using learning based discriminative distance functions and visualization of patient similarity with relative neighborhood graphsbased on shape and derived features. We considered two learning based techniques, namely learning from equivalence constraints and the intrinsic Random Forest distance. The generic approach enables for learning arbitrary user-defined concepts of similarity depending on the application. This is demonstrated with the proposed applications, including automated diagnosis and interventional suitability classification, where classification rates of up to 88.9% and 85.9% could be observed on a set of valve models from 288 and 102 patients respectively.

Human Learning and Memory

Science.gov (United States)

Lieberman, David A.

2012-01-01

This innovative textbook is the first to integrate learning and memory, behaviour, and cognition. It focuses on fascinating human research in both memory and learning (while also bringing in important animal studies) and brings the reader up to date with the latest developments in the subject. Students are encouraged to think critically: key…

Localized brain activation related to the strength of auditory learning in a parrot.

Directory of Open Access Journals (Sweden)

Hiroko Eda-Fujiwara

Full Text Available Parrots and songbirds learn their vocalizations from a conspecific tutor, much like human infants acquire spoken language. Parrots can learn human words and it has been suggested that they can use them to communicate with humans. The caudomedial pallium in the parrot brain is homologous with that of songbirds, and analogous to the human auditory association cortex, involved in speech processing. Here we investigated neuronal activation, measured as expression of the protein product of the immediate early gene ZENK, in relation to auditory learning in the budgerigar (Melopsittacus undulatus, a parrot. Budgerigar males successfully learned to discriminate two Japanese words spoken by another male conspecific. Re-exposure to the two discriminanda led to increased neuronal activation in the caudomedial pallium, but not in the hippocampus, compared to untrained birds that were exposed to the same words, or were not exposed to words. Neuronal activation in the caudomedial pallium of the experimental birds was correlated significantly and positively with the percentage of correct responses in the discrimination task. These results suggest that in a parrot, the caudomedial pallium is involved in auditory learning. Thus, in parrots, songbirds and humans, analogous brain regions may contain the neural substrate for auditory learning and memory.

Age-related sensitive periods influence visual language discrimination in adults.

Science.gov (United States)

Weikum, Whitney M; Vouloumanos, Athena; Navarra, Jordi; Soto-Faraco, Salvador; Sebastián-Gallés, Núria; Werker, Janet F

2013-01-01

Adults as well as infants have the capacity to discriminate languages based on visual speech alone. Here, we investigated whether adults' ability to discriminate languages based on visual speech cues is influenced by the age of language acquisition. Adult participants who had all learned English (as a first or second language) but did not speak French were shown faces of bilingual (French/English) speakers silently reciting sentences in either language. Using only visual speech information, adults who had learned English from birth or as a second language before the age of 6 could discriminate between French and English significantly better than chance. However, adults who had learned English as a second language after age 6 failed to discriminate these two languages, suggesting that early childhood exposure is crucial for using relevant visual speech information to separate languages visually. These findings raise the possibility that lowered sensitivity to non-native visual speech cues may contribute to the difficulties encountered when learning a new language in adulthood.

Discriminating Children with Autism from Children with Learning Difficulties with an Adaptation of the Short Sensory Profile

Science.gov (United States)

O'Brien, Justin; Tsermentseli, Stella; Cummins, Omar; Happe, Francesca; Heaton, Pamela; Spencer, Janine

2009-01-01

In this article, we examine the extent to which children with autism and children with learning difficulties can be discriminated from their responses to different patterns of sensory stimuli. Using an adapted version of the Short Sensory Profile (SSP), sensory processing was compared in 34 children with autism to 33 children with typical…

Data preprocessing techniques for classification without discrimination

NARCIS (Netherlands)

Kamiran, F.; Calders, T.G.K.

2012-01-01

Recently, the following Discrimination-Aware Classification Problem was introduced: Suppose we are given training data that exhibit unlawful discrimination; e.g., toward sensitive attributes such as gender or ethnicity. The task is to learn a classifier that optimizes accuracy, but does not have

Human capital and human resource management to achieve ambidextrous learning: A structural perspective

Directory of Open Access Journals (Sweden)

Mirta Diaz-Fernandez

2017-01-01

Full Text Available Organisational learning has become increasingly important for strategic renewal. Ambidextrous organisations are especially successful in the current environment, where firms are required to be efficient and adapt to change. Using a structural approach, this study discusses arguments about the nature of ambidexterity and identifies the kinds of human capital that better support specific learning types and HRM practices suited to these components of human capital. Results highlight learning differences between marketing and production units, as well as different HRM practices and human capital orientations. This study points out that human capital mediates between HRM practices and learning.

Hippocampal theta activity is selectively associated with contingency detection but not discrimination in rabbit discrimination-reversal eyeblink conditioning.

Science.gov (United States)

Nokia, Miriam S; Wikgren, Jan

2010-04-01

The relative power of the hippocampal theta-band ( approximately 6 Hz) activity (theta ratio) is thought to reflect a distinct neural state and has been shown to affect learning rate in classical eyeblink conditioning in rabbits. We sought to determine if the theta ratio is mostly related to the detection of the contingency between the stimuli used in conditioning or also to the learning of more complex inhibitory associations when a highly demanding delay discrimination-reversal eyeblink conditioning paradigm is used. A high hippocampal theta ratio was not only associated with a fast increase in conditioned responding in general but also correlated with slow emergence of discriminative responding due to sustained responding to the conditioned stimulus not paired with an unconditioned stimulus. The results indicate that the neural state reflected by the hippocampal theta ratio is specifically linked to forming associations between stimuli rather than to the learning of inhibitory associations needed for successful discrimination. This is in line with the view that the hippocampus is responsible for contingency detection in the early phase of learning in eyeblink conditioning. (c) 2009 Wiley-Liss, Inc.

Activations of human auditory cortex to phonemic and nonphonemic vowels during discrimination and memory tasks.

Science.gov (United States)

Harinen, Kirsi; Rinne, Teemu

2013-08-15

We used fMRI to investigate activations within human auditory cortex (AC) to vowels during vowel discrimination, vowel (categorical n-back) memory, and visual tasks. Based on our previous studies, we hypothesized that the vowel discrimination task would be associated with increased activations in the anterior superior temporal gyrus (STG), while the vowel memory task would enhance activations in the posterior STG and inferior parietal lobule (IPL). In particular, we tested the hypothesis that activations in the IPL during vowel memory tasks are associated with categorical processing. Namely, activations due to categorical processing should be higher during tasks performed on nonphonemic (hard to categorize) than on phonemic (easy to categorize) vowels. As expected, we found distinct activation patterns during vowel discrimination and vowel memory tasks. Further, these task-dependent activations were different during tasks performed on phonemic or nonphonemic vowels. However, activations in the IPL associated with the vowel memory task were not stronger during nonphonemic than phonemic vowel blocks. Together these results demonstrate that activations in human AC to vowels depend on both the requirements of the behavioral task and the phonemic status of the vowels. Copyright © 2013 Elsevier Inc. All rights reserved.

Model-observer similarity, error modeling and social learning in rhesus macaques.

Directory of Open Access Journals (Sweden)

Elisabetta Monfardini

Full Text Available Monkeys readily learn to discriminate between rewarded and unrewarded items or actions by observing their conspecifics. However, they do not systematically learn from humans. Understanding what makes human-to-monkey transmission of knowledge work or fail could help identify mediators and moderators of social learning that operate regardless of language or culture, and transcend inter-species differences. Do monkeys fail to learn when human models show a behavior too dissimilar from the animals' own, or when they show a faultless performance devoid of error? To address this question, six rhesus macaques trained to find which object within a pair concealed a food reward were successively tested with three models: a familiar conspecific, a 'stimulus-enhancing' human actively drawing the animal's attention to one object of the pair without actually performing the task, and a 'monkey-like' human performing the task in the same way as the monkey model did. Reward was manipulated to ensure that all models showed equal proportions of errors and successes. The 'monkey-like' human model improved the animals' subsequent object discrimination learning as much as a conspecific did, whereas the 'stimulus-enhancing' human model tended on the contrary to retard learning. Modeling errors rather than successes optimized learning from the monkey and 'monkey-like' models, while exacerbating the adverse effect of the 'stimulus-enhancing' model. These findings identify error modeling as a moderator of social learning in monkeys that amplifies the models' influence, whether beneficial or detrimental. By contrast, model-observer similarity in behavior emerged as a mediator of social learning, that is, a prerequisite for a model to work in the first place. The latter finding suggests that, as preverbal infants, macaques need to perceive the model as 'like-me' and that, once this condition is fulfilled, any agent can become an effective model.

The evolutionary basis of human social learning.

Science.gov (United States)

Morgan, T J H; Rendell, L E; Ehn, M; Hoppitt, W; Laland, K N

2012-02-22

Humans are characterized by an extreme dependence on culturally transmitted information. Such dependence requires the complex integration of social and asocial information to generate effective learning and decision making. Recent formal theory predicts that natural selection should favour adaptive learning strategies, but relevant empirical work is scarce and rarely examines multiple strategies or tasks. We tested nine hypotheses derived from theoretical models, running a series of experiments investigating factors affecting when and how humans use social information, and whether such behaviour is adaptive, across several computer-based tasks. The number of demonstrators, consensus among demonstrators, confidence of subjects, task difficulty, number of sessions, cost of asocial learning, subject performance and demonstrator performance all influenced subjects' use of social information, and did so adaptively. Our analysis provides strong support for the hypothesis that human social learning is regulated by adaptive learning rules.

Discrimination of human and nonhuman blood using Raman spectroscopy with self-reference algorithm

Science.gov (United States)

Bian, Haiyi; Wang, Peng; Wang, Jun; Yin, Huancai; Tian, Yubing; Bai, Pengli; Wu, Xiaodong; Wang, Ning; Tang, Yuguo; Gao, Jing

2017-09-01

We report a self-reference algorithm to discriminate human and nonhuman blood by calculating the ratios of identification Raman peaks to reference Raman peaks and choosing appropriate threshold values. The influence of using different reference peaks and identification peaks was analyzed in detail. The Raman peak at 1003 cm-1 was proved to be a stable reference peak to avoid the influencing factors, such as the incident laser intensity and the amount of sample. The Raman peak at 1341 cm-1 was found to be an efficient identification peak, which indicates that the difference between human and nonhuman blood results from the C-H bend in tryptophan. The comparison between self-reference algorithm and partial least square method was made. It was found that the self-reference algorithm not only obtained the discrimination results with the same accuracy, but also provided information on the difference of chemical composition. In addition, the performance of self-reference algorithm whose true positive rate is 100% is significant for customs inspection to avoid genetic disclosure and forensic science.

Accounting for individual differences in human associative learning

OpenAIRE

Byrom, Nicola C.

2013-01-01

Associative learning has provided fundamental insights to understanding psychopathology. However, psychopathology occurs along a continuum and as such, identification of disruptions in processes of associative learning associated with aspects of psychopathology illustrates a general flexibility in human associative learning. A handful of studies have looked specifically at individual differences in human associative learning, but while much work has concentrated on accounting for flexibility ...

Quantifying explainable discrimination and removing illegal discrimination in automated decision making

KAUST Repository

Kamiran, Faisal

2012-11-18

Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train discrimination-free classifiers on such historical data that are discriminative, with respect to the given sensitive attribute. Existing techniques that deal with this problem aim at removing all discrimination and do not take into account that part of the discrimination may be explainable by other attributes. For example, in a job application, the education level of a job candidate could be such an explainable attribute. If the data contain many highly educated male candidates and only few highly educated women, a difference in acceptance rates between woman and man does not necessarily reflect gender discrimination, as it could be explained by the different levels of education. Even though selecting on education level would result in more males being accepted, a difference with respect to such a criterion would not be considered to be undesirable, nor illegal. Current state-of-the-art techniques, however, do not take such gender-neutral explanations into account and tend to overreact and actually start reverse discriminating, as we will show in this paper. Therefore, we introduce and analyze the refined notion of conditional non-discrimination in classifier design. We show that some of the differences in decisions across the sensitive groups can be explainable and are hence tolerable. Therefore, we develop methodology for quantifying the explainable discrimination and algorithmic techniques for removing the illegal discrimination when one or more attributes are considered as explanatory. Experimental evaluation on synthetic and real-world classification datasets demonstrates that the new techniques are superior to the old ones in this new context, as they succeed in

Discriminant forest classification method and system

Science.gov (United States)

Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

2012-11-06

A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

45 CFR 1151.21 - Discrimination prohibited.

Science.gov (United States)

2010-10-01

... 45 Public Welfare 3 2010-10-01 2010-10-01 false Discrimination prohibited. 1151.21 Section 1151.21... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination Prohibited Accessibility § 1151.21 Discrimination prohibited. No qualified handicapped person shall, because...

Legal Provisions, Discrimination and Uncertainty on LGBT community in Albania. Laws on human rights vs exerted rights of LGBT persons

Directory of Open Access Journals (Sweden)

Urjana Curi

2018-03-01

On March 13, 2010, the Anti-Discrimination Law, one of the essential legal instruments that protects human rights in Albania, and also includes the prohibition of discrimination on the basis of sexual orientation, came into force. Albania has already the Commissioner for Protection from Discrimination. Two LGBT organizations have already been established in Albania: the Alliance against Discrimination LGBT and LGBT Pro Albania. They aim to protect the rights of sexual minorities in Albania and promote a national movement of social mobilization to protect and promote the rights of this community in Albania

Perceptual learning modifies untrained pursuit eye movements

OpenAIRE

Szpiro, Sarit F. A.; Spering, Miriam; Carrasco, Marisa

2014-01-01

Perceptual learning improves detection and discrimination of relevant visual information in mature humans, revealing sensory plasticity. Whether visual perceptual learning affects motor responses is unknown. Here we implemented a protocol that enabled us to address this question. We tested a perceptual response (motion direction estimation, in which observers overestimate motion direction away from a reference) and a motor response (voluntary smooth pursuit eye movements). Perceptual training...

45 CFR 1110.3 - Discrimination prohibited.

Science.gov (United States)

2010-10-01

... 45 Public Welfare 3 2010-10-01 2010-10-01 false Discrimination prohibited. 1110.3 Section 1110.3... HUMANITIES GENERAL NONDISCRIMINATION IN FEDERALLY ASSISTED PROGRAMS § 1110.3 Discrimination prohibited. (a... from participation in, be denied the benefits of, or be otherwise subjected, to discrimination under...

45 CFR 1151.31 - Discrimination prohibited.

Science.gov (United States)

2010-10-01

... 45 Public Welfare 3 2010-10-01 2010-10-01 false Discrimination prohibited. 1151.31 Section 1151.31... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination Prohibited Employment § 1151.31 Discrimination prohibited. (a) No qualified handicapped person shall, on the...

Deep learning in color: towards automated quark/gluon jet discrimination

International Nuclear Information System (INIS)

Komiske, Patrick T.; Metodiev, Eric M.; Schwartz, Matthew D.

2017-01-01

Artificial intelligence offers the potential to automate challenging data-processing tasks in collider physics. Here, to establish its prospects, we explore to what extent deep learning with convolutional neural networks can discriminate quark and gluon jets better than observables designed by physicists. Our approach builds upon the paradigm that a jet can be treated as an image, with intensity given by the local calorimeter deposits. We supplement this construction by adding color to the images, with red, green and blue intensities given by the transverse momentum in charged particles, transverse momentum in neutral particles, and pixel-level charged particle counts. Overall, the deep networks match or outperform traditional jet variables. We also find that, while various simulations produce different quark and gluon jets, the neural networks are surprisingly insensitive to these differences, similar to traditional observables. This suggests that the networks can extract robust physical information from imperfect simulations.

Discriminative kernel feature extraction and learning for object recognition and detection

DEFF Research Database (Denmark)

Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

2015-01-01

Feature extraction and learning is critical for object recognition and detection. By embedding context cue of image attributes into the kernel descriptors, we propose a set of novel kernel descriptors called context kernel descriptors (CKD). The motivation of CKD is to use the spatial consistency...... even in high-dimensional space. In addition, the latent connection between Rényi quadratic entropy and the mapping data in kernel feature space further facilitates us to capture the geometric structure as well as the information about the underlying labels of the CKD using CSQMI. Thus the resulting...... codebook and reduced CKD are discriminative. We report superior performance of our algorithm for object recognition on benchmark datasets like Caltech-101 and CIFAR-10, as well as for detection on a challenging chicken feet dataset....

Accurate classification of brain gliomas by discriminate dictionary learning based on projective dictionary pair learning of proton magnetic resonance spectra.

Science.gov (United States)

Adebileje, Sikiru Afolabi; Ghasemi, Keyvan; Aiyelabegan, Hammed Tanimowo; Saligheh Rad, Hamidreza

2017-04-01

Proton magnetic resonance spectroscopy is a powerful noninvasive technique that complements the structural images of cMRI, which aids biomedical and clinical researches, by identifying and visualizing the compositions of various metabolites within the tissues of interest. However, accurate classification of proton magnetic resonance spectroscopy is still a challenging issue in clinics due to low signal-to-noise ratio, overlapping peaks of metabolites, and the presence of background macromolecules. This paper evaluates the performance of a discriminate dictionary learning classifiers based on projective dictionary pair learning method for brain gliomas proton magnetic resonance spectroscopy spectra classification task, and the result were compared with the sub-dictionary learning methods. The proton magnetic resonance spectroscopy data contain a total of 150 spectra (74 healthy, 23 grade II, 23 grade III, and 30 grade IV) from two databases. The datasets from both databases were first coupled together, followed by column normalization. The Kennard-Stone algorithm was used to split the datasets into its training and test sets. Performance comparison based on the overall accuracy, sensitivity, specificity, and precision was conducted. Based on the overall accuracy of our classification scheme, the dictionary pair learning method was found to outperform the sub-dictionary learning methods 97.78% compared with 68.89%, respectively. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Discrimination against Black Students

Science.gov (United States)

Aloud, Ashwaq; Alsulayyim, Maryam

2016-01-01

Discrimination is a structured way of abusing people based on racial differences, hence barring them from accessing wealth, political participation and engagement in many spheres of human life. Racism and discrimination are inherently rooted in institutions in the society, the problem has spread across many social segments of the society including…

Using human brain activity to guide machine learning.

Science.gov (United States)

Fong, Ruth C; Scheirer, Walter J; Cox, David D

2018-03-29

Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human brain has long served as a source of inspiration for machine learning, little effort has been made to directly use data collected from working brains as a guide for machine learning algorithms. Here we demonstrate a new paradigm of "neurally-weighted" machine learning, which takes fMRI measurements of human brain activity from subjects viewing images, and infuses these data into the training process of an object recognition learning algorithm to make it more consistent with the human brain. After training, these neurally-weighted classifiers are able to classify images without requiring any additional neural data. We show that our neural-weighting approach can lead to large performance gains when used with traditional machine vision features, as well as to significant improvements with already high-performing convolutional neural network features. The effectiveness of this approach points to a path forward for a new class of hybrid machine learning algorithms which take both inspiration and direct constraints from neuronal data.

Techniques for discrimination-free predictive models (Chapter 12)

NARCIS (Netherlands)

Kamiran, F.; Calders, T.G.K.; Pechenizkiy, M.; Custers, B.H.M.; Calders, T.G.K.; Schermer, B.W.; Zarsky, T.Z.

2013-01-01

In this chapter, we give an overview of the techniques developed ourselves for constructing discrimination-free classifiers. In discrimination-free classification the goal is to learn a predictive model that classifies future data objects as accurately as possible, yet the predicted labels should be

Effects of subchronic phencyclidine (PCP treatment on social behaviors, and operant discrimination and reversal learning in C57BL/6J mice

Directory of Open Access Journals (Sweden)

Jonathan L Brigman

2009-02-01

Full Text Available Subchronic treatment with the psychotomimetic phencyclidine (PCP has been proposed as a rodent model of the negative and cognitive/executive symptoms of schizophrenia. There has, however, been a paucity of studies on this model in mice, despite the growing use of the mouse as a subject in genetic and molecular studies of schizophrenia. In the present study, we evaluated the effects of subchronic PCP treatment (5 mg/kg twice daily x 7 days, followed by 7 days withdrawal in C57BL/6J mice on 1 social behaviors using a sociability/social novelty-preference paradigm, and 2 pairwise visual discrimination and reversal learning using a touchscreen-based operant system. Results showed that mice subchronically treated with PCP made more visits to (but did not spend more time with a social stimulus relative to an inanimate one, and made more visits and spent more time investigating a novel social stimulus over a familiar one. Subchronic PCP treatment did not significantly affect behavior in either the discrimination or reversal learning tasks. These data encourage further analysis of the potential utility of mouse subchronic PCP treatment for modeling the social withdrawal component of schizophrenia. They also indicate that the treatment regimen employed was insufficient to impair our measures of discrimination and reversal learning in the C57BL/6J strain. Further work will be needed to identify alternative methods (e.g., repeated cycles of subchronic PCP treatment, use of different mouse strains that produce discrimination and/or reversal impairment, as well as other cognitive/executive measures that are sensitive to chronic PCP treatment in mice.

A novel perceptual discrimination training task: Reducing fear overgeneralization in the context of fear learning.

Science.gov (United States)

Ginat-Frolich, Rivkah; Klein, Zohar; Katz, Omer; Shechner, Tomer

2017-06-01

Generalization is an adaptive learning mechanism, but it can be maladaptive when it occurs in excess. A novel perceptual discrimination training task was therefore designed to moderate fear overgeneralization. We hypothesized that improvement in basic perceptual discrimination would translate into lower fear overgeneralization in affective cues. Seventy adults completed a fear-conditioning task prior to being allocated into training or placebo groups. Predesignated geometric shape pairs were constructed for the training task. A target shape from each pair was presented. Thereafter, participants in the training group were shown both shapes and asked to identify the image that differed from the target. Placebo task participants only indicated the location of each shape on the screen. All participants then viewed new geometric pairs and indicated whether they were identical or different. Finally, participants completed a fear generalization test consisting of perceptual morphs ranging from the CS + to the CS-. Fear-conditioning was observed through physiological and behavioural measures. Furthermore, the training group performed better than the placebo group on the assessment task and exhibited decreased fear generalization in response to threat/safety cues. The findings offer evidence for the effectiveness of the novel discrimination training task, setting the stage for future research with clinical populations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Further Exploration of Human Neonatal Chromatic-Achromatic Discrimination.

Science.gov (United States)

Adams, Russell J.

1995-01-01

Newborns were habituated to white squares of varying size and luminance and retested with colored squares for recovery of habituation. Newborns could discriminate yellow-green from white in large squares, but not in small squares. They could not discriminate blue, blue-green, or purple from white. Results suggest newborns have little…

Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning

Directory of Open Access Journals (Sweden)

Yuan Xu

2015-01-01

Full Text Available Very high resolution (VHR image change detection is challenging due to the low discriminative ability of change feature and the difficulty of change decision in utilizing the multilevel contextual information. Most change feature extraction techniques put emphasis on the change degree description (i.e., in what degree the changes have happened, while they ignore the change pattern description (i.e., how the changes changed, which is of equal importance in characterizing the change signatures. Moreover, the simultaneous consideration of the classification robust to the registration noise and the multiscale region-consistent fusion is often neglected in change decision. To overcome such drawbacks, in this paper, a novel VHR image change detection method is proposed based on sparse change descriptor and robust discriminative dictionary learning. Sparse change descriptor combines the change degree component and the change pattern component, which are encoded by the sparse representation error and the morphological profile feature, respectively. Robust change decision is conducted by multiscale region-consistent fusion, which is implemented by the superpixel-level cosparse representation with robust discriminative dictionary and the conditional random field model. Experimental results confirm the effectiveness of the proposed change detection technique.

Comparison of learning ability and memory retention in altricial (Bengalese finch, Lonchura striata var. domestica) and precocial (blue-breasted quail, Coturnix chinensis) birds using a color discrimination task.

Science.gov (United States)

Ueno, Aki; Suzuki, Kaoru

2014-02-01

The present study sought to assess the potential application of avian models with different developmental modes to studies on cognition and neuroscience. Six altricial Bengalese finches (Lonchura striata var. domestica), and eight precocial blue-breasted quails (Coturnix chinensis) were presented with color discrimination tasks to compare their respective faculties for learning and memory retention within the context of the two developmental modes. Tasks consisted of presenting birds with discriminative cues in the form of colored feeder lids, and birds were considered to have learned a task when 80% of their attempts at selecting the correctly colored lid in two consecutive blocks of 10 trials were successful. All of the finches successfully performed the required experimental tasks, whereas only half of the quails were able to execute the same tasks. In the learning test, finches required significantly fewer trials than quails to learn the task (finches: 13.5 ± 9.14 trials, quails: 45.8 ± 4.35 trials, P memory retention tests, which were conducted 45 days after the learning test, finches retained the ability to discriminate between colors correctly (95.0 ± 4.47%), whereas quails did not retain any memory of the experimental procedure and so could not be tested. These results suggested that altricial and precocial birds both possess the faculty for learning and retaining discrimination-type tasks, but that altricial birds perform better than precocial birds in both faculties. The present findings imply that developmental mode is an important consideration for assessing the suitability of bird species for particular experiments. © 2013 Japanese Society of Animal Science.

Improved neutron-gamma discrimination for a 3He neutron detector using subspace learning methods

Science.gov (United States)

Wang, C. L.; Funk, L. L.; Riedel, R. A.; Berry, K. D.

2017-05-01

3He gas based neutron Linear-Position-Sensitive Detectors (LPSDs) have been used for many neutron scattering instruments. Traditional Pulse-height Analysis (PHA) for Neutron-Gamma Discrimination (NGD) resulted in the neutron-gamma efficiency ratio (NGD ratio) on the order of 105-106. The NGD ratios of 3He detectors need to be improved for even better scientific results from neutron scattering. Digital Signal Processing (DSP) analyses of waveforms were proposed for obtaining better NGD ratios, based on features extracted from rise-time, pulse amplitude, charge integration, a simplified Wiener filter, and the cross-correlation between individual and template waveforms of neutron and gamma events. Fisher Linear Discriminant Analysis (FLDA) and three Multivariate Analyses (MVAs) of the features were performed. The NGD ratios are improved by about 102-103 times compared with the traditional PHA method. Our results indicate the NGD capabilities of 3He tube detectors can be significantly improved with subspace-learning based methods, which may result in a reduced data-collection time and better data quality for further data reduction.

Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans.

Science.gov (United States)

Oddo, Calogero Maria; Raspopovic, Stanisa; Artoni, Fiorenzo; Mazzoni, Alberto; Spigler, Giacomo; Petrini, Francesco; Giambattistelli, Federica; Vecchio, Fabrizio; Miraglia, Francesca; Zollo, Loredana; Di Pino, Giovanni; Camboni, Domenico; Carrozza, Maria Chiara; Guglielmelli, Eugenio; Rossini, Paolo Maria; Faraguna, Ugo; Micera, Silvestro

2016-03-08

Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we show that texture discrimination can be artificially provided in human subjects by implementing a neuromorphic real-time mechano-neuro-transduction (MNT), which emulates to some extent the firing dynamics of SA1 cutaneous afferents. The MNT process was used to modulate the temporal pattern of electrical spikes delivered to the human median nerve via percutaneous microstimulation in four intact subjects and via implanted intrafascicular stimulation in one transradial amputee. Both approaches allowed the subjects to reliably discriminate spatial coarseness of surfaces as confirmed also by a hybrid neural model of the median nerve. Moreover, MNT-evoked EEG activity showed physiologically plausible responses that were superimposable in time and topography to the ones elicited by a natural mechanical tactile stimulation. These findings can open up novel opportunities for sensory restoration in the next generation of neuro-prosthetic hands.

Application of Discriminant Analysis on Romanian Insurance Market

OpenAIRE

Constantin Anghelache; Dan Armeanu

2008-01-01

Discriminant analysis is a supervised learning technique that can be used in order to determine which variables are the best predictors of the classification of objects belonging to a population into predetermined classes. At the same time, discriminant analysis provides a powerful tool that enables researchers to make predictions regarding the classification of new objects into predefined classes. The main goal of discriminant analysis is to determine which of the N descrip...

Decision theory for discrimination-aware classification

KAUST Repository

Kamiran, Faisal

2012-12-01

Social discrimination (e.g., against females) arising from data mining techniques is a growing concern worldwide. In recent years, several methods have been proposed for making classifiers learned over discriminatory data discriminationaware. However, these methods suffer from two major shortcomings: (1) They require either modifying the discriminatory data or tweaking a specific classification algorithm and (2) They are not flexible w.r.t. discrimination control and multiple sensitive attribute handling. In this paper, we present two solutions for discrimination-aware classification that neither require data modification nor classifier tweaking. Our first and second solutions exploit, respectively, the reject option of probabilistic classifier(s) and the disagreement region of general classifier ensembles to reduce discrimination. We relate both solutions with decision theory for better understanding of the process. Our experiments using real-world datasets demonstrate that our solutions outperform existing state-ofthe-art methods, especially at low discrimination which is a significant advantage. The superior performance coupled with flexible control over discrimination and easy applicability to multiple sensitive attributes makes our solutions an important step forward in practical discrimination-aware classification. © 2012 IEEE.

Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques

OpenAIRE

Guo, Doudou; Juan, Jiaxiang; Chang, Liying; Zhang, Jingjin; Huang, Danfeng

2017-01-01

Plant-based sensing on water stress can provide sensitive and direct reference for precision irrigation system in greenhouse. However, plant information acquisition, interpretation, and systematical application remain insufficient. This study developed a discrimination method for plant root zone water status in greenhouse by integrating phenotyping and machine learning techniques. Pakchoi plants were used and treated by three root zone moisture levels, 40%, 60%, and 80% relative water content...

Discrimination of schizophrenia auditory hallucinators by machine learning of resting-state functional MRI.

Science.gov (United States)

Chyzhyk, Darya; Graña, Manuel; Öngür, Döst; Shinn, Ann K

2015-05-01

Auditory hallucinations (AH) are a symptom that is most often associated with schizophrenia, but patients with other neuropsychiatric conditions, and even a small percentage of healthy individuals, may also experience AH. Elucidating the neural mechanisms underlying AH in schizophrenia may offer insight into the pathophysiology associated with AH more broadly across multiple neuropsychiatric disease conditions. In this paper, we address the problem of classifying schizophrenia patients with and without a history of AH, and healthy control (HC) subjects. To this end, we performed feature extraction from resting state functional magnetic resonance imaging (rsfMRI) data and applied machine learning classifiers, testing two kinds of neuroimaging features: (a) functional connectivity (FC) measures computed by lattice auto-associative memories (LAAM), and (b) local activity (LA) measures, including regional homogeneity (ReHo) and fractional amplitude of low frequency fluctuations (fALFF). We show that it is possible to perform classification within each pair of subject groups with high accuracy. Discrimination between patients with and without lifetime AH was highest, while discrimination between schizophrenia patients and HC participants was worst, suggesting that classification according to the symptom dimension of AH may be more valid than discrimination on the basis of traditional diagnostic categories. FC measures seeded in right Heschl's gyrus (RHG) consistently showed stronger discriminative power than those seeded in left Heschl's gyrus (LHG), a finding that appears to support AH models focusing on right hemisphere abnormalities. The cortical brain localizations derived from the features with strong classification performance are consistent with proposed AH models, and include left inferior frontal gyrus (IFG), parahippocampal gyri, the cingulate cortex, as well as several temporal and prefrontal cortical brain regions. Overall, the observed findings suggest that

Haptic Human-Human Interaction Through a Compliant Connection Does Not Improve Motor Learning in a Force Field

NARCIS (Netherlands)

Beckers, Niek; Keemink, Arvid; van Asseldonk, Edwin; van der Kooij, Herman; Prattichizzo, Domenico; Shinoda, Hiroyuki; Tan, Hong Z.; Ruffaldi, Emanuele; Frisoli, Antonio

2018-01-01

Humans have a natural ability to haptically interact with other humans, for instance during physically assisting a child to learn how to ride a bicycle. A recent study has shown that haptic human-human interaction can improve individual motor performance and motor learning rate while learning to

Performance of four different rat strains in the autoshaping, two-object discrimination, and swim maze tests of learning and memory.

Science.gov (United States)

Andrews, J S; Jansen, J H; Linders, S; Princen, A; Broekkamp, C L

1995-04-01

The performance of four strains of rats commonly used in behavioural research was assessed in three different tests of learning and memory. The four strains included three outbred lines (Long-Evans, Sprague-Dawley, Wistar) and one inbred strain (S3). Learning and memory were tested using three different paradigms: autoshaping of a lever press, a two-object discrimination test, and performance in a two-island swim maze task. The pigmented strains showed better performance in the autoshaping procedure: the majority of the Long-Evans and the S3 rats acquired the response, and the majority of the Wistar and Sprague-Dawley failed to acquire the response in the set time. The albino strains were slightly better in the swim maze than the pigmented strains. There appeared to be a speed/accuracy trade-off in the strategy used to solve the task. This was also evident following treatment with the cholinergic-depleting agent hemicholinium-3. The performance of the Long-Evans rats was most affected by the treatment in terms of accuracy and the Wistar and Sprague-Dawleys in terms of speed. In the two-object discrimination test only the Long-Evans showed satisfactory performance and were able to discriminate a novel from a known object a short interval after initial exposure. These results show large task- and strain-dependent differences in performance in tests of learning and memory. Some of the performance variation may be due to emotional differences between the strains and may be alleviated by extra training. However, the response to pharmacological manipulation may require more careful evaluation.(ABSTRACT TRUNCATED AT 250 WORDS)

SAR Target Recognition via Supervised Discriminative Dictionary Learning and Sparse Representation of the SAR-HOG Feature

Directory of Open Access Journals (Sweden)

Shengli Song

2016-08-01

Full Text Available Automatic target recognition (ATR in synthetic aperture radar (SAR images plays an important role in both national defense and civil applications. Although many methods have been proposed, SAR ATR is still very challenging due to the complex application environment. Feature extraction and classification are key points in SAR ATR. In this paper, we first design a novel feature, which is a histogram of oriented gradients (HOG-like feature for SAR ATR (called SAR-HOG. Then, we propose a supervised discriminative dictionary learning (SDDL method to learn a discriminative dictionary for SAR ATR and propose a strategy to simplify the optimization problem. Finally, we propose a SAR ATR classifier based on SDDL and sparse representation (called SDDLSR, in which both the reconstruction error and the classification error are considered. Extensive experiments are performed on the MSTAR database under standard operating conditions and extended operating conditions. The experimental results show that SAR-HOG can reliably capture the structures of targets in SAR images, and SDDL can further capture subtle differences among the different classes. By virtue of the SAR-HOG feature and SDDLSR, the proposed method achieves the state-of-the-art performance on MSTAR database. Especially for the extended operating conditions (EOC scenario “Training 17 ∘ —Testing 45 ∘ ”, the proposed method improves remarkably with respect to the previous works.

Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

Science.gov (United States)

Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

2015-09-01

With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques.

Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques.

Science.gov (United States)

Guo, Doudou; Juan, Jiaxiang; Chang, Liying; Zhang, Jingjin; Huang, Danfeng

2017-08-15

Plant-based sensing on water stress can provide sensitive and direct reference for precision irrigation system in greenhouse. However, plant information acquisition, interpretation, and systematical application remain insufficient. This study developed a discrimination method for plant root zone water status in greenhouse by integrating phenotyping and machine learning techniques. Pakchoi plants were used and treated by three root zone moisture levels, 40%, 60%, and 80% relative water content. Three classification models, Random Forest (RF), Neural Network (NN), and Support Vector Machine (SVM) were developed and validated in different scenarios with overall accuracy over 90% for all. SVM model had the highest value, but it required the longest training time. All models had accuracy over 85% in all scenarios, and more stable performance was observed in RF model. Simplified SVM model developed by the top five most contributing traits had the largest accuracy reduction as 29.5%, while simplified RF and NN model still maintained approximately 80%. For real case application, factors such as operation cost, precision requirement, and system reaction time should be synthetically considered in model selection. Our work shows it is promising to discriminate plant root zone water status by implementing phenotyping and machine learning techniques for precision irrigation management.

Toward Accountable Discrimination-Aware Data Mining: The Importance of Keeping the Human in the Loop-and Under the Looking Glass.

Science.gov (United States)

Berendt, Bettina; Preibusch, Sören

2017-06-01

"Big Data" and data-mined inferences are affecting more and more of our lives, and concerns about their possible discriminatory effects are growing. Methods for discrimination-aware data mining and fairness-aware data mining aim at keeping decision processes supported by information technology free from unjust grounds. However, these formal approaches alone are not sufficient to solve the problem. In the present article, we describe reasons why discrimination with data can and typically does arise through the combined effects of human and machine-based reasoning, and argue that this requires a deeper understanding of the human side of decision-making with data mining. We describe results from a large-scale human-subjects experiment that investigated such decision-making, analyzing the reasoning that participants reported during their task to assess whether a loan request should or would be granted. We derive data protection by design strategies for making decision-making discrimination-aware in an accountable way, grounding these requirements in the accountability principle of the European Union General Data Protection Regulation, and outline how their implementations can integrate algorithmic, behavioral, and user interface factors.

Statistical and Machine-Learning Classifier Framework to Improve Pulse Shape Discrimination System Design

Energy Technology Data Exchange (ETDEWEB)

Wurtz, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kaplan, A. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-10-28

Pulse shape discrimination (PSD) is a variety of statistical classifier. Fully-­realized statistical classifiers rely on a comprehensive set of tools for designing, building, and implementing. PSD advances rely on improvements to the implemented algorithm. PSD advances can be improved by using conventional statistical classifier or machine learning methods. This paper provides the reader with a glossary of classifier-­building elements and their functions in a fully-­designed and operational classifier framework that can be used to discover opportunities for improving PSD classifier projects. This paper recommends reporting the PSD classifier’s receiver operating characteristic (ROC) curve and its behavior at a gamma rejection rate (GRR) relevant for realistic applications.

Subcortical plasticity following perceptual learning in a pitch discrimination task

OpenAIRE

Carcagno, Samuele; Plack, Christopher J.

2011-01-01

Practice can lead to dramatic improvements in the discrimination of auditory stimuli. In this study, we investigated changes of the frequency-following response (FFR), a subcortical component of the auditory evoked potentials, after a period of pitch discrimination training. Twenty-seven adult listeners were trained for 10 h on a pitch discrimination task using one of three different complex tone stimuli. One had a static pitch contour, one had a rising pitch contour, and one had a falling pi...

Improved Discriminability of Spatiotemporal Neural Patterns in Rat Motor Cortical Areas as Directional Choice Learning Progresses

Directory of Open Access Journals (Sweden)

Hongwei eMao

2015-03-01

Full Text Available Animals learn to choose a proper action among alternatives to improve their odds of success in food foraging and other activities critical for survival. Through trial-and-error, they learn correct associations between their choices and external stimuli. While a neural network that underlies such learning process has been identified at a high level, it is still unclear how individual neurons and a neural ensemble adapt as learning progresses. In this study, we monitored the activity of single units in the rat medial and lateral agranular (AGm and AGl, respectively areas as rats learned to make a left or right side lever press in response to a left or right side light cue. We noticed that rat movement parameters during the performance of the directional choice task quickly became stereotyped during the first 2-3 days or sessions. But learning the directional choice problem took weeks to occur. Accompanying rats’ behavioral performance adaptation, we observed neural modulation by directional choice in recorded single units. Our analysis shows that ensemble mean firing rates in the cue-on period did not change significantly as learning progressed, and the ensemble mean rate difference between left and right side choices did not show a clear trend of change either. However, the spatiotemporal firing patterns of the neural ensemble exhibited improved discriminability between the two directional choices through learning. These results suggest a spatiotemporal neural coding scheme in a motor cortical neural ensemble that may be responsible for and contributing to learning the directional choice task.

Different levels of food restriction reveal genotype-specific differences in learning a visual discrimination task.

Directory of Open Access Journals (Sweden)

Kalina Makowiecki

Full Text Available In behavioural experiments, motivation to learn can be achieved using food rewards as positive reinforcement in food-restricted animals. Previous studies reduce animal weights to 80-90% of free-feeding body weight as the criterion for food restriction. However, effects of different degrees of food restriction on task performance have not been assessed. We compared learning task performance in mice food-restricted to 80 or 90% body weight (BW. We used adult wildtype (WT; C57Bl/6j and knockout (ephrin-A2⁻/⁻ mice, previously shown to have a reverse learning deficit. Mice were trained in a two-choice visual discrimination task with food reward as positive reinforcement. When mice reached criterion for one visual stimulus (80% correct in three consecutive 10 trial sets they began the reverse learning phase, where the rewarded stimulus was switched to the previously incorrect stimulus. For the initial learning and reverse phase of the task, mice at 90%BW took almost twice as many trials to reach criterion as mice at 80%BW. Furthermore, WT 80 and 90%BW groups significantly differed in percentage correct responses and learning strategy in the reverse learning phase, whereas no differences between weight restriction groups were observed in ephrin-A2⁻/⁻ mice. Most importantly, genotype-specific differences in reverse learning strategy were only detected in the 80%BW groups. Our results indicate that increased food restriction not only results in better performance and a shorter training period, but may also be necessary for revealing behavioural differences between experimental groups. This has important ethical and animal welfare implications when deciding extent of diet restriction in behavioural studies.

Decision theory for discrimination-aware classification

KAUST Repository

Kamiran, Faisal; Karim, Asim A.; Zhang, Xiangliang

2012-01-01

Social discrimination (e.g., against females) arising from data mining techniques is a growing concern worldwide. In recent years, several methods have been proposed for making classifiers learned over discriminatory data discriminationaware

Exploring the spatio-temporal neural basis of face learning

Science.gov (United States)

Yang, Ying; Xu, Yang; Jew, Carol A.; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

2017-01-01

Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150–250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150–250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces. PMID:28570739

Large number discrimination by mosquitofish.

Directory of Open Access Journals (Sweden)

Christian Agrillo

Full Text Available BACKGROUND: Recent studies have demonstrated that fish display rudimentary numerical abilities similar to those observed in mammals and birds. The mechanisms underlying the discrimination of small quantities (<4 were recently investigated while, to date, no study has examined the discrimination of large numerosities in fish. METHODOLOGY/PRINCIPAL FINDINGS: Subjects were trained to discriminate between two sets of small geometric figures using social reinforcement. In the first experiment mosquitofish were required to discriminate 4 from 8 objects with or without experimental control of the continuous variables that co-vary with number (area, space, density, total luminance. Results showed that fish can use the sole numerical information to compare quantities but that they preferentially use cumulative surface area as a proxy of the number when this information is available. A second experiment investigated the influence of the total number of elements to discriminate large quantities. Fish proved to be able to discriminate up to 100 vs. 200 objects, without showing any significant decrease in accuracy compared with the 4 vs. 8 discrimination. The third experiment investigated the influence of the ratio between the numerosities. Performance was found to decrease when decreasing the numerical distance. Fish were able to discriminate numbers when ratios were 1:2 or 2:3 but not when the ratio was 3:4. The performance of a sample of undergraduate students, tested non-verbally using the same sets of stimuli, largely overlapped that of fish. CONCLUSIONS/SIGNIFICANCE: Fish are able to use pure numerical information when discriminating between quantities larger than 4 units. As observed in human and non-human primates, the numerical system of fish appears to have virtually no upper limit while the numerical ratio has a clear effect on performance. These similarities further reinforce the view of a common origin of non-verbal numerical systems in all

Human Spaceflight Conjunction Assessment: Lessons Learned

Science.gov (United States)

Smith, Jason T.

2011-01-01

This viewgraph presentation reviews the process of a human space flight conjunction assessment and lessons learned from the more than twelve years of International Space Station (ISS) operations. Also, the application of these lessons learned to a recent ISS conjunction assessment with object 84180 on July 16, 2009 is also presented.

ROBOT LEARNING OF OBJECT MANIPULATION TASK ACTIONS FROM HUMAN DEMONSTRATIONS

Directory of Open Access Journals (Sweden)

Maria Kyrarini

2017-08-01

Full Text Available Robot learning from demonstration is a method which enables robots to learn in a similar way as humans. In this paper, a framework that enables robots to learn from multiple human demonstrations via kinesthetic teaching is presented. The subject of learning is a high-level sequence of actions, as well as the low-level trajectories necessary to be followed by the robot to perform the object manipulation task. The multiple human demonstrations are recorded and only the most similar demonstrations are selected for robot learning. The high-level learning module identifies the sequence of actions of the demonstrated task. Using Dynamic Time Warping (DTW and Gaussian Mixture Model (GMM, the model of demonstrated trajectories is learned. The learned trajectory is generated by Gaussian mixture regression (GMR from the learned Gaussian mixture model.  In online working phase, the sequence of actions is identified and experimental results show that the robot performs the learned task successfully.

Horse breed discrimination using machine learning methods

Czech Academy of Sciences Publication Activity Database

Burócziová, Monika; Riha, J.

2009-01-01

Roč. 50, č. 4 (2009), s. 375-377 ISSN 1234-1983 Institutional research plan: CEZ:AV0Z50450515 Keywords : Breed discrimination * Genetics diversity * Horse breeds Subject RIV: EG - Zoology Impact factor: 1.324, year: 2009

Bioelectronic tongue using heterodimeric human taste receptor for the discrimination of sweeteners with human-like performance.

Science.gov (United States)

Song, Hyun Seok; Jin, Hye Jun; Ahn, Sae Ryun; Kim, Daesan; Lee, Sang Hun; Kim, Un-Kyung; Simons, Christopher T; Hong, Seunghun; Park, Tai Hyun

2014-10-28

The sense of taste helps humans to obtain information and form a picture of the world by recognizing chemicals in their environments. Over the past decade, large advances have been made in understanding the mechanisms of taste detection and mimicking its capability using artificial sensor devices. However, the detection capability of previous artificial taste sensors has been far inferior to that of animal tongues, in terms of its sensitivity and selectivity. Herein, we developed a bioelectronic tongue using heterodimeric human sweet taste receptors for the detection and discrimination of sweeteners with human-like performance, where single-walled carbon nanotube field-effect transistors were functionalized with nanovesicles containing human sweet taste receptors and used to detect the binding of sweeteners to the taste receptors. The receptors are heterodimeric G-protein-coupled receptors (GPCRs) composed of human taste receptor type 1 member 2 (hTAS1R2) and human taste receptor type 1 member 3 (hTAS1R3), which have multiple binding sites and allow a human tongue-like broad selectivity for the detection of sweeteners. This nanovesicle-based bioelectronic tongue can be a powerful tool for the detection of sweeteners as an alternative to labor-intensive and time-consuming cell-based assays and the sensory evaluation panels used in the food and beverage industry. Furthermore, this study also allows the artificial sensor to exam the functional activity of dimeric GPCRs.

Autonomous development and learning in artificial intelligence and robotics: Scaling up deep learning to human-like learning.

Science.gov (United States)

Oudeyer, Pierre-Yves

2017-01-01

Autonomous lifelong development and learning are fundamental capabilities of humans, differentiating them from current deep learning systems. However, other branches of artificial intelligence have designed crucial ingredients towards autonomous learning: curiosity and intrinsic motivation, social learning and natural interaction with peers, and embodiment. These mechanisms guide exploration and autonomous choice of goals, and integrating them with deep learning opens stimulating perspectives.

Limited taste discrimination in Drosophila.

Science.gov (United States)

Masek, Pavel; Scott, Kristin

2010-08-17

In the gustatory systems of mammals and flies, different populations of sensory cells recognize different taste modalities, such that there are cells that respond selectively to sugars and others to bitter compounds. This organization readily allows animals to distinguish compounds of different modalities but may limit the ability to distinguish compounds within one taste modality. Here, we developed a behavioral paradigm in Drosophila melanogaster to evaluate directly the tastes that a fly distinguishes. These studies reveal that flies do not discriminate among different sugars, or among different bitter compounds, based on chemical identity. Instead, flies show a limited ability to distinguish compounds within a modality based on intensity or palatability. Taste associative learning, similar to olfactory learning, requires the mushroom bodies, suggesting fundamental similarities in brain mechanisms underlying behavioral plasticity. Overall, these studies provide insight into the discriminative capacity of the Drosophila gustatory system and the modulation of taste behavior.

Discriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles.

Science.gov (United States)

Meyer, Arne F; Diepenbrock, Jan-Philipp; Happel, Max F K; Ohl, Frank W; Anemüller, Jörn

2014-01-01

Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF) estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa) is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF) estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA) do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to natural stimuli and

Discriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles.

Directory of Open Access Journals (Sweden)

Arne F Meyer

Full Text Available Analysis of sensory neurons' processing characteristics requires simultaneous measurement of presented stimuli and concurrent spike responses. The functional transformation from high-dimensional stimulus space to the binary space of spike and non-spike responses is commonly described with linear-nonlinear models, whose linear filter component describes the neuron's receptive field. From a machine learning perspective, this corresponds to the binary classification problem of discriminating spike-eliciting from non-spike-eliciting stimulus examples. The classification-based receptive field (CbRF estimation method proposed here adapts a linear large-margin classifier to optimally predict experimental stimulus-response data and subsequently interprets learned classifier weights as the neuron's receptive field filter. Computational learning theory provides a theoretical framework for learning from data and guarantees optimality in the sense that the risk of erroneously assigning a spike-eliciting stimulus example to the non-spike class (and vice versa is minimized. Efficacy of the CbRF method is validated with simulations and for auditory spectro-temporal receptive field (STRF estimation from experimental recordings in the auditory midbrain of Mongolian gerbils. Acoustic stimulation is performed with frequency-modulated tone complexes that mimic properties of natural stimuli, specifically non-Gaussian amplitude distribution and higher-order correlations. Results demonstrate that the proposed approach successfully identifies correct underlying STRFs, even in cases where second-order methods based on the spike-triggered average (STA do not. Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. Thus, CbRF estimation may prove useful for investigation of neuronal processes in response to

Action Recognition Using Discriminative Structured Trajectory Groups

KAUST Repository

Atmosukarto, Indriyati

2015-01-06

In this paper, we develop a novel framework for action recognition in videos. The framework is based on automatically learning the discriminative trajectory groups that are relevant to an action. Different from previous approaches, our method does not require complex computation for graph matching or complex latent models to localize the parts. We model a video as a structured bag of trajectory groups with latent class variables. We model action recognition problem in a weakly supervised setting and learn discriminative trajectory groups by employing multiple instance learning (MIL) based Support Vector Machine (SVM) using pre-computed kernels. The kernels depend on the spatio-temporal relationship between the extracted trajectory groups and their associated features. We demonstrate both quantitatively and qualitatively that the classification performance of our proposed method is superior to baselines and several state-of-the-art approaches on three challenging standard benchmark datasets.

Dissociable Learning Processes Underlie Human Pain Conditioning.

Science.gov (United States)

Zhang, Suyi; Mano, Hiroaki; Ganesh, Gowrishankar; Robbins, Trevor; Seymour, Ben

2016-01-11

Pavlovian conditioning underlies many aspects of pain behavior, including fear and threat detection [1], escape and avoidance learning [2], and endogenous analgesia [3]. Although a central role for the amygdala is well established [4], both human and animal studies implicate other brain regions in learning, notably ventral striatum and cerebellum [5]. It remains unclear whether these regions make different contributions to a single aversive learning process or represent independent learning mechanisms that interact to generate the expression of pain-related behavior. We designed a human parallel aversive conditioning paradigm in which different Pavlovian visual cues probabilistically predicted thermal pain primarily to either the left or right arm and studied the acquisition of conditioned Pavlovian responses using combined physiological recordings and fMRI. Using computational modeling based on reinforcement learning theory, we found that conditioning involves two distinct types of learning process. First, a non-specific "preparatory" system learns aversive facial expressions and autonomic responses such as skin conductance. The associated learning signals-the learned associability and prediction error-were correlated with fMRI brain responses in amygdala-striatal regions, corresponding to the classic aversive (fear) learning circuit. Second, a specific lateralized system learns "consummatory" limb-withdrawal responses, detectable with electromyography of the arm to which pain is predicted. Its related learned associability was correlated with responses in ipsilateral cerebellar cortex, suggesting a novel computational role for the cerebellum in pain. In conclusion, our results show that the overall phenotype of conditioned pain behavior depends on two dissociable reinforcement learning circuits. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Sleep Deprivation Impairs the Human Central and Peripheral Nervous System Discrimination of Social Threat.

Science.gov (United States)

Goldstein-Piekarski, Andrea N; Greer, Stephanie M; Saletin, Jared M; Walker, Matthew P

2015-07-15

Facial expressions represent one of the most salient cues in our environment. They communicate the affective state and intent of an individual and, if interpreted correctly, adaptively influence the behavior of others in return. Processing of such affective stimuli is known to require reciprocal signaling between central viscerosensory brain regions and peripheral-autonomic body systems, culminating in accurate emotion discrimination. Despite emerging links between sleep and affective regulation, the impact of sleep loss on the discrimination of complex social emotions within and between the CNS and PNS remains unknown. Here, we demonstrate in humans that sleep deprivation impairs both viscerosensory brain (anterior insula, anterior cingulate cortex, amygdala) and autonomic-cardiac discrimination of threatening from affiliative facial cues. Moreover, sleep deprivation significantly degrades the normally reciprocal associations between these central and peripheral emotion-signaling systems, most prominent at the level of cardiac-amygdala coupling. In addition, REM sleep physiology across the sleep-rested night significantly predicts the next-day success of emotional discrimination within this viscerosensory network across individuals, suggesting a role for REM sleep in affective brain recalibration. Together, these findings establish that sleep deprivation compromises the faithful signaling of, and the "embodied" reciprocity between, viscerosensory brain and peripheral autonomic body processing of complex social signals. Such impairments hold ecological relevance in professional contexts in which the need for accurate interpretation of social cues is paramount yet insufficient sleep is pervasive. Copyright © 2015 the authors 0270-6474/15/3510135-11$15.00/0.

A behavioural preparation for the study of human Pavlovian conditioning.

Science.gov (United States)

Arcediano, F; Ortega, N; Matute, H

1996-08-01

Conditioned suppression is a useful technique for assessing whether subjects have learned a CS-US association, but it is difficult to use in humans because of the need for an aversive US. The purpose of this research was to develop a non-aversive procedure that would produce suppression. Subjects learned to press the space bar of a computer as part of a video game, but they had to stop pressing whenever a visual US appeared, or they would lose points. In Experiment 1, we used an A+/B- discrimination design: The US always followed Stimulus A and never followed Stimulus B. Although no information about the existence of CSs was given to the subjects, suppression ratio results showed a discrimination learning curve-that is, subjects learned to suppress responding in anticipation of the US when Stimulus A was present but not during the presentations of Stimulus B. Experiment 2 explored the potential of this preparation by using two different instruction sets and assessing post-experimental judgements of CS A and CS B in addition to suppression ratios. The results of these experiments suggest that conditioned suppression can be reliably and conveniently used in the human laboratory, providing a bridge between experiments on animal conditioning and experiments on human judgements of causality.

Common Elements Enhance or Retard Negative Patterning Discrimination Learning Depending on Modality of Stimuli

Science.gov (United States)

Redhead, Edward S.; Curtis, Cheryl

2013-01-01

Human contingency learning studies were used to compare the predictions of configural and elemental theories. In two experiments, participants were required to learn which stimuli were associated with an increase in core temperature of a fictitious nuclear plant. Experiments investigated the rate at which a simple negative patterning…

Explosion Monitoring with Machine Learning: A LSTM Approach to Seismic Event Discrimination

Science.gov (United States)

Magana-Zook, S. A.; Ruppert, S. D.

2017-12-01

The streams of seismic data that analysts look at to discriminate natural from man- made events will soon grow from gigabytes of data per day to exponentially larger rates. This is an interesting problem as the requirement for real-time answers to questions of non-proliferation will remain the same, and the analyst pool cannot grow as fast as the data volume and velocity will. Machine learning is a tool that can solve the problem of seismic explosion monitoring at scale. Using machine learning, and Long Short-term Memory (LSTM) models in particular, analysts can become more efficient by focusing their attention on signals of interest. From a global dataset of earthquake and explosion events, a model was trained to recognize the different classes of events, given their spectrograms. Optimal recurrent node count and training iterations were found, and cross validation was performed to evaluate model performance. A 10-fold mean accuracy of 96.92% was achieved on a balanced dataset of 30,002 instances. Given that the model is 446.52 MB it can be used to simultaneously characterize all incoming signals by researchers looking at events in isolation on desktop machines, as well as at scale on all of the nodes of a real-time streaming platform. LLNL-ABS-735911

Magnetic field discrimination, learning, and memory in the yellow stingray (Urobatis jamaicensis).

Science.gov (United States)

Newton, Kyle C; Kajiura, Stephen M

2017-07-01

Elasmobranch fishes (sharks, skates, and rays) have been hypothesized to use the geomagnetic field as a cue for orienting and navigating across a wide range of spatial scales. Magnetoreception has been demonstrated in many invertebrate and vertebrate taxa, including elasmobranchs, but this sensory modality and the cognitive abilities of cartilaginous fishes are poorly studied. Wild caught yellow stingrays, Urobatis jamaicensis (N = 8), underwent conditioning to associate a magnetic stimulus with a food reward in order to elicit foraging behaviors. Behavioral conditioning consisted of burying magnets and non-magnetic controls at random locations within a test arena and feeding stingrays as they passed over the hidden magnets. The location of the magnets and controls was changed for each trial, and all confounding sensory cues were eliminated. The stingrays learned to discriminate the magnetic stimuli within a mean of 12.6 ± 0.7 SE training sessions of four trials per session. Memory probes were conducted at intervals between 90 and 180 days post-learning criterion, and six of eight stingrays completed the probes with a ≥75% success rate and minimum latency to complete the task. These results show the fastest rate of learning and longest memory window for any batoid (skate or ray) to date. This study demonstrates that yellow stingrays, and possibly other elasmobranchs, can use a magnetic stimulus as a geographic marker for the location of resources and is an important step toward understanding whether these fishes use geomagnetic cues during spatial navigation tasks in the natural environment.

Development and assessment of a lysophospholipid-based deep learning model to discriminate geographical origins of white rice.

Science.gov (United States)

Long, Nguyen Phuoc; Lim, Dong Kyu; Mo, Changyeun; Kim, Giyoung; Kwon, Sung Won

2017-08-17

Geographical origin determination of white rice has become the major issue of food industry. However, there is still lack of a high-throughput method for rapidly and reproducibly differentiating the geographical origins of commercial white rice. In this study, we developed a method that employed lipidomics and deep learning to discriminate white rice from Korea to China. A total of 126 white rice of 30 cultivars from different regions were utilized for the method development and validation. By using direct infusion-mass spectrometry-based targeted lipidomics, 17 lysoglycerophospholipids were simultaneously characterized within minutes per sample. Unsupervised data exploration showed a noticeable overlap of white rice between two countries. In addition, lysophosphatidylcholines (lysoPCs) were prominent in white rice from Korea while lysophosphatidylethanolamines (lysoPEs) were enriched in white rice from China. A deep learning prediction model was built using 2014 white rice and validated using two different batches of 2015 white rice. The model accurately discriminated white rice from two countries. Among 10 selected predictors, lysoPC(18:2), lysoPC(14:0), and lysoPE(16:0) were the three most important features. Random forest and gradient boosting machine models also worked well in this circumstance. In conclusion, this study provides an architecture for high-throughput classification of white rice from different geographical origins.

Human reinforcement learning subdivides structured action spaces by learning effector-specific values.

Science.gov (United States)

Gershman, Samuel J; Pesaran, Bijan; Daw, Nathaniel D

2009-10-28

Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable because of the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning-such as prediction error signals for action valuation associated with dopamine and the striatum-can cope with this "curse of dimensionality." We propose a reinforcement learning framework that allows for learned action valuations to be decomposed into effector-specific components when appropriate to a task, and test it by studying to what extent human behavior and blood oxygen level-dependent (BOLD) activity can exploit such a decomposition in a multieffector choice task. Subjects made simultaneous decisions with their left and right hands and received separate reward feedback for each hand movement. We found that choice behavior was better described by a learning model that decomposed the values of bimanual movements into separate values for each effector, rather than a traditional model that treated the bimanual actions as unitary with a single value. A decomposition of value into effector-specific components was also observed in value-related BOLD signaling, in the form of lateralized biases in striatal correlates of prediction error and anticipatory value correlates in the intraparietal sulcus. These results suggest that the human brain can use decomposed value representations to "divide and conquer" reinforcement learning over high-dimensional action spaces.

Discriminative sparse coding on multi-manifolds

KAUST Repository

Wang, J.J.-Y.; Bensmail, H.; Yao, N.; Gao, Xin

2013-01-01

Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics. However, the conventional sparse coding algorithms and their manifold-regularized variants (graph sparse coding and Laplacian sparse coding), learn codebooks and codes in an unsupervised manner and neglect class information that is available in the training set. To address this problem, we propose a novel discriminative sparse coding method based on multi-manifolds, that learns discriminative class-conditioned codebooks and sparse codes from both data feature spaces and class labels. First, the entire training set is partitioned into multiple manifolds according to the class labels. Then, we formulate the sparse coding as a manifold-manifold matching problem and learn class-conditioned codebooks and codes to maximize the manifold margins of different classes. Lastly, we present a data sample-manifold matching-based strategy to classify the unlabeled data samples. Experimental results on somatic mutations identification and breast tumor classification based on ultrasonic images demonstrate the efficacy of the proposed data representation and classification approach. 2013 The Authors. All rights reserved.

Discriminative sparse coding on multi-manifolds

KAUST Repository

Wang, J.J.-Y.

2013-09-26

Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics. However, the conventional sparse coding algorithms and their manifold-regularized variants (graph sparse coding and Laplacian sparse coding), learn codebooks and codes in an unsupervised manner and neglect class information that is available in the training set. To address this problem, we propose a novel discriminative sparse coding method based on multi-manifolds, that learns discriminative class-conditioned codebooks and sparse codes from both data feature spaces and class labels. First, the entire training set is partitioned into multiple manifolds according to the class labels. Then, we formulate the sparse coding as a manifold-manifold matching problem and learn class-conditioned codebooks and codes to maximize the manifold margins of different classes. Lastly, we present a data sample-manifold matching-based strategy to classify the unlabeled data samples. Experimental results on somatic mutations identification and breast tumor classification based on ultrasonic images demonstrate the efficacy of the proposed data representation and classification approach. 2013 The Authors. All rights reserved.

A machine learning model with human cognitive biases capable of learning from small and biased datasets.

Science.gov (United States)

Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro

2018-05-09

Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.

On Logical Characterisation of Human Concept Learning based on Terminological Systems

DEFF Research Database (Denmark)

Badie, Farshad

2018-01-01

The central focus of this article is the epistemological assumption that knowledge could be generated based on human beings' experiences and over their conceptions of the world. Logical characterisation of human inductive learning over their produced conceptions within terminological systems and ...... and analysis of actual human inductive reasoning (and learning). This research connects with the topics 'logic & learning', 'cognitive modelling' and 'terminological knowledge representation'.......The central focus of this article is the epistemological assumption that knowledge could be generated based on human beings' experiences and over their conceptions of the world. Logical characterisation of human inductive learning over their produced conceptions within terminological systems...

Amplifying human ability through autonomics and machine learning in IMPACT

Science.gov (United States)

Dzieciuch, Iryna; Reeder, John; Gutzwiller, Robert; Gustafson, Eric; Coronado, Braulio; Martinez, Luis; Croft, Bryan; Lange, Douglas S.

2017-05-01

Amplifying human ability for controlling complex environments featuring autonomous units can be aided by learned models of human and system performance. In developing a command and control system that allows a small number of people to control a large number of autonomous teams, we employ an autonomics framework to manage the networks that represent mission plans and the networks that are composed of human controllers and their autonomous assistants. Machine learning allows us to build models of human and system performance useful for monitoring plans and managing human attention and task loads. Machine learning also aids in the development of tactics that human supervisors can successfully monitor through the command and control system.

Comparison of model and human observer performance for detection and discrimination tasks using dual-energy x-ray images

International Nuclear Information System (INIS)

Richard, Samuel; Siewerdsen, Jeffrey H.

2008-01-01

Model observer performance, computed theoretically using cascaded systems analysis (CSA), was compared to the performance of human observers in detection and discrimination tasks. Dual-energy (DE) imaging provided a wide range of acquisition and decomposition parameters for which observer performance could be predicted and measured. This work combined previously derived observer models (e.g., Fisher-Hotelling and non-prewhitening) with CSA modeling of the DE image noise-equivalent quanta (NEQ) and imaging task (e.g., sphere detection, shape discrimination, and texture discrimination) to yield theoretical predictions of detectability index (d ' ) and area under the receiver operating characteristic (A Z ). Theoretical predictions were compared to human observer performance assessed using 9-alternative forced-choice tests to yield measurement of A Z as a function of DE image acquisition parameters (viz., allocation of dose between the low- and high-energy images) and decomposition technique [viz., three DE image decomposition algorithms: standard log subtraction (SLS), simple-smoothing of the high-energy image (SSH), and anti-correlated noise reduction (ACNR)]. Results showed good agreement between theory and measurements over a broad range of imaging conditions. The incorporation of an eye filter and internal noise in the observer models demonstrated improved correspondence with human observer performance. Optimal acquisition and decomposition parameters were shown to depend on the imaging task; for example, ACNR and SSH yielded the greatest performance in the detection of soft-tissue and bony lesions, respectively. This study provides encouraging evidence that Fourier-based modeling of NEQ computed via CSA and imaging task provides a good approximation to human observer performance for simple imaging tasks, helping to bridge the gap between Fourier metrics of detector performance (e.g., NEQ) and human observer performance.

Microarray multiplex assay for the simultaneous detection and discrimination of hepatitis B, hepatitis C, and human immunodeficiency type-1 viruses in human blood samples

International Nuclear Information System (INIS)

Hsia, Chu Chieh; Chizhikov, Vladimir E.; Yang, Amy X.; Selvapandiyan, Angamuthu; Hewlett, Indira; Duncan, Robert; Puri, Raj K.; Nakhasi, Hira L.; Kaplan, Gerardo G.

2007-01-01

Hepatitis B virus (HBV), hepatitis C virus (HCV), and human immunodeficiency virus type-1 (HIV-1) are transfusion-transmitted human pathogens that have a major impact on blood safety and public health worldwide. We developed a microarray multiplex assay for the simultaneous detection and discrimination of these three viruses. The microarray consists of 16 oligonucleotide probes, immobilized on a silylated glass slide. Amplicons from multiplex PCR were labeled with Cy-5 and hybridized to the microarray. The assay detected 1 International Unit (IU), 10 IU, 20 IU of HBV, HCV, and HIV-1, respectively, in a single multiplex reaction. The assay also detected and discriminated the presence of two or three of these viruses in a single sample. Our data represent a proof-of-concept for the possible use of highly sensitive multiplex microarray assay to screen and confirm the presence of these viruses in blood donors and patients

Visual discrimination transfer and modulation by biogenic amines in honeybees.

Science.gov (United States)

Vieira, Amanda Rodrigues; Salles, Nayara; Borges, Marco; Mota, Theo

2018-05-10

For more than a century, visual learning and memory have been studied in the honeybee Apis mellifera using operant appetitive conditioning. Although honeybees show impressive visual learning capacities in this well-established protocol, operant training of free-flying animals cannot be combined with invasive protocols for studying the neurobiological basis of visual learning. In view of this, different attempts have been made to develop new classical conditioning protocols for studying visual learning in harnessed honeybees, though learning performance remains considerably poorer than that for free-flying animals. Here, we investigated the ability of honeybees to use visual information acquired during classical conditioning in a new operant context. We performed differential visual conditioning of the proboscis extension reflex (PER) followed by visual orientation tests in a Y-maze. Classical conditioning and Y-maze retention tests were performed using the same pair of perceptually isoluminant chromatic stimuli, to avoid the influence of phototaxis during free-flying orientation. Visual discrimination transfer was clearly observed, with pre-trained honeybees significantly orienting their flights towards the former positive conditioned stimulus (CS+), thus showing that visual memories acquired by honeybees are resistant to context changes between conditioning and the retention test. We combined this visual discrimination approach with selective pharmacological injections to evaluate the effect of dopamine and octopamine in appetitive visual learning. Both octopaminergic and dopaminergic antagonists impaired visual discrimination performance, suggesting that both these biogenic amines modulate appetitive visual learning in honeybees. Our study brings new insight into cognitive and neurobiological mechanisms underlying visual learning in honeybees. © 2018. Published by The Company of Biologists Ltd.

Classification of astrocyto-mas and meningiomas using statistical discriminant analysis on MRI data

International Nuclear Information System (INIS)

Siromoney, Anna; Prasad, G.N.S.; Raghuram, Lakshminarayan; Korah, Ipeson; Siromoney, Arul; Chandrasekaran, R.

2001-01-01

The objective of this study was to investigate the usefulness of Multivariate Discriminant Analysis for classifying two groups of primary brain tumours, astrocytomas and meningiomas, from Magnetic Resonance Images. Discriminant analysis is a multivariate technique concerned with separating distinct sets of objects and with allocating new objects to previously defined groups. Allocation or classification rules are usually developed from learning examples in a supervised learning environment. Data from signal intensity measurements in the multiple scan performed on each patient in routine clinical scanning was analysed using Fisher's Classification, which is one method of discriminant analysis

Associative learning and the control of human dietary behavior.

Science.gov (United States)

Brunstrom, Jeffrey M

2007-07-01

Most of our food likes and disliked are learned. Relevant forms of associative learning have been identified in animals. However, observations of the same associative processes are relatively scarce in humans. The first section of this paper outlines reasons why this might be the case. Emphasis is placed on recent research exploring individual differences and the importance or otherwise of hunger and contingency awareness. The second section briefly considers the effect of learning on meal size, and the author revisits the question of how learned associations might come to influence energy intake in humans.

Chromatic illumination discrimination ability reveals that human colour constancy is optimised for blue daylight illuminations.

Directory of Open Access Journals (Sweden)

Bradley Pearce

Full Text Available The phenomenon of colour constancy in human visual perception keeps surface colours constant, despite changes in their reflected light due to changing illumination. Although colour constancy has evolved under a constrained subset of illuminations, it is unknown whether its underlying mechanisms, thought to involve multiple components from retina to cortex, are optimised for particular environmental variations. Here we demonstrate a new method for investigating colour constancy using illumination matching in real scenes which, unlike previous methods using surface matching and simulated scenes, allows testing of multiple, real illuminations. We use real scenes consisting of solid familiar or unfamiliar objects against uniform or variegated backgrounds and compare discrimination performance for typical illuminations from the daylight chromaticity locus (approximately blue-yellow and atypical spectra from an orthogonal locus (approximately red-green, at correlated colour temperature 6700 K, all produced in real time by a 10-channel LED illuminator. We find that discrimination of illumination changes is poorer along the daylight locus than the atypical locus, and is poorest particularly for bluer illumination changes, demonstrating conversely that surface colour constancy is best for blue daylight illuminations. Illumination discrimination is also enhanced, and therefore colour constancy diminished, for uniform backgrounds, irrespective of the object type. These results are not explained by statistical properties of the scene signal changes at the retinal level. We conclude that high-level mechanisms of colour constancy are biased for the blue daylight illuminations and variegated backgrounds to which the human visual system has typically been exposed.

Human-Guided Learning for Probabilistic Logic Models

Directory of Open Access Journals (Sweden)

Phillip Odom

2018-06-01

Full Text Available Advice-giving has been long explored in the artificial intelligence community to build robust learning algorithms when the data is noisy, incorrect or even insufficient. While logic based systems were effectively used in building expert systems, the role of the human has been restricted to being a “mere labeler” in recent times. We hypothesize and demonstrate that probabilistic logic can provide an effective and natural way for the expert to specify domain advice. Specifically, we consider different types of advice-giving in relational domains where noise could arise due to systematic errors or class-imbalance inherent in the domains. The advice is provided as logical statements or privileged features that are thenexplicitly considered by an iterative learning algorithm at every update. Our empirical evidence shows that human advice can effectively accelerate learning in noisy, structured domains where so far humans have been merely used as labelers or as designers of the (initial or final structure of the model.

Predictors of return rate discrimination in slot machine play.

Science.gov (United States)

Coates, Ewan; Blaszczynski, Alex

2014-09-01

The purpose of this study was to investigate the extent to which accurate estimates of payback percentages and volatility combined with prior learning, enabled players to successfully discriminate between multi-line/multi-credit slot machines that provided differing rates of reinforcement. The aim was to determine if the capacity to discriminate structural characteristics of gaming machines influenced player choices in selecting 'favourite' slot machines. Slot machine gambling history, gambling beliefs and knowledge, impulsivity, illusions of control, and problem solving style were assessed in a sample of 48 first year undergraduate psychology students. Participants were subsequently exposed to a choice paradigm where they could freely select to play either of two concurrently presented PC-simulated slot machines programmed to randomly differ in expected player return rates (payback percentage) and win frequency (volatility). Results suggest that prior learning and cognitions (particularly gambler's fallacy) but not payback, were major contributors to the ability of a player to discriminate volatility between slot machines. Participants displayed a general tendency to discriminate payback, but counter-intuitively placed more bets on the slot machine with lower payback percentage rates.

Learning and Transforming Reality: Women from Rosario's Neighborhoods Demand Access to Public Health Services Free of Discrimination

Science.gov (United States)

Chiarotti, Susana

2005-01-01

This article focuses on the activities of two women's groups in Argentina -- CLADEM and INSGENAR. CLADEM, which has a much broader presence in Latin America, aims to give a feminist perspective to the construction of real democracies with social justice, free of discrimination and with full exercise of human rights. INSGENAR is a local,…

Learning Semantics of Gestural Instructions for Human-Robot Collaboration

Science.gov (United States)

Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

2018-01-01

Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions. PMID:29615888

Learning Semantics of Gestural Instructions for Human-Robot Collaboration.

Science.gov (United States)

Shukla, Dadhichi; Erkent, Özgür; Piater, Justus

2018-01-01

Designed to work safely alongside humans, collaborative robots need to be capable partners in human-robot teams. Besides having key capabilities like detecting gestures, recognizing objects, grasping them, and handing them over, these robots need to seamlessly adapt their behavior for efficient human-robot collaboration. In this context we present the fast, supervised Proactive Incremental Learning (PIL) framework for learning associations between human hand gestures and the intended robotic manipulation actions. With the proactive aspect, the robot is competent to predict the human's intent and perform an action without waiting for an instruction. The incremental aspect enables the robot to learn associations on the fly while performing a task. It is a probabilistic, statistically-driven approach. As a proof of concept, we focus on a table assembly task where the robot assists its human partner. We investigate how the accuracy of gesture detection affects the number of interactions required to complete the task. We also conducted a human-robot interaction study with non-roboticist users comparing a proactive with a reactive robot that waits for instructions.

Dimensional feature weighting utilizing multiple kernel learning for single-channel talker location discrimination using the acoustic transfer function.

Science.gov (United States)

Takashima, Ryoichi; Takiguchi, Tetsuya; Ariki, Yasuo

2013-02-01

This paper presents a method for discriminating the location of the sound source (talker) using only a single microphone. In a previous work, the single-channel approach for discriminating the location of the sound source was discussed, where the acoustic transfer function from a user's position is estimated by using a hidden Markov model of clean speech in the cepstral domain. In this paper, each cepstral dimension of the acoustic transfer function is newly weighted, in order to obtain the cepstral dimensions having information that is useful for classifying the user's position. Then, this paper proposes a feature-weighting method for the cepstral parameter using multiple kernel learning, defining the base kernels for each cepstral dimension of the acoustic transfer function. The user's position is trained and classified by support vector machine. The effectiveness of this method has been confirmed by sound source (talker) localization experiments performed in different room environments.

Machine learning applications in genetics and genomics.

Science.gov (United States)

Libbrecht, Maxwell W; Noble, William Stafford

2015-06-01

The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets. Here, we provide an overview of machine learning applications for the analysis of genome sequencing data sets, including the annotation of sequence elements and epigenetic, proteomic or metabolomic data. We present considerations and recurrent challenges in the application of supervised, semi-supervised and unsupervised machine learning methods, as well as of generative and discriminative modelling approaches. We provide general guidelines to assist in the selection of these machine learning methods and their practical application for the analysis of genetic and genomic data sets.

Discriminative Elastic-Net Regularized Linear Regression.

Science.gov (United States)

Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

2017-03-01

In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

Lexical exposure to native language dialects can improve non-native phonetic discrimination.

Science.gov (United States)

Olmstead, Annie J; Viswanathan, Navin

2018-04-01

Nonnative phonetic learning is an area of great interest for language researchers, learners, and educators alike. In two studies, we examined whether nonnative phonetic discrimination of Hindi dental and retroflex stops can be improved by exposure to lexical items bearing the critical nonnative stops. We extend the lexical retuning paradigm of Norris, McQueen, and Cutler (Cognitive Psychology, 47, 204-238, 2003) by having naive American English (AE)-speaking participants perform a pretest-training-posttest procedure. They performed an AXB discrimination task with the Hindi retroflex and dental stops before and after transcribing naturally produced words from an Indian English speaker that either contained these tokens or not. Only those participants who heard words with the critical nonnative phones improved in their posttest discrimination. This finding suggests that exposure to nonnative phones in native lexical contexts supports learning of difficult nonnative phonetic discrimination.

Second-order conditioning and conditioned inhibition: influences of speed versus accuracy on human causal learning.

Directory of Open Access Journals (Sweden)

Jessica C Lee

Full Text Available In human causal learning, excitatory and inhibitory learning effects can sometimes be found in the same paradigm by altering the learning conditions. This study aims to explore whether learning in the feature negative paradigm can be dissociated by emphasising speed over accuracy. In two causal learning experiments, participants were given a feature negative discrimination in which the outcome caused by one cue was prevented by the addition of another. Participants completed training trials either in a self-paced fashion with instructions emphasising accuracy, or under strict time constraints with instructions emphasising speed. Using summation tests in which the preventative cue was paired with another causal cue, participants in the accuracy groups correctly rated the preventative cue as if it reduced the probability of the outcome. However, participants in the speed groups rated the preventative cue as if it increased the probability of the outcome. In Experiment 1, both speed and accuracy groups later judged the same cue to be preventative in a reasoned inference task. Experiment 2 failed to find evidence of similar dissociations in retrospective revaluation (release from overshadowing vs. mediated extinction or learning about a redundant cue (blocking vs. augmentation. However in the same experiment, the tendency for the accuracy group to show conditioned inhibition and the speed group to show second-order conditioning was consistent even across sub-sets of the speed and accuracy groups with equivalent accuracy in training, suggesting that second-order conditioning is not merely a consequence of poorer acquisition. This dissociation mirrors the trade-off between second-order conditioning and conditioned inhibition observed in animal conditioning when training is extended.

Gendered-Caste Discrimination, Human Rights Education, and the Enforcement of the Prevention of Atrocities Act in India

Science.gov (United States)

Kapoor, Dip

2007-01-01

Despite the constitutional ban on the practice of untouchability and caste-based discrimination, this article elaborates on a gendered-caste-based discriminatory reality in rural India, the difficulties of enforcing legal remedies, and on related human rights praxis to address gendered-caste atrocities by drawing on the experiences of a Canadian…

Subcortical plasticity following perceptual learning in a pitch discrimination task.

Science.gov (United States)

Carcagno, Samuele; Plack, Christopher J

2011-02-01

Practice can lead to dramatic improvements in the discrimination of auditory stimuli. In this study, we investigated changes of the frequency-following response (FFR), a subcortical component of the auditory evoked potentials, after a period of pitch discrimination training. Twenty-seven adult listeners were trained for 10 h on a pitch discrimination task using one of three different complex tone stimuli. One had a static pitch contour, one had a rising pitch contour, and one had a falling pitch contour. Behavioral measures of pitch discrimination and FFRs for all the stimuli were measured before and after the training phase for these participants, as well as for an untrained control group (n = 12). Trained participants showed significant improvements in pitch discrimination compared to the control group for all three trained stimuli. These improvements were partly specific for stimuli with the same pitch modulation (dynamic vs. static) and with the same pitch trajectory (rising vs. falling) as the trained stimulus. Also, the robustness of FFR neural phase locking to the sound envelope increased significantly more in trained participants compared to the control group for the static and rising contour, but not for the falling contour. Changes in FFR strength were partly specific for stimuli with the same pitch modulation (dynamic vs. static) of the trained stimulus. Changes in FFR strength, however, were not specific for stimuli with the same pitch trajectory (rising vs. falling) as the trained stimulus. These findings indicate that even relatively low-level processes in the mature auditory system are subject to experience-related change.

Preliminary evidence of a neurophysiological basis for individual discrimination in filial imprinting.

Science.gov (United States)

Town, Stephen Michael

2011-12-01

Filial imprinting involves a predisposition for biologically important stimuli and a learning process directing preferences towards a particular stimulus. Learning underlies discrimination between imprinted and unfamiliar individuals and depends upon the IMM (intermediate and medial mesopallium). Here, IMM neurons responded differentially to familiar and unfamiliar conspecifics following socialization and the neurophysiological effects of social experience differed between hemispheres. Such findings may provide a neurophysiological basis for individual discrimination in imprinting. Copyright © 2011 Elsevier B.V. All rights reserved.

Consistent individual differences in human social learning strategies.

Science.gov (United States)

Molleman, Lucas; van den Berg, Pieter; Weissing, Franz J

2014-04-04

Social learning has allowed humans to build up extensive cultural repertoires, enabling them to adapt to a wide variety of environmental and social conditions. However, it is unclear which social learning strategies people use, especially in social contexts where their payoffs depend on the behaviour of others. Here we show experimentally that individuals differ in their social learning strategies and that they tend to employ the same learning strategy irrespective of the interaction context. Payoff-based learners focus on their peers' success, while decision-based learners disregard payoffs and exclusively focus on their peers' past behaviour. These individual differences may be of considerable importance for cultural evolution. By means of a simple model, we demonstrate that groups harbouring individuals with different learning strategies may be faster in adopting technological innovations and can be more efficient through successful role differentiation. Our study highlights the importance of individual variation for human interactions and sheds new light on the dynamics of cultural evolution.

Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model

OpenAIRE

Lu, Jiasen; Kannan, Anitha; Yang, Jianwei; Parikh, Devi; Batra, Dhruv

2017-01-01

We present a novel training framework for neural sequence models, particularly for grounded dialog generation. The standard training paradigm for these models is maximum likelihood estimation (MLE), or minimizing the cross-entropy of the human responses. Across a variety of domains, a recurring problem with MLE trained generative neural dialog models (G) is that they tend to produce 'safe' and generic responses ("I don't know", "I can't tell"). In contrast, discriminative dialog models (D) th...

An unsupervised learning algorithm: application to the discrimination of seismic events and quarry blasts in the vicinity of Istanbul

Directory of Open Access Journals (Sweden)

H. S. Kuyuk

2011-01-01

Full Text Available The results of the application of an unsupervised learning (neural network approach comprising a Self Organizing Map (SOM, to distinguish micro-earthquakes from quarry blasts in the vicinity of Istanbul, Turkey, are presented and discussed. The SOM is constructed as a neural classifier and complementary reliability estimator to distinguish seismic events, and was employed for varying map sizes. Input parameters consisting of frequency and time domain data (complexity, spectral ratio, S/P wave amplitude peak ratio and origin time of events extracted from the vertical components of digital seismograms were estimated as discriminants for 179 (1.8 < M_d < 3.0 local events. The results show that complexity and amplitude peak ratio parameters of the observed velocity seismogram may suffice for a reliable discrimination, while origin time and spectral ratio were found to be fuzzy and misleading classifiers for this problem. The SOM discussed here achieved a discrimination reliability that could be employed routinely in observatory practice; however, about 6% of all events were classified as ambiguous cases. This approach was developed independently for this particular classification, but it could be applied to different earthquake regions.

Learning objects as coadjuvants in the human physiology teaching-learning process

Directory of Open Access Journals (Sweden)

Marcus Vinícius Lara

2014-08-01

Full Text Available The use of Information and Communication Technologies (ICTs in the academic environment of biomedical area has gained much importance, both for their ability to complement the understanding of the subject obtained in the classroom, is the ease of access, or makes more pleasure the learning process, since these tools are present in everyday of the students and use a simple language. Considering that, this study aims to report the experience of building learning objects in human physiology as a tool for learning facilitation, and discuss the impact of this teaching methodology

Individual differences in the learning potential of human beings

Science.gov (United States)

Stern, Elsbeth

2017-01-01

To the best of our knowledge, the genetic foundations that guide human brain development have not changed fundamentally during the past 50,000 years. However, because of their cognitive potential, humans have changed the world tremendously in the past centuries. They have invented technical devices, institutions that regulate cooperation and competition, and symbol systems, such as script and mathematics, that serve as reasoning tools. The exceptional learning ability of humans allows newborns to adapt to the world they are born into; however, there are tremendous individual differences in learning ability among humans that become obvious in school at the latest. Cognitive psychology has developed models of memory and information processing that attempt to explain how humans learn (general perspective), while the variation among individuals (differential perspective) has been the focus of psychometric intelligence research. Although both lines of research have been proceeding independently, they increasingly converge, as both investigate the concepts of working memory and knowledge construction. This review begins with presenting state-of-the-art research on human information processing and its potential in academic learning. Then, a brief overview of the history of psychometric intelligence research is combined with presenting recent work on the role of intelligence in modern societies and on the nature-nurture debate. Finally, promising approaches to integrating the general and differential perspective will be discussed in the conclusion of this review.

Acoustic characteristics used by Japanese macaques for individual discrimination.

Science.gov (United States)

Furuyama, Takafumi; Kobayasi, Kohta I; Riquimaroux, Hiroshi

2017-10-01

The vocalizations of primates contain information about speaker individuality. Many primates, including humans, are able to distinguish conspecifics based solely on vocalizations. The purpose of this study was to investigate the acoustic characteristics used by Japanese macaques in individual vocal discrimination. Furthermore, we tested human subjects using monkey vocalizations to evaluate species specificity with respect to such discriminations. Two monkeys and five humans were trained to discriminate the coo calls of two unfamiliar monkeys. We created a stimulus continuum between the vocalizations of the two monkeys as a set of probe stimuli (whole morph). We also created two sets of continua in which only one acoustic parameter, fundamental frequency ( f 0 ) or vocal tract characteristic (VTC), was changed from the coo call of one monkey to that of another while the other acoustic feature remained the same ( f 0 morph and VTC morph, respectively). According to the results, the reaction times both of monkeys and humans were correlated with the morph proportion under the whole morph and f 0 morph conditions. The reaction time to the VTC morph was correlated with the morph proportion in both monkeys, whereas the reaction time in humans, on average, was not correlated with morph proportion. Japanese monkeys relied more consistently on VTC than did humans for discriminating monkey vocalizations. Our results support the idea that the auditory system of primates is specialized for processing conspecific vocalizations and suggest that VTC is a significant acoustic feature used by Japanese macaques to discriminate conspecific vocalizations. © 2017. Published by The Company of Biologists Ltd.

"Wide-Awake Learning": Integrative Learning and Humanities Education

Science.gov (United States)

Booth, Alan

2011-01-01

This article reviews the development of integrative learning and argues that it has an important role to play in broader conceptions of the undergraduate curriculum recently advanced in the UK. It suggests that such a focus might also provide arts and humanities educators with a hopeful prospect in difficult times: a means by which the distinctive…

Editorial: Technology for higher education, adult learning and human performance

OpenAIRE

Minhong Wang; Chi-Cheng Chang; Feng Wu

2013-01-01

This special issue is dedicated to technology-enabled approaches for improving higher education, adult learning, and human performance. Improvement of learning and human development for sustainable development has been recognized as a key strategy for individuals, institutions, and organizations to strengthen their competitive advantages. It becomes crucial to help adult learners and knowledge workers to improve their self-directed and life-long learning capabilities. Meanwhile, advances in t...

Human-like brain hemispheric dominance in birdsong learning.

Science.gov (United States)

Moorman, Sanne; Gobes, Sharon M H; Kuijpers, Maaike; Kerkhofs, Amber; Zandbergen, Matthijs A; Bolhuis, Johan J

2012-07-31

Unlike nonhuman primates, songbirds learn to vocalize very much like human infants acquire spoken language. In humans, Broca's area in the frontal lobe and Wernicke's area in the temporal lobe are crucially involved in speech production and perception, respectively. Songbirds have analogous brain regions that show a similar neural dissociation between vocal production and auditory perception and memory. In both humans and songbirds, there is evidence for lateralization of neural responsiveness in these brain regions. Human infants already show left-sided dominance in their brain activation when exposed to speech. Moreover, a memory-specific left-sided dominance in Wernicke's area for speech perception has been demonstrated in 2.5-mo-old babies. It is possible that auditory-vocal learning is associated with hemispheric dominance and that this association arose in songbirds and humans through convergent evolution. Therefore, we investigated whether there is similar song memory-related lateralization in the songbird brain. We exposed male zebra finches to tutor or unfamiliar song. We found left-sided dominance of neuronal activation in a Broca-like brain region (HVC, a letter-based name) of juvenile and adult zebra finch males, independent of the song stimulus presented. In addition, juvenile males showed left-sided dominance for tutor song but not for unfamiliar song in a Wernicke-like brain region (the caudomedial nidopallium). Thus, left-sided dominance in the caudomedial nidopallium was specific for the song-learning phase and was memory-related. These findings demonstrate a remarkable neural parallel between birdsong and human spoken language, and they have important consequences for our understanding of the evolution of auditory-vocal learning and its neural mechanisms.

Visual Tracking via Feature Tensor Multimanifold Discriminate Analysis

Directory of Open Access Journals (Sweden)

Ting-quan Deng

2014-01-01

Full Text Available In the visual tracking scenarios, if there are multiple objects, due to the interference of similar objects, tracking may fail in the progress of occlusion to separation. To address this problem, this paper proposed a visual tracking algorithm with discrimination through multimanifold learning. Color-gradient-based feature tensor was used to describe object appearance for accommodation of partial occlusion. A prior multimanifold tensor dataset is established through the template matching tracking algorithm. For the purpose of discrimination, tensor distance was defined to determine the intramanifold and intermanifold neighborhood relationship in multimanifold space. Then multimanifold discriminate analysis was employed to construct multilinear projection matrices of submanifolds. Finally, object states were obtained by combining with sequence inference. Meanwhile, the multimanifold dataset and manifold learning embedded projection should be updated online. Experiments were conducted on two real visual surveillance sequences to evaluate the proposed algorithm with three state-of-the-art tracking methods qualitatively and quantitatively. Experimental results show that the proposed algorithm can achieve effective and robust effect in multi-similar-object mutual occlusion scenarios.

Effects of Systematic Human Relations Training on Inmate Participants

Science.gov (United States)

Davis, E. Duane; And Others

1976-01-01

The present study was conducted to determine the applicability of human relations training in the rehabilitation of selected prisoners in a Southern prison. Inmates who participated in the study were able to learn discrimination between helpful and nonhelpful communication and to make positive gains in their work behavior. (Author)

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos.

Science.gov (United States)

Aghamohammadi, Amirhossein; Ang, Mei Choo; A Sundararajan, Elankovan; Weng, Ng Kok; Mogharrebi, Marzieh; Banihashem, Seyed Yashar

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods.

Perceptual learning modifies untrained pursuit eye movements.

Science.gov (United States)

Szpiro, Sarit F A; Spering, Miriam; Carrasco, Marisa

2014-07-07

Perceptual learning improves detection and discrimination of relevant visual information in mature humans, revealing sensory plasticity. Whether visual perceptual learning affects motor responses is unknown. Here we implemented a protocol that enabled us to address this question. We tested a perceptual response (motion direction estimation, in which observers overestimate motion direction away from a reference) and a motor response (voluntary smooth pursuit eye movements). Perceptual training led to greater overestimation and, remarkably, it modified untrained smooth pursuit. In contrast, pursuit training did not affect overestimation in either pursuit or perception, even though observers in both training groups were exposed to the same stimuli for the same time period. A second experiment revealed that estimation training also improved discrimination, indicating that overestimation may optimize perceptual sensitivity. Hence, active perceptual training is necessary to alter perceptual responses, and an acquired change in perception suffices to modify pursuit, a motor response. © 2014 ARVO.

GENDER DISCRIMINATION AND THE EFFECTS ON WOMEN HUMAN RESOURCES MANAGERS CAREERS

OpenAIRE

BULUT, Dilvin; KIZILDAĞ, Duygu

2017-01-01

Working women have been faced obstacles based on gender discrimination in Turkey and inthe world at the point of career development,. Women have been exposed to gender-based obstaclesinstead of evaluating objectively with their success and competence as an employee. In this study,gender discrimination problems faced by women in their business life are evaluated. The purpose of  this study, a research was conducted to determine the effect of gender discrimination on the careers ofwomen manager...

Teaching and Learning French--A Tale of Desire in the Humanities

Science.gov (United States)

Cunningham, Catriona

2017-01-01

This article considers the way we talk about learning and teaching the humanities in higher education in the UK. By using the tools of the arts and humanities within the scholarship of learning and teaching, and examining a personal perspective, the author explores the transformational impact of French language learning and teaching. Close textual…

Age and education adjusted normative data and discriminative validity for Rey's Auditory Verbal Learning Test in the elderly Greek population.

Science.gov (United States)

Messinis, Lambros; Nasios, Grigorios; Mougias, Antonios; Politis, Antonis; Zampakis, Petros; Tsiamaki, Eirini; Malefaki, Sonia; Gourzis, Phillipos; Papathanasopoulos, Panagiotis

2016-01-01

Rey's Auditory Verbal Learning Test (RAVLT) is a widely used neuropsychological test to assess episodic memory. In the present study we sought to establish normative and discriminative validity data for the RAVLT in the elderly population using previously adapted learning lists for the Greek adult population. We administered the test to 258 cognitively healthy elderly participants, aged 60-89 years, and two patient groups (192 with amnestic mild cognitive impairment, aMCI, and 65 with Alzheimer's disease, AD). From the statistical analyses, we found that age and education contributed significantly to most trials of the RAVLT, whereas the influence of gender was not significant. Younger elderly participants with higher education outperformed the older elderly with lower education levels. Moreover, both clinical groups performed significantly worse on most RAVLT trials and composite measures than matched cognitively healthy controls. Furthermore, the AD group performed more poorly than the aMCI group on most RAVLT variables. Receiver operating characteristic (ROC) analysis was used to examine the utility of the RAVLT trials to discriminate cognitively healthy controls from aMCI and AD patients. Area under the curve (AUC), an index of effect size, showed that most of the RAVLT measures (individual and composite) included in this study adequately differentiated between the performance of healthy elders and aMCI/AD patients. We also provide cutoff scores in discriminating cognitively healthy controls from aMCI and AD patients, based on the sensitivity and specificity of the prescribed scores. Moreover, we present age- and education-specific normative data for individual and composite scores for the Greek adapted RAVLT in elderly subjects aged between 60 and 89 years for use in clinical and research settings.

Convergent transcriptional specializations in the brains of humans and song-learning birds

DEFF Research Database (Denmark)

Pfenning, Andreas R.; Hara, Erina; Whitney, Osceola

2014-01-01

Song-learning birds and humans share independently evolved similarities in brain pathways for vocal learning that are essential for song and speech and are not found in most other species. Comparisons of brain transcriptomes of song-learning birds and humans relative to vocal nonlearners identified...... convergent gene expression specializations in specific song and speech brain regions of avian vocal learners and humans. The strongest shared profiles relate bird motor and striatal song-learning nuclei, respectively, with human laryngeal motor cortex and parts of the striatum that control speech production...... and learning. Most of the associated genes function in motor control and brain connectivity. Thus, convergent behavior and neural connectivity for a complex trait are associated with convergent specialized expression of multiple genes....

Conditioning procedure and color discrimination in the honeybee Apis mellifera

Science.gov (United States)

Giurfa, Martin

We studied the influence of the conditioning procedure on color discrimination by free-flying honeybees. We asked whether absolute and differential conditioning result in different discrimination capabilities for the same pairs of colored targets. In absolute conditioning, bees were rewarded on a single color; in differential conditioning, bees were rewarded on the same color but an alternative, non-rewarding, similar color was also visible. In both conditioning procedures, bees learned their respective task and could also discriminate the training stimulus from a novel stimulus that was perceptually different from the trained one. Discrimination between perceptually closer stimuli was possible after differential conditioning but not after absolute conditioning. Differences in attention inculcated by these training procedures may underlie the different discrimination performances of the bees.

A Web-Server of Cell Type Discrimination System

Directory of Open Access Journals (Sweden)

Anyou Wang

2014-01-01

Full Text Available Discriminating cell types is a daily request for stem cell biologists. However, there is not a user-friendly system available to date for public users to discriminate the common cell types, embryonic stem cells (ESCs, induced pluripotent stem cells (iPSCs, and somatic cells (SCs. Here, we develop WCTDS, a web-server of cell type discrimination system, to discriminate the three cell types and their subtypes like fetal versus adult SCs. WCTDS is developed as a top layer application of our recent publication regarding cell type discriminations, which employs DNA-methylation as biomarkers and machine learning models to discriminate cell types. Implemented by Django, Python, R, and Linux shell programming, run under Linux-Apache web server, and communicated through MySQL, WCTDS provides a friendly framework to efficiently receive the user input and to run mathematical models for analyzing data and then to present results to users. This framework is flexible and easy to be expended for other applications. Therefore, WCTDS works as a user-friendly framework to discriminate cell types and subtypes and it can also be expended to detect other cell types like cancer cells.

Do domestic dogs learn words based on humans' referential behaviour?

Directory of Open Access Journals (Sweden)

Sebastian Tempelmann

Full Text Available Some domestic dogs learn to comprehend human words, although the nature and basis of this learning is unknown. In the studies presented here we investigated whether dogs learn words through an understanding of referential actions by humans rather than simple association. In three studies, each modelled on a study conducted with human infants, we confronted four word-experienced dogs with situations involving no spatial-temporal contiguity between the word and the referent; the only available cues were referential actions displaced in time from exposure to their referents. We found that no dogs were able to reliably link an object with a label based on social-pragmatic cues alone in all the tests. However, one dog did show skills in some tests, possibly indicating an ability to learn based on social-pragmatic cues.

Discrimination of artificial categories structured by family resemblances: a comparative study in people (Homo sapiens) and pigeons (Columba livia).

Science.gov (United States)

Makino, Hiroshi; Jitsumori, Masako

2007-02-01

Adult humans (Homo sapiens) and pigeons (Columba livia) were trained to discriminate artificial categories that the authors created by mimicking 2 properties of natural categories. One was a family resemblance relationship: The highly variable exemplars, including those that did not have features in common, were structured by a similarity network with the features correlating to one another in each category. The other was a polymorphous rule: No single feature was essential for distinguishing the categories, and all the features overlapped between the categories. Pigeons learned the categories with ease and then showed a prototype effect in accord with the degrees of family resemblance for novel stimuli. Some evidence was also observed for interactive effects of learning of individual exemplars and feature frequencies. Humans had difficulty in learning the categories. The participants who learned the categories generally responded to novel stimuli in an all-or-none fashion on the basis of their acquired classification decision rules. The processes that underlie the classification performances of the 2 species are discussed.

Gender Discrimination, Human Capital and Marriage

OpenAIRE

Sylvain E. Dessy; Stephane Pallage

2009-01-01

We show that the recognition of basic women's rights in developing countries may have important positive spillovers on the whole sphere of labor market transactions, with more women seeking education and an overall lesser wage discrimination against women. A combination of basic women's rights such as marriage consent, access to credit and the right to do business is shown to have important effects on the wage women can earn for their labor. Access to credit/entrepreneurship, in particular, r...

Learning and motivation in the human striatum.

Science.gov (United States)

Shohamy, Daphna

2011-06-01

The past decade has seen a dramatic change in our understanding of the role of the striatum in behavior. Early perspectives emphasized a role for the striatum in habitual learning of stimulus-response associations and sequences of actions. Recent advances from human neuroimaging research suggest a broader role for the striatum in motivated learning. New findings demonstrate that the striatum represents multiple learning signals and highlight the contribution of the striatum across many cognitive domains and contexts. Recent findings also emphasize interactions between the striatum and other specialized brain systems for learning. Together, these findings suggest that the striatum contributes to a distributed network that learns to select actions based on their predicted value in order to optimize behavior. Copyright © 2011 Elsevier Ltd. All rights reserved.

Discrimination of Fearful and Angry Emotional Voices in Sleeping Human Neonates: a Study of the Mismatch Brain Responses

Directory of Open Access Journals (Sweden)

Dandan eZhang

2014-12-01

Full Text Available Appropriate processing of human voices with different threat-related emotions is of evolutionarily adaptive value for the survival of individuals. Nevertheless, it is still not clear whether the sensitivity to threat-related information is present at birth. Using an oddball paradigm, the current study investigated the neural correlates underlying automatic processing of emotional voices of fear and anger in sleeping neonates. Event-related potential data showed that the frontocentral scalp distribution of the neonatal brain could discriminate fearful voices from angry voices; the mismatch response (MMR was larger in response to the deviant stimuli of anger, compared with the standard stimuli of fear. Furthermore, this fear-anger MMR discrimination was observed only when neonates were in active sleep state. Although the neonates’ sensitivity to threat-related voices is not likely associated with a conceptual understanding of fearful and angry emotions, this special discrimination in early life may provide a foundation for later emotion and social cognition development.

Human Subjects Protection: A Source for Ethical Service-Learning Practice

Science.gov (United States)

Wendler, Rachael

2012-01-01

Human subjects research ethics were developed to ensure responsible conduct when university researchers learn by interacting with community members. As service-learning students also learn by interacting with community members, a similar set of principles may strengthen the ethical practice of service-learning. This article identifies ethical…

Genetic Discrimination: A Legal Or Biological Issue?

Directory of Open Access Journals (Sweden)

Bárbara Augusta de Paula Araujo Myssior

2016-12-01

Full Text Available This essay debates the technological evolution that, from the decoding of the human genome has opened up many scientific benefits, and yet brings up a new kind of segregation: genetic discrimination. Based on the right to privacy, as well as the concept of genetic identity, as well as data protection and information, worked up the genetic discrimination. Therefore, documentary research and critical analysis of scientific papers were taken, using up of the inductive reasoning method. As a result, elucidate how such discrimination affects individuals, it is possible to conclude that regardless of the type of discrimination, all should be restrained by law.

Fos Protein Expression in Olfactory-Related Brain Areas after Learning and after Reactivation of a Slowly Acquired Olfactory Discrimination Task in the Rat

Science.gov (United States)

Roullet, Florence; Lienard, Fabienne; Datiche, Frederique; Cattarelli, Martine

2005-01-01

Fos protein immunodetection was used to investigate the neuronal activation elicited in some olfactory-related areas after either learning of an olfactory discrimination task or its reactivation 10 d later. Trained rats (T) progressively acquired the association between one odor of a pair and water-reward in a four-arm maze. Two groups of…

Medical students’ perception of lesbian, gay, bisexual, and transgender (LGBT) discrimination in their learning environment and their self-reported comfort level for caring for LGBT patients: a survey study

OpenAIRE

Nama, Nassr; MacPherson, Paul; Sampson, Margaret; McMillan, Hugh J.

2017-01-01

ABSTRACT Background: Historically, medical students who are lesbian, gay, bisexual or transgendered (LGBT) report higher rates of social stress, depression, and anxiety, while LGBT patients have reported discrimination and poorer access to healthcare. Objective: The objectives of this study were: (1) to assess if medical students have perceived discrimination in their learning environment and; (2) to determine self-reported comfort level for caring for LGBT patients. Design: Medical students ...

Serum Metabolomic Profiles for Human Pancreatic Cancer Discrimination

Directory of Open Access Journals (Sweden)

Takao Itoi

2017-04-01

Full Text Available This study evaluated the clinical use of serum metabolomics to discriminate malignant cancers including pancreatic cancer (PC from malignant diseases, such as biliary tract cancer (BTC, intraductal papillary mucinous carcinoma (IPMC, and various benign pancreaticobiliary diseases. Capillary electrophoresismass spectrometry was used to analyze charged metabolites. We repeatedly analyzed serum samples (n = 41 of different storage durations to identify metabolites showing high quantitative reproducibility, and subsequently analyzed all samples (n = 140. Overall, 189 metabolites were quantified and 66 metabolites had a 20% coefficient of variation and, of these, 24 metabolites showed significant differences among control, benign, and malignant groups (p < 0.05; Steel–Dwass test. Four multiple logistic regression models (MLR were developed and one MLR model clearly discriminated all disease patients from healthy controls with an area under receiver operating characteristic curve (AUC of 0.970 (95% confidential interval (CI, 0.946–0.994, p < 0.0001. Another model to discriminate PC from BTC and IPMC yielded AUC = 0.831 (95% CI, 0.650–1.01, p = 0.0020 with higher accuracy compared with tumor markers including carcinoembryonic antigen (CEA, carbohydrate antigen 19-9 (CA19-9, pancreatic cancer-associated antigen (DUPAN2 and s-pancreas-1 antigen (SPAN1. Changes in metabolomic profiles might be used to screen for malignant cancers as well as to differentiate between PC and other malignant diseases.

Associative learning in baboons (Papio papio) and humans (Homo sapiens): species differences in learned attention to visual features.

Science.gov (United States)

Fagot, J; Kruschke, J K; Dépy, D; Vauclair, J

1998-10-01

We examined attention shifting in baboons and humans during the learning of visual categories. Within a conditional matching-to-sample task, participants of the two species sequentially learned two two-feature categories which shared a common feature. Results showed that humans encoded both features of the initially learned category, but predominantly only the distinctive feature of the subsequently learned category. Although baboons initially encoded both features of the first category, they ultimately retained only the distinctive features of each category. Empirical data from the two species were analyzed with the 1996 ADIT connectionist model of Kruschke. ADIT fits the baboon data when the attentional shift rate is zero, and the human data when the attentional shift rate is not zero. These empirical and modeling results suggest species differences in learned attention to visual features.

HIV/AIDS and the principle of non-discrimination and non-stigmatization

Directory of Open Access Journals (Sweden)

Volnei Garrafa

2012-01-01

Full Text Available The text examines the article 11 of the Universal Declaration on Bioethics and Human Rights of UNESCO that deals with the principle of non-discrimination and non-stigmatization. Both concepts are related to the theme of human dignity, while discrimination is an inherent part of stigma: stigma does not exist if there is no discrimination. In this context, this paper aims to study the relationship between stigma, discrimination and HIV / AIDS. The study argues that to loosen the bonds that hold the subjects that are attached to them is necessary questioning the broader forces - social, cultural, political and economic - that structure stigma, stigmatization and discrimination as social processes directly linked to production and reproduction of structural inequalities.

Intrinsically motivated reinforcement learning for human-robot interaction in the real-world.

Science.gov (United States)

Qureshi, Ahmed Hussain; Nakamura, Yutaka; Yoshikawa, Yuichiro; Ishiguro, Hiroshi

2018-03-26

For a natural social human-robot interaction, it is essential for a robot to learn the human-like social skills. However, learning such skills is notoriously hard due to the limited availability of direct instructions from people to teach a robot. In this paper, we propose an intrinsically motivated reinforcement learning framework in which an agent gets the intrinsic motivation-based rewards through the action-conditional predictive model. By using the proposed method, the robot learned the social skills from the human-robot interaction experiences gathered in the real uncontrolled environments. The results indicate that the robot not only acquired human-like social skills but also took more human-like decisions, on a test dataset, than a robot which received direct rewards for the task achievement. Copyright © 2018 Elsevier Ltd. All rights reserved.

Forced sterilization of women as discrimination.

Science.gov (United States)

Patel, Priti

2017-01-01

There has been a long history of subjecting marginalized women to forced and coerced sterilization. In recent years, the practice has been documented in countries in North and South America, Europe, Asia, and Africa. It has targeted women who are ethnic and racial minorities, women with disabilities, women living with HIV, and poor women. A handful of courts have issued decisions on the recent forced sterilization of marginalized women finding that such actions violate the women's rights. However, they have all failed to address the women's claims of discrimination. The failure to acknowledge that forced sterilization is at its core a violation of the prohibition of discrimination undermines efforts to eradicate the practice. It further fails to recognize that coerced and forced sterilization fundamentally seeks to deny women deemed as "unworthy" the ability to procreate. Four key principles outlined in the human rights in patient care framework highlight the importance of a finding that the prohibition of discrimination was violated in cases of forced sterilization: the need to highlight the vulnerability of marginalized populations to discrimination in health care settings; the importance of the rights of medical providers; the role of the state in addressing systemic human rights violations in health care settings; and the application of human rights to patient care. Based on these principles, it is clear that finding a violation of the prohibition of discrimination in forced sterilization cases is critical in addressing the systemic nature of the practice, acknowledging the marginalization of specific groups and effectively ending forced sterilization through addressing the underlying purpose of the practice. If litigators, non-governmental organizations and judicial officers are mindful of these principles when dealing with cases of forced sterilization, it is likely that they will be better able to eradicate forced sterilization.

Development of the Human Factors Skills for Healthcare Instrument: a valid and reliable tool for assessing interprofessional learning across healthcare practice settings.

Science.gov (United States)

Reedy, Gabriel B; Lavelle, Mary; Simpson, Thomas; Anderson, Janet E

2017-10-01

A central feature of clinical simulation training is human factors skills, providing staff with the social and cognitive skills to cope with demanding clinical situations. Although these skills are critical to safe patient care, assessing their learning is challenging. This study aimed to develop, pilot and evaluate a valid and reliable structured instrument to assess human factors skills, which can be used pre- and post-simulation training, and is relevant across a range of healthcare professions. Through consultation with a multi-professional expert group, we developed and piloted a 39-item survey with 272 healthcare professionals attending training courses across two large simulation centres in London, one specialising in acute care and one in mental health, both serving healthcare professionals working across acute and community settings. Following psychometric evaluation, the final 12-item instrument was evaluated with a second sample of 711 trainees. Exploratory factor analysis revealed a 12-item, one-factor solution with good internal consistency (α=0.92). The instrument had discriminant validity, with newly qualified trainees scoring significantly lower than experienced trainees ( t (98)=4.88, pSkills for Healthcare Instrument provides a reliable and valid method of assessing trainees' human factors skills self-efficacy across acute and mental health settings. This instrument has the potential to improve the assessment and evaluation of human factors skills learning in both uniprofessional and interprofessional clinical simulation training.

Human-level control through deep reinforcement learning

Science.gov (United States)

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

2015-02-01

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

Human-level control through deep reinforcement learning.

Science.gov (United States)

Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A; Veness, Joel; Bellemare, Marc G; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

2015-02-26

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

Connecticut – Sexual Orientation and Gender Identity Law and Documentation of Discrimination

OpenAIRE

Sears, Brad

2009-01-01

A Connecticut statute bans employment discrimination on the basis of sexual orientation. No Connecticut statutes prohibit discrimination on the basis of gender identity or expression. In November 2000, the Connecticut Commission on Human Rights and Opportunities – the agency responsible for administering the anti-discrimination statutes and for processing discrimination complaints – ruled that statutes prohibiting sex discrimination also banned discrimination on the basis of gender identity. ...

Gender and vocal production mode discrimination using the high frequencies for speech and singing

Science.gov (United States)

Monson, Brian B.; Lotto, Andrew J.; Story, Brad H.

2014-01-01

Humans routinely produce acoustical energy at frequencies above 6 kHz during vocalization, but this frequency range is often not represented in communication devices and speech perception research. Recent advancements toward high-definition (HD) voice and extended bandwidth hearing aids have increased the interest in the high frequencies. The potential perceptual information provided by high-frequency energy (HFE) is not well characterized. We found that humans can accomplish tasks of gender discrimination and vocal production mode discrimination (speech vs. singing) when presented with acoustic stimuli containing only HFE at both amplified and normal levels. Performance in these tasks was robust in the presence of low-frequency masking noise. No substantial learning effect was observed. Listeners also were able to identify the sung and spoken text (excerpts from “The Star-Spangled Banner”) with very few exposures. These results add to the increasing evidence that the high frequencies provide at least redundant information about the vocal signal, suggesting that its representation in communication devices (e.g., cell phones, hearing aids, and cochlear implants) and speech/voice synthesizers could improve these devices and benefit normal-hearing and hearing-impaired listeners. PMID:25400613

Discrimination in Employment

Science.gov (United States)

Abzug, Bella

1975-01-01

This testimony, before a public hearing of the New York City Commission on Human Rights in May 1974, expressly focuses on discrimination in employment, asserting that this has had the most direct effect on minorities and women in the country; while legal protections have grown stronger, they have not been used effectively. (Author/JM)

A parallel spatiotemporal saliency and discriminative online learning method for visual target tracking in aerial videos

Science.gov (United States)

2018-01-01

Visual tracking in aerial videos is a challenging task in computer vision and remote sensing technologies due to appearance variation difficulties. Appearance variations are caused by camera and target motion, low resolution noisy images, scale changes, and pose variations. Various approaches have been proposed to deal with appearance variation difficulties in aerial videos, and amongst these methods, the spatiotemporal saliency detection approach reported promising results in the context of moving target detection. However, it is not accurate for moving target detection when visual tracking is performed under appearance variations. In this study, a visual tracking method is proposed based on spatiotemporal saliency and discriminative online learning methods to deal with appearance variations difficulties. Temporal saliency is used to represent moving target regions, and it was extracted based on the frame difference with Sauvola local adaptive thresholding algorithms. The spatial saliency is used to represent the target appearance details in candidate moving regions. SLIC superpixel segmentation, color, and moment features can be used to compute feature uniqueness and spatial compactness of saliency measurements to detect spatial saliency. It is a time consuming process, which prompted the development of a parallel algorithm to optimize and distribute the saliency detection processes that are loaded into the multi-processors. Spatiotemporal saliency is then obtained by combining the temporal and spatial saliencies to represent moving targets. Finally, a discriminative online learning algorithm was applied to generate a sample model based on spatiotemporal saliency. This sample model is then incrementally updated to detect the target in appearance variation conditions. Experiments conducted on the VIVID dataset demonstrated that the proposed visual tracking method is effective and is computationally efficient compared to state-of-the-art methods. PMID:29438421

Awake, long-term intranasal insulin treatment does not affect object memory, odor discrimination, or reversal learning in mice.

Science.gov (United States)

Bell, Genevieve A; Fadool, Debra Ann

2017-05-15

Intranasal insulin delivery is currently being used in clinical trials to test for improvement in human memory and cognition, and in particular, for lessening memory loss attributed to neurodegenerative diseases. Studies have reported the effects of short-term intranasal insulin treatment on various behaviors, but less have examined long-term effects. The olfactory bulb contains the highest density of insulin receptors in conjunction with the highest level of insulin transport within the brain. Previous research from our laboratory has demonstrated that acute insulin intranasal delivery (IND) enhanced both short- and long-term memory as well as increased two-odor discrimination in a two-choice paradigm. Herein, we investigated the behavioral and physiological effects of chronic insulin IND. Adult, male C57BL6/J mice were intranasally treated with 5μg/μl of insulin twice daily for 30 and 60days. Metabolic assessment indicated no change in body weight, caloric intake, or energy expenditure following chronic insulin IND, but an increase in the frequency of meal bouts selectively in the dark cycle. Unlike acute insulin IND, which has been shown to cause enhanced performance in odor habituation/dishabituation and two-odor discrimination tasks in mice, chronic insulin IND did not enhance olfactometry-based odorant discrimination or olfactory reversal learning. In an object memory recognition task, insulin IND-treated mice did not perform differently than controls, regardless of task duration. Biochemical analyses of the olfactory bulb revealed a modest 1.3 fold increase in IR kinase phosphorylation but no significant increase in Kv1.3 phosphorylation. Substrate phosphorylation of IR kinase downstream effectors (MAPK/ERK and Akt signaling) proved to be highly variable. These data indicate that chronic administration of insulin IND in mice fails to enhance olfactory ability, object memory recognition, or a majority of systems physiology metabolic factors - as reported to

Learning collaborative teamwork: an argument for incorporating the humanities.

Science.gov (United States)

Hall, Pippa; Brajtman, Susan; Weaver, Lynda; Grassau, Pamela Anne; Varpio, Lara

2014-11-01

A holistic, collaborative interprofessional team approach, which includes patients and families as significant decision-making members, has been proposed to address the increasing burden being placed on the health-care system. This project hypothesized that learning activities related to the humanities during clinical placements could enhance interprofessional teamwork. Through an interprofessional team of faculty, clinical staff, students, and patient representatives, we developed and piloted the self-learning module, "interprofessional education for collaborative person-centred practice through the humanities". The module was designed to provide learners from different professions and educational levels with a clinical placement/residency experience that would enable them, through a lens of the humanities, to better understand interprofessional collaborative person-centred care without structured interprofessional placement activities. Learners reported the self-paced and self-directed module to be a satisfactory learning experience in all four areas of care at our institution, and certain attitudes and knowledge were significantly and positively affected. The module's evaluation resulted in a revised edition providing improved structure and instruction for students with no experience in self-directed learning. The module was recently adapted into an interactive bilingual (French and English) online e-learning module to facilitate its integration into the pre-licensure curriculum at colleges and universities.

Object recognition with hierarchical discriminant saliency networks

Directory of Open Access Journals (Sweden)

Sunhyoung eHan

2014-09-01

Full Text Available The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognitionmodel, the hierarchical discriminant saliency network (HDSN, whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. The HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a neuralnetwork implementation, all layers are convolutional and implement acombination of filtering, rectification, and pooling. The rectificationis performed with a parametric extension of the now popular rectified linearunits (ReLUs, whose parameters can be tuned for the detection of targetobject classes. This enables a number of functional enhancementsover neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation ofsaliency responses by the discriminant power of the underlying features,and the ability to detect both feature presence and absence.In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity totarget object classes and invariance. The resulting performance demonstrates benefits for all the functional enhancements of the HDSN.

Effectiveness of using blended learning strategies for teaching and learning human anatomy.

Science.gov (United States)

Pereira, José A; Pleguezuelos, Eulogio; Merí, Alex; Molina-Ros, Antoni; Molina-Tomás, M Carmen; Masdeu, Carlos

2007-02-01

This study aimed to implement innovative teaching methods--blended learning strategies--that include the use of new information technologies in the teaching of human anatomy and to analyse both the impact of these strategies on academic performance, and the degree of user satisfaction. The study was carried out among students in Year 1 of the biology degree curriculum (human biology profile) at Pompeu Fabra University, Barcelona. Two groups of students were tested on knowledge of the anatomy of the locomotor system and results compared between groups. Blended learning strategies were employed in 1 group (BL group, n = 69); the other (TT group; n = 65) received traditional teaching aided by complementary material that could be accessed on the Internet. Both groups were evaluated using the same types of examination. The average marks presented statistically significant differences (BL 6.3 versus TT 5.0; P < 0.0001). The percentage pass rate for the subject in the first call was higher in the BL group (87.9% versus 71.4%; P = 0.02), reflecting a lower incidence of students who failed to sit the examination (BL 4.3% versus TT 13.8%; P = 0.05). There were no differences regarding overall satisfaction with the teaching received. Blended learning was more effective than traditional teaching for teaching human anatomy.

Mimvec: a deep learning approach for analyzing the human phenome.

Science.gov (United States)

Gan, Mingxin; Li, Wenran; Zeng, Wanwen; Wang, Xiaojian; Jiang, Rui

2017-09-21

The human phenome has been widely used with a variety of genomic data sources in the inference of disease genes. However, most existing methods thus far derive phenotype similarity based on the analysis of biomedical databases by using the traditional term frequency-inverse document frequency (TF-IDF) formulation. This framework, though intuitive, not only ignores semantic relationships between words but also tends to produce high-dimensional vectors, and hence lacks the ability to precisely capture intrinsic semantic characteristics of biomedical documents. To overcome these limitations, we propose a framework called mimvec to analyze the human phenome by making use of the state-of-the-art deep learning technique in natural language processing. We converted 24,061 records in the Online Mendelian Inheritance in Man (OMIM) database to low-dimensional vectors using our method. We demonstrated that the vector presentation not only effectively enabled classification of phenotype records against gene ones, but also succeeded in discriminating diseases of different inheritance styles and different mechanisms. We further derived pairwise phenotype similarities between 7988 human inherited diseases using their vector presentations. With a joint analysis of this phenome with multiple genomic data, we showed that phenotype overlap indeed implied genotype overlap. We finally used the derived phenotype similarities with genomic data to prioritize candidate genes and demonstrated advantages of this method over existing ones. Our method is capable of not only capturing semantic relationships between words in biomedical records but also alleviating the dimensional disaster accompanying the traditional TF-IDF framework. With the approaching of precision medicine, there will be abundant electronic records of medicine and health awaiting for deep analysis, and we expect to see a wide spectrum of applications borrowing the idea of our method in the near future.

Role of amygdala central nucleus in feature negative discriminations

Science.gov (United States)

Holland, Peter C.

2012-01-01

Consistent with a popular theory of associative learning, the Pearce-Hall (1980) model, the surprising omission of expected events enhances cue associability (the ease with which a cue may enter into new associations), across a wide variety of behavioral training procedures. Furthermore, previous experiments from this laboratory showed that these enhancements are absent in rats with impaired function of the amygdala central nucleus (CeA). A notable exception to these assertions is found in feature negative (FN) discrimination learning, in which a “target” stimulus is reinforced when it is presented alone but nonreinforced when it is presented in compound with another, “feature” stimulus. According to the Pearce-Hall model, reinforcer omission on compound trials should enhance the associability of the feature relative to control training conditions. However, prior experiments have shown no evidence that CeA lesions affect FN discrimination learning. Here we explored this apparent contradiction by evaluating the hypothesis that the surprising omission of an event confers enhanced associability on a cue only if that cue itself generates the disconfirmed prediction. Thus, in a FN discrimination, the surprising omission of the reinforcer on compound trials would enhance the associability of the target stimulus but not that of the feature. Our data confirmed this hypothesis, and showed this enhancement to depend on intact CeA function, as in other procedures. The results are consistent with modern reformulations of both cue and reward processing theories that assign roles for both individual and aggregate error terms in associative learning. PMID:22889308

Human likeness: cognitive and affective factors affecting adoption of robot-assisted learning systems

Science.gov (United States)

Yoo, Hosun; Kwon, Ohbyung; Lee, Namyeon

2016-07-01

With advances in robot technology, interest in robotic e-learning systems has increased. In some laboratories, experiments are being conducted with humanoid robots as artificial tutors because of their likeness to humans, the rich possibilities of using this type of media, and the multimodal interaction capabilities of these robots. The robot-assisted learning system, a special type of e-learning system, aims to increase the learner's concentration, pleasure, and learning performance dramatically. However, very few empirical studies have examined the effect on learning performance of incorporating humanoid robot technology into e-learning systems or people's willingness to accept or adopt robot-assisted learning systems. In particular, human likeness, the essential characteristic of humanoid robots as compared with conventional e-learning systems, has not been discussed in a theoretical context. Hence, the purpose of this study is to propose a theoretical model to explain the process of adoption of robot-assisted learning systems. In the proposed model, human likeness is conceptualized as a combination of media richness, multimodal interaction capabilities, and para-social relationships; these factors are considered as possible determinants of the degree to which human cognition and affection are related to the adoption of robot-assisted learning systems.

Discriminative Structured Dictionary Learning on Grassmann Manifolds and Its Application on Image Restoration.

Science.gov (United States)

Pan, Han; Jing, Zhongliang; Qiao, Lingfeng; Li, Minzhe

2017-09-25

Image restoration is a difficult and challenging problem in various imaging applications. However, despite of the benefits of a single overcomplete dictionary, there are still several challenges for capturing the geometric structure of image of interest. To more accurately represent the local structures of the underlying signals, we propose a new problem formulation for sparse representation with block-orthogonal constraint. There are three contributions. First, a framework for discriminative structured dictionary learning is proposed, which leads to a smooth manifold structure and quotient search spaces. Second, an alternating minimization scheme is proposed after taking both the cost function and the constraints into account. This is achieved by iteratively alternating between updating the block structure of the dictionary defined on Grassmann manifold and sparsifying the dictionary atoms automatically. Third, Riemannian conjugate gradient is considered to track local subspaces efficiently with a convergence guarantee. Extensive experiments on various datasets demonstrate that the proposed method outperforms the state-of-the-art methods on the removal of mixed Gaussian-impulse noise.

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

How discriminating are discriminative instruments?

Science.gov (United States)

Hankins, Matthew

2008-05-27

The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL). The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness), but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta) is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

How discriminating are discriminative instruments?

Directory of Open Access Journals (Sweden)

Hankins Matthew

2008-05-01

Full Text Available Abstract The McMaster framework introduced by Kirshner & Guyatt is the dominant paradigm for the development of measures of health status and health-related quality of life (HRQL. The framework defines the functions of such instruments as evaluative, predictive or discriminative. Evaluative instruments are required to be sensitive to change (responsiveness, but there is no corresponding index of the degree to which discriminative instruments are sensitive to cross-sectional differences. This paper argues that indices of validity and reliability are not sufficient to demonstrate that a discriminative instrument performs its function of discriminating between individuals, and that the McMaster framework would be augmented by the addition of a separate index of discrimination. The coefficient proposed by Ferguson (Delta is easily adapted to HRQL instruments and is a direct, non-parametric index of the degree to which an instrument distinguishes between individuals. While Delta should prove useful in the development and evaluation of discriminative instruments, further research is required to elucidate the relationship between the measurement properties of discrimination, reliability and responsiveness.

Improved object optimal synthetic description, modeling, learning, and discrimination by GEOGINE computational kernel

Science.gov (United States)

Fiorini, Rodolfo A.; Dacquino, Gianfranco

2005-03-01

GEOGINE (GEOmetrical enGINE), a state-of-the-art OMG (Ontological Model Generator) based on n-D Tensor Invariants for n-Dimensional shape/texture optimal synthetic representation, description and learning, was presented in previous conferences elsewhere recently. Improved computational algorithms based on the computational invariant theory of finite groups in Euclidean space and a demo application is presented. Progressive model automatic generation is discussed. GEOGINE can be used as an efficient computational kernel for fast reliable application development and delivery in advanced biomedical engineering, biometric, intelligent computing, target recognition, content image retrieval, data mining technological areas mainly. Ontology can be regarded as a logical theory accounting for the intended meaning of a formal dictionary, i.e., its ontological commitment to a particular conceptualization of the world object. According to this approach, "n-D Tensor Calculus" can be considered a "Formal Language" to reliably compute optimized "n-Dimensional Tensor Invariants" as specific object "invariant parameter and attribute words" for automated n-Dimensional shape/texture optimal synthetic object description by incremental model generation. The class of those "invariant parameter and attribute words" can be thought as a specific "Formal Vocabulary" learned from a "Generalized Formal Dictionary" of the "Computational Tensor Invariants" language. Even object chromatic attributes can be effectively and reliably computed from object geometric parameters into robust colour shape invariant characteristics. As a matter of fact, any highly sophisticated application needing effective, robust object geometric/colour invariant attribute capture and parameterization features, for reliable automated object learning and discrimination can deeply benefit from GEOGINE progressive automated model generation computational kernel performance. Main operational advantages over previous

Using a model of human visual perception to improve deep learning.

Science.gov (United States)

Stettler, Michael; Francis, Gregory

2018-04-17

Deep learning algorithms achieve human-level (or better) performance on many tasks, but there still remain situations where humans learn better or faster. With regard to classification of images, we argue that some of those situations are because the human visual system represents information in a format that promotes good training and classification. To demonstrate this idea, we show how occluding objects can impair performance of a deep learning system that is trained to classify digits in the MNIST database. We describe a human inspired segmentation and interpolation algorithm that attempts to reconstruct occluded parts of an image, and we show that using this reconstruction algorithm to pre-process occluded images promotes training and classification performance. Copyright © 2018 Elsevier Ltd. All rights reserved.

Background Paper for the Expert Meeting on the Gender-Related Aspects of Race Discrimination

Directory of Open Access Journals (Sweden)

Kimberlé Crenshaw

2002-01-01

Full Text Available Neither the gender aspects of racial discrimination nor the racial aspects of gender discrimination are fully comprehended within human rights discourses. Building on the growing recognition that race and gender discrimination are not mutually exclusive phenomena, this background paper forwards a provisional framework to identify various forms of subordination that can be said to reflect the interactive effects of race and gender discrimination. It suggests a provisional protocol to be followed to better identify the occasions in which such interactive discrimination may have occurred, and posits further that the responsibility to address the causes and consequences of such discrimination be shared widely among all human rights institutions.

Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.

Science.gov (United States)

Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L; Schulz, Andreas L; Ohl, Frank W; Lommerzheim, Marcel; Neumann, Heiko

2016-01-01

Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden

The spontaneous replication error and the mismatch discrimination mechanisms of human DNA polymerase β

Science.gov (United States)

Koag, Myong-Chul; Nam, Kwangho; Lee, Seongmin

2014-01-01

To provide molecular-level insights into the spontaneous replication error and the mismatch discrimination mechanisms of human DNA polymerase β (polβ), we report four crystal structures of polβ complexed with dG•dTTP and dA•dCTP mismatches in the presence of Mg2+ or Mn2+. The Mg2+-bound ground-state structures show that the dA•dCTP-Mg2+ complex adopts an ‘intermediate’ protein conformation while the dG•dTTP-Mg2+ complex adopts an open protein conformation. The Mn2+-bound ‘pre-chemistry-state’ structures show that the dA•dCTP-Mn2+ complex is structurally very similar to the dA•dCTP-Mg2+ complex, whereas the dG•dTTP-Mn2+ complex undergoes a large-scale conformational change to adopt a Watson–Crick-like dG•dTTP base pair and a closed protein conformation. These structural differences, together with our molecular dynamics simulation studies, suggest that polβ increases replication fidelity via a two-stage mismatch discrimination mechanism, where one is in the ground state and the other in the closed conformation state. In the closed conformation state, polβ appears to allow only a Watson–Crick-like conformation for purine•pyrimidine base pairs, thereby discriminating the mismatched base pairs based on their ability to form the Watson–Crick-like conformation. Overall, the present studies provide new insights into the spontaneous replication error and the replication fidelity mechanisms of polβ. PMID:25200079

Wavelet transform and real-time learning method for myoelectric signal in motion discrimination

International Nuclear Information System (INIS)

Liu Haihua; Chen Xinhao; Chen Yaguang

2005-01-01

This paper discusses the applicability of the Wavelet transform for analyzing an EMG signal and discriminating motion classes. In many previous works, researchers have dealt with steady EMG and have proposed suitable analyzing methods for the EMG, for example FFT and STFT. Therefore, it is difficult for the previous approaches to discriminate motions from the EMG in the different phases of muscle activity, i.e., pre-activity, in activity, postactivity phases, as well as the period of motion transition from one to another. In this paper, we introduce the Wavelet transform using the Coiflet mother wavelet into our real-time EMG prosthetic hand controller for discriminating motions from steady and unsteady EMG. A preliminary experiment to discriminate three hand motions from four channel EMG in the initial pre-activity and in activity phase is carried out to show the effectiveness of the approach. However, future research efforts are necessary to discriminate more motions much precisely

Visual discrimination following partial telencephalic ablations in nurse sharks (Ginglymostoma cirratum).

Science.gov (United States)

Graeber, R C; Schroeder, D M; Jane, J A; Ebbesson, S O

1978-07-15

An instrumental conditioning task was used to examine the role of the nurse shark telencephalon in black-white (BW) and horizontal-vertical stripes (HV) discrimination performance. In the first experiment, subjects initially received either bilateral anterior telencephalic control lesions or bilateral posterior telencephalic lesions aimed at destroying the central telencephalic nuclei (CN), which are known to receive direct input from the thalamic visual area. Postoperatively, the sharks were trained first on BW and then on HV. Those with anterior lesions learned both tasks as rapidly as unoperated subjects. Those with posterior lesions exhibited visual discrimination deficits related to the amount of damage to the CN and its connecting pathways. Severe damage resulted in an inability to learn either task but caused no impairments in motivation or general learning ability. In the second experiment, the sharks were first trained on BW and HV and then operated. Suction ablations were used to remove various portions of the CN. Sharks with 10% or less damage to the CN retained the preoperatively acquired discriminations almost perfectly. Those with 11-50% damage had to be retrained on both tasks. Almost total removal of the CN produced behavioral indications of blindness along with an inability to perform above the chance level on BW despite excellent retention of both discriminations over a 28-day period before surgery. It appears, however, that such sharks can still detect light. These results implicate the central telencephalic nuclei in the control of visually guided behavior in sharks.

Development of Human Resources Using New Technologies in Long-Life Learning

Directory of Open Access Journals (Sweden)

Micu Bogdan Ghilic

2011-01-01

Full Text Available Information and communication technologies (ICT offer new opportunities to reinvent the education and to make people and makes learning more fun and contemporary but poses many problems to educational institutions. Implementation of ICT determines major structural changes in the organizations and mental switch from bureaucratic mentality to customer-oriented one. In this paper I try to evaluate methods of developing the lifelong learning programs, impact to human resources training and development and the impact of this process on educational institutions. E-learning usage in training the human resources can make a new step in development of the education institutions, human resources and companies.

Human reinforcement learning subdivides structured action spaces by learning effector-specific values

OpenAIRE

Gershman, Samuel J.; Pesaran, Bijan; Daw, Nathaniel D.

2009-01-01

Humans and animals are endowed with a large number of effectors. Although this enables great behavioral flexibility, it presents an equally formidable reinforcement learning problem of discovering which actions are most valuable, due to the high dimensionality of the action space. An unresolved question is how neural systems for reinforcement learning – such as prediction error signals for action valuation associated with dopamine and the striatum – can cope with this “curse of dimensionality...

Learning to Segment Human by Watching YouTube.

Science.gov (United States)

Liang, Xiaodan; Wei, Yunchao; Chen, Yunpeng; Shen, Xiaohui; Yang, Jianchao; Lin, Liang; Yan, Shuicheng

2016-08-05

An intuition on human segmentation is that when a human is moving in a video, the video-context (e.g., appearance and motion clues) may potentially infer reasonable mask information for the whole human body. Inspired by this, based on popular deep convolutional neural networks (CNN), we explore a very-weakly supervised learning framework for human segmentation task, where only an imperfect human detector is available along with massive weakly-labeled YouTube videos. In our solution, the video-context guided human mask inference and CNN based segmentation network learning iterate to mutually enhance each other until no further improvement gains. In the first step, each video is decomposed into supervoxels by the unsupervised video segmentation. The superpixels within the supervoxels are then classified as human or non-human by graph optimization with unary energies from the imperfect human detection results and the predicted confidence maps by the CNN trained in the previous iteration. In the second step, the video-context derived human masks are used as direct labels to train CNN. Extensive experiments on the challenging PASCAL VOC 2012 semantic segmentation benchmark demonstrate that the proposed framework has already achieved superior results than all previous weakly-supervised methods with object class or bounding box annotations. In addition, by augmenting with the annotated masks from PASCAL VOC 2012, our method reaches a new stateof- the-art performance on the human segmentation task.

Gender and the right to non-discrimination in international human rights law

OpenAIRE

Netkova, Bistra

2016-01-01

Discrimination against women based on the fact that they are women is a deeply rooted practice in all societies. However, the level of discrimination varies greatly with the level of development of the given society and strongly influences and vice versa it is influenced by the status of women in a given society. Addressing this gender-based discrimination is a difficult task because it is closely linked to the concept of equality, and state’s action and inactions. The article establishes tha...

A Human/Computer Learning Network to Improve Biodiversity Conservation and Research

OpenAIRE

Kelling, Steve; Gerbracht, Jeff; Fink, Daniel; Lagoze, Carl; Wong, Weng-Keen; Yu, Jun; Damoulas, Theodoros; Gomes, Carla

2012-01-01

In this paper we describe eBird, a citizen-science project that takes advantage of the human observational capacity to identify birds to species, which is then used to accurately represent patterns of bird occurrences across broad spatial and temporal extents. eBird employs artificial intelligence techniques such as machine learning to improve data quality by taking advantage of the synergies between human computation and mechanical computation. We call this a Human-Computer Learning Network,...

Medical students’ perception of lesbian, gay, bisexual, and transgender (LGBT) discrimination in their learning environment and their self-reported comfort level for caring for LGBT patients: a survey study

Science.gov (United States)

Nama, Nassr; MacPherson, Paul; Sampson, Margaret; McMillan, Hugh J.

2017-01-01

ABSTRACT Background: Historically, medical students who are lesbian, gay, bisexual or transgendered (LGBT) report higher rates of social stress, depression, and anxiety, while LGBT patients have reported discrimination and poorer access to healthcare. Objective: The objectives of this study were: (1) to assess if medical students have perceived discrimination in their learning environment and; (2) to determine self-reported comfort level for caring for LGBT patients. Design: Medical students at the University of Ottawa (N = 671) were contacted via email and invited to complete a confidential web-based survey. Results: Response rate was 15.4% (103/671). This included 66 cis-gender heterosexuals (64.1%) and 37 LGBT students (35.9%). Anti-LGBT discrimination had been witnessed by 14.6% and heterosexism by 31.1% of respondents. Anti-LGBT discrimination most often originated from fellow medical students. Respondents who self-identified as LGBT were more likely to have perceived heterosexism (favoring opposite-sex relationships) (OR = 8.2, p LGBT discrimination (OR = 6.6, p = 0.002). While half of LGBT students shared their status with all classmates (51.4%), they were more likely to conceal this from staff physicians (OR = 27.2, p = 0.002). Almost half of medical students (41.7%) reported anti-LGBT jokes, rumors, and/or bullying by fellow medical students and/or other members of the healthcare team. Still, most respondents indicated that they felt comfortable with and capable of providing medical care to LGBT patients (≥83.5%), and were interested in further education around LGBT health issues (84.5%). Conclusion: Anti-LGBT discrimination and heterosexism are noted by medical students, indicating a suboptimal learning environment for LGBT students. Nonetheless, students report a high level of comfort and confidence providing health care to LGBT patients. PMID:28853327

Medical students' perception of lesbian, gay, bisexual, and transgender (LGBT) discrimination in their learning environment and their self-reported comfort level for caring for LGBT patients: a survey study.

Science.gov (United States)

Nama, Nassr; MacPherson, Paul; Sampson, Margaret; McMillan, Hugh J

2017-01-01

Historically, medical students who are lesbian, gay, bisexual or transgendered (LGBT) report higher rates of social stress, depression, and anxiety, while LGBT patients have reported discrimination and poorer access to healthcare. The objectives of this study were: (1) to assess if medical students have perceived discrimination in their learning environment and; (2) to determine self-reported comfort level for caring for LGBT patients. Medical students at the University of Ottawa (N = 671) were contacted via email and invited to complete a confidential web-based survey. Response rate was 15.4% (103/671). This included 66 cis-gender heterosexuals (64.1%) and 37 LGBT students (35.9%). Anti-LGBT discrimination had been witnessed by 14.6% and heterosexism by 31.1% of respondents. Anti-LGBT discrimination most often originated from fellow medical students. Respondents who self-identified as LGBT were more likely to have perceived heterosexism (favoring opposite-sex relationships) (OR = 8.2, p LGBT discrimination (OR = 6.6, p = 0.002). While half of LGBT students shared their status with all classmates (51.4%), they were more likely to conceal this from staff physicians (OR = 27.2, p = 0.002). Almost half of medical students (41.7%) reported anti-LGBT jokes, rumors, and/or bullying by fellow medical students and/or other members of the healthcare team. Still, most respondents indicated that they felt comfortable with and capable of providing medical care to LGBT patients (≥83.5%), and were interested in further education around LGBT health issues (84.5%). Anti-LGBT discrimination and heterosexism are noted by medical students, indicating a suboptimal learning environment for LGBT students. Nonetheless, students report a high level of comfort and confidence providing health care to LGBT patients.

Infant discrimination of humanoid robots

Directory of Open Access Journals (Sweden)

Goh eMatsuda

2015-09-01

Full Text Available Recently, extremely humanlike robots called androids have been developed, some of which are already being used in the field of entertainment. In the context of psychological studies, androids are expected to be used in the future as fully controllable human stimuli to investigate human nature. In this study, we used an android to examine infant discrimination ability between human beings and non-human agents. Participants (N = 42 infants were assigned to three groups based on their age, i.e., 6- to 8-month-olds, 9- to 11-month-olds, and 12- to 14-month-olds, and took part in a preferential looking paradigm. Of three types of agents involved in the paradigm—a human, an android modeled on the human, and a mechanical-looking robot made from the android—two at a time were presented side-by-side as they performed a grasping action. Infants’ looking behavior was measured using an eye tracking system, and the amount of time spent focusing on each of three areas of interest (face, goal, and body was analyzed. Results showed that all age groups predominantly looked at the robot and at the face area, and that infants aged over 9 months watched the goal area for longer than the body area. There was no difference in looking times and areas focused on between the human and the android. These findings suggest that 6- to 14-month-olds are unable to discriminate between the human and the android, although they can distinguish the mechanical robot from the human.

"Human Immunodeficiency Virus serostatus disclosure-Rate, reactions, and discrimination": a cross-sectional study at a rural tertiary care hospital.

Science.gov (United States)

Joge, Umesh S; Deo, Deepali S; Choudhari, Sonali G; Malkar, Vilas R; Ughade, Harshada M

2013-01-01

From the moment scientists identified Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS), social responses of fear, denial, stigma, and discrimination have accompanied the epidemic. To assess the rate of disclosure of HIV serostatus, reactions by the HIV/AIDS patients and their spouse, and discrimination faced by the patients. The present cross-sectional study was conducted at Antiretroviral Therapy (ART) center of a rural tertiary care hospital, situated in Marathawada region of Maharashtra state from November 2008 to October 2010. Totally, 801 HIV-positive patients coming to ART center for treatment were included after ensuring confidentiality and taking informed consent. A preformed questionnaire was used to enquire about reaction after diagnosis, disclosure, and discrimination faced by the patients. The data analyzed using descriptive statistics and Chi-square test. The most common immediate reaction by the HIV patients after getting diagnosed as seropositive was fear (593, 74.03%) followed by depression (385, 48.06%) and suicidal thoughts (98, 12.25%). Out of 801 patients, 769 (96%) had spouse and of these maximum number of patients (653, 84.92%) had disclosed HIV status to their spouses. Most common immediate reaction by spouse after disclosure was crime (324, 42.13%) followed by horror (294, 38.23%) and anger (237, 36.29%). Maximum number of patients were discriminated by friends (120, 71.01%) followed by discrimination at workplace (49, 67.12%), by neighbors (32, 56.14%), and by relatives (53, 43.80%). Male positives were granted greater acceptance, care, and support by their spouses. More percentage of females discriminated by neighbors, relatives, and friends and at workplace which might be due to factors like customs, morals, and taboos.

Early postnatal x-irradiation of the hippocampus and discrimination learning in adult rats

International Nuclear Information System (INIS)

Gazzara, R.A.; Altman, J.

1981-01-01

Rats with X-irradiation-produced degranulation of the hippocampal dentate gyrus were trained in the acquisition and reversal of simultaneous visual and tactile discriminations in a T-maze. These experiments employed the same treatment, apparatus, and procedure but varied in task difficulty. In the brightness and roughness discriminations, the irradiated rats were not handicapped in acquiring or reversing discriminations of low or low-moderate task difficulty. However, these rats were handicapped in acquiring and reversing discriminations of moderate and high task difficulty. In a Black/White discrimination, in which the stimuli were restricted to the goal-arm walls, the irradiated rats were handicapped in the acquisition (low task difficulty) and reversal (moderate task difficulty) phases of the task. These results suggest that the irradiated rats were not handicapped when the noticeability of the stimuli was high, irrespective of modality used, but were handicapped when the noticeability of the stimuli was low. In addition, these results are consistent with the hypothesis that rats with hippocampal damage are inattentive due to hyperactivity

A Human Capabilities Framework for Evaluating Student Learning

Science.gov (United States)

Walker, Melanie

2008-01-01

This paper proposes a human capabilities approach for evaluating student learning and the social and pedagogical arrangements that support equality in capabilities for all students. It outlines the focus on valuable beings and doings in the capability approach developed by Amartya Sen, and Martha Nussbaum's capabilities focus on human flourishing.…

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.

Man's other best friend: domestic cats (F. silvestris catus) and their discrimination of human emotion cues.

Science.gov (United States)

Galvan, Moriah; Vonk, Jennifer

2016-01-01

The ability of domestic dogs (C. lupus famaliaris) to follow and attend to human emotion expressions is well documented. It is unknown whether domestic cats (F. silvestris catus) possess similar abilities. Because cats belong to the same order (Carnivora), but did not evolve to live in complex social groups, research with them enables us to tease apart the influence of social structure versus domestication processes on the capacity to recognize human communicative cues, such as emotions. Two experiments were conducted to determine the extent to which domestic cats discriminate between human emotion cues. The first experiment presented cats with facial and postural cues of happiness and anger from both an unfamiliar experimenter and their familiar owner in the absence of vocal cues. The second experiment presented cats with vocal cues of human emotion through a positively or negatively charged conversation between an experimenter and owner. Domestic cats were only modestly sensitive to emotion, particularly when displayed by their owner, suggesting that a history of human interaction alone may not be sufficient to shape such abilities in domestic cats.

Gender Discrimination and Growth: Theory and Evidence from India

OpenAIRE

Berta Esteve-Volart

2004-01-01

Gender inequality is an acute and persistent problem, especially in developing countries. This paper argues that gender discrimination is an inefficient practice. We model gender discrimination as the complete exclusion of females from the labor market or as the exclusion of females from managerial positions. The distortions in the allocation of talent between managerial and unskilled positions, and in human capital investment, are analyzed. It is found that both types of discrimination lower...

Debriefing after Human Patient Simulation and Nursing Students' Learning

Science.gov (United States)

Benhuri, Gloria

2014-01-01

Human Patient Simulation (HPS) exercises with life-like computerized manikins provide clinical experiences for nursing students in a safe environment followed by debriefing that promotes learning. Quantitative research in techniques to support learning from debriefing is limited. The purpose of the quantitative quasi-experimental study using a…

Data mining for isotope discrimination in atom probe tomography

Energy Technology Data Exchange (ETDEWEB)

Broderick, Scott R. [Department of Materials Science and Engineering and Institute for Combinatorial Discovery, Iowa State University, Ames, IA 50011-2230 (United States); Bryden, Aaron [Ames National Laboratory, Ames, IA 50011-2230 (United States); Suram, Santosh K. [Department of Materials Science and Engineering and Institute for Combinatorial Discovery, Iowa State University, Ames, IA 50011-2230 (United States); Rajan, Krishna, E-mail: krajan@iastate.edu [Department of Materials Science and Engineering and Institute for Combinatorial Discovery, Iowa State University, Ames, IA 50011-2230 (United States)

2013-09-15

Ions with similar time-of-flights (TOF) can be discriminated by mapping their kinetic energy. While current generation position-sensitive detectors have been considered insufficient for capturing the isotope kinetic energy, we demonstrate in this paper that statistical learning methodologies can be used to capture the kinetic energy from all of the parameters currently measured by mathematically transforming the signal. This approach works because the kinetic energy is sufficiently described by the descriptors on the potential, the material, and the evaporation process within atom probe tomography (APT). We discriminate the isotopes for Mg and Al by capturing the kinetic energy, and then decompose the TOF spectrum into its isotope components and identify the isotope for each individual atom measured. This work demonstrates the value of advanced data mining methods to help enhance the information resolution of the atom probe. - Highlights: ► Atom probe tomography and statistical learning were combined for data enhancement. ► Multiple eigenvalue decompositions decomposed a spectrum with overlapping peaks. ► The isotope of each atom was determined by kinetic energy discrimination. ► Eigenspectra were identified and new chemical information was identified.

Utilizing Service Learning in a College-Level Human Sexuality Course

Science.gov (United States)

Jenkins, Dusty D.

2017-01-01

Implementing service learning into college courses has been shown to have positive benefits for both students and community members; however, service learning has not been largely evaluated in the literature on human sexuality courses. Thus, the purpose of the current study was to design, implement, and evaluate a service learning project in a…

Theorising Learning and Nature: Post-Human Possibilities and Problems

Science.gov (United States)

Quinn, Jocey

2013-01-01

In their predominantly theoretical turn to the material, post-humanist feminists often focus on "nature", arguing that the nature/culture binary has collapsed and that fixed distinctions between human and non-human spheres no longer hold. Conversely, outdoor learning sees nature as a space where humans act and has been more concerned…

Social learning in humans and other animals.

Directory of Open Access Journals (Sweden)

Jean-François eGariépy

2014-03-01

Full Text Available Decisions made by individuals can be influenced by what others think and do. Social learning includes a wide array of behaviors such as imitation, observational learning of novel foraging techniques, peer or parental influences on individual preferences, as well as outright teaching. These processes are believed to underlie an important part of cultural variation among human populations and may also explain intraspecific variation in behavior between geographically distinct populations of animals. Recent neurobiological studies have begun to uncover the neural basis of social learning. Here we review experimental evidence from the past few decades showing that social learning is a widespread set of skills present in multiple animal species. In mammals, the temporoparietal junction, the dorsomedial and dorsolateral prefrontal cortex, as well as the anterior cingulate gyrus, appear to play critical roles in social learning. Birds, fish and insects also learn from others, but the underlying neural mechanisms remain poorly understood. We discuss the evolutionary implications of these findings and highlight the importance of emerging animal models that permit precise modification of neural circuit function for elucidating the neural basis of social learning.

Discrimination performance in aging is vulnerable to interference and dissociable from spatial memory

Science.gov (United States)

Johnson, Sarah A.; Sacks, Patricia K.; Turner, Sean M.; Gaynor, Leslie S.; Ormerod, Brandi K.; Maurer, Andrew P.; Bizon, Jennifer L.

2016-01-01

Hippocampal-dependent episodic memory and stimulus discrimination abilities are both compromised in the elderly. The reduced capacity to discriminate between similar stimuli likely contributes to multiple aspects of age-related cognitive impairment; however, the association of these behaviors within individuals has never been examined in an animal model. In the present study, young and aged F344×BN F1 hybrid rats were cross-characterized on the Morris water maze test of spatial memory and a dentate gyrus-dependent match-to-position test of spatial discrimination ability. Aged rats showed overall impairments relative to young in spatial learning and memory on the water maze task. Although young and aged learned to apply a match-to-position response strategy in performing easy spatial discriminations within a similar number of trials, a majority of aged rats were impaired relative to young in performing difficult spatial discriminations on subsequent tests. Moreover, all aged rats were susceptible to cumulative interference during spatial discrimination tests, such that error rate increased on later trials of test sessions. These data suggest that when faced with difficult discriminations, the aged rats were less able to distinguish current goal locations from those of previous trials. Increasing acetylcholine levels with donepezil did not improve aged rats’ abilities to accurately perform difficult spatial discriminations or reduce their susceptibility to interference. Interestingly, better spatial memory abilities were not significantly associated with higher performance on difficult spatial discriminations. This observation, along with the finding that aged rats made more errors under conditions in which interference was high, suggests that match-to-position spatial discrimination performance may rely on extra-hippocampal structures such as the prefrontal cortex, in addition to the dentate gyrus. PMID:27317194

Object recognition with hierarchical discriminant saliency networks.

Science.gov (United States)

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

Human resource management and learning for innovation: pharmaceuticals in Mexico

OpenAIRE

Santiago-Rodriguez, Fernando

2010-01-01

This paper investigates the influence of human resource management on learning from internal and external sources of knowledge. Learning for innovation is a key ingredient of catching-up processes. The analysis builds on survey data about pharmaceutical firms in Mexico. Results show that the influence of human resource management is contingent on the knowledge flows and innovation goals pursued by the firm. Practices such as training-- particularly from external partners; and remuneration for...

Do allopatric male Calopteryx virgo damselflies learn species recognition?

Science.gov (United States)

Kuitunen, Katja; Haukilehto, Elina; Raatikainen, Kaisa J; Hakkarainen, Hanne; Miettinen, Minna; Högmander, Harri; Kotiaho, Janne S

2012-03-01

There is a growing amount of empirical evidence that premating reproductive isolation of two closely related species can be reinforced by natural selection arising from avoidance of maladaptive hybridization. However, as an alternative for this popular reinforcement theory, it has been suggested that learning to prefer conspecifics or to discriminate heterospecifics could cause a similar pattern of reinforced premating isolation, but this possibility is much less studied. Here, we report results of a field experiment in which we examined (i) whether allopatric Calopteryx virgo damselfly males that have not encountered heterospecific females of the congener C. splendens initially show discrimination, and (ii) whether C. virgo males learn to discriminate heterospecifics or learn to associate with conspecifics during repeated experimental presentation of females. Our experiment revealed that there was a statistically nonsignificant tendency for C. virgo males to show initial discrimination against heterospecific females but because we did not use sexually naïve individuals in our experiment, we were not able to separate the effect of innate or associative learning. More importantly, however, our study revealed that species discrimination might be further strengthened by learning, especially so that C. virgo males increase their association with conspecific females during repeated presentation trials. The role of learning to discriminate C. splendens females was less clear. We conclude that learning might play a role in species recognition also when individuals are not naïve but have already encountered potential conspecific mates.

The effects of acute nicotine on contextual safety discrimination.

Science.gov (United States)

Kutlu, Munir G; Oliver, Chicora; Gould, Thomas J

2014-11-01

Anxiety disorders, such as post-traumatic stress disorder (PTSD), may be related to an inability to distinguish safe versus threatening environments and to extinguish fear memories. Given the high rate of cigarette smoking in patients with PTSD, as well as the recent finding that an acute dose of nicotine impairs extinction of contextual fear memory, we conducted a series of experiments to investigate the effect of acute nicotine in an animal model of contextual safety discrimination. Following saline or nicotine (at 0.0275, 0.045, 0.09 and 0.18 mg/kg) administration, C57BL/6J mice were trained in a contextual discrimination paradigm, in which the subjects received presentations of conditioned stimuli (CS) that co-terminated with a foot-shock in one context (context A (CXA)) and only CS presentations without foot-shock in a different context (context B (CXB)). Therefore, CXA was designated as the 'dangerous context', whereas CXB was designated as the 'safe context'. Our results suggested that saline-treated animals showed a strong discrimination between dangerous and safe contexts, while acute nicotine dose-dependently impaired contextual safety discrimination (Experiment 1). Furthermore, our results demonstrate that nicotine-induced impairment of contextual safety discrimination learning was not a result of increased generalized freezing (Experiment 2) or contingent on the common CS presentations in both contexts (Experiment 3). Finally, our results show that increasing the temporal gap between CXA and CXB during training abolished the impairing effects of nicotine (Experiment 4). The findings of this study may help link nicotine exposure to the safety learning deficits seen in anxiety disorder and PTSD patients. © The Author(s) 2014.

Examination of the Safety of Pediatric Vaccine Schedules in a Non-Human Primate Model: Assessments of Neurodevelopment, Learning, and Social Behavior

Science.gov (United States)

Curtis, Britni; Liberato, Noelle; Rulien, Megan; Morrisroe, Kelly; Kenney, Caroline; Yutuc, Vernon; Ferrier, Clayton; Marti, C. Nathan; Mandell, Dorothy; Burbacher, Thomas M.; Sackett, Gene P.

2015-01-01

Background In the 1990s, the mercury-based preservative thimerosal was used in most pediatric vaccines. Although there are currently only two thimerosal-containing vaccines (TCVs) recommended for pediatric use, parental perceptions that vaccines pose safety concerns are affecting vaccination rates, particularly in light of the much expanded and more complex schedule in place today. Objectives The objective of this study was to examine the safety of pediatric vaccine schedules in a non-human primate model. Methods We administered vaccines to six groups of infant male rhesus macaques (n = 12–16/group) using a standardized thimerosal dose where appropriate. Study groups included the recommended 1990s Pediatric vaccine schedule, an accelerated 1990s Primate schedule with or without the measles–mumps–rubella (MMR) vaccine, the MMR vaccine only, and the expanded 2008 schedule. We administered saline injections to age-matched control animals (n = 16). Infant development was assessed from birth to 12 months of age by examining the acquisition of neonatal reflexes, the development of object concept permanence (OCP), computerized tests of discrimination learning, and infant social behavior. Data were analyzed using analysis of variance, multilevel modeling, and survival analyses, where appropriate. Results We observed no group differences in the acquisition of OCP. During discrimination learning, animals receiving TCVs had improved performance on reversal testing, although some of these same animals showed poorer performance in subsequent learning-set testing. Analysis of social and nonsocial behaviors identified few instances of negative behaviors across the entire infancy period. Although some group differences in specific behaviors were reported at 2 months of age, by 12 months all infants, irrespective of vaccination status, had developed the typical repertoire of macaque behaviors. Conclusions This comprehensive 5-year case–control study, which closely examined

Beyond human capital explanations for the gender pay gap among executives: investigating board embeddedness effects on discrimination

OpenAIRE

Oehmichen, Jana; Sarry, Maximilian A.; Wolff, Michael

2014-01-01

This paper examines the gender pay gap in top management teams and how it is affected by directors’ embeddedness. We can reconfirm the result of previous studies that differences in managerial compensation between women and men exist, even after controlling for company properties and human capital attributes. Drawing on the language theory of discrimination, we then question how the embeddedness of directors—the actual deciders on executive compensation levels— affects the p...

Cortical activity patterns predict robust speech discrimination ability in noise

Science.gov (United States)

Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

2012-01-01

The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

"Human immunodeficiency virus serostatus disclosure-Rate, reactions, and discrimination": A cross-sectional study at a rural tertiary care hospital

Directory of Open Access Journals (Sweden)

Umesh S Joge

2013-01-01

Full Text Available Background: From the moment scientists identified Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome (HIV/AIDS, social responses of fear, denial, stigma, and discrimination have accompanied the epidemic. Aims: To assess the rate of disclosure of HIV serostatus, reactions by the HIV/AIDS patients and their spouse, and discrimination faced by the patients. Methods: The present cross-sectional study was conducted at Antiretroviral Therapy (ART center of a rural tertiary care hospital, situated in Marathawada region of Maharashtra state from November 2008 to October 2010. Totally, 801 HIV-positive patients coming to ART center for treatment were included after ensuring confidentiality and taking informed consent. A preformed questionnaire was used to enquire about reaction after diagnosis, disclosure, and discrimination faced by the patients. The data analyzed using descriptive statistics and Chi-square test. Results: The most common immediate reaction by the HIV patients after getting diagnosed as seropositive was fear (593, 74.03% followed by depression (385, 48.06% and suicidal thoughts (98, 12.25%. Out of 801 patients, 769 (96% had spouse and of these maximum number of patients (653, 84.92% had disclosed HIV status to their spouses. Most common immediate reaction by spouse after disclosure was crime (324, 42.13% followed by horror (294, 38.23% and anger (237, 36.29%. Maximum number of patients were discriminated by friends (120, 71.01% followed by discrimination at workplace (49, 67.12%, by neighbors (32, 56.14%, and by relatives (53, 43.80%. Conclusion: Male positives were granted greater acceptance, care, and support by their spouses. More percentage of females discriminated by neighbors, relatives, and friends and at workplace which might be due to factors like customs, morals, and taboos.

Discrimination and Anti-discrimination in Denmark

DEFF Research Database (Denmark)

Olsen, Tore Vincents

The purpose of this report is to describe and analyse Danish anti-discrimination legislation and the debate about discrimination in Denmark in order to identify present and future legal challenges. The main focus is the implementation of the EU anti-discrimination directives in Danish law...

Separate and combined effects of the cannabinoid agonists nabilone and Δ⁹-THC in humans discriminating Δ⁹-THC.

Science.gov (United States)

Lile, Joshua A; Kelly, Thomas H; Hays, Lon R

2011-07-01

Agonist replacement treatment is a promising strategy to manage cannabis-use disorders. The aim of this study was to assess the combined effects of the synthetic cannabinoid agonist nabilone and Δ⁹-tetrahydrocannabinol (Δ⁹-THC) using drug-discrimination procedures, which are sensitive to drug interactions. Testing the concurrent administration of nabilone and Δ⁹-THC was also conducted to provide initial safety and tolerability data, which is important because cannabis users will likely lapse during treatment. Six cannabis users learned to discriminate 30 mg oral Δ⁹-THC from placebo and then received nabilone (0, 1 and 3mg) and Δ⁹-THC (0, 5, 15 and 30 mg), alone and in combination. Subjects completed the multiple-choice procedure to assess drug reinforcement, and self-report, task performance and physiological measures were collected. Δ⁹-THC and nabilone alone shared discriminative-stimulus effects with the training dose of Δ⁹-THC, increased crossover point on the multiple-choice procedure, produced overlapping subject ratings and decreased skin temperature. Nabilone alone also elevated heart rate. In combination, nabilone shifted the discriminative-stimulus effects of Δ⁹-THC leftward/upward and enhanced Δ⁹-THC effects on the other outcome measures. These results replicate a previous study demonstrating that nabilone shares agonist effects with the active constituent of cannabis in cannabis users, and contribute further by indicating that nabilone would likely be safe and well tolerated when combined with cannabis. These data support the conduct of future studies to determine if nabilone treatment would produce cross-tolerance to the abuse-related effects of cannabis and reduce cannabis use. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Gender Discrimination, Education and Economic Growth in a Generalized Uzawa-Lucas Two-Sector Model

OpenAIRE

Zhang Wei-Bin

2014-01-01

This paper is mainly concerned with relationships between economic growth and gender discrimination in labor markets and education. Although discrimination in different fields has well been addresses and modelled in the economic literature, there are only a few growth models with endogenous wealth and human capital accumulation, gender time distribution between work, leisure and education under gender (positive or negative) discrimination. The production and economic structures, human capital...

Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Jinhee Park

2016-11-01

Full Text Available Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on water using radar has not been extensively studied, unlike the case on dry ground, due to its unique challenge. Namely, not only is the radar cross section of a human on water small, but the micro-Doppler signatures are much noisier due to water drops and waves. In this paper, we first investigate whether discriminative signatures could be obtained for activities on water through a simulation study. Then, we show how we can effectively achieve high classification accuracy by applying deep convolutional neural networks (DCNN directly to the spectrogram of real measurement data. From the five-fold cross-validation on our dataset, which consists of five aquatic activities, we report that the conventional feature-based scheme only achieves an accuracy of 45.1%. In contrast, the DCNN trained using only the collected data attains 66.7%, and the transfer learned DCNN, which takes a DCNN pre-trained on a RGB image dataset and fine-tunes the parameters using the collected data, achieves a much higher 80.3%, which is a significant performance boost.

Context effects in a temporal discrimination task" further tests of the Scalar Expectancy Theory and Learning-to-Time models.

Science.gov (United States)

Arantes, Joana; Machado, Armando

2008-07-01

Pigeons were trained on two temporal bisection tasks, which alternated every two sessions. In the first task, they learned to choose a red key after a 1-s signal and a green key after a 4-s signal; in the second task, they learned to choose a blue key after a 4-s signal and a yellow key after a 16-s signal. Then the pigeons were exposed to a series of test trials in order to contrast two timing models, Learning-to-Time (LeT) and Scalar Expectancy Theory (SET). The models made substantially different predictions particularly for the test trials in which the sample duration ranged from 1 s to 16 s and the choice keys were Green and Blue, the keys associated with the same 4-s samples: LeT predicted that preference for Green should increase with sample duration, a context effect, but SET predicted that preference for Green should not vary with sample duration. The results were consistent with LeT. The present study adds to the literature the finding that the context effect occurs even when the two basic discriminations are never combined in the same session.

Weakly Supervised Dictionary Learning

Science.gov (United States)

You, Zeyu; Raich, Raviv; Fern, Xiaoli Z.; Kim, Jinsub

2018-05-01

We present a probabilistic modeling and inference framework for discriminative analysis dictionary learning under a weak supervision setting. Dictionary learning approaches have been widely used for tasks such as low-level signal denoising and restoration as well as high-level classification tasks, which can be applied to audio and image analysis. Synthesis dictionary learning aims at jointly learning a dictionary and corresponding sparse coefficients to provide accurate data representation. This approach is useful for denoising and signal restoration, but may lead to sub-optimal classification performance. By contrast, analysis dictionary learning provides a transform that maps data to a sparse discriminative representation suitable for classification. We consider the problem of analysis dictionary learning for time-series data under a weak supervision setting in which signals are assigned with a global label instead of an instantaneous label signal. We propose a discriminative probabilistic model that incorporates both label information and sparsity constraints on the underlying latent instantaneous label signal using cardinality control. We present the expectation maximization (EM) procedure for maximum likelihood estimation (MLE) of the proposed model. To facilitate a computationally efficient E-step, we propose both a chain and a novel tree graph reformulation of the graphical model. The performance of the proposed model is demonstrated on both synthetic and real-world data.

Sex differences in the acoustic structure of vowel-like grunt vocalizations in baboons and their perceptual discrimination by baboon listeners

Science.gov (United States)

Rendall, Drew; Owren, Michael J.; Weerts, Elise; Hienz, Robert D.

2004-01-01

This study quantifies sex differences in the acoustic structure of vowel-like grunt vocalizations in baboons (Papio spp.) and tests the basic perceptual discriminability of these differences to baboon listeners. Acoustic analyses were performed on 1028 grunts recorded from 27 adult baboons (11 males and 16 females) in southern Africa, focusing specifically on the fundamental frequency (F0) and formant frequencies. The mean F0 and the mean frequencies of the first three formants were all significantly lower in males than they were in females, more dramatically so for F0. Experiments using standard psychophysical procedures subsequently tested the discriminability of adult male and adult female grunts. After learning to discriminate the grunt of one male from that of one female, five baboon subjects subsequently generalized this discrimination both to new call tokens from the same individuals and to grunts from novel males and females. These results are discussed in the context of both the possible vocal anatomical basis for sex differences in call structure and the potential perceptual mechanisms involved in their processing by listeners, particularly as these relate to analogous issues in human speech production and perception.

Gender discrimination and nursing: α literature review.

Science.gov (United States)

Kouta, Christiana; Kaite, Charis P

2011-01-01

This article aims to examine gender stereotypes in relation to men in nursing, discuss gender discrimination cases in nursing, and explore methods used for promoting equal educational opportunities during nursing studies. The literature review was based on related databases, such as CINAHL, Science Direct, MEDLINE, and EBSCO. Legal case studies are included in order to provide a more practical example of those barriers existing for men pursuing nursing, as well as statistical data concerning gender discrimination and male attrition to nursing schools in relation to those barriers. These strengthen the validity of the manuscript. Literature review showed that gender discrimination is still prevalent within nursing profession. Nursing faculty should prepare male nursing students to interact effectively with female clients as well. Role modeling the therapeutic relationship with clients is one strategy that may help male students. In general, the faculty should provide equal learning opportunities to nursing students. Copyright © 2011 Elsevier Inc. All rights reserved.

Fast learning of simple perceptual discriminations reduces brain activation in working memory and in high-level auditory regions.

Science.gov (United States)

Daikhin, Luba; Ahissar, Merav

2015-07-01

Introducing simple stimulus regularities facilitates learning of both simple and complex tasks. This facilitation may reflect an implicit change in the strategies used to solve the task when successful predictions regarding incoming stimuli can be formed. We studied the modifications in brain activity associated with fast perceptual learning based on regularity detection. We administered a two-tone frequency discrimination task and measured brain activation (fMRI) under two conditions: with and without a repeated reference tone. Although participants could not explicitly tell the difference between these two conditions, the introduced regularity affected both performance and the pattern of brain activation. The "No-Reference" condition induced a larger activation in frontoparietal areas known to be part of the working memory network. However, only the condition with a reference showed fast learning, which was accompanied by a reduction of activity in two regions: the left intraparietal area, involved in stimulus retention, and the posterior superior-temporal area, involved in representing auditory regularities. We propose that this joint reduction reflects a reduction in the need for online storage of the compared tones. We further suggest that this change reflects an implicit strategic shift "backwards" from reliance mainly on working memory networks in the "No-Reference" condition to increased reliance on detected regularities stored in high-level auditory networks.

Movement-related theta rhythm in humans: coordinating self-directed hippocampal learning.

Directory of Open Access Journals (Sweden)

Raphael Kaplan

Full Text Available The hippocampus is crucial for episodic or declarative memory and the theta rhythm has been implicated in mnemonic processing, but the functional contribution of theta to memory remains the subject of intense speculation. Recent evidence suggests that the hippocampus might function as a network hub for volitional learning. In contrast to human experiments, electrophysiological recordings in the hippocampus of behaving rodents are dominated by theta oscillations reflecting volitional movement, which has been linked to spatial exploration and encoding. This literature makes the surprising cross-species prediction that the human hippocampal theta rhythm supports memory by coordinating exploratory movements in the service of self-directed learning. We examined the links between theta, spatial exploration, and memory encoding by designing an interactive human spatial navigation paradigm combined with multimodal neuroimaging. We used both non-invasive whole-head Magnetoencephalography (MEG to look at theta oscillations and Functional Magnetic Resonance Imaging (fMRI to look at brain regions associated with volitional movement and learning. We found that theta power increases during the self-initiation of virtual movement, additionally correlating with subsequent memory performance and environmental familiarity. Performance-related hippocampal theta increases were observed during a static pre-navigation retrieval phase, where planning for subsequent navigation occurred. Furthermore, periods of the task showing movement-related theta increases showed decreased fMRI activity in the parahippocampus and increased activity in the hippocampus and other brain regions that strikingly overlap with the previously observed volitional learning network (the reverse pattern was seen for stationary periods. These fMRI changes also correlated with participant's performance. Our findings suggest that the human hippocampal theta rhythm supports memory by coordinating

Global classification of human facial healthy skin using PLS discriminant analysis and clustering analysis.

Science.gov (United States)

Guinot, C; Latreille, J; Tenenhaus, M; Malvy, D J

2001-04-01

Today's classifications of healthy skin are predominantly based on a very limited number of skin characteristics, such as skin oiliness or susceptibility to sun exposure. The aim of the present analysis was to set up a global classification of healthy facial skin, using mathematical models. This classification is based on clinical, biophysical skin characteristics and self-reported information related to the skin, as well as the results of a theoretical skin classification assessed separately for the frontal and the malar zones of the face. In order to maximize the predictive power of the models with a minimum of variables, the Partial Least Square (PLS) discriminant analysis method was used. The resulting PLS components were subjected to clustering analyses to identify the plausible number of clusters and to group the individuals according to their proximities. Using this approach, four PLS components could be constructed and six clusters were found relevant. So, from the 36 hypothetical combinations of the theoretical skin types classification, we tended to a strengthened six classes proposal. Our data suggest that the association of the PLS discriminant analysis and the clustering methods leads to a valid and simple way to classify healthy human skin and represents a potentially useful tool for cosmetic and dermatological research.

A Weighted Block Dictionary Learning Algorithm for Classification

OpenAIRE

Shi, Zhongrong

2016-01-01

Discriminative dictionary learning, playing a critical role in sparse representation based classification, has led to state-of-the-art classification results. Among the existing discriminative dictionary learning methods, two different approaches, shared dictionary and class-specific dictionary, which associate each dictionary atom to all classes or a single class, have been studied. The shared dictionary is a compact method but with lack of discriminative information; the class-specific dict...

Sequential causal learning in humans and rats

NARCIS (Netherlands)

Lu, H.; Rojas, R.R.; Beckers, T.; Yuille, A.; Love, B.C.; McRae, K.; Sloutsky, V.M.

2008-01-01

Recent experiments (Beckers, De Houwer, Pineño, & Miller, 2005;Beckers, Miller, De Houwer, & Urushihara, 2006) have shown that pretraining with unrelated cues can dramatically influence the performance of humans in a causal learning paradigm and rats in a standard Pavlovian conditioning paradigm.

Testing declarative memory in laboratory rats and mice using the nonconditioned social discrimination procedure.

Science.gov (United States)

Engelmann, Mario; Hädicke, Jana; Noack, Julia

2011-07-14

Testing declarative memory in laboratory rodents can provide insights into the fundamental mechanisms underlying this type of learning and memory processing, and these insights are likely to be applicable to humans. Here we provide a detailed description of the social discrimination procedure used to investigate recognition memory in rats and mice, as established during the last 20 years in our laboratory. The test is based on the use of olfactory signals for social communication in rodents; this involves a direct encounter between conspecifics, during which the investigatory behavior of the experimental subject serves as an index for learning and memory performance. The procedure is inexpensive, fast and very reliable, but it requires well-trained human observers. We include recent modifications to the procedure that allow memory extinction to be investigated by retroactive and proactive interference, and that enable the dissociated analysis of the central nervous processing of the volatile fraction of an individual's olfactory signature. Depending on the memory retention interval under study (short-term memory, intermediate-term memory, long-term memory or long-lasting memory), the protocol takes ~10 min or up to several days to complete.

Enhanced odor discrimination and impaired olfactory memory by spatially controlled switch of AMPA receptors.

Science.gov (United States)

Shimshek, Derya R; Bus, Thorsten; Kim, Jinhyun; Mihaljevic, Andre; Mack, Volker; Seeburg, Peter H; Sprengel, Rolf; Schaefer, Andreas T

2005-11-01

Genetic perturbations of alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionate receptors (AMPARs) are widely used to dissect molecular mechanisms of sensory coding, learning, and memory. In this study, we investigated the role of Ca2+-permeable AMPARs in olfactory behavior. AMPAR modification was obtained by depletion of the GluR-B subunit or expression of unedited GluR-B(Q), both leading to increased Ca2+ permeability of AMPARs. Mice with this functional AMPAR switch, specifically in forebrain, showed enhanced olfactory discrimination and more rapid learning in a go/no-go operant conditioning task. Olfactory memory, however, was dramatically impaired. GluR-B depletion in forebrain was ectopically variable ("mosaic") among individuals and strongly correlated with decreased olfactory memory in hippocampus and cortex. Accordingly, memory was rescued by transgenic GluR-B expression restricted to piriform cortex and hippocampus, while enhanced odor discrimination was independent of both GluR-B variability and transgenic GluR-B expression. Thus, correlated differences in behavior and levels of GluR-B expression allowed a mechanistic and spatial dissection of olfactory learning, discrimination, and memory capabilities.

Casual Games and Casual Learning About Human Biological Systems

Science.gov (United States)

Price, C. Aaron; Gean, Katherine; Christensen, Claire G.; Beheshti, Elham; Pernot, Bryn; Segovia, Gloria; Person, Halcyon; Beasley, Steven; Ward, Patricia

2016-02-01

Casual games are everywhere. People play them throughout life to pass the time, to engage in social interactions, and to learn. However, their simplicity and use in distraction-heavy environments can attenuate their potential for learning. This experimental study explored the effects playing an online, casual game has on awareness of human biological systems. Two hundred and forty-two children were given pretests at a Museum and posttests at home after playing either a treatment or control game. Also, 41 children were interviewed to explore deeper meanings behind the test results. Results show modest improvement in scientific attitudes, ability to identify human biological systems and in the children's ability to describe how those systems work together in real-world scenarios. Interviews reveal that children drew upon their prior school learning as they played the game. Also, on the surface they perceived the game as mainly entertainment but were easily able to discern learning outcomes when prompted. Implications for the design of casual games and how they can be used to enhance transfer of knowledge from the classroom to everyday life are discussed.

Genetic dissection of behavioral flexibility: reversal learning in mice.

Science.gov (United States)

Laughlin, Rick E; Grant, Tara L; Williams, Robert W; Jentsch, J David

2011-06-01

Behavioral inflexibility is a feature of schizophrenia, attention-deficit/hyperactivity disorder, and behavior addictions that likely results from heritable deficits in the inhibitory control over behavior. Here, we investigate the genetic basis of individual differences in flexibility, measured using an operant reversal learning task. We quantified discrimination acquisition and subsequent reversal learning in a cohort of 51 BXD strains of mice (2-5 mice/strain, n = 176) for which we have matched data on sequence, gene expression in key central nervous system regions, and neuroreceptor levels. Strain variation in trials to criterion on acquisition and reversal was high, with moderate heritability (∼.3). Acquisition and reversal learning phenotypes did not covary at the strain level, suggesting that these traits are effectively under independent genetic control. Reversal performance did covary with dopamine D2 receptor levels in the ventral midbrain, consistent with a similar observed relationship between impulsivity and D2 receptors in humans. Reversal, but not acquisition, is linked to a locus on mouse chromosome 10 with a peak likelihood ratio statistic at 86.2 megabase (p work demonstrates the clear trait independence between, and genetic control of, discrimination acquisition and reversal and illustrates how globally coherent data sets for a single panel of highly related strains can be interrogated and integrated to uncover genetic sources and molecular and neuropharmacological candidates of complex behavioral traits relevant to human psychopathology. Copyright © 2011 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Teaching medical humanities in the digital world: affordances of technology-enhanced learning.

Science.gov (United States)

Kemp, Sandra Joy; Day, Giskin

2014-12-01

Medical humanities courses are typically taught in face-to-face teaching environments, but now medical humanities educators, alongside educators from other disciplines, are facing shifts in higher education towards online (and sometimes open) courses. For the medical humanities educator, there is limited guidance regarding how technology-enhanced learning design can support the learning outcomes associated with medical humanities. This article aims to provide useful direction for such educators on how digital technologies can be used through learner-focused pedagogies. Specific examples are provided as to how the affordances of Web 2.0 and other tools can be realised in innovative ways to help achieve skills development within the medical humanities. The guidance, alongside the practical suggestions for implementation, can provide important conceptual background for medical humanities educators who wish to embrace technology-enhanced learning, and reconceptualise or redesign medical humanities for an online or blended teaching environment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Social Fear Learning: from Animal Models to Human Function.

Science.gov (United States)

Debiec, Jacek; Olsson, Andreas

2017-07-01

Learning about potential threats is critical for survival. Learned fear responses are acquired either through direct experiences or indirectly through social transmission. Social fear learning (SFL), also known as vicarious fear learning, is a paradigm successfully used for studying the transmission of threat information between individuals. Animal and human studies have begun to elucidate the behavioral, neural and molecular mechanisms of SFL. Recent research suggests that social learning mechanisms underlie a wide range of adaptive and maladaptive phenomena, from supporting flexible avoidance in dynamic environments to intergenerational transmission of trauma and anxiety disorders. This review discusses recent advances in SFL studies and their implications for basic, social and clinical sciences. Copyright © 2017 Elsevier Ltd. All rights reserved.

Infants Discriminate Voicing and Place of Articulation with Reduced Spectral and Temporal Modulation Cues

Science.gov (United States)

Cabrera, Laurianne; Lorenzi, Christian; Bertoncini, Josiane

2015-01-01

Purpose: This study assessed the role of spectro-temporal modulation cues in the discrimination of 2 phonetic contrasts (voicing and place) for young infants. Method: A visual-habituation procedure was used to assess the ability of French-learning 6-month-old infants with normal hearing to discriminate voiced versus unvoiced (/aba/-/apa/) and…

Mixed-complexity artificial grammar learning in humans and macaque monkeys: evaluating learning strategies.

Science.gov (United States)

Wilson, Benjamin; Smith, Kenny; Petkov, Christopher I

2015-03-01

Artificial grammars (AG) can be used to generate rule-based sequences of stimuli. Some of these can be used to investigate sequence-processing computations in non-human animals that might be related to, but not unique to, human language. Previous AG learning studies in non-human animals have used different AGs to separately test for specific sequence-processing abilities. However, given that natural language and certain animal communication systems (in particular, song) have multiple levels of complexity, mixed-complexity AGs are needed to simultaneously evaluate sensitivity to the different features of the AG. Here, we tested humans and Rhesus macaques using a mixed-complexity auditory AG, containing both adjacent (local) and non-adjacent (longer-distance) relationships. Following exposure to exemplary sequences generated by the AG, humans and macaques were individually tested with sequences that were either consistent with the AG or violated specific adjacent or non-adjacent relationships. We observed a considerable level of cross-species correspondence in the sensitivity of both humans and macaques to the adjacent AG relationships and to the statistical properties of the sequences. We found no significant sensitivity to the non-adjacent AG relationships in the macaques. A subset of humans was sensitive to this non-adjacent relationship, revealing interesting between- and within-species differences in AG learning strategies. The results suggest that humans and macaques are largely comparably sensitive to the adjacent AG relationships and their statistical properties. However, in the presence of multiple cues to grammaticality, the non-adjacent relationships are less salient to the macaques and many of the humans. © 2015 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Discriminative clustering on manifold for adaptive transductive classification.

Science.gov (United States)

Zhang, Zhao; Jia, Lei; Zhang, Min; Li, Bing; Zhang, Li; Li, Fanzhang

2017-10-01

In this paper, we mainly propose a novel adaptive transductive label propagation approach by joint discriminative clustering on manifolds for representing and classifying high-dimensional data. Our framework seamlessly combines the unsupervised manifold learning, discriminative clustering and adaptive classification into a unified model. Also, our method incorporates the adaptive graph weight construction with label propagation. Specifically, our method is capable of propagating label information using adaptive weights over low-dimensional manifold features, which is different from most existing studies that usually predict the labels and construct the weights in the original Euclidean space. For transductive classification by our formulation, we first perform the joint discriminative K-means clustering and manifold learning to capture the low-dimensional nonlinear manifolds. Then, we construct the adaptive weights over the learnt manifold features, where the adaptive weights are calculated through performing the joint minimization of the reconstruction errors over features and soft labels so that the graph weights can be joint-optimal for data representation and classification. Using the adaptive weights, we can easily estimate the unknown labels of samples. After that, our method returns the updated weights for further updating the manifold features. Extensive simulations on image classification and segmentation show that our proposed algorithm can deliver the state-of-the-art performance on several public datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genetic Discrimination: A Legal Or Biological Issue?

OpenAIRE

Myssior, Bárbara Augusta de Paula Araujo; Silva, Luís Eduardo Gomes

2016-01-01

This essay debates the technological evolution that, from the decoding of the human genome has opened up many scientific benefits, and yet brings up a new kind of segregation: genetic discrimination. Based on the right to privacy, as well as the concept of genetic identity, as well as data protection and information, worked up the genetic discrimination. Therefore, documentary research and critical analysis of scientific papers were taken, using up of the inductive reasoning method. As a resu...

Suboptimal Criterion Learning in Static and Dynamic Environments.

Directory of Open Access Journals (Sweden)

Elyse H Norton

2017-01-01

Full Text Available Humans often make decisions based on uncertain sensory information. Signal detection theory (SDT describes detection and discrimination decisions as a comparison of stimulus "strength" to a fixed decision criterion. However, recent research suggests that current responses depend on the recent history of stimuli and previous responses, suggesting that the decision criterion is updated trial-by-trial. The mechanisms underpinning criterion setting remain unknown. Here, we examine how observers learn to set a decision criterion in an orientation-discrimination task under both static and dynamic conditions. To investigate mechanisms underlying trial-by-trial criterion placement, we introduce a novel task in which participants explicitly set the criterion, and compare it to a more traditional discrimination task, allowing us to model this explicit indication of criterion dynamics. In each task, stimuli were ellipses with principal orientations drawn from two categories: Gaussian distributions with different means and equal variance. In the covert-criterion task, observers categorized a displayed ellipse. In the overt-criterion task, observers adjusted the orientation of a line that served as the discrimination criterion for a subsequently presented ellipse. We compared performance to the ideal Bayesian learner and several suboptimal models that varied in both computational and memory demands. Under static and dynamic conditions, we found that, in both tasks, observers used suboptimal learning rules. In most conditions, a model in which the recent history of past samples determines a belief about category means fit the data best for most observers and on average. Our results reveal dynamic adjustment of discrimination criterion, even after prolonged training, and indicate how decision criteria are updated over time.

Visual learning alters the spontaneous activity of the resting human brain: an fNIRS study.

Science.gov (United States)

Niu, Haijing; Li, Hao; Sun, Li; Su, Yongming; Huang, Jing; Song, Yan

2014-01-01

Resting-state functional connectivity (RSFC) has been widely used to investigate spontaneous brain activity that exhibits correlated fluctuations. RSFC has been found to be changed along the developmental course and after learning. Here, we investigated whether and how visual learning modified the resting oxygenated hemoglobin (HbO) functional brain connectivity by using functional near-infrared spectroscopy (fNIRS). We demonstrate that after five days of training on an orientation discrimination task constrained to the right visual field, resting HbO functional connectivity and directed mutual interaction between high-level visual cortex and frontal/central areas involved in the top-down control were significantly modified. Moreover, these changes, which correlated with the degree of perceptual learning, were not limited to the trained left visual cortex. We conclude that the resting oxygenated hemoglobin functional connectivity could be used as a predictor of visual learning, supporting the involvement of high-level visual cortex and the involvement of frontal/central cortex during visual perceptual learning.

Human Factors Throughout the Life Cycle: Lessons Learned from the Shuttle Program. [Human Factors in Ground Processing

Science.gov (United States)

Kanki, Barbara G.

2011-01-01

With the ending of the Space Shuttle Program, it is critical that we not forget the Human Factors lessons we have learned over the years. At every phase of the life cycle, from manufacturing, processing and integrating vehicle and payload, to launch, flight operations, mission control and landing, hundreds of teams have worked together to achieve mission success in one of the most complex, high-risk socio-technical enterprises ever designed. Just as there was great diversity in the types of operations performed at every stage, there was a myriad of human factors that could further complicate these human systems. A single mishap or close call could point to issues at the individual level (perceptual or workload limitations, training, fatigue, human error susceptibilities), the task level (design of tools, procedures and aspects of the workplace), as well as the organizational level (appropriate resources, safety policies, information access and communication channels). While we have often had to learn through human mistakes and technological failures, we have also begun to understand how to design human systems in which individuals can excel, where tasks and procedures are not only safe but efficient, and how organizations can foster a proactive approach to managing risk and supporting human enterprises. Panelists will talk about their experiences as they relate human factors to a particular phase of the shuttle life cycle. They will conclude with a framework for tying together human factors lessons-learned into system-level risk management strategies.

A comparative analysis of the categorization of multidimensional stimuli: I. Unidimensional classification does not necessarily imply analytic processing; evidence from pigeons (Columba livia), squirrels (Sciurus carolinensis), and humans (Homo sapiens).

Science.gov (United States)

Wills, A J; Lea, Stephen E G; Leaver, Lisa A; Osthaus, Britta; Ryan, Catriona M E; Suret, Mark B; Bryant, Catherine M L; Chapman, Sue J A; Millar, Louise

2009-11-01

Pigeons (Columba livia), gray squirrels (Sciurus carolinensis), and undergraduates (Homo sapiens) learned discrimination tasks involving multiple mutually redundant dimensions. First, pigeons and undergraduates learned conditional discriminations between stimuli composed of three spatially separated dimensions, after first learning to discriminate the individual elements of the stimuli. When subsequently tested with stimuli in which one of the dimensions took an anomalous value, the majority of both species categorized test stimuli by their overall similarity to training stimuli. However some individuals of both species categorized them according to a single dimension. In a second set of experiments, squirrels, pigeons, and undergraduates learned go/no-go discriminations using multiple simultaneous presentations of stimuli composed of three spatially integrated, highly salient dimensions. The tendency to categorize test stimuli including anomalous dimension values unidimensionally was higher than in the first set of experiments and did not differ significantly between species. The authors conclude that unidimensional categorization of multidimensional stimuli is not diagnostic for analytic cognitive processing, and that any differences between human's and pigeons' behavior in such tasks are not due to special features of avian visual cognition.

The Impacts of System and Human Factors on Online Learning Systems Use and Learner Satisfaction

Science.gov (United States)

Alshare, Khaled A.; Freeze, Ronald D.; Lane, Peggy L.; Wen, H. Joseph

2011-01-01

Success in an online learning environment is tied to both human and system factors. This study illuminates the unique contributions of human factors (comfort with online learning, self-management of learning, and perceived Web self-efficacy) to online learning system success, which is measured in terms of usage and satisfaction. The research model…

Human resource recommendation algorithm based on ensemble learning and Spark

Science.gov (United States)

Cong, Zihan; Zhang, Xingming; Wang, Haoxiang; Xu, Hongjie

2017-08-01

Aiming at the problem of “information overload” in the human resources industry, this paper proposes a human resource recommendation algorithm based on Ensemble Learning. The algorithm considers the characteristics and behaviours of both job seeker and job features in the real business circumstance. Firstly, the algorithm uses two ensemble learning methods-Bagging and Boosting. The outputs from both learning methods are then merged to form user interest model. Based on user interest model, job recommendation can be extracted for users. The algorithm is implemented as a parallelized recommendation system on Spark. A set of experiments have been done and analysed. The proposed algorithm achieves significant improvement in accuracy, recall rate and coverage, compared with recommendation algorithms such as UserCF and ItemCF.

Only Some Are Dead Men Walking: Teaching about Race Discrimination and the Death Penalty

Science.gov (United States)

Bordt, Rebecca L.

2004-01-01

This paper describes an experiential learning exercise I have used to teach race discrimination in my introductory and criminology courses. The exercise is designed to introduce students to the concept of non-conscious forms of racial bias, a form of race discrimination often difficult for students to grasp. Using a hypothetical criminal case,…

Original article Temperamental variation in learned irrelevance in humans

Directory of Open Access Journals (Sweden)

Aleksandra Gruszka

2015-07-01

Full Text Available Background Learned irrelevance (LIRR represents one of the mechanisms of attentional set-shifting and refers to the inability to attend to, or to learn about, any aspect of a stimulus previously experienced as irrelevant. Although it has been extensively studied in the context of clinical populations, not much is known about LIRR effects in relation to normal variation in individual differences. The present study was designed to assess how temperamental factors may modulate LIRR. Participants and procedures Sixty-eight healthy volunteers performed a visual discrimination learning task modelled after Wisconsin Card Sorting Test. To test the susceptibility to learned irrelevance, participants were expected to shift their attention either to a dimension that prior to the extra-dimensional shift was completely irrelevant, or to a dimension that was previously partly correlated with reinforcement. Temperamental traits were assessed using the Formal Characteristics of Behaviour-Temperament Inventory (Zawadzki & Strelau, 1997. Intelligence level was stratified according to Raven’s Advanced Progressive Matrices (Raven, Raven, & Court, 2003. Results Low level of Briskness and high level of Perseverance were related to enhanced susceptibility to LIRR. High levels of Activity and Emotional Reactivity were related to the poorer performance on the extra-dimensional set-shifting. No effects of other temperament characteristics or intelligence on LIRR were observed. Conclusions The results confirm a strong variation in LIRR related to individual differences in temperament, which appears to be unrelated to DA function. Our results highlight the importance of considering individual differences in studies on cognitive control.

Differential autoshaping to common and distinctive elements of positive and negative discriminative stimuli.

Science.gov (United States)

Wasserman, E A; Anderson, P A

1974-11-01

The learning by hungry pigeons of a discrimination between two successively presented compound visual stimuli was investigated using a two-key autoshaping procedure. Common and distinctive stimulus elements were simultaneously presented on separate keys and either followed by food delivery, S+, or not, S-. The subjects acquired both between-trial and within-trial discriminations. On S+ trials, pigeons pecked the distinctive stimulus more than the common stimulus; before responding ceased on S- trials, they pecked the common stimulus more than the distinctive one. Mastery of the within-display discrimination during S+ trials preceded mastery of the between-trials discrimination. These findings extend the Jenkins-Sainsbury analysis of discriminations based upon a single distinguishing feature to discriminations in which common and distinctive elements are associated with both the positive and negative discriminative stimuli. The similarity of these findings to other effects found in autoshaping-approach to signals that forecast reinforcement and withdrawal from signals that forecast nonreinforcement-is also discussed.

Modeling human learning involved in car driving

NARCIS (Netherlands)

Wewerinke, P.H.

1994-01-01

In this paper, car driving is considered at the level of human tracking and maneuvering in the context of other traffic. A model analysis revealed the most salient features determining driving performance and safety. Learning car driving is modelled based on a system theoretical approach and based

Hierarchical Discriminant Analysis

Directory of Open Access Journals (Sweden)

Di Lu

2018-01-01

Full Text Available The Internet of Things (IoT generates lots of high-dimensional sensor intelligent data. The processing of high-dimensional data (e.g., data visualization and data classification is very difficult, so it requires excellent subspace learning algorithms to learn a latent subspace to preserve the intrinsic structure of the high-dimensional data, and abandon the least useful information in the subsequent processing. In this context, many subspace learning algorithms have been presented. However, in the process of transforming the high-dimensional data into the low-dimensional space, the huge difference between the sum of inter-class distance and the sum of intra-class distance for distinct data may cause a bias problem. That means that the impact of intra-class distance is overwhelmed. To address this problem, we propose a novel algorithm called Hierarchical Discriminant Analysis (HDA. It minimizes the sum of intra-class distance first, and then maximizes the sum of inter-class distance. This proposed method balances the bias from the inter-class and that from the intra-class to achieve better performance. Extensive experiments are conducted on several benchmark face datasets. The results reveal that HDA obtains better performance than other dimensionality reduction algorithms.

International and Regional Institutional Dialogues for Human Rights for LGBT persons: The quest for recognition, anti-discrimination, and marriage in Southeast Asia

OpenAIRE

Holzhacker, Ronald

2016-01-01

There is a rich interplay between civil society organizations and institutions involved in human rights norm diffusion and the ‘ricochet’ of ideas at the regional level across Southeast Asia. There is a broad discussion occurring about human rights for LGBT persons and SOGI rights (Sexual Orientation and Gender Identity) including recognition, non-discrimination in employment, education, and housing, and partnership recognition and same-sex marriage. We focus on four countries, Thailand, Viet...

Acute Moderate Exercise Improves Mnemonic Discrimination in Young Adults

Science.gov (United States)

Suwabe, Kazuya; Hyodo, Kazuki; Byun, Kyeongho; Ochi, Genta; Yassa, Michael A.; Soya, Hideaki

2018-01-01

Increasing evidence suggests that regular moderate exercise increases neurogenesis in the dentate gyrus (DG) of the hippocampus and improves memory functions in both humans and animals. The DG is known to play a role in pattern separation, which is the ability to discriminate among similar experiences, a fundamental component of episodic memory. While long-term voluntary exercise improves pattern separation, there is little evidence of alterations in DG function after an acute exercise session. Our previous studies showing acute moderate exercise-enhanced DG activation in rats, and acute moderate exercise-enhanced prefrontal activation and executive function in humans, led us to postulate that acute moderate exercise may also activate the hippocampus, including more specifically the DG, thus improving pattern separation. We thus investigated the effects of a 10-min moderate exercise (50% V̇O2peak) session, the recommended intensity for health promotion, on mnemonic discrimination (a behavioral index of pattern separation) in young adults. An acute bout of moderate exercise improved mnemonic discrimination performance in high similarity lures. These results support our hypothesis that acute moderate exercise improves DG-mediated pattern separation in humans, proposing a useful human acute-exercise model for analyzing the neuronal substrate underlying acute and regular exercise-enhanced episodic memory based on the hippocampus. PMID:27997992

A dictionary learning approach for human sperm heads classification.

Science.gov (United States)

Shaker, Fariba; Monadjemi, S Amirhassan; Alirezaie, Javad; Naghsh-Nilchi, Ahmad Reza

2017-12-01

To diagnose infertility in men, semen analysis is conducted in which sperm morphology is one of the factors that are evaluated. Since manual assessment of sperm morphology is time-consuming and subjective, automatic classification methods are being developed. Automatic classification of sperm heads is a complicated task due to the intra-class differences and inter-class similarities of class objects. In this research, a Dictionary Learning (DL) technique is utilized to construct a dictionary of sperm head shapes. This dictionary is used to classify the sperm heads into four different classes. Square patches are extracted from the sperm head images. Columnized patches from each class of sperm are used to learn class-specific dictionaries. The patches from a test image are reconstructed using each class-specific dictionary and the overall reconstruction error for each class is used to select the best matching class. Average accuracy, precision, recall, and F-score are used to evaluate the classification method. The method is evaluated using two publicly available datasets of human sperm head shapes. The proposed DL based method achieved an average accuracy of 92.2% on the HuSHeM dataset, and an average recall of 62% on the SCIAN-MorphoSpermGS dataset. The results show a significant improvement compared to a previously published shape-feature-based method. We have achieved high-performance results. In addition, our proposed approach offers a more balanced classifier in which all four classes are recognized with high precision and recall. In this paper, we use a Dictionary Learning approach in classifying human sperm heads. It is shown that the Dictionary Learning method is far more effective in classifying human sperm heads than classifiers using shape-based features. Also, a dataset of human sperm head shapes is introduced to facilitate future research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Duo: A Human/Wearable Hybrid for Learning About Common Manipulate Objects

National Research Council Canada - National Science Library

Kemp, Charles C

2002-01-01

... with them. Duo is a human/wearable hybrid that is designed to learn about this important domain of human intelligence by interacting with natural manipulable objects in unconstrained environments...

Dissociable brain systems mediate vicarious learning of stimulus-response and action-outcome contingencies.

Science.gov (United States)

Liljeholm, Mimi; Molloy, Ciara J; O'Doherty, John P

2012-07-18

Two distinct strategies have been suggested to support action selection in humans and other animals on the basis of experiential learning: a goal-directed strategy that generates decisions based on the value and causal antecedents of action outcomes, and a habitual strategy that relies on the automatic elicitation of actions by environmental stimuli. In the present study, we investigated whether a similar dichotomy exists for actions that are acquired vicariously, through observation of other individuals rather than through direct experience, and assessed whether these strategies are mediated by distinct brain regions. We scanned participants with functional magnetic resonance imaging while they performed an observational learning task designed to encourage either goal-directed encoding of the consequences of observed actions, or a mapping of observed actions to conditional discriminative cues. Activity in different parts of the action observation network discriminated between the two conditions during observational learning and correlated with the degree of insensitivity to outcome devaluation in subsequent performance. Our findings suggest that, in striking parallel to experiential learning, neural systems mediating the observational acquisition of actions may be dissociated into distinct components: a goal-directed, outcome-sensitive component and a less flexible stimulus-response component.

Kosovo – UNMIK accountability: Human Rights Advisory Panel Finds Discrimination in Privatization Cases

Directory of Open Access Journals (Sweden)

Wolfgang Benedek

2015-10-01

Full Text Available ENGLISH: The Human Rights Advisory Panel (HRAP established in 2006 to strengthen the accountability of UNMIK in Kosovo so far has dealt mainly with cases regarding property and missing persons. In two recent cases of members of the Egyptian and the Serbian minority (Fillim Guga and Nevenka Ristić it also dealt with privatization of socially - owned enterprises and found discrimination on ethnic grounds by the Special Chamber of the Supreme Court, established by UNMIK for such cases, which raises the accountability of UNMIK. In doing so the panel applied Article 14 of the ECHR on prohibition of discrimination in conjunction with Article 6 ECHR on fair trial in the light of relevant jurisprudence of the European Court of Human Rights. It also pointed out that in these cases the Special Chamber did not recognize a prima facie case of indirect discrimination and did not apply the principle of reversal of proof as required by the Anti - Discrimination Law of Kosovo. On behalf of UNMIK, the Special Representative of the Secretary - General defended the findings of the Special Chamber. The conclusions and recommendations in the Opinion of the Panel hold UNMIK accountable for the violations found and require it to take immediate and effective measures including an apology and adequate compensation for non-pecuniary damage as well as urging EULEX and other competent authorities in Kosovo to reopen the case by the Special Chamber. The work of the HRAP raises wider issues of accountability of international missions like UNMIK, to which it makes an important contribution. DEUTSCH: Das menschenrechtliche Beratungspanel, welches 2006 ins Leben gerufen wurde, um die Verantwortlichkeit von UNMIK im Kosovo zu stärken, hat sich bisher hauptsächlich mit Fällen zum Eigentumsrecht und hinsichtlich verschwundener Personen beschäftigt. In zwei aktuellen Fällen, die Mitglieder der ägyptischen bzw. serbischen Minderheit betrafen (Fillim Guga und Nevenka Risti

Multi-task learning with group information for human action recognition

Science.gov (United States)

Qian, Li; Wu, Song; Pu, Nan; Xu, Shulin; Xiao, Guoqiang

2018-04-01

Human action recognition is an important and challenging task in computer vision research, due to the variations in human motion performance, interpersonal differences and recording settings. In this paper, we propose a novel multi-task learning framework with group information (MTL-GI) for accurate and efficient human action recognition. Specifically, we firstly obtain group information through calculating the mutual information according to the latent relationship between Gaussian components and action categories, and clustering similar action categories into the same group by affinity propagation clustering. Additionally, in order to explore the relationships of related tasks, we incorporate group information into multi-task learning. Experimental results evaluated on two popular benchmarks (UCF50 and HMDB51 datasets) demonstrate the superiority of our proposed MTL-GI framework.

Associationism and cognition: human contingency learning at 25.

Science.gov (United States)

Shanks, David R

2007-03-01

A major topic within human learning, the field of contingency judgement, began to emerge about 25 years ago following publication of an article on depressive realism by Alloy and Abramson (1979). Subsequently, associationism has been the dominant theoretical framework for understanding contingency learning but this has been challenged in recent years by an alternative cognitive or inferential approach. This article outlines the key conceptual differences between these approaches and summarizes some of the main methods that have been employed to distinguish between them.

The KEEP Phone Discrimination Test. Technical Report No. 64.

Science.gov (United States)

Smith, Kenneth; And Others

The urban, ethnically Hawaiian child typically experiences great difficulty in learning to read English. In order to determine whether phonological confusion is a source of dialectical interference, the Kamehameha Early Education Program (KEEP) Phone Discrimination Test (KPDT) was developed for the one hundred twelve students in the KEEP school…

Differential discriminator

International Nuclear Information System (INIS)

Dukhanov, V.I.; Mazurov, I.B.

1981-01-01

A principal flowsheet of a differential discriminator intended for operation in a spectrometric circuit with statistical time distribution of pulses is described. The differential discriminator includes four integrated discriminators and a channel of piled-up signal rejection. The presence of the rejection channel enables the discriminator to operate effectively at loads of 14x10 3 pulse/s. The temperature instability of the discrimination thresholds equals 250 μV/ 0 C. The discrimination level changes within 0.1-5 V, the level shift constitutes 0.5% for the filling ratio of 1:10. The rejection coefficient is not less than 90%. Alpha spectrum of the 228 Th source is presented to evaluate the discriminator operation with the rejector. The rejector provides 50 ns time resolution

Hedging Your Bets by Learning Reward Correlations in the Human Brain

Science.gov (United States)

Wunderlich, Klaus; Symmonds, Mkael; Bossaerts, Peter; Dolan, Raymond J.

2011-01-01

Summary Human subjects are proficient at tracking the mean and variance of rewards and updating these via prediction errors. Here, we addressed whether humans can also learn about higher-order relationships between distinct environmental outcomes, a defining ecological feature of contexts where multiple sources of rewards are available. By manipulating the degree to which distinct outcomes are correlated, we show that subjects implemented an explicit model-based strategy to learn the associated outcome correlations and were adept in using that information to dynamically adjust their choices in a task that required a minimization of outcome variance. Importantly, the experimentally generated outcome correlations were explicitly represented neuronally in right midinsula with a learning prediction error signal expressed in rostral anterior cingulate cortex. Thus, our data show that the human brain represents higher-order correlation structures between rewards, a core adaptive ability whose immediate benefit is optimized sampling. PMID:21943609

Observation versus classification in supervised category learning.

Science.gov (United States)

Levering, Kimery R; Kurtz, Kenneth J

2015-02-01

The traditional supervised classification paradigm encourages learners to acquire only the knowledge needed to predict category membership (a discriminative approach). An alternative that aligns with important aspects of real-world concept formation is learning with a broader focus to acquire knowledge of the internal structure of each category (a generative approach). Our work addresses the impact of a particular component of the traditional classification task: the guess-and-correct cycle. We compare classification learning to a supervised observational learning task in which learners are shown labeled examples but make no classification response. The goals of this work sit at two levels: (1) testing for differences in the nature of the category representations that arise from two basic learning modes; and (2) evaluating the generative/discriminative continuum as a theoretical tool for understand learning modes and their outcomes. Specifically, we view the guess-and-correct cycle as consistent with a more discriminative approach and therefore expected it to lead to narrower category knowledge. Across two experiments, the observational mode led to greater sensitivity to distributional properties of features and correlations between features. We conclude that a relatively subtle procedural difference in supervised category learning substantially impacts what learners come to know about the categories. The results demonstrate the value of the generative/discriminative continuum as a tool for advancing the psychology of category learning and also provide a valuable constraint for formal models and associated theories.

Observing tutorial dialogues collaboratively: insights about human tutoring effectiveness from vicarious learning.

Science.gov (United States)

Chi, Michelene T H; Roy, Marguerite; Hausmann, Robert G M

2008-03-01

The goals of this study are to evaluate a relatively novel learning environment, as well as to seek greater understanding of why human tutoring is so effective. This alternative learning environment consists of pairs of students collaboratively observing a videotape of another student being tutored. Comparing this collaboratively observing environment to four other instructional methods-one-on-one human tutoring, observing tutoring individually, collaborating without observing, and studying alone-the results showed that students learned to solve physics problems just as effectively from observing tutoring collaboratively as the tutees who were being tutored individually. We explain the effectiveness of this learning environment by postulating that such a situation encourages learners to become active and constructive observers through interactions with a peer. In essence, collaboratively observing combines the benefit of tutoring with the benefit of collaborating. The learning outcomes of the tutees and the collaborative observers, along with the tutoring dialogues, were used to further evaluate three hypotheses explaining why human tutoring is an effective learning method. Detailed analyses of the protocols at several grain sizes suggest that tutoring is effective when tutees are independently or jointly constructing knowledge: with the tutor, but not when the tutor independently conveys knowledge. 2008 Cognitive Science Society, Inc.

Combining fMRI and behavioral measures to examine the process of human learning.

Science.gov (United States)

Karuza, Elisabeth A; Emberson, Lauren L; Aslin, Richard N

2014-03-01

Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning. Copyright © 2013 Elsevier Inc. All rights reserved.

Structural Discrimination

DEFF Research Database (Denmark)

Thorsen, Mira Skadegård

discrimination as two ways of articulating particular, opaque forms of racial discrimination that occur in everyday Danish (and other) contexts, and have therefore become normalized. I present and discuss discrimination as it surfaces in data from my empirical studies of discrimination in Danish contexts...

Intrinsic interactive reinforcement learning - Using error-related potentials for real world human-robot interaction.

Science.gov (United States)

Kim, Su Kyoung; Kirchner, Elsa Andrea; Stefes, Arne; Kirchner, Frank

2017-12-14

Reinforcement learning (RL) enables robots to learn its optimal behavioral strategy in dynamic environments based on feedback. Explicit human feedback during robot RL is advantageous, since an explicit reward function can be easily adapted. However, it is very demanding and tiresome for a human to continuously and explicitly generate feedback. Therefore, the development of implicit approaches is of high relevance. In this paper, we used an error-related potential (ErrP), an event-related activity in the human electroencephalogram (EEG), as an intrinsically generated implicit feedback (rewards) for RL. Initially we validated our approach with seven subjects in a simulated robot learning scenario. ErrPs were detected online in single trial with a balanced accuracy (bACC) of 91%, which was sufficient to learn to recognize gestures and the correct mapping between human gestures and robot actions in parallel. Finally, we validated our approach in a real robot scenario, in which seven subjects freely chose gestures and the real robot correctly learned the mapping between gestures and actions (ErrP detection (90% bACC)). In this paper, we demonstrated that intrinsically generated EEG-based human feedback in RL can successfully be used to implicitly improve gesture-based robot control during human-robot interaction. We call our approach intrinsic interactive RL.

Human Systems Integration in Practice: Constellation Lessons Learned

Science.gov (United States)

Zumbado, Jennifer Rochlis

2012-01-01

NASA's Constellation program provided a unique testbed for Human Systems Integration (HSI) as a fundamental element of the Systems Engineering process. Constellation was the first major program to have HSI mandated by NASA's Human Rating document. Proper HSI is critical to the success of any project that relies on humans to function as operators, maintainers, or controllers of a system. HSI improves mission, system and human performance, significantly reduces lifecycle costs, lowers risk and minimizes re-design. Successful HSI begins with sufficient project schedule dedicated to the generation of human systems requirements, but is by no means solely a requirements management process. A top-down systems engineering process that recognizes throughout the organization, human factors as a technical discipline equal to traditional engineering disciplines with authority for the overall system. This partners with a bottoms-up mechanism for human-centered design and technical issue resolution. The Constellation Human Systems Integration Group (HSIG) was a part of the Systems Engineering and Integration (SE&I) organization within the program office, and existed alongside similar groups such as Flight Performance, Environments & Constraints, and Integrated Loads, Structures and Mechanisms. While the HSIG successfully managed, via influence leadership, a down-and-in Community of Practice to facilitate technical integration and issue resolution, it lacked parallel top-down authority to drive integrated design. This presentation will discuss how HSI was applied to Constellation, the lessons learned and best practices it revealed, and recommendations to future NASA program and project managers. This presentation will discuss how Human Systems Integration (HSI) was applied to NASA's Constellation program, the lessons learned and best practices it revealed, and recommendations to future NASA program and project managers on how to accomplish this critical function.

Multiple reversal olfactory learning in honeybees

Directory of Open Access Journals (Sweden)

Theo Mota

2010-07-01

Full Text Available In multiple reversal learning, animals trained to discriminate a reinforced from a non-reinforced stimulus are subjected to various, successive reversals of stimulus contingencies (e.g. A+ vs. B-, A- vs. B+, A+ vs. B-. This protocol is useful to determine whether or not animals learn to learn and solve successive discriminations faster (or with fewer errors with increasing reversal experience. Here we used the olfactory conditioning of proboscis extension reflex to study how honeybees Apis mellifera perform in a multiple reversal task. Our experiment contemplated four consecutive differential conditioning phases involving the same odors (A+ vs. B- to A- vs. B+ to A+ vs. B- to A- vs. B+. We show that bees in which the weight of reinforced or non-reinforced stimuli was similar mastered the multiple olfactory reversals. Bees which failed the task exhibited asymmetric responses to reinforced and non-reinforced stimuli, thus being unable to rapidly reverse stimulus contingencies. Efficient reversers did not improve their successive discriminations but rather tended to generalize their choice to both odors at the end of conditioning. As a consequence, both discrimination and reversal efficiency decreasedalong experimental phases. This result invalidates a learning-to-learn effect and indicates that bees do not only respond to the actual stimulus contingencies but rather combine these with an average of past experiences with the same stimuli.  

Enhanced odor discrimination and impaired olfactory memory by spatially controlled switch of AMPA receptors.

Directory of Open Access Journals (Sweden)

Derya R Shimshek

2005-11-01

Full Text Available Genetic perturbations of alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionate receptors (AMPARs are widely used to dissect molecular mechanisms of sensory coding, learning, and memory. In this study, we investigated the role of Ca2+-permeable AMPARs in olfactory behavior. AMPAR modification was obtained by depletion of the GluR-B subunit or expression of unedited GluR-B(Q, both leading to increased Ca2+ permeability of AMPARs. Mice with this functional AMPAR switch, specifically in forebrain, showed enhanced olfactory discrimination and more rapid learning in a go/no-go operant conditioning task. Olfactory memory, however, was dramatically impaired. GluR-B depletion in forebrain was ectopically variable ("mosaic" among individuals and strongly correlated with decreased olfactory memory in hippocampus and cortex. Accordingly, memory was rescued by transgenic GluR-B expression restricted to piriform cortex and hippocampus, while enhanced odor discrimination was independent of both GluR-B variability and transgenic GluR-B expression. Thus, correlated differences in behavior and levels of GluR-B expression allowed a mechanistic and spatial dissection of olfactory learning, discrimination, and memory capabilities.

Human-simulation-based learning to prevent medication error: A systematic review.

Science.gov (United States)

Sarfati, Laura; Ranchon, Florence; Vantard, Nicolas; Schwiertz, Vérane; Larbre, Virginie; Parat, Stéphanie; Faudel, Amélie; Rioufol, Catherine

2018-01-31

In the past 2 decades, there has been an increasing interest in simulation-based learning programs to prevent medication error (ME). To improve knowledge, skills, and attitudes in prescribers, nurses, and pharmaceutical staff, these methods enable training without directly involving patients. However, best practices for simulation for healthcare providers are as yet undefined. By analysing the current state of experience in the field, the present review aims to assess whether human simulation in healthcare helps to reduce ME. A systematic review was conducted on Medline from 2000 to June 2015, associating the terms "Patient Simulation," "Medication Errors," and "Simulation Healthcare." Reports of technology-based simulation were excluded, to focus exclusively on human simulation in nontechnical skills learning. Twenty-one studies assessing simulation-based learning programs were selected, focusing on pharmacy, medicine or nursing students, or concerning programs aimed at reducing administration or preparation errors, managing crises, or learning communication skills for healthcare professionals. The studies varied in design, methodology, and assessment criteria. Few demonstrated that simulation was more effective than didactic learning in reducing ME. This review highlights a lack of long-term assessment and real-life extrapolation, with limited scenarios and participant samples. These various experiences, however, help in identifying the key elements required for an effective human simulation-based learning program for ME prevention: ie, scenario design, debriefing, and perception assessment. The performance of these programs depends on their ability to reflect reality and on professional guidance. Properly regulated simulation is a good way to train staff in events that happen only exceptionally, as well as in standard daily activities. By integrating human factors, simulation seems to be effective in preventing iatrogenic risk related to ME, if the program is

Unsupervised discrimination of patterns in spiking neural networks with excitatory and inhibitory synaptic plasticity.

Science.gov (United States)

Srinivasa, Narayan; Cho, Youngkwan

2014-01-01

A spiking neural network model is described for learning to discriminate among spatial patterns in an unsupervised manner. The network anatomy consists of source neurons that are activated by external inputs, a reservoir that resembles a generic cortical layer with an excitatory-inhibitory (EI) network and a sink layer of neurons for readout. Synaptic plasticity in the form of STDP is imposed on all the excitatory and inhibitory synapses at all times. While long-term excitatory STDP enables sparse and efficient learning of the salient features in inputs, inhibitory STDP enables this learning to be stable by establishing a balance between excitatory and inhibitory currents at each neuron in the network. The synaptic weights between source and reservoir neurons form a basis set for the input patterns. The neural trajectories generated in the reservoir due to input stimulation and lateral connections between reservoir neurons can be readout by the sink layer neurons. This activity is used for adaptation of synapses between reservoir and sink layer neurons. A new measure called the discriminability index (DI) is introduced to compute if the network can discriminate between old patterns already presented in an initial training session. The DI is also used to compute if the network adapts to new patterns without losing its ability to discriminate among old patterns. The final outcome is that the network is able to correctly discriminate between all patterns-both old and new. This result holds as long as inhibitory synapses employ STDP to continuously enable current balance in the network. The results suggest a possible direction for future investigation into how spiking neural networks could address the stability-plasticity question despite having continuous synaptic plasticity.

Human detection and discrimination of tactile repeatability, mechanical backlash, and temporal delay in a combined tactile-kinesthetic haptic display system.

Science.gov (United States)

Doxon, Andrew J; Johnson, David E; Tan, Hong Z; Provancher, William R

2013-01-01

Many of the devices used in haptics research are over-engineered for the task and are designed with capabilities that go far beyond human perception levels. Designing devices that more closely match the limits of human perception will make them smaller, less expensive, and more useful. However, many device-centric perception thresholds have yet to be evaluated. To this end, three experiments were conducted, using one degree-of-freedom contact location feedback device in combination with a kinesthetic display, to provide a more explicit set of specifications for similar tactile-kinesthetic haptic devices. The first of these experiments evaluated the ability of humans to repeatedly localize tactile cues across the fingerpad. Subjects could localize cues to within 1.3 mm and showed bias toward the center of the fingerpad. The second experiment evaluated the minimum perceptible difference of backlash at the tactile element. Subjects were able to discriminate device backlash in excess of 0.46 mm on low-curvature models and 0.93 mm on high-curvature models. The last experiment evaluated the minimum perceptible difference of system delay between user action and device reaction. Subjects were able to discriminate delays in excess of 61 ms. The results from these studies can serve as the maximum (i.e., most demanding) device specifications for most tactile-kinesthetic haptic systems.

Human simulations of vocabulary learning.

Science.gov (United States)

Gillette, J; Gleitman, H; Gleitman, L; Lederer, A

1999-12-07

The work reported here experimentally investigates a striking generalization about vocabulary acquisition: Noun learning is superior to verb learning in the earliest moments of child language development. The dominant explanation of this phenomenon in the literature invokes differing conceptual requirements for items in these lexical categories: Verbs are cognitively more complex than nouns and so their acquisition must await certain mental developments in the infant. In the present work, we investigate an alternative hypothesis; namely, that it is the information requirements of verb learning, not the conceptual requirements, that crucially determine the acquisition order. Efficient verb learning requires access to structural features of the exposure language and thus cannot take place until a scaffolding of noun knowledge enables the acquisition of clause-level syntax. More generally, we experimentally investigate the hypothesis that vocabulary acquisition takes place via an incremental constraint-satisfaction procedure that bootstraps itself into successively more sophisticated linguistic representations which, in turn, enable new kinds of vocabulary learning. If the experimental subjects were young children, it would be difficult to distinguish between this information-centered hypothesis and the conceptual change hypothesis. Therefore the experimental "learners" are adults. The items to be "acquired" in the experiments were the 24 most frequent nouns and 24 most frequent verbs from a sample of maternal speech to 18-24-month-old infants. The various experiments ask about the kinds of information that will support identification of these words as they occur in mother-to-child discourse. Both the proportion correctly identified and the type of word that is identifiable changes significantly as a function of information type. We discuss these results as consistent with the incremental construction of a highly lexicalized grammar by cognitively and pragmatically

Multiview Discriminative Geometry Preserving Projection for Image Classification

Directory of Open Access Journals (Sweden)

Ziqiang Wang

2014-01-01

Full Text Available In many image classification applications, it is common to extract multiple visual features from different views to describe an image. Since different visual features have their own specific statistical properties and discriminative powers for image classification, the conventional solution for multiple view data is to concatenate these feature vectors as a new feature vector. However, this simple concatenation strategy not only ignores the complementary nature of different views, but also ends up with “curse of dimensionality.” To address this problem, we propose a novel multiview subspace learning algorithm in this paper, named multiview discriminative geometry preserving projection (MDGPP for feature extraction and classification. MDGPP can not only preserve the intraclass geometry and interclass discrimination information under a single view, but also explore the complementary property of different views to obtain a low-dimensional optimal consensus embedding by using an alternating-optimization-based iterative algorithm. Experimental results on face recognition and facial expression recognition demonstrate the effectiveness of the proposed algorithm.

The interaction between acoustic salience and language experience in developmental speech perception: evidence from nasal place discrimination.

Science.gov (United States)

Narayan, Chandan R; Werker, Janet F; Beddor, Patrice Speeter

2010-05-01

Previous research suggests that infant speech perception reorganizes in the first year: young infants discriminate both native and non-native phonetic contrasts, but by 10-12 months difficult non-native contrasts are less discriminable whereas performance improves on native contrasts. In the current study, four experiments tested the hypothesis that, in addition to the influence of native language experience, acoustic salience also affects the perceptual reorganization that takes place in infancy. Using a visual habituation paradigm, two nasal place distinctions that differ in relative acoustic salience, acoustically robust labial-alveolar [ma]-[na] and acoustically less salient alveolar-velar [na]-[ enga], were presented to infants in a cross-language design. English-learning infants at 6-8 and 10-12 months showed discrimination of the native and acoustically robust [ma]-[na] (Experiment 1), but not the non-native (in initial position) and acoustically less salient [na]-[ enga] (Experiment 2). Very young (4-5-month-old) English-learning infants tested on the same native and non-native contrasts also showed discrimination of only the [ma]-[na] distinction (Experiment 3). Filipino-learning infants, whose ambient language includes the syllable-initial alveolar (/n/)-velar (/ eng/) contrast, showed discrimination of native [na]-[ enga] at 10-12 months, but not at 6-8 months (Experiment 4). These results support the hypothesis that acoustic salience affects speech perception in infancy, with native language experience facilitating discrimination of an acoustically similar phonetic distinction [na]-[ enga]. We discuss the implications of this developmental profile for a comprehensive theory of speech perception in infancy.