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Sample records for left frontal convolution

  1. Grammatical distinctions in the left frontal cortex.

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    Shapiro, K A; Pascual-Leone, A; Mottaghy, F M; Gangitano, M; Caramazza, A

    2001-08-15

    Selective deficits in producing verbs relative to nouns in speech are well documented in neuropsychology and have been associated with left hemisphere frontal cortical lesions resulting from stroke and other neurological disorders. The basis for these impairments is unresolved: Do they arise because of differences in the way grammatical categories of words are organized in the brain, or because of differences in the neural representation of actions and objects? We used repetitive transcranial magnetic stimulation (rTMS) to suppress the excitability of a portion of left prefrontal cortex and to assess its role in producing nouns and verbs. In one experiment subjects generated real words; in a second, they produced pseudowords as nouns or verbs. In both experiments, response latencies increased for verbs but were unaffected for nouns following rTMS. These results demonstrate that grammatical categories have a neuroanatomical basis and that the left prefrontal cortex is selectively engaged in processing verbs as grammatical objects.

  2. Jealousy increased by induced relative left frontal cortical activity.

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    Kelley, Nicholas J; Eastwick, Paul W; Harmon-Jones, Eddie; Schmeichel, Brandon J

    2015-10-01

    Asymmetric frontal cortical activity may be one key to the process linking social exclusion to jealous feelings. The current research examined the causal role of asymmetric frontal brain activity in modulating jealousy in response to social exclusion. Transcranial direct-current stimulation (tDCS) over the frontal cortex to manipulate asymmetric frontal cortical activity was combined with a modified version of the Cyberball paradigm designed to induce jealousy. After receiving 15 min of tDCS, participants were excluded by a desired partner and reported how jealous they felt. Among individuals who were excluded, tDCS to increase relative left frontal cortical activity caused greater levels of self-reported jealousy compared to tDCS to increase relative right frontal cortical activity or sham stimulation. Limitations concerning the specificity of this effect and implications for the role of the asymmetric prefrontal cortical activity in motivated behaviors are discussed. (c) 2015 APA, all rights reserved).

  3. Decoding rule search domain in the left inferior frontal gyrus

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    Babcock, Laura; Vallesi, Antonino

    2018-01-01

    Traditionally, the left hemisphere has been thought to extract mainly verbal patterns of information, but recent evidence has shown that the left Inferior Frontal Gyrus (IFG) is active during inductive reasoning in both the verbal and spatial domains. We aimed to understand whether the left IFG supports inductive reasoning in a domain-specific or domain-general fashion. To do this we used Multi-Voxel Pattern Analysis to decode the representation of domain during a rule search task. Thirteen participants were asked to extract the rule underlying streams of letters presented in different spatial locations. Each rule was either verbal (letters forming words) or spatial (positions forming geometric figures). Our results show that domain was decodable in the left prefrontal cortex, suggesting that this region represents domain-specific information, rather than processes common to the two domains. A replication study with the same participants tested two years later confirmed these findings, though the individual representations changed, providing evidence for the flexible nature of representations. This study extends our knowledge on the neural basis of goal-directed behaviors and on how information relevant for rule extraction is flexibly mapped in the prefrontal cortex. PMID:29547623

  4. Exercising self-control increases relative left frontal cortical activation.

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    Schmeichel, Brandon J; Crowell, Adrienne; Harmon-Jones, Eddie

    2016-02-01

    Self-control refers to the capacity to override or alter a predominant response tendency. The current experiment tested the hypothesis that exercising self-control temporarily increases approach motivation, as revealed by patterns of electrical activity in the prefrontal cortex. Participants completed a writing task that did vs did not require them to exercise self-control. Then they viewed pictures known to evoke positive, negative or neutral affect. We assessed electroencephalographic (EEG) activity while participants viewed the pictures, and participants reported their trait levels of behavioral inhibition system (BIS) and behavioral activation system (BAS) sensitivity at the end of the study. We found that exercising (vs not exercising) self-control increased relative left frontal cortical activity during picture viewing, particularly among individuals with relatively higher BAS than BIS, and particularly during positive picture viewing. A similar but weaker pattern emerged during negative picture viewing. The results suggest that exercising self-control temporarily increases approach motivation, which may help to explain the aftereffects of self-control (i.e. ego depletion). © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  5. Relative left frontal activity in reappraisal and suppression of negative emotion: Evidence from frontal alpha asymmetry (FAA).

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    Choi, Damee; Sekiya, Takahiro; Minote, Natsumi; Watanuki, Shigeki

    2016-11-01

    Previous studies have shown that reappraisal (changing the way that one thinks about emotional events) is an effective strategy for regulating emotion, compared with suppression (reducing emotion-expressive behavior). In the present study, we investigated relative left frontal activity when participants were instructed to use reappraisal and suppression of negative emotion, by measuring frontal alpha asymmetry (FAA). Two electroencephalography (EEG) experiments were conducted; FAA was analyzed while 102 healthy participants (59 men, 43 women) watched negative images after being instructed to perform reappraisal (Experiment 1) and suppression (Experiment 2). Habitual use of reappraisal and suppression was also assessed using the emotion regulation questionnaire (ERQ). The results of Experiment 1 showed that relative left frontal activity was greater when instructed to use reappraisal of negative images than when normally viewing negative images. In contrast, we observed no difference between conditions of instructed suppression and normal viewing in Experiment 2. In addition, in male participants, habitual use of reappraisal was positively correlated with increased relative left frontal activity for instructed reappraisal, while habitual use of suppression did not show a significant correlation with changes in relative left frontal activity for instructed suppression. These results suggest that emotional responses to negative images might be decreased for instructed reappraisal, but not suppression. These findings support previous reports that reappraisal is an effective emotion regulation strategy, compared with suppression. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Paediatric frontal chest radiograph screening with fine-tuned convolutional neural networks

    CSIR Research Space (South Africa)

    Gerrand, Jonathan D

    2017-07-01

    Full Text Available of fine-tuned convolutional neural networks (CNN). We use two popular CNN models that are pre-trained on a large natural image dataset and two distinct datasets containing paediatric and adult radiographs respectively. Evaluation is performed using a 5...

  7. Origin of human motor readiness field linked to left middle frontal gyrus by MEG and PET

    DEFF Research Database (Denmark)

    Pedersen, Jane Rygaard; Johannsen, P; Bak, Christen Kjeldahl

    1998-01-01

    Combined magnetoencephalography and positron emission tomography identified a prior source of activity in the left middle frontal gyrus duping uncued movements of the right index finger Voluntary movements gave rise to a change in the cortical electrical potential known as the Bereitschaftspotent......Combined magnetoencephalography and positron emission tomography identified a prior source of activity in the left middle frontal gyrus duping uncued movements of the right index finger Voluntary movements gave rise to a change in the cortical electrical potential known...... sources subsequently to be active were mapped to the supplementary motor area, premotor cortex, and motor cortex (M1), all in the left hemisphere. (C) 1998 Academic Press....

  8. Right inferior frontal gyrus activation is associated with memory improvement in patients with left frontal low-grade glioma resection.

    Directory of Open Access Journals (Sweden)

    Eliane C Miotto

    Full Text Available Patients with low-grade glioma (LGG have been studied as a model of functional brain reorganization due to their slow-growing nature. However, there is no information regarding which brain areas are involved during verbal memory encoding after extensive left frontal LGG resection. In addition, it remains unknown whether these patients can improve their memory performance after instructions to apply efficient strategies. The neural correlates of verbal memory encoding were investigated in patients who had undergone extensive left frontal lobe (LFL LGG resections and healthy controls using fMRI both before and after directed instructions were given for semantic organizational strategies. Participants were scanned during the encoding of word lists under three different conditions before and after a brief period of practice. The conditions included semantically unrelated (UR, related-non-structured (RNS, and related-structured words (RS, allowing for different levels of semantic organization. All participants improved on memory recall and semantic strategy application after the instructions for the RNS condition. Healthy subjects showed increased activation in the left inferior frontal gyrus (IFG and middle frontal gyrus (MFG during encoding for the RNS condition after the instructions. Patients with LFL excisions demonstrated increased activation in the right IFG for the RNS condition after instructions were given for the semantic strategies. Despite extensive damage in relevant areas that support verbal memory encoding and semantic strategy applications, patients that had undergone resections for LFL tumor could recruit the right-sided contralateral homologous areas after instructions were given and semantic strategies were practiced. These results provide insights into changes in brain activation areas typically implicated in verbal memory encoding and semantic processing.

  9. Right inferior frontal gyrus activation is associated with memory improvement in patients with left frontal low-grade glioma resection.

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    Miotto, Eliane C; Balardin, Joana B; Vieira, Gilson; Sato, Joao R; Martin, Maria da Graça M; Scaff, Milberto; Teixeira, Manoel J; Junior, Edson Amaro

    2014-01-01

    Patients with low-grade glioma (LGG) have been studied as a model of functional brain reorganization due to their slow-growing nature. However, there is no information regarding which brain areas are involved during verbal memory encoding after extensive left frontal LGG resection. In addition, it remains unknown whether these patients can improve their memory performance after instructions to apply efficient strategies. The neural correlates of verbal memory encoding were investigated in patients who had undergone extensive left frontal lobe (LFL) LGG resections and healthy controls using fMRI both before and after directed instructions were given for semantic organizational strategies. Participants were scanned during the encoding of word lists under three different conditions before and after a brief period of practice. The conditions included semantically unrelated (UR), related-non-structured (RNS), and related-structured words (RS), allowing for different levels of semantic organization. All participants improved on memory recall and semantic strategy application after the instructions for the RNS condition. Healthy subjects showed increased activation in the left inferior frontal gyrus (IFG) and middle frontal gyrus (MFG) during encoding for the RNS condition after the instructions. Patients with LFL excisions demonstrated increased activation in the right IFG for the RNS condition after instructions were given for the semantic strategies. Despite extensive damage in relevant areas that support verbal memory encoding and semantic strategy applications, patients that had undergone resections for LFL tumor could recruit the right-sided contralateral homologous areas after instructions were given and semantic strategies were practiced. These results provide insights into changes in brain activation areas typically implicated in verbal memory encoding and semantic processing.

  10. Role of the left frontal aslant tract in stuttering: a brain stimulation and tractographic study.

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    Kemerdere, Rahsan; de Champfleur, Nicolas Menjot; Deverdun, Jérémy; Cochereau, Jérôme; Moritz-Gasser, Sylvie; Herbet, Guillaume; Duffau, Hugues

    2016-01-01

    The neural correlates of stuttering are to date incompletely understood. Although the possible involvement of the basal ganglia, the cerebellum and certain parts of the cerebral cortex in this speech disorder has previously been reported, there are still not many studies investigating the role of white matter fibers in stuttering. Axonal stimulation during awake surgery provides a unique opportunity to study the functional role of structural connectivity. Here, our goal was to investigate the white matter tracts implicated in stuttering, by combining direct electrostimulation mapping and postoperative tractography imaging, with a special focus on the left frontal aslant tract. Eight patients with no preoperative stuttering underwent awake surgery for a left frontal low-grade glioma. Intraoperative cortical and axonal electrical mapping was used to interfere in speech processing and subsequently provoke stuttering. We further assessed the relationship between the subcortical sites leading to stuttering and the spatial course of the frontal aslant tract. All patients experienced intraoperative stuttering during axonal electrostimulation. On postsurgical tractographies, the subcortical distribution of stimulated sites matched the topographical position of the left frontal aslant tract. This white matter pathway was preserved during surgery, and no patients had postoperative stuttering. For the first time to our knowledge, by using direct axonal stimulation combined with postoperative tractography, we provide original data supporting a pivotal role of the left frontal aslant tract in stuttering. We propose that this speech disorder could be the result of a disconnection within a large-scale cortico-subcortical circuit subserving speech motor control.

  11. Convolutional neural networks for the detection of diseased hearts using CT images and left atrium patches

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    Dormer, James D.; Halicek, Martin; Ma, Ling; Reilly, Carolyn M.; Schreibmann, Eduard; Fei, Baowei

    2018-02-01

    Cardiovascular disease is a leading cause of death in the United States. The identification of cardiac diseases on conventional three-dimensional (3D) CT can have many clinical applications. An automated method that can distinguish between healthy and diseased hearts could improve diagnostic speed and accuracy when the only modality available is conventional 3D CT. In this work, we proposed and implemented convolutional neural networks (CNNs) to identify diseased hears on CT images. Six patients with healthy hearts and six with previous cardiovascular disease events received chest CT. After the left atrium for each heart was segmented, 2D and 3D patches were created. A subset of the patches were then used to train separate convolutional neural networks using leave-one-out cross-validation of patient pairs. The results of the two neural networks were compared, with 3D patches producing the higher testing accuracy. The full list of 3D patches from the left atrium was then classified using the optimal 3D CNN model, and the receiver operating curves (ROCs) were produced. The final average area under the curve (AUC) from the ROC curves was 0.840 +/- 0.065 and the average accuracy was 78.9% +/- 5.9%. This demonstrates that the CNN-based method is capable of distinguishing healthy hearts from those with previous cardiovascular disease.

  12. Using Convolutional Neural Network Filters to Measure Left-Right Mirror Symmetry in Images

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    Anselm Brachmann

    2016-12-01

    Full Text Available We propose a method for measuring symmetry in images by using filter responses from Convolutional Neural Networks (CNNs. The aim of the method is to model human perception of left/right symmetry as closely as possible. Using the Convolutional Neural Network (CNN approach has two main advantages: First, CNN filter responses closely match the responses of neurons in the human visual system; they take information on color, edges and texture into account simultaneously. Second, we can measure higher-order symmetry, which relies not only on color, edges and texture, but also on the shapes and objects that are depicted in images. We validated our algorithm on a dataset of 300 music album covers, which were rated according to their symmetry by 20 human observers, and compared results with those from a previously proposed method. With our method, human perception of symmetry can be predicted with high accuracy. Moreover, we demonstrate that the inclusion of features from higher CNN layers, which encode more abstract image content, increases the performance further. In conclusion, we introduce a model of left/right symmetry that closely models human perception of symmetry in CD album covers.

  13. Convolutional neural network regression for short-axis left ventricle segmentation in cardiac cine MR sequences.

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    Tan, Li Kuo; Liew, Yih Miin; Lim, Einly; McLaughlin, Robert A

    2017-07-01

    Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac function and morphology to aid subsequent management of cardiac pathologies. In this paper, we parameterize the complete (all short axis slices and phases) LV segmentation task in terms of the radial distances between the LV centerpoint and the endo- and epicardial contours in polar space. We then utilize convolutional neural network regression to infer these parameters. Utilizing parameter regression, as opposed to conventional pixel classification, allows the network to inherently reflect domain-specific physical constraints. We have benchmarked our approach primarily against the publicly-available left ventricle segmentation challenge (LVSC) dataset, which consists of 100 training and 100 validation cardiac MRI cases representing a heterogeneous mix of cardiac pathologies and imaging parameters across multiple centers. Our approach attained a .77 Jaccard index, which is the highest published overall result in comparison to other automated algorithms. To test general applicability, we also evaluated against the Kaggle Second Annual Data Science Bowl, where the evaluation metric was the indirect clinical measures of LV volume rather than direct myocardial contours. Our approach attained a Continuous Ranked Probability Score (CRPS) of .0124, which would have ranked tenth in the original challenge. With this we demonstrate the effectiveness of convolutional neural network regression paired with domain-specific features in clinical segmentation. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Specific marker of feigned memory impairment: The activation of left superior frontal gyrus.

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    Chen, Zi-Xiang; Xue, Li; Liang, Chun-Yu; Wang, Li-Li; Mei, Wei; Zhang, Qiang; Zhao, Hu

    2015-11-01

    Faking memory impairment means normal people complain lots of memory problems without organic damage in forensic assessments. Using alternative forced-choice paradigm, containing digital or autobiographical information, previous neuroimaging studies have indicated that faking memory impairment could cause the activation in the prefrontal and parietal regions, and might involve a fronto-parietal-subcortical circuit. However, it is still unclear whether different memory types have influence on faking or not. Since different memory types, such as long-term memory (LTM) and short-term memory (STM), were found supported by different brain areas, we hypothesized that feigned STM or LTM impairment had distinct neural activation mapping. Besides that, some common neural correlates may act as the general characteristic of feigned memory impairment. To verify this hypothesis, the functional magnetic resonance imaging (fMRI) combined with an alternative word forced-choice paradigm were used in this study. A total of 10 right-handed participants, in this study, had to perform both STW and LTM tasks respectively under answering correctly, answering randomly and feigned memory impairment conditions. Our results indicated that the activation of the left superior frontal gyrus and the left medial frontal gyrus was associated with feigned LTM impairment, whereas the left superior frontal gyrus, the left precuneus and the right anterior cingulate cortex (ACC) were highly activated while feigning STM impairment. Furthermore, an overlapping was found in the left superior frontal gyrus, and it suggested that the activity of the left superior frontal gyrus might be acting as a specific marker of feigned memory impairment. Copyright © 2015. Published by Elsevier Ltd.

  15. Functional and anatomical connectivity abnormalities in left inferior frontal gyrus in schizophrenia.

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    Jeong, Bumseok; Wible, Cynthia G; Hashimoto, Ryu-ichiro; Kubicki, Marek

    2009-12-01

    Functional studies in schizophrenia demonstrate prominent abnormalities within the left inferior frontal gyrus (IFG) and also suggest the functional connectivity abnormalities in language network including left IFG and superior temporal gyrus during semantic processing. White matter connections between regions involved in the semantic network have also been indicated in schizophrenia. However, an association between functional and anatomical connectivity disruptions within the semantic network in schizophrenia has not been established. Functional (using levels of processing paradigm) as well as diffusion tensor imaging data from 10 controls and 10 chronic schizophrenics were acquired and analyzed. First, semantic encoding specific activation was estimated, showing decreased activation within the left IFG in schizophrenia. Second, functional time series were extracted from this area, and left IFG specific functional connectivity maps were produced for each subject. In an independent analysis, tract-based spatial statistics (TBSS) was used to compare fractional anisotropy (FA) values between groups, and to correlate these values with functional connectivity maps. Schizophrenia patients showed weaker functional connectivity within the language network that includes left IFG and left superior temporal sulcus/middle temporal gyrus. FA was reduced in several white matter regions including left inferior frontal and left internal capsule. Finally, left inferior frontal white matter FA was positively correlated with connectivity measures of the semantic network in schizophrenics, but not in controls. Our results indicate an association between anatomical and functional connectivity abnormalities within the semantic network in schizophrenia, suggesting further that the functional abnormalities observed in this disorder might be directly related to white matter disruptions. 2009 Wiley-Liss, Inc.

  16. Memory of music: roles of right hippocampus and left inferior frontal gyrus.

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    Watanabe, Takamitsu; Yagishita, Sho; Kikyo, Hideyuki

    2008-01-01

    We investigated neural correlates of retrieval success for music memory using event-related functional magnetic resonance imaging. To minimize the interference from MRI scan noise, we used sparse temporal sampling technique. Newly composed music materials were employed as stimuli, which enabled us to detect regions in absence of effects of experience with the music stimuli in this study. Whole brain analyses demonstrated significant retrieval success activities in the right hippocampus, bilateral lateral temporal regions, left inferior frontal gyrus and left precuneus. Anatomically defined region-of-interests analyses showed that the activity of the right hippocampus was stronger than that of the left, while the activities of the inferior frontal gyri showed the reverse pattern. Furthermore, performance-based analyses demonstrated that the retrieval success activity of the right hippocampus was positively correlated with the corrected recognition rate, suggesting that the right hippocampus contributes to the accuracy of music retrieval outcome.

  17. Are orchids left and dandelions right? Frontal brain activation asymmetry and its sensitivity to developmental context.

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    Fortier, Paz; Van Lieshout, Ryan J; Waxman, Jordana A; Boyle, Michael H; Saigal, Saroj; Schmidt, Louis A

    2014-08-01

    To clarify long-standing conceptual and empirical inconsistencies in models describing the relation between frontal brain asymmetry and emotion, we tested a theory of biological sensitivity to context. We examined whether asymmetry of alpha activation in frontal brain regions, as measured by resting electroencephalography, is sensitive to early developmental contexts. Specifically, we investigated whether frontal asymmetry moderates the association between birth weight and adult outcomes. Adults with left frontal asymmetry (LFA) who were born at extremely low birth weight exhibited high levels of attention problems and withdrawn behaviors in their 30s, whereas normal-birth-weight adults with LFA had low levels of these problem behaviors. Adults with right frontal asymmetry (RFA) displayed a relatively moderate amount of problem behavior regardless of birth weight. Our findings suggest that LFA is associated with sensitivity to developmental context and may help explain why LFA is associated with both positive and negative outcomes, whereas RFA seems to be associated with a more canalized process in some contexts. © The Author(s) 2014.

  18. Behavioral approach system sensitivity and risk taking interact to predict left-frontal EEG asymmetry.

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    Black, Chelsea L; Goldstein, Kim E; LaBelle, Denise R; Brown, Christopher W; Harmon-Jones, Eddie; Abramson, Lyn Y; Alloy, Lauren B

    2014-09-01

    The Behavioral Approach System (BAS) hypersensitivity theory of bipolar disorder (BD; Alloy & Abramson, 2010; Depue & Iacono, 1989) suggests that hyperreactivity in the BAS results in the extreme fluctuations of mood characteristic of BD. In addition to risk conferred by BAS hypersensitivity, cognitive and personality variables may play a role in determining risk. We evaluated relationships among BAS sensitivity, risk taking, and an electrophysiological correlate of approach motivation, relative left-frontal electroencephalography (EEG) asymmetry. BAS sensitivity moderated the relationship between risk taking and EEG asymmetry. More specifically, individuals who were high in BAS sensitivity showed left-frontal EEG asymmetry regardless of their level of risk-taking behavior. However, among individuals who were moderate in BAS sensitivity, risk taking was positively associated with asymmetry. These findings suggest that cognitive and personality correlates of bipolar risk may evidence unique contributions to a neural measure of trait-approach motivation. Clinical implications of these findings are discussed. Copyright © 2014. Published by Elsevier Ltd.

  19. Modulating phonemic fluency performance in healthy subjects with transcranial magnetic stimulation over the left or right lateral frontal cortex.

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    Smirni, Daniela; Turriziani, Patrizia; Mangano, Giuseppa Renata; Bracco, Martina; Oliveri, Massimiliano; Cipolotti, Lisa

    2017-07-28

    A growing body of evidence have suggested that non-invasive brain stimulation techniques, such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), can improve the performance of aphasic patients in language tasks. For example, application of inhibitory rTMS or tDCs over the right frontal lobe of dysphasic patients resulted in improved naming abilities. Several studies have also reported that in healthy controls (HC) tDCS application over the left prefrontal cortex (PFC) improve performance in naming and semantic fluency tasks. The aim of this study was to investigate in HC, for the first time, the effects of inhibitory repetitive TMS (rTMS) over left and right lateral frontal cortex (BA 47) on two phonemic fluency tasks (FAS or FPL). 44 right-handed HCs were administered rTMS or sham over the left or right lateral frontal cortex in two separate testing sessions, with a 24h interval, followed by the two phonemic fluency tasks. To account for possible practice effects, an additional 22 HCs were tested on only the phonemic fluency task across two sessions with no stimulation. We found that rTMS-inhibition over the left lateral frontal cortex significantly worsened phonemic fluency performance when compared to sham. In contrast, rTMS-inhibition over the right lateral frontal cortex significantly improved phonemic fluency performance when compared to sham. These results were not accounted for practice effects. We speculated that rTMS over the right lateral frontal cortex may induce plastic neural changes to the left lateral frontal cortex by suppressing interhemispheric inhibitory interactions. This resulted in an increased excitability (disinhibition) of the contralateral unstimulated left lateral frontal cortex, consequently enhancing phonemic fluency performance. Conversely, application of rTMS over the left lateral frontal cortex may induce a temporary, virtual lesion, with effects similar to those reported in left frontal

  20. Automatic detection of anatomical regions in frontal x-ray images: comparing convolutional neural networks to random forest

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    Olory Agomma, R.; Vázquez, C.; Cresson, T.; De Guise, J.

    2018-02-01

    Most algorithms to detect and identify anatomical structures in medical images require either to be initialized close to the target structure, or to know that the structure is present in the image, or to be trained on a homogeneous database (e.g. all full body or all lower limbs). Detecting these structures when there is no guarantee that the structure is present in the image, or when the image database is heterogeneous (mixed configurations), is a challenge for automatic algorithms. In this work we compared two state-of-the-art machine learning techniques in order to determine which one is the most appropriate for predicting targets locations based on image patches. By knowing the position of thirteen landmarks points, labelled by an expert in EOS frontal radiography, we learn the displacement between salient points detected in the image and these thirteen landmarks. The learning step is carried out with a machine learning approach by exploring two methods: Convolutional Neural Network (CNN) and Random Forest (RF). The automatic detection of the thirteen landmarks points in a new image is then obtained by averaging the positions of each one of these thirteen landmarks estimated from all the salient points in the new image. We respectively obtain for CNN and RF, an average prediction error (both mean and standard deviation in mm) of 29 +/-18 and 30 +/- 21 for the thirteen landmarks points, indicating the approximate location of anatomical regions. On the other hand, the learning time is 9 days for CNN versus 80 minutes for RF. We provide a comparison of the results between the two machine learning approaches.

  1. Mirror Neurons, the Representation of Word meaning, and the Foot of the Third Left Frontal Convolution

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    de Zubicaray, Greig; Postle, Natasha; McMahon, Katie; Meredith, Matthew; Ashton, Roderick

    2010-01-01

    Previous neuroimaging research has attempted to demonstrate a preferential involvement of the human mirror neuron system (MNS) in the comprehension of effector-related action word (verb) meanings. These studies have assumed that Broca's area (or Brodmann's area 44) is the homologue of a monkey premotor area (F5) containing mouth and hand mirror…

  2. Elevated left mid-frontal cortical activity prospectively predicts conversion to bipolar I disorder

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    Nusslock, Robin; Harmon-Jones, Eddie; Alloy, Lauren B.; Urosevic, Snezana; Goldstein, Kim; Abramson, Lyn Y.

    2013-01-01

    Bipolar disorder is characterized by a hypersensitivity to reward-relevant cues and a propensity to experience an excessive increase in approach-related affect, which may be reflected in hypo/manic symptoms. The present study examined the relationship between relative left-frontal electroencephalographic (EEG) activity, a proposed neurophysiological index of approach-system sensitivity and approach/reward-related affect, and bipolar course and state-related variables. Fifty-eight individuals with cyclothymia or bipolar II disorder and 59 healthy control participants with no affective psychopathology completed resting EEG recordings. Alpha power was obtained and asymmetry indices computed for homologous electrodes. Bipolar spectrum participants were classified as being in a major/minor depressive episode, a hypomanic episode, or a euthymic/remitted state at EEG recording. Participants were then followed prospectively for an average 4.7 year follow-up period with diagnostic interview assessments every four-months. Sixteen bipolar spectrum participants converted to bipolar I disorder during follow-up. Consistent with hypotheses, elevated relative left-frontal EEG activity at baseline 1) prospectively predicted a greater likelihood of converting from cyclothymia or bipolar II disorder to bipolar I disorder over the 4.7 year follow-up period, 2) was associated with an earlier age-of-onset of first bipolar spectrum episode, and 3) was significantly elevated in bipolar spectrum individuals in a hypomanic episode at EEG recording. This is the first study to identify a neurophysiological marker that prospectively predicts conversion to bipolar I disorder. The fact that unipolar depression is characterized by decreased relative left-frontal EEG activity suggests that unipolar depression and vulnerability to hypo/mania may be characterized by different profiles of frontal EEG asymmetry. PMID:22775582

  3. Statistical parametric mapping for analyzing interictal magnetoencephalography in patients with left frontal lobe epilepsy.

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    Zhu, Haitao; Zhu, Jinlong; Bao, Forrest Sheng; Liu, Hongyi; Zhu, Xuchuang; Wu, Ting; Yang, Lu; Zou, Yuanjie; Zhang, Rui; Zheng, Gang

    2016-01-01

    Frontal lobe epilepsy is a common epileptic disorder and is characterized by recurring seizures that arise in the frontal lobes. The purpose of this study is to identify the epileptogenic regions and other abnormal regions in patients with left frontal lobe epilepsy (LFLE) based on the magnetoencephalogram (MEG), and to understand the effects of clinical variables on brain activities in patients with LFLE. Fifteen patients with LFLE (23.20 ± 8.68 years, 6 female and 9 male) and 16 healthy controls (23.13 ± 7.66 years, 6 female and 10 male) were included in resting-stage MEG examinations. Epileptogenic regions of LFLE patients were confirmed by surgery. Regional brain activations were quantified using statistical parametric mapping (SPM). The correlation between the activations of the abnormal brain regions and the clinical seizure parameters were computed for LFLE patients. Brain activations of LFLE patients were significantly elevated in left superior/middle/inferior frontal gyri, postcentral gyrus, inferior temporal gyrus, insula, parahippocampal gyrus and amygdala, including the epileptogenic regions. Remarkable decreased activations were found mainly in the left parietal gyrus and precuneus. There is a positive correlation between the duration of the epilepsy (in month) and activations of the abnormal regions, while no relation was found between age of seizure onset (year), seizure frequency and the regions of the abnormal activity of the epileptic patients. Our findings suggest that the aberrant brain activities of LFLE patients were not restricted to the epileptogenic zones. Long duration of epilepsy might induce further functional damage in patients with LFLE. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

  4. Accurate external localization of the left frontal cortex in dogs by using pointer based frameless neuronavigation

    Directory of Open Access Journals (Sweden)

    Robrecht Dockx

    2017-07-01

    Full Text Available Background In humans, non-stereotactic frameless neuronavigation systems are used as a topographical tool for non-invasive brain stimulation methods such as Transcranial Magnetic Stimulation (TMS. TMS studies in dogs may provide treatment modalities for several neuropsychological disorders in dogs. Nevertheless, an accurate non-invasive localization of a stimulation target has not yet been performed in this species. Hypothesis This study was primarily put forward to externally locate the left frontal cortex in 18 healthy dogs by means of a human non-stereotactic neuronavigation system. Secondly, the accuracy of the external localization was assessed. Animals A total of 18 healthy dogs, drawn at random from the research colony present at the faculty of Veterinary Medicine (Ghent University, were used. Methods Two sets of coordinates (X, Y, Z and X″, Y″, Z″ were compared on each dog their tomographical dataset. Results The non-stereotactic neuronavigation system was able to externally locate the frontal cortex in dogs with accuracy comparable with human studies. Conclusion and clinical importance This result indicates that a non-stereotactic neuronavigation system can accurately externally locate the left frontal cortex and paves the way to use guided non-invasive brain stimulation methods as an alternative treatment procedure for neurological and behavioral disorders in dogs. This technique could, in analogy with human guided non-invasive brain stimulation, provide a better treatment outcome for dogs suffering from anxiety disorders when compared to its non-guided alternative.

  5. Enhanced activation of the left inferior frontal gyrus in deaf and dyslexic adults during rhyming.

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    MacSweeney, Mairéad; Brammer, Michael J; Waters, Dafydd; Goswami, Usha

    2009-07-01

    Hearing developmental dyslexics and profoundly deaf individuals both have difficulties processing the internal structure of words (phonological processing) and learning to read. In hearing non-impaired readers, the development of phonological representations depends on audition. In hearing dyslexics, many argue, auditory processes may be impaired. In congenitally profoundly deaf individuals, auditory speech processing is essentially absent. Two separate literatures have previously reported enhanced activation in the left inferior frontal gyrus in both deaf and dyslexic adults when contrasted with hearing non-dyslexics during reading or phonological tasks. Here, we used a rhyme judgement task to compare adults from these two special populations to a hearing non-dyslexic control group. All groups were matched on non-verbal intelligence quotient, reading age and rhyme performance. Picture stimuli were used since this requires participants to generate their own phonological representations, rather than have them partially provided via text. By testing well-matched groups of participants on the same task, we aimed to establish whether previous literatures reporting differences between individuals with and without phonological processing difficulties have identified the same regions of differential activation in these two distinct populations. The data indicate greater activation in the deaf and dyslexic groups than in the hearing non-dyslexic group across a large portion of the left inferior frontal gyrus. This includes the pars triangularis, extending superiorly into the middle frontal gyrus and posteriorly to include the pars opercularis, and the junction with the ventral precentral gyrus. Within the left inferior frontal gyrus, there was variability between the two groups with phonological processing difficulties. The superior posterior tip of the left pars opercularis, extending into the precentral gyrus, was activated to a greater extent by deaf than dyslexic

  6. Left ventricle segmentation in cardiac MRI images using fully convolutional neural networks

    Science.gov (United States)

    Vázquez Romaguera, Liset; Costa, Marly Guimarães Fernandes; Romero, Francisco Perdigón; Costa Filho, Cicero Ferreira Fernandes

    2017-03-01

    According to the World Health Organization, cardiovascular diseases are the leading cause of death worldwide, accounting for 17.3 million deaths per year, a number that is expected to grow to more than 23.6 million by 2030. Most cardiac pathologies involve the left ventricle; therefore, estimation of several functional parameters from a previous segmentation of this structure can be helpful in diagnosis. Manual delineation is a time consuming and tedious task that is also prone to high intra and inter-observer variability. Thus, there exists a need for automated cardiac segmentation method to help facilitate the diagnosis of cardiovascular diseases. In this work we propose a deep fully convolutional neural network architecture to address this issue and assess its performance. The model was trained end to end in a supervised learning stage from whole cardiac MRI images input and ground truth to make a per pixel classification. For its design, development and experimentation was used Caffe deep learning framework over an NVidia Quadro K4200 Graphics Processing Unit. The net architecture is: Conv64-ReLU (2x) - MaxPooling - Conv128-ReLU (2x) - MaxPooling - Conv256-ReLU (2x) - MaxPooling - Conv512-ReLu-Dropout (2x) - Conv2-ReLU - Deconv - Crop - Softmax. Training and testing processes were carried out using 5-fold cross validation with short axis cardiac magnetic resonance images from Sunnybrook Database. We obtained a Dice score of 0.92 and 0.90, Hausdorff distance of 4.48 and 5.43, Jaccard index of 0.97 and 0.97, sensitivity of 0.92 and 0.90 and specificity of 0.99 and 0.99, overall mean values with SGD and RMSProp, respectively.

  7. Palilalia, echolalia, and echopraxia-palipraxia as ictal manifestations in a patient with left frontal lobe epilepsy.

    Science.gov (United States)

    Cho, Yang-Je; Han, Sang-Don; Song, Sook Keun; Lee, Byung In; Heo, Kyoung

    2009-06-01

    Palilalia is a relatively rare pathologic speech behavior and has been reported in various neurologic and psychiatric disorders. We encountered a case of palilalia, echolalia, and echopraxia-palipraxia as ictal phenomena of left frontal lobe epilepsy. A 55-year-old, right-handed man was admitted because of frequent episodes of rapid reiteration of syllables. Video-electroencephalography monitoring revealed stereotypical episodes of palilalia accompanied by rhythmic head nodding and right-arm posturing with ictal discharges over the left frontocentral area. He also displayed echolalia or echopraxia-palipraxia, partially responding to an examiner's stimulus. Magnetic resonance imaging revealed encephalomalacia on the left superior frontal gyrus and ictal single photon emission computed tomography showed hyperperfusion just above the lesion, corresponding to the left supplementary motor area (SMA), and subcortical nuclei. This result suggests that the neuroanatomic substrate involved in the generation of these behaviors as ictal phenomena might exist in the SMA of the left frontal lobe.

  8. Subliminal semantic priming changes the dynamic causal influence between the left frontal and temporal cortex.

    Science.gov (United States)

    Matsumoto, Atsushi; Kakigi, Ryusuke

    2014-01-01

    Recent neuroimaging experiments have revealed that subliminal priming of a target stimulus leads to the reduction of neural activity in specific regions concerned with processing the target. Such findings lead to questions about the degree to which the subliminal priming effect is based only on decreased activity in specific local brain regions, as opposed to the influence of neural mechanisms that regulate communication between brain regions. To address this question, this study recorded EEG during performance of a subliminal semantic priming task. We adopted an information-based approach that used independent component analysis and multivariate autoregressive modeling. Results indicated that subliminal semantic priming caused significant modulation of alpha band activity in the left inferior frontal cortex and modulation of gamma band activity in the left inferior temporal regions. The multivariate autoregressive approach confirmed significant increases in information flow from the inferior frontal cortex to inferior temporal regions in the early time window that was induced by subliminal priming. In the later time window, significant enhancement of bidirectional causal flow between these two regions underlying subliminal priming was observed. Results suggest that unconscious processing of words influences not only local activity of individual brain regions but also the dynamics of neural communication between those regions.

  9. Working memory and the identification of facial expression in patients with left frontal glioma.

    Science.gov (United States)

    Mu, Yong-Gao; Huang, Ling-Juan; Li, Shi-Yun; Ke, Chao; Chen, Yu; Jin, Yu; Chen, Zhong-Ping

    2012-09-01

    Patients with brain tumors may have cognitive dysfunctions including memory deterioration, such as working memory, that affect quality of life. This study was to explore the presence of defects in working memory and the identification of facial expressions in patients with left frontal glioma. This case-control study recruited 11 matched pairs of patients and healthy control subjects (mean age ± standard deviation, 37.00 ± 10.96 years vs 36.73 ± 11.20 years; 7 male and 4 female) from March through December 2011. The psychological tests contained tests that estimate verbal/visual-spatial working memory, executive function, and the identification of facial expressions. According to the paired samples analysis, there were no differences in the anxiety and depression scores or in the intelligence quotients between the 2 groups (P > .05). All indices of the Digit Span Test were significantly worse in patients than in control subjects (P patient and control groups. Of all 7 Wisconsin Card Sorting Test (WCST) indexes, only the Preservative Response was significantly different between patients and control subjects (P Patients were significantly less accurate in detecting angry facial expressions than were control subjects (30.3% vs 57.6%; P identification of other expressions. The backward indexes of the Digit Span Test were associated with emotion scores and tumor size and grade (P Patients with left frontal glioma had deficits in verbal working memory and the ability to identify anger. These may have resulted from damage to functional frontal cortex regions, in which roles in these 2 capabilities have not been confirmed. However, verbal working memory performance might be affected by emotional and tumor-related factors.

  10. Facilitation of speech repetition accuracy by theta burst stimulation of the left posterior inferior frontal gyrus.

    Science.gov (United States)

    Restle, Julia; Murakami, Takenobu; Ziemann, Ulf

    2012-07-01

    The posterior part of the inferior frontal gyrus (pIFG) in the left hemisphere is thought to form part of the putative human mirror neuron system and is assigned a key role in mapping sensory perception onto motor action. Accordingly, the pIFG is involved in motor imitation of the observed actions of others but it is not known to what extent speech repetition of auditory-presented sentences is also a function of the pIFG. Here we applied fMRI-guided facilitating intermittent theta burst transcranial magnetic stimulation (iTBS), or depressant continuous TBS (cTBS), or intermediate TBS (imTBS) over the left pIFG of healthy subjects and compared speech repetition accuracy of foreign Japanese sentences before and after TBS. We found that repetition accuracy improved after iTBS and, to a lesser extent, after imTBS, but remained unchanged after cTBS. In a control experiment, iTBS was applied over the left middle occipital gyrus (MOG), a region not involved in sensorimotor processing of auditory-presented speech. Repetition accuracy remained unchanged after iTBS of MOG. We argue that the stimulation type and stimulation site specific facilitating effect of iTBS over left pIFG on speech repetition accuracy indicates a causal role of the human left-hemispheric pIFG in the translation of phonological perception to motor articulatory output for repetition of speech. This effect may prove useful in rehabilitation strategies that combine repetitive speech training with iTBS of the left pIFG in speech disorders, such as aphasia after cerebral stroke. Copyright © 2012 Elsevier Ltd. All rights reserved.

  11. Reasoning by analogy requires the left frontal pole: lesion-deficit mapping and clinical implications.

    Science.gov (United States)

    Urbanski, Marika; Bréchemier, Marie-Laure; Garcin, Béatrice; Bendetowicz, David; Thiebaut de Schotten, Michel; Foulon, Chris; Rosso, Charlotte; Clarençon, Frédéric; Dupont, Sophie; Pradat-Diehl, Pascale; Labeyrie, Marc-Antoine; Levy, Richard; Volle, Emmanuelle

    2016-06-01

    SEE BURGESS DOI101093/BRAIN/AWW092 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE  : Analogical reasoning is at the core of the generalization and abstraction processes that enable concept formation and creativity. The impact of neurological diseases on analogical reasoning is poorly known, despite its importance in everyday life and in society. Neuroimaging studies of healthy subjects and the few studies that have been performed on patients have highlighted the importance of the prefrontal cortex in analogical reasoning. However, the critical cerebral bases for analogical reasoning deficits remain elusive. In the current study, we examined analogical reasoning abilities in 27 patients with focal damage in the frontal lobes and performed voxel-based lesion-behaviour mapping and tractography analyses to investigate the structures critical for analogical reasoning. The findings revealed that damage to the left rostrolateral prefrontal region (or some of its long-range connections) specifically impaired the ability to reason by analogies. A short version of the analogy task predicted the existence of a left rostrolateral prefrontal lesion with good accuracy. Experimental manipulations of the analogy tasks suggested that this region plays a role in relational matching or integration. The current lesion approach demonstrated that the left rostrolateral prefrontal region is a critical node in the analogy network. Our results also suggested that analogy tasks should be translated to clinical practice to refine the neuropsychological assessment of patients with frontal lobe lesions. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  12. Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer’s disease

    Science.gov (United States)

    Franzmeier, Nicolai; Düzel, Emrah; Jessen, Frank; Buerger, Katharina; Levin, Johannes; Duering, Marco; Dichgans, Martin; Haass, Christian; Suárez-Calvet, Marc; Fagan, Anne M; Paumier, Katrina; Benzinger, Tammie; Masters, Colin L; Morris, John C; Perneczky, Robert; Janowitz, Daniel; Catak, Cihan; Wolfsgruber, Steffen; Wagner, Michael; Teipel, Stefan; Kilimann, Ingo; Ramirez, Alfredo; Rossor, Martin; Jucker, Mathias; Chhatwal, Jasmeer; Spottke, Annika; Boecker, Henning; Brosseron, Frederic; Falkai, Peter; Fliessbach, Klaus; Heneka, Michael T; Laske, Christoph; Nestor, Peter; Peters, Oliver; Fuentes, Manuel; Menne, Felix; Priller, Josef; Spruth, Eike J; Franke, Christiana; Schneider, Anja; Kofler, Barbara; Westerteicher, Christine; Speck, Oliver; Wiltfang, Jens; Bartels, Claudia; Araque Caballero, Miguel Ángel; Metzger, Coraline; Bittner, Daniel; Weiner, Michael; Lee, Jae-Hong; Salloway, Stephen; Danek, Adrian; Goate, Alison; Schofield, Peter R; Bateman, Randall J; Ewers, Michael

    2018-01-01

    Abstract Patients with Alzheimer’s disease vary in their ability to sustain cognitive abilities in the presence of brain pathology. A major open question is which brain mechanisms may support higher reserve capacity, i.e. relatively high cognitive performance at a given level of Alzheimer’s pathology. Higher functional MRI-assessed functional connectivity of a hub in the left frontal cortex is a core candidate brain mechanism underlying reserve as it is associated with education (i.e. a protective factor often associated with higher reserve) and attenuated cognitive impairment in prodromal Alzheimer’s disease. However, no study has yet assessed whether such hub connectivity of the left frontal cortex supports reserve throughout the evolution of pathological brain changes in Alzheimer’s disease, including the presymptomatic stage when cognitive decline is subtle. To address this research gap, we obtained cross-sectional resting state functional MRI in 74 participants with autosomal dominant Alzheimer’s disease, 55 controls from the Dominantly Inherited Alzheimer’s Network and 75 amyloid-positive elderly participants, as well as 41 amyloid-negative cognitively normal elderly subjects from the German Center of Neurodegenerative Diseases multicentre study on biomarkers in sporadic Alzheimer’s disease. For each participant, global left frontal cortex connectivity was computed as the average resting state functional connectivity between the left frontal cortex (seed) and each voxel in the grey matter. As a marker of disease stage, we applied estimated years from symptom onset in autosomal dominantly inherited Alzheimer’s disease and cerebrospinal fluid tau levels in sporadic Alzheimer’s disease cases. In both autosomal dominant and sporadic Alzheimer’s disease patients, higher levels of left frontal cortex connectivity were correlated with greater education. For autosomal dominant Alzheimer’s disease, a significant left frontal cortex connectivity

  13. [Hyperlexia in an adult patient with lesions in the left medial frontal lobe].

    Science.gov (United States)

    Suzuki, K; Yamadori, A; Kumabe, T; Endo, K; Fujii, T; Yoshimoto, T

    2000-04-01

    A 69-year-old right-handed woman developed a transcortical motor aphasia with hyperlexia following resection of a glioma in the left medial frontal lobe. Neurological examination revealed grasp reflex in the right hand and underutilization of the right upper extremity. An MRI demonstrated lesions in the left medial frontal lobe including the supplementary motor area and the anterior part of the cingulate gyrus, which extended to the anterior part of the body of corpus callosum. Neuropsychologically she was alert and cooperative. She demonstrated transcortical motor aphasia. Her verbal output began with echolalia. Furthermore hyperlexia was observed in daily activities and during examinations. During conversation she suddenly read words written on objects around her which were totally irrelevant to the talk. When she was walking in the ward with an examiner she read words written on a trash bag that passed by and signboards which indicated a name of a room. Her conversation while walking was intermingled with reading words, which was irrelevant to the conversation. She also read time on analog clocks, which were hung on a wall in a watch store. In a naming task, she read words written on objects first and named them upon repeated question about their names. When an examiner opened a newspaper in front of her without any instructions she began reading until the examiner prohibited it. Then she began reading again when an examiner turned the page, although she remembered that she should not read it aloud. She showed mild ideomotor apraxia of a left hand. Utilization behavior, imitation behavior, hypergraphia, or compulsive use of objects was not observed throughout the course. Hyperlexic tendency is a prominent feature of this patient's language output. Hyperlexia was often reported in children with pervasive developmental disorders including autism. There are only a few reports about hyperlexia in adults and some of them were related to diffuse brain dysfunction

  14. Functions of the left superior frontal gyrus in humans: a lesion study.

    Science.gov (United States)

    du Boisgueheneuc, Foucaud; Levy, Richard; Volle, Emmanuelle; Seassau, Magali; Duffau, Hughes; Kinkingnehun, Serge; Samson, Yves; Zhang, Sandy; Dubois, Bruno

    2006-12-01

    The superior frontal gyrus (SFG) is thought to contribute to higher cognitive functions and particularly to working memory (WM), although the nature of its involvement remains a matter of debate. To resolve this issue, methodological tools such as lesion studies are needed to complement the functional imaging approach. We have conducted the first lesion study to investigate the role of the SFG in WM and address the following questions: do lesions of the SFG impair WM and, if so, what is the nature of the WM impairment? To answer these questions, we compared the performance of eight patients with a left prefrontal lesion restricted to the SFG with that of a group of 11 healthy control subjects and two groups of patients with focal brain lesions [prefrontal lesions sparing the SFG (n = 5) and right parietal lesions (n = 4)] in a series of WM tasks. The WM tasks (derived from the classical n-back paradigm) allowed us to study the impact of the SFG lesions on domain (verbal, spatial, face) and complexity (1-, 2- and 3-back) processing within WM. As expected, patients with a left SFG lesion exhibited a WM deficit when compared with all control groups, and the impairment increased with the complexity of the tasks. This complexity effect was significantly more marked for the spatial domain. Voxel-to-voxel mapping of each subject's performance showed that the lateral and posterior portion of the SFG (mostly Brodmann area 8, rostral to the frontal eye field) was the subregion that contributed the most to the WM impairment. These data led us to conclude that (i) the lateral and posterior portion of the left SFG is a key component of the neural network of WM; (ii) the participation of this region in WM is triggered by the highest level of executive processing; (iii) the left SFG is also involved in spatially oriented processing. Our findings support a hybrid model of the anatomical and functional organization of the lateral SFG for WM, according to which this region is

  15. Perturbation of the left inferior frontal gyrus triggers adaptive plasticity in the right homologous area during speech production

    OpenAIRE

    Hartwigsen, Gesa; Saur, Dorothee; Price, Cathy J.; Ulmer, Stephan; Baumgaertner, Annette; Siebner, Hartwig R.

    2013-01-01

    The role of the right hemisphere in aphasia recovery is unclear. We demonstrate that a virtual lesion of left inferior frontal gyrus (IFG) decreased activity in the targeted area and increased activity in the contralateral homologous area during pseudoword repetition. This was associated with a stronger facilitatory drive from the right IFG to the left IFG. Importantly, responses became faster with increased influence of the right IFG on the left IFG. Our results shed new light on the dynamic...

  16. Effects of childhood trauma on left inferior frontal gyrus function during response inhibition across psychotic disorders.

    Science.gov (United States)

    Quidé, Y; O'Reilly, N; Watkeys, O J; Carr, V J; Green, M J

    2018-07-01

    Childhood trauma is a risk factor for psychosis. Deficits in response inhibition are common to psychosis and trauma-exposed populations, and associated brain functions may be affected by trauma exposure in psychotic disorders. We aimed to identify the influence of trauma-exposure on brain activation and functional connectivity during a response inhibition task. We used functional magnetic resonance imaging to examine brain function within regions-of-interest [left and right inferior frontal gyrus (IFG), right dorsolateral prefrontal cortex, right supplementary motor area, right inferior parietal lobule and dorsal anterior cingulate cortex], during the performance of a Go/No-Go Flanker task, in 112 clinical cases with psychotic disorders and 53 healthy controls (HCs). Among the participants, 71 clinical cases and 21 HCs reported significant levels of childhood trauma exposure, while 41 clinical cases and 32 HCs did not. In the absence of effects on response inhibition performance, childhood trauma exposure was associated with increased activation in the left IFG, and increased connectivity between the left IFG seed region and the cerebellum and calcarine sulcus, in both cases and healthy individuals. There was no main effect of psychosis, and no trauma-by-psychosis interaction for any other region-of-interest. Within the clinical sample, the effects of trauma-exposure on the left IFG activation were mediated by symptom severity. Trauma-related increases in activation of the left IFG were not associated with performance differences, or dependent on clinical diagnostic status; increased IFG functionality may represent a compensatory (overactivation) mechanism required to exert adequate inhibitory control of the motor response.

  17. Segmentation of left ventricle myocardium in porcine cardiac cine MR images using a hybrid of fully convolutional neural networks and convolutional LSTM

    Science.gov (United States)

    Zhang, Dongqing; Icke, Ilknur; Dogdas, Belma; Parimal, Sarayu; Sampath, Smita; Forbes, Joseph; Bagchi, Ansuman; Chin, Chih-Liang; Chen, Antong

    2018-03-01

    In the development of treatments for cardiovascular diseases, short axis cardiac cine MRI is important for the assessment of various structural and functional properties of the heart. In short axis cardiac cine MRI, Cardiac properties including the ventricle dimensions, stroke volume, and ejection fraction can be extracted based on accurate segmentation of the left ventricle (LV) myocardium. One of the most advanced segmentation methods is based on fully convolutional neural networks (FCN) and can be successfully used to do segmentation in cardiac cine MRI slices. However, the temporal dependency between slices acquired at neighboring time points is not used. Here, based on our previously proposed FCN structure, we proposed a new algorithm to segment LV myocardium in porcine short axis cardiac cine MRI by incorporating convolutional long short-term memory (Conv-LSTM) to leverage the temporal dependency. In this approach, instead of processing each slice independently in a conventional CNN-based approach, the Conv-LSTM architecture captures the dynamics of cardiac motion over time. In a leave-one-out experiment on 8 porcine specimens (3,600 slices), the proposed approach was shown to be promising by achieving average mean Dice similarity coefficient (DSC) of 0.84, Hausdorff distance (HD) of 6.35 mm, and average perpendicular distance (APD) of 1.09 mm when compared with manual segmentations, which improved the performance of our previous FCN-based approach (average mean DSC=0.84, HD=6.78 mm, and APD=1.11 mm). Qualitatively, our model showed robustness against low image quality and complications in the surrounding anatomy due to its ability to capture the dynamics of cardiac motion.

  18. Prominence vs. aboutness in sequencing: a functional distinction within the left inferior frontal gyrus.

    Science.gov (United States)

    Bornkessel-Schlesewsky, Ina; Grewe, Tanja; Schlesewsky, Matthias

    2012-02-01

    Prior research on the neural bases of syntactic comprehension suggests that activation in the left inferior frontal gyrus (lIFG) correlates with the processing of word order variations. However, there are inconsistencies with respect to the specific subregion within the IFG that is implicated by these findings: the pars opercularis or the pars triangularis. Here, we examined the hypothesis that the dissociation between pars opercularis and pars triangularis activation may reflect functional differences between clause-medial and clause-initial word order permutations, respectively. To this end, we directly compared clause-medial and clause-initial object-before-subject orders in German in a within-participants, event-related fMRI design. Our results showed increased activation for object-initial sentences in a bilateral network of frontal, temporal and subcortical regions. Within the lIFG, posterior and inferior subregions showed only a main effect of word order, whereas more anterior and superior subregions showed effects of word order and sentence type, with higher activation for sentences with an argument in the clause-initial position. These findings are interpreted as evidence for a functional gradation of sequence processing within the left IFG: posterior subportions correlate with argument prominence-based (local) aspects of sequencing, while anterior subportions correlate with aboutness-based aspects of sequencing, which are crucial in linking the current sentence to the wider discourse. This proposal appears compatible with more general hypotheses about information processing gradients in prefrontal cortex (Koechlin & Summerfield, 2007). Copyright © 2010 Elsevier Inc. All rights reserved.

  19. Repetition Suppression in the Left Inferior Frontal Gyrus Predicts Tone Learning Performance.

    Science.gov (United States)

    Asaridou, Salomi S; Takashima, Atsuko; Dediu, Dan; Hagoort, Peter; McQueen, James M

    2016-06-01

    Do individuals differ in how efficiently they process non-native sounds? To what extent do these differences relate to individual variability in sound-learning aptitude? We addressed these questions by assessing the sound-learning abilities of Dutch native speakers as they were trained on non-native tone contrasts. We used fMRI repetition suppression to the non-native tones to measure participants' neuronal processing efficiency before and after training. Although all participants improved in tone identification with training, there was large individual variability in learning performance. A repetition suppression effect to tone was found in the bilateral inferior frontal gyri (IFGs) before training. No whole-brain effect was found after training; a region-of-interest analysis, however, showed that, after training, repetition suppression to tone in the left IFG correlated positively with learning. That is, individuals who were better in learning the non-native tones showed larger repetition suppression in this area. Crucially, this was true even before training. These findings add to existing evidence that the left IFG plays an important role in sound learning and indicate that individual differences in learning aptitude stem from differences in the neuronal efficiency with which non-native sounds are processed. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  20. Transcranial Magnetic Stimulation over Left Inferior Frontal and Posterior Temporal Cortex Disrupts Gesture-Speech Integration.

    Science.gov (United States)

    Zhao, Wanying; Riggs, Kevin; Schindler, Igor; Holle, Henning

    2018-02-21

    Language and action naturally occur together in the form of cospeech gestures, and there is now convincing evidence that listeners display a strong tendency to integrate semantic information from both domains during comprehension. A contentious question, however, has been which brain areas are causally involved in this integration process. In previous neuroimaging studies, left inferior frontal gyrus (IFG) and posterior middle temporal gyrus (pMTG) have emerged as candidate areas; however, it is currently not clear whether these areas are causally or merely epiphenomenally involved in gesture-speech integration. In the present series of experiments, we directly tested for a potential critical role of IFG and pMTG by observing the effect of disrupting activity in these areas using transcranial magnetic stimulation in a mixed gender sample of healthy human volunteers. The outcome measure was performance on a Stroop-like gesture task (Kelly et al., 2010a), which provides a behavioral index of gesture-speech integration. Our results provide clear evidence that disrupting activity in IFG and pMTG selectively impairs gesture-speech integration, suggesting that both areas are causally involved in the process. These findings are consistent with the idea that these areas play a joint role in gesture-speech integration, with IFG regulating strategic semantic access via top-down signals acting upon temporal storage areas. SIGNIFICANCE STATEMENT Previous neuroimaging studies suggest an involvement of inferior frontal gyrus and posterior middle temporal gyrus in gesture-speech integration, but findings have been mixed and due to methodological constraints did not allow inferences of causality. By adopting a virtual lesion approach involving transcranial magnetic stimulation, the present study provides clear evidence that both areas are causally involved in combining semantic information arising from gesture and speech. These findings support the view that, rather than being

  1. Greater Activity in the Frontal Cortex on Left Curves: A Vector-Based fNIRS Study of Left and Right Curve Driving.

    Directory of Open Access Journals (Sweden)

    Noriyuki Oka

    Full Text Available In the brain, the mechanisms of attention to the left and the right are known to be different. It is possible that brain activity when driving also differs with different horizontal road alignments (left or right curves, but little is known about this. We found driver brain activity to be different when driving on left and right curves, in an experiment using a large-scale driving simulator and functional near-infrared spectroscopy (fNIRS.The participants were fifteen healthy adults. We created a course simulating an expressway, comprising straight line driving and gentle left and right curves, and monitored the participants under driving conditions, in which they drove at a constant speed of 100 km/h, and under non-driving conditions, in which they simply watched the screen (visual task. Changes in hemoglobin concentrations were monitored at 48 channels including the prefrontal cortex, the premotor cortex, the primary motor cortex and the parietal cortex. From orthogonal vectors of changes in deoxyhemoglobin and changes in oxyhemoglobin, we calculated changes in cerebral oxygen exchange, reflecting neural activity, and statistically compared the resulting values from the right and left curve sections.Under driving conditions, there were no sites where cerebral oxygen exchange increased significantly more during right curves than during left curves (p > 0.05, but cerebral oxygen exchange increased significantly more during left curves (p < 0.05 in the right premotor cortex, the right frontal eye field and the bilateral prefrontal cortex. Under non-driving conditions, increases were significantly greater during left curves (p < 0.05 only in the right frontal eye field.Left curve driving was thus found to require more brain activity at multiple sites, suggesting that left curve driving may require more visual attention than right curve driving. The right frontal eye field was activated under both driving and non-driving conditions.

  2. Greater Activity in the Frontal Cortex on Left Curves: A Vector-Based fNIRS Study of Left and Right Curve Driving

    Science.gov (United States)

    Oka, Noriyuki; Yoshino, Kayoko; Yamamoto, Kouji; Takahashi, Hideki; Li, Shuguang; Sugimachi, Toshiyuki; Nakano, Kimihiko; Suda, Yoshihiro; Kato, Toshinori

    2015-01-01

    Objectives In the brain, the mechanisms of attention to the left and the right are known to be different. It is possible that brain activity when driving also differs with different horizontal road alignments (left or right curves), but little is known about this. We found driver brain activity to be different when driving on left and right curves, in an experiment using a large-scale driving simulator and functional near-infrared spectroscopy (fNIRS). Research Design and Methods The participants were fifteen healthy adults. We created a course simulating an expressway, comprising straight line driving and gentle left and right curves, and monitored the participants under driving conditions, in which they drove at a constant speed of 100 km/h, and under non-driving conditions, in which they simply watched the screen (visual task). Changes in hemoglobin concentrations were monitored at 48 channels including the prefrontal cortex, the premotor cortex, the primary motor cortex and the parietal cortex. From orthogonal vectors of changes in deoxyhemoglobin and changes in oxyhemoglobin, we calculated changes in cerebral oxygen exchange, reflecting neural activity, and statistically compared the resulting values from the right and left curve sections. Results Under driving conditions, there were no sites where cerebral oxygen exchange increased significantly more during right curves than during left curves (p > 0.05), but cerebral oxygen exchange increased significantly more during left curves (p right premotor cortex, the right frontal eye field and the bilateral prefrontal cortex. Under non-driving conditions, increases were significantly greater during left curves (p right frontal eye field. Conclusions Left curve driving was thus found to require more brain activity at multiple sites, suggesting that left curve driving may require more visual attention than right curve driving. The right frontal eye field was activated under both driving and non-driving conditions

  3. Transcranial direct current stimulation over left inferior frontal cortex improves speech fluency in adults who stutter.

    Science.gov (United States)

    Chesters, Jennifer; Möttönen, Riikka; Watkins, Kate E

    2018-04-01

    See Crinion (doi:10.1093/brain/awy075) for a scientific commentary on this article.Stuttering is a neurodevelopmental condition affecting 5% of children, and persisting in 1% of adults. Promoting lasting fluency improvement in adults who stutter is a particular challenge. Novel interventions to improve outcomes are of value, therefore. Previous work in patients with acquired motor and language disorders reported enhanced benefits of behavioural therapies when paired with transcranial direct current stimulation. Here, we report the results of the first trial investigating whether transcranial direct current stimulation can improve speech fluency in adults who stutter. We predicted that applying anodal stimulation to the left inferior frontal cortex during speech production with temporary fluency inducers would result in longer-lasting fluency improvements. Thirty male adults who stutter completed a randomized, double-blind, controlled trial of anodal transcranial direct current stimulation over left inferior frontal cortex. Fifteen participants received 20 min of 1-mA stimulation on five consecutive days while speech fluency was temporarily induced using choral and metronome-timed speech. The other 15 participants received the same speech fluency intervention with sham stimulation. Speech fluency during reading and conversation was assessed at baseline, before and after the stimulation on each day of the 5-day intervention, and at 1 and 6 weeks after the end of the intervention. Anodal stimulation combined with speech fluency training significantly reduced the percentage of disfluent speech measured 1 week after the intervention compared with fluency intervention alone. At 6 weeks after the intervention, this improvement was maintained during reading but not during conversation. Outcome scores at both post-intervention time points on a clinical assessment tool (the Stuttering Severity Instrument, version 4) also showed significant improvement in the group receiving

  4. Left Frontal Hub Connectivity during Memory Performance Supports Reserve in Aging and Mild Cognitive Impairment.

    Science.gov (United States)

    Franzmeier, Nicolai; Hartmann, Julia C; Taylor, Alexander N W; Araque Caballero, Miguel Á; Simon-Vermot, Lee; Buerger, Katharina; Kambeitz-Ilankovic, Lana M; Ertl-Wagner, Birgit; Mueller, Claudia; Catak, Cihan; Janowitz, Daniel; Stahl, Robert; Dichgans, Martin; Duering, Marco; Ewers, Michael

    2017-01-01

    Reserve in aging and Alzheimer's disease (AD) is defined as maintaining cognition at a relatively high level in the presence of neurodegeneration, an ability often associated with higher education among other life factors. Recent evidence suggests that higher resting-state functional connectivity within the frontoparietal control network, specifically the left frontal cortex (LFC) hub, contributes to higher reserve. Following up these previous resting-state fMRI findings, we probed memory-task related functional connectivity of the LFC hub as a neural substrate of reserve. In elderly controls (CN, n = 37) and patients with mild cognitive impairment (MCI, n = 17), we assessed global connectivity of the LFC hub during successful face-name association learning, using generalized psychophysiological interaction analyses. Reserve was quantified as residualized memory performance, accounted for gender and proxies of neurodegeneration (age, hippocampus atrophy, and APOE genotype). We found that greater education was associated with higher LFC-connectivity in both CN and MCI during successful memory. Furthermore, higher LFC-connectivity predicted higher residualized memory (i.e., reserve). These results suggest that higher LFC-connectivity contributes to reserve in both healthy and pathological aging.

  5. Perturbation of the left inferior frontal gyrus triggers adaptive plasticity in the right homologous area during speech production

    DEFF Research Database (Denmark)

    Hartwigsen, Gesa; Saur, Dorothee; Price, Cathy J

    2013-01-01

    The role of the right hemisphere in aphasia recovery after left hemisphere damage remains unclear. Increased activation of the right hemisphere has been observed after left hemisphere damage. This may simply reflect a release from transcallosal inhibition that does not contribute to language...... functions. Alternatively, the right hemisphere may actively contribute to language functions by supporting disrupted processing in the left hemisphere via interhemispheric connections. To test this hypothesis, we applied off-line continuous theta burst stimulation (cTBS) over the left inferior frontal gyrus...... (IFG) in healthy volunteers, then used functional MRI to investigate acute changes in effective connectivity between the left and right hemispheres during repetition of auditory and visual words and pseudowords. In separate sessions, we applied cTBS over the left anterior IFG (aIFG) or posterior IFG (p...

  6. Transcortical mixed aphasia due to cerebral infarction in left inferior frontal lobe and temporo-parietal lobe

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    Maeshima, S.; Matsumoto, T.; Ueyoshi, A. [Department of Physical Medicine and Rehabilitation, Wakayama Medical University, Wakayama (Japan); Toshiro, H.; Sekiguchi, E.; Okita, R.; Yamaga, H.; Ozaki, F.; Moriwaki, H. [Department of Neurological Surgery, Hidaka General Hospital, Wakayama (Japan); Roger, P. [School of Communication Sciences and Disorders, University of Sydney, Sydney, NSW (Australia)

    2002-02-01

    We present a case of transcortical mixed aphasia caused by a cerebral embolism. A 77-year-old right-handed man was admitted to our hospital with speech disturbance and a right hemianopia. His spontaneous speech was remarkably reduced, and object naming, word fluency, comprehension, reading and writing were all severely disturbed. However, repetition of phonemes and sentences and reading aloud were fully preserved. Although magnetic resonance imaging (MRI) showed cerebral infarcts in the left frontal and parieto-occipital lobe which included the inferior frontal gyrus and angular gyrus, single photon emission CT revealed a wider area of low perfusion over the entire left hemisphere except for part of the left perisylvian language areas. The amytal (Wada) test, which was performed via the left internal carotid artery, revealed that the left hemisphere was dominant for language. Hence, it appears that transcortical mixed aphasia may be caused by the isolation of perisylvian speech areas, even if there is a lesion in the inferior frontal gyrus, due to disconnection from surrounding areas. (orig.)

  7. Transcortical mixed aphasia due to cerebral infarction in left inferior frontal lobe and temporo-parietal lobe

    International Nuclear Information System (INIS)

    Maeshima, S.; Matsumoto, T.; Ueyoshi, A.; Toshiro, H.; Sekiguchi, E.; Okita, R.; Yamaga, H.; Ozaki, F.; Moriwaki, H.; Roger, P.

    2002-01-01

    We present a case of transcortical mixed aphasia caused by a cerebral embolism. A 77-year-old right-handed man was admitted to our hospital with speech disturbance and a right hemianopia. His spontaneous speech was remarkably reduced, and object naming, word fluency, comprehension, reading and writing were all severely disturbed. However, repetition of phonemes and sentences and reading aloud were fully preserved. Although magnetic resonance imaging (MRI) showed cerebral infarcts in the left frontal and parieto-occipital lobe which included the inferior frontal gyrus and angular gyrus, single photon emission CT revealed a wider area of low perfusion over the entire left hemisphere except for part of the left perisylvian language areas. The amytal (Wada) test, which was performed via the left internal carotid artery, revealed that the left hemisphere was dominant for language. Hence, it appears that transcortical mixed aphasia may be caused by the isolation of perisylvian speech areas, even if there is a lesion in the inferior frontal gyrus, due to disconnection from surrounding areas. (orig.)

  8. The left inferior frontal gyrus: A neural crossroads between abstract and concrete knowledge.

    Science.gov (United States)

    Della Rosa, Pasquale Anthony; Catricalà, Eleonora; Canini, Matteo; Vigliocco, Gabriella; Cappa, Stefano F

    2018-07-15

    Evidence from both neuropsychology and neuroimaging suggests that different types of information are necessary for representing and processing concrete and abstract word meanings. Both abstract and concrete concepts, however, conjointly rely on perceptual, verbal and contextual knowledge, with abstract concepts characterized by low values of imageability (IMG) (low sensory-motor grounding) and low context availability (CA) (more difficult to contextualize). Imaging studies supporting differences between abstract and concrete concepts show a greater recruitment of the left inferior frontal gyrus (LIFG) for abstract concepts, which has been attributed either to the representation of abstract-specific semantic knowledge or to the request for more executive control than in the case of concrete concepts. We conducted an fMRI study on 27 participants, using a lexical decision task involving both abstract and concrete words, whose IMG and CA values were explicitly modelled in separate parametric analyses. The LIFG was significantly more activated for abstract than for concrete words, and a conjunction analysis showed a common activation for words with low IMG or low CA only in the LIFG, in the same area reported for abstract words. A regional template map of brain activations was then traced for words with low IMG or low CA, and BOLD regional time-series were extracted and correlated with the specific LIFG neural activity elicited for abstract words. The regions associated to low IMG, which were functionally correlated with LIFG, were mainly in the left hemisphere, while those associated with low CA were in the right hemisphere. Finally, in order to reveal which LIFG-related network increased its connectivity with decreases of IMG or CA, we conducted generalized psychophysiological interaction analyses. The connectivity strength values extracted from each region connected with the LIFG were correlated with specific LIFG neural activity for abstract words, and a regression

  9. Enhancing verbal creativity: modulating creativity by altering the balance between right and left inferior frontal gyrus with tDCS.

    Science.gov (United States)

    Mayseless, N; Shamay-Tsoory, S G

    2015-04-16

    Creativity is the production of novel ideas that have value. Previous research indicated that while regions in the right hemisphere are implicated in the production of new ideas, damage to the left inferior frontal gyrus (IFG) is associated with increased creativity, indicating that the left IFG damage may have a "releasing" effect on creativity. To examine this, in the present study we used transcranial direct current stimulation (tDCS) to modulate activity of the right and the left IFG. In the first experiment we show that whereas anodal tDCS over the right IFG coupled with cathodal tDCS over the left IFG increases creativity as measured by a verbal divergent thinking task, the reverse stimulation does not affect creative production. To further confirm that only altering the balance between the two hemispheres is crucial in modulating creativity, in the second experiment we show that stimulation targeting separately the left IFG (cathodal stimulation) or the right IFG (anodal stimulation) did not result in changes in creativity as measured by verbal divergent thinking. These findings support the balance hypothesis, according to which verbal creativity requires a balance of activation between the right and the left frontal lobes, and more specifically, between the right and the left IFG. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

  10. Activation of the left inferior frontal gyrus in the first 200 ms of reading: evidence from magnetoencephalography (MEG).

    Science.gov (United States)

    Cornelissen, Piers L; Kringelbach, Morten L; Ellis, Andrew W; Whitney, Carol; Holliday, Ian E; Hansen, Peter C

    2009-01-01

    It is well established that the left inferior frontal gyrus plays a key role in the cerebral cortical network that supports reading and visual word recognition. Less clear is when in time this contribution begins. We used magnetoencephalography (MEG), which has both good spatial and excellent temporal resolution, to address this question. MEG data were recorded during a passive viewing paradigm, chosen to emphasize the stimulus-driven component of the cortical response, in which right-handed participants were presented words, consonant strings, and unfamiliar faces to central vision. Time-frequency analyses showed a left-lateralized inferior frontal gyrus (pars opercularis) response to words between 100-250 ms in the beta frequency band that was significantly stronger than the response to consonant strings or faces. The left inferior frontal gyrus response to words peaked at approximately 130 ms. This response was significantly later in time than the left middle occipital gyrus, which peaked at approximately 115 ms, but not significantly different from the peak response in the left mid fusiform gyrus, which peaked at approximately 140 ms, at a location coincident with the fMRI-defined visual word form area (VWFA). Significant responses were also detected to words in other parts of the reading network, including the anterior middle temporal gyrus, the left posterior middle temporal gyrus, the angular and supramarginal gyri, and the left superior temporal gyrus. These findings suggest very early interactions between the vision and language domains during visual word recognition, with speech motor areas being activated at the same time as the orthographic word-form is being resolved within the fusiform gyrus. This challenges the conventional view of a temporally serial processing sequence for visual word recognition in which letter forms are initially decoded, interact with their phonological and semantic representations, and only then gain access to a speech code.

  11. Correlations between measures of executive attention and cortical thickness of left posterior middle frontal gyrus - a dichotic listening study

    Directory of Open Access Journals (Sweden)

    Lundervold Arvid

    2009-10-01

    Full Text Available Abstract Background The frontal lobe has been associated to a wide range of cognitive control functions and is also vulnerable to degeneration in old age. A recent study by Thomsen and colleagues showed a difference between a young and old sample in grey matter density and activation in the left middle frontal cortex (MFC and performance on a dichotic listening task. The present study investigated this brain behaviour association within a sample of healthy older individuals, and predicted a positive correlation between performance in a condition requiring executive attention and measures of grey matter structure of the posterior left MFC. Methods A dichotic listening forced attention paradigm was used to measure attention control functions. Subjects were instructed to report only the left or the right ear syllable of a dichotically presented consonant-vowel syllable pair. A conflict situation appears when subjects are instructed to report the left ear stimulus, caused by the conflict with the bottom-up, stimulus-driven right ear advantage. Overcoming this processing conflict was used as a measure of executive attention. Thickness and volumes of frontal lobe regions were derived from automated segmentation of 3D magnetic resonance image acquisitions. Results The results revealed a statistically significant positive correlation between the thickness measure of the left posterior MFC and performance on the dichotic listening measures of executive attention. Follow-up analyses showed that this correlation was only statistically significant in the subgroup that showed the typical bottom-up, stimulus-driven right ear advantage. Conclusion The results suggest that the left MFC is a part of an executive attention network, and that the dichotic listening forced attention paradigm may be a feasible tool for assessing subtle attentional dysfunctions in older adults.

  12. Neural substrates of semantic relationships: common and distinct left-frontal activities for generation of synonyms vs. antonyms.

    Science.gov (United States)

    Jeon, Hyeon-Ae; Lee, Kyoung-Min; Kim, Young-Bo; Cho, Zang-Hee

    2009-11-01

    Synonymous and antonymous relationships among words may reflect the organization and/or processing in the mental lexicon and its implementation in the brain. In this study, functional magnetic resonance imaging (fMRI) is employed to compare brain activities during generation of synonyms (SYN) and antonyms (ANT) prompted by the same words. Both SYN and ANT, when compared with reading nonwords (NW), activated a region in the left middle frontal gyrus (BA 46). Neighboring this region, there was a dissociation observed in that the ANT activation extended more anteriorly and laterally to the SYN activation. The activations in the left middle frontal gyrus may be related to mental processes that are shared in the SYN and ANT generations, such as engaging semantically related parts of mental lexicon for the word search, whereas the distinct activations unique for either SYN or ANT generation may reflect the additional component of antonym retrieval, namely, reversing the polarity of semantic relationship in one crucial dimension. These findings suggest that specific components in the semantic processing, such as the polarity reversal for antonym generation and the similarity assessment for synonyms, are separately and systematically laid out in the left-frontal cortex.

  13. Training and Validating a Deep Convolutional Neural Network for Computer-Aided Detection and Classification of Abnormalities on Frontal Chest Radiographs.

    Science.gov (United States)

    Cicero, Mark; Bilbily, Alexander; Colak, Errol; Dowdell, Tim; Gray, Bruce; Perampaladas, Kuhan; Barfett, Joseph

    2017-05-01

    Convolutional neural networks (CNNs) are a subtype of artificial neural network that have shown strong performance in computer vision tasks including image classification. To date, there has been limited application of CNNs to chest radiographs, the most frequently performed medical imaging study. We hypothesize CNNs can learn to classify frontal chest radiographs according to common findings from a sufficiently large data set. Our institution's research ethics board approved a single-center retrospective review of 35,038 adult posterior-anterior chest radiographs and final reports performed between 2005 and 2015 (56% men, average age of 56, patient type: 24% inpatient, 39% outpatient, 37% emergency department) with a waiver for informed consent. The GoogLeNet CNN was trained using 3 graphics processing units to automatically classify radiographs as normal (n = 11,702) or into 1 or more of cardiomegaly (n = 9240), consolidation (n = 6788), pleural effusion (n = 7786), pulmonary edema (n = 1286), or pneumothorax (n = 1299). The network's performance was evaluated using receiver operating curve analysis on a test set of 2443 radiographs with the criterion standard being board-certified radiologist interpretation. Using 256 × 256-pixel images as input, the network achieved an overall sensitivity and specificity of 91% with an area under the curve of 0.964 for classifying a study as normal (n = 1203). For the abnormal categories, the sensitivity, specificity, and area under the curve, respectively, were 91%, 91%, and 0.962 for pleural effusion (n = 782), 82%, 82%, and 0.868 for pulmonary edema (n = 356), 74%, 75%, and 0.850 for consolidation (n = 214), 81%, 80%, and 0.875 for cardiomegaly (n = 482), and 78%, 78%, and 0.861 for pneumothorax (n = 167). Current deep CNN architectures can be trained with modest-sized medical data sets to achieve clinically useful performance at detecting and excluding common pathology on chest radiographs.

  14. Subliminal and supraliminal processing of facial expression of emotions: brain oscillation in the left/right frontal area.

    Science.gov (United States)

    Balconi, Michela; Ferrari, Chiara

    2012-03-26

    The unconscious effects of an emotional stimulus have been highlighted by a vast amount of research, whereover it remains questionable whether it is possible to assign a specific function to cortical brain oscillations in the unconscious perception of facial expressions of emotions. Alpha band variation was monitored within the right- and left-cortical side when subjects consciously (supraliminal stimulation) or unconsciously (subliminal stimulation) processed facial patterns. Twenty subjects looked at six facial expressions of emotions (anger, fear, surprise, disgust, happiness, sadness, and neutral) under two different conditions: supraliminal (200 ms) vs. subliminal (30 ms) stimulation (140 target-mask pairs for each condition). The results showed that conscious/unconscious processing and the significance of the stimulus can modulate the alpha power. Moreover, it was found that there was an increased right frontal activity for negative emotions vs. an increased left response for positive emotion. The significance of facial expressions was adduced to elucidate cortical different responses to emotional types.

  15. Hostile Attribution Bias Mediates the Relationship Between Structural Variations in the Left Middle Frontal Gyrus and Trait Angry Rumination

    Directory of Open Access Journals (Sweden)

    Yueyue Wang

    2018-04-01

    Full Text Available Angry rumination is a common mental phenomenon which may lead to negative social behaviors such as aggression. Although numerous neuroimaging studies have focused on brain area activation during angry rumination, to our knowledge no study has examined the neuroanatomical and cognitive mechanisms of this process. In this study, we conducted a voxel-based morphometry analysis, using a region of interest analysis to identify the structural and cognitive mechanisms underlying individual differences in trait angry rumination (as measured by the Angry Rumination Scale in a sample of 82 undergraduate students. We found that angry rumination was positively correlated with gray matter density in the left middle frontal gyrus (left-MFG, which is implicated in inhibition control, working memory, and emotional regulation. The mediation analysis further revealed that hostile attribution bias (as measured by the Social Information Processing–Attribution Bias Questionnaire acted as a cognitive mechanism underlying the positive association between the left-MFG gray matter density and trait angry rumination. These findings suggest that hostile attribution bias may contribute to trait angry rumination, while the left-MFG may play an important role in the development of hostile attribution bias and trait angry rumination. The study reveals the brain mechanisms of trait angry rumination and plays a role in revealing the cognitive mechanisms of the development of trait angry rumination.

  16. The left inferior frontal gyrus is involved in adjusting response bias during a perceptual decision-making task.

    Science.gov (United States)

    Reckless, Greg E; Ousdal, Olga T; Server, Andres; Walter, Henrik; Andreassen, Ole A; Jensen, Jimmy

    2014-05-01

    Changing the way we make decisions from one environment to another allows us to maintain optimal decision-making. One way decision-making may change is how biased one is toward one option or another. Identifying the regions of the brain that underlie the change in bias will allow for a better understanding of flexible decision-making. An event-related, perceptual decision-making task where participants had to detect a picture of an animal amongst distractors was used during functional magnetic resonance imaging. Positive and negative financial motivation were used to affect a change in response bias, and changes in decision-making behavior were quantified using signal detection theory. Response bias became relatively more liberal during both positive and negative motivated trials compared to neutral trials. For both motivational conditions, the larger the liberal shift in bias, the greater the left inferior frontal gyrus (IFG) activity. There was no relationship between individuals' belief that they used a different strategy and their actual change in response bias. The present findings suggest that the left IFG plays a role in adjusting response bias across different decision environments. This suggests a potential role for the left IFG in flexible decision-making.

  17. Early aphasia rehabilitation is associated with functional reactivation of the left inferior frontal gyrus: a pilot study.

    Science.gov (United States)

    Mattioli, Flavia; Ambrosi, Claudia; Mascaro, Lorella; Scarpazza, Cristina; Pasquali, Patrizia; Frugoni, Marina; Magoni, Mauro; Biagi, Laura; Gasparotti, Roberto

    2014-02-01

    Early poststroke aphasia rehabilitation effects and their functional MRI (fMRI) correlates were investigated in a pilot, controlled longitudinal study. Twelve patients with mild/moderate aphasia (8 Broca, 3 anomic, and 1 Wernicke) were randomly assigned to daily language rehabilitation for 2 weeks (starting 2.2 [mean] days poststroke) or no rehabilitation. The Aachen Aphasia Test and fMRI recorded during an auditory comprehension task were performed at 3 time intervals: mean 2.2 (T1), 16.2 (T2), and 190 (T3) days poststroke. Groups did not differ in terms of age, education, aphasia severity, lesions volume, baseline fMRI activations, and in task performance during fMRI across examinations. Rehabilitated patients significantly improved in naming and written language tasks (Paphasia treatment is useful, has durable effects, and may lead to early enhanced recruitment of brain areas, particularly the left inferior frontal gyrus, which persists in the chronic phase.

  18. Bihemispheric stimulation over left and right inferior frontal region enhances recovery from apraxia of speech in chronic aphasia.

    Science.gov (United States)

    Marangolo, Paola; Fiori, Valentina; Cipollari, Susanna; Campana, Serena; Razzano, Carmelina; Di Paola, Margherita; Koch, Giacomo; Caltagirone, Carlo

    2013-11-01

    Several studies have already shown that transcranial direct current stimulation (tDCS) is a useful tool for enhancing recovery in aphasia. However, all tDCS studies have previously investigated the effects using unihemisperic stimulation. No reports to date have examined the role of bihemispheric tDCS on aphasia recovery. Here, eight aphasic persons with apraxia of speech underwent intensive language therapy in two different conditions: real bihemispheric anodic ipsilesional stimulation over the left Broca's area and cathodic contralesional stimulation over the right homologue of Broca's area, and a sham condition. In both conditions, patients underwent concurrent language therapy for their apraxia of speech. The language treatment lasted 10 days (Monday to Friday, then weekend off, then Monday to Friday). There was a 14-day intersession interval between the real and the sham conditions. In all patients, language measures were collected before (T0), at the end of (T10) and 1 week after the end of (F/U) treatment. Results showed that after simultaneous excitatory stimulation to the left frontal hemisphere and inhibitory stimulation to the right frontal hemisphere regions, patients exhibited a significant recovery not only in terms of better accuracy and speed in articulating the treated stimuli but also in other language tasks (picture description, noun and verb naming, word repetition, word reading) which persisted in the follow-up session. Taken together, these data suggest that bihemispheric anodic ipsilesional and cathodic contralesional stimulation in chronic aphasia patients may affect the treated function, resulting in a positive influence on different language tasks. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  19. Left frontal meningioangiomatosis associated with type IIIc focal cortical dysplasia causing refractory epilepsy and literature review.

    Science.gov (United States)

    Roux, Alexandre; Mellerio, Charles; Lechapt-Zalcman, Emmanuelle; Still, Megan; Zerah, Michel; Bourgeois, Marie; Pallud, Johan

    2018-03-29

    We report the surgical management of a lesional drug-resistant epilepsy caused by a meningioangiomatosis associated with a type IIIc focal cortical dysplasia located in the left supplementary motor area in a young male patient. A first anatomical-based partial surgical resection was performed at 11 years old under general anaesthesia without intraoperative mapping, which allowed for postoperative seizure control (Engel IA) for six years. The patient then presented with intractable right sensatory and aphasic focal onset seizures despite two appropriate antiepileptic drugs. A second functional-based surgical resection was performed using intraoperative cortico-subcortical functional mapping with direct electrical stimulation under awake conditions. A complete surgical resection was performed and a left partial supplementary motor area syndrome was observed. At six postoperative months, the patient is seizure free (Engel IA) with an ongoing decrease in antiepileptic drug therapy. Intraoperative functional brain mapping can be applied to preserve the brain function and networks around a meningioangiomatosis to facilitate the resection of potentially epileptogenic perilesional dysplastic cortex and to tailor the extent of resection to functional boundaries. Copyright © 2018. Published by Elsevier Inc.

  20. Morphometry of Left Frontal and Temporal Poles Predicts Analogical Reasoning Abilities.

    Science.gov (United States)

    Aichelburg, Clarisse; Urbanski, Marika; Thiebaut de Schotten, Michel; Humbert, Frederic; Levy, Richard; Volle, Emmanuelle

    2016-03-01

    Analogical reasoning is critical for making inferences and adapting to novelty. It can be studied experimentally using tasks that require creating similarities between situations or concepts, i.e., when their constituent elements share a similar organization or structure. Brain correlates of analogical reasoning have mostly been explored using functional imaging that has highlighted the involvement of the left rostrolateral prefrontal cortex (rlPFC) in healthy subjects. However, whether inter-individual variability in analogical reasoning ability in a healthy adult population is related to differences in brain architecture is unknown. We investigated this question by employing linear regression models of performance in analogy tasks and voxel-based morphometry in 54 healthy subjects. Our results revealed that the ability to reason by analogy was associated with structural variability in the left rlPFC and the anterior part of the inferolateral temporal cortex. Tractography of diffusion-weighted images suggested that these 2 regions have a different set of connections but may exchange information via the arcuate fasciculus. These results suggest that enhanced integrative and semantic abilities supported by structural variation in these areas (or their connectivity) may lead to more efficient analogical reasoning. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. Subliminal and Supraliminal Processing of Facial Expression of Emotions: Brain Oscillation in the Left/Right Frontal Area

    Directory of Open Access Journals (Sweden)

    Michela Balconi

    2012-03-01

    Full Text Available The unconscious effects of an emotional stimulus have been highlighted by a vast amount of research, whereover it remains questionable whether it is possible to assign a specific function to cortical brain oscillations in the unconscious perception of facial expressions of emotions. Alpha band variation was monitored within the right- and left-cortical side when subjects consciously (supraliminal stimulation or unconsciously (subliminal stimulation processed facial patterns. Twenty subjects looked at six facial expressions of emotions (anger, fear, surprise, disgust, happiness, sadness, and neutral under two different conditions: supraliminal (200 ms vs. subliminal (30 ms stimulation (140 target-mask pairs for each condition. The results showed that conscious/unconscious processing and the significance of the stimulus can modulate the alpha power. Moreover, it was found that there was an increased right frontal activity for negative emotions vs. an increased left response for positive emotion. The significance of facial expressions was adduced to elucidate cortical different responses to emotional types.

  2. Comparison of Metabolite Concentrations in the Left Dorsolateral Prefrontal Cortex, the Left Frontal White Matter, and the Left Hippocampus in Patients in Stable Schizophrenia Treated with Antipsychotics with or without Antidepressants. 1H-NMR Spectroscopy Study

    Directory of Open Access Journals (Sweden)

    Dominik Strzelecki

    2015-10-01

    Full Text Available Managing affective, negative, and cognitive symptoms remains the most difficult therapeutic problem in stable phase of schizophrenia. Efforts include administration of antidepressants. Drugs effects on brain metabolic parameters can be evaluated by means of proton nuclear magnetic resonance (1H-NMR spectroscopy. We compared spectroscopic parameters in the left prefrontal cortex (DLPFC, the left frontal white matter (WM and the left hippocampus and assessed the relationship between treatment and the spectroscopic parameters in both groups. We recruited 25 patients diagnosed with schizophrenia (DSM-IV-TR, with dominant negative symptoms and in stable clinical condition, who were treated with antipsychotic and antidepressive medication for minimum of three months. A group of 25 patients with schizophrenia, who were taking antipsychotic drugs but not antidepressants, was matched. We compared metabolic parameters (N-acetylaspartate (NAA, myo-inositol (mI, glutamatergic parameters (Glx, choline (Cho, and creatine (Cr between the two groups. All patients were also assessed with the Positive and Negative Syndrome Scale (PANSS and the Calgary Depression Scale for Schizophrenia (CDSS. In patients receiving antidepressants we observed significantly higher NAA/Cr and NAA/Cho ratios within the DLPFC, as well as significantly higher mI/Cr within the frontal WM. Moreover, we noted significantly lower values of parameters associated with the glutamatergic transmission—Glx/Cr and Glx/Cho in the hippocampus. Doses of antipsychotic drugs in the group treated with antidepressants were also significantly lower in the patients showing similar severity of psychopathology.

  3. The effect of left frontal transcranial direct-current stimulation on propranolol-induced fear memory acquisition and consolidation deficits.

    Science.gov (United States)

    Nasehi, Mohammad; Khani-Abyaneh, Mozhgan; Ebrahimi-Ghiri, Mohaddeseh; Zarrindast, Mohammad-Reza

    2017-07-28

    Accumulating evidence supports the efficacy of transcranial direct current stimulation (tDCS) in modulating numerous cognitive functions. Despite the fact that tDCS has been used for the enhancement of memory and cognition, very few animal studies have addressed its impact on the modulation of fear memory. This study was designed to determine whether pre/post-training frontal tDCS application would alter fear memory acquisition and/or consolidation deficits induced by propranolol in NMRI mice. Results indicated that administration of β1-adrenoceptor blocker propranolol (0.1mg/kg) impaired fear memory retrieval. Pre/post-training application of anodal tDCS when propranolol was administered prior to training reversed contextual memory retrieval whereas only the anodal application prior to training could induce the same result in the auditory test. Meanwhile, anodal stimulation had no effect on fear memories by itself. Moreover, regardless of when cathode was applied and propranolol administered, their combination restored contextual memory retrieval, while only cathodal stimulation prior to training facilitated the contextual memory retrieval. Also, auditory memory retrieval was restored when cathodal stimulation and propranolol occurred prior to training but it was abolished when stimulation occurred after training and propranolol was administered prior to training. Collectively, our findings show that tDCS applied on the left frontal cortex of mice affects fear memory performance. This alteration seems to be task-dependent and varies depending on the nature and timing of the stimulation. In certain conditions, tDCS reverses the effect of propranolol. These results provide initial evidence to support the timely use of tDCS for the modulation of fear-related memories. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Motor Speech Apraxia in a 70-Year-Old Man with Left Dorsolateral Frontal Arachnoid Cyst: A [18F]FDG PET-CT Study

    Directory of Open Access Journals (Sweden)

    Nicolaas I. Bohnen

    2016-01-01

    Full Text Available Motor speech apraxia is a speech disorder of impaired syllable sequencing which, when seen with advancing age, is suggestive of a neurodegenerative process affecting cortical structures in the left frontal lobe. Arachnoid cysts can be associated with neurologic symptoms due to compression of underlying brain structures though indications for surgical intervention are unclear. We present the case of a 70-year-old man who presented with a two-year history of speech changes along with decreased initiation and talkativeness, shorter utterances, and dysnomia. [18F]Fluorodeoxyglucose (FDG Positron Emission and Computed Tomography (PET-CT and magnetic resonance imaging (MRI showed very focal left frontal cortical hypometabolism immediately adjacent to an arachnoid cyst but no specific evidence of a neurodegenerative process.

  5. Differential activity in left inferior frontal gyrus for pseudo and real words: an event-related functional MRI study on auditory lexical decision

    International Nuclear Information System (INIS)

    Xiao Zhuangwei; Xu Weixiong; Zhang Xuexin; Wang Xiaoyi; Weng Xuchu; Wu Renhua; Wu Xiaoping

    2006-01-01

    Objective: To study lexical processing of pseudo words and real words by using a fast event-related functional MRI (ER-fMRI) design. Methods: Participants did an auditory lexical decision task on a list of pseudo-randomly intermixed real and pseudo Chinese two-character (or two-syllable) words. Pseudo words were constructed by recombining constituent characters of the real words to control for sublexical codes properties. Results: The behavioral performance of fourteen participants indicated that response to pseudowords was significantly slower and less accurate than to real words (mean error rate: 9.9% versus 3.9%, mean reaction time: 1618 ms versus 1143 ms). Processing of pseudo words and real words activated a highly comparable network of brain regions, including bilateral inferior frontal gyrus, superior, middle temporal gyrus, calcarine and lingual gyrus, and left supramarginal gyrus. Mirroring a behavioral lexical effect, left inferior frontal gyrus (IFG) was significantly more activated for pseudo words than for real words. Conclusion: The results indicate that the processing of left inferior frontal gyrus in judging pseudo words and real words is not related to grapheme-to-phoneme conversion, but rather to making positive versus negative responses in decision making. (authors)

  6. Abnormal Degree Centrality of Bilateral Putamen and Left Superior Frontal Gyrus in Schizophrenia with Auditory Hallucinations: A Resting-state Functional Magnetic Resonance Imaging Study.

    Science.gov (United States)

    Chen, Cheng; Wang, Hui-Ling; Wu, Shi-Hao; Huang, Huan; Zou, Ji-Lin; Chen, Jun; Jiang, Tian-Zi; Zhou, Yuan; Wang, Gao-Hua

    2015-12-05

    Dysconnectivity hypothesis of schizophrenia has been increasingly emphasized. Recent researches showed that this dysconnectivity might be related to occurrence of auditory hallucination (AH). However, there is still no consistent conclusion. This study aimed to explore intrinsic dysconnectivity pattern of whole-brain functional networks at voxel level in schizophrenic with AH. Auditory hallucinated patients group (n = 42 APG), no hallucinated patients group (n = 42 NPG) and normal controls (n = 84 NCs) were analyzed by resting-state functional magnetic resonance imaging. The functional connectivity metrics index (degree centrality [DC]) across the entire brain networks was calculated and evaluated among three groups. DC decreased in the bilateral putamen and increased in the left superior frontal gyrus in all the patients. However, in APG, the changes of DC were more obvious compared with NPG. Symptomology scores were negatively correlated with the DC of bilateral putamen in all patients. AH score of APG positively correlated with the DC in left superior frontal gyrus but negatively correlated with the DC in bilateral putamen. Our findings corroborated that schizophrenia was characterized by functional dysconnectivity, and the abnormal DC in bilateral putamen and left superior frontal gyrus might be crucial in the occurrence of AH.

  7. Differential activity in left inferior frontal gyrus for pseudowords and real words: an event-related fMRI study on auditory lexical decision.

    Science.gov (United States)

    Xiao, Zhuangwei; Zhang, John X; Wang, Xiaoyi; Wu, Renhua; Hu, Xiaoping; Weng, Xuchu; Tan, Li Hai

    2005-06-01

    After Newman and Twieg and others, we used a fast event-related functional magnetic resonance imaging (fMRI) design and contrasted the lexical processing of pseudowords and real words. Participants carried out an auditory lexical decision task on a list of randomly intermixed real and pseudo Chinese two-character (or two-syllable) words. The pseudowords were constructed by recombining constituent characters of the real words to control for sublexical code properties. Processing of pseudowords and real words activated a highly comparable network of brain regions, including bilateral inferior frontal gyrus, superior, middle temporal gyrus, calcarine and lingual gyrus, and left supramarginal gyrus. Mirroring a behavioral lexical effect, left inferior frontal gyrus (IFG) was significantly more activated for pseudowords than for real words. This result disconfirms a popular view that this area plays a role in grapheme-to-phoneme conversion, as such a conversion process was unnecessary in our task with auditory stimulus presentation. An alternative view was supported that attributes increased activity in left IFG for pseudowords to general processes in decision making, specifically in making positive versus negative responses. Activation in left supramarginal gyrus was of a much larger volume for real words than for pseudowords, suggesting a role of this region in the representation of phonological or semantic information for two-character Chinese words at the lexical level.

  8. Dissociating Effects of Scrambling and Topicalization within the Left Frontal and Temporal Language Areas: An fMRI Study in Kaqchikel Maya.

    Science.gov (United States)

    Ohta, Shinri; Koizumi, Masatoshi; Sakai, Kuniyoshi L

    2017-01-01

    Some natural languages grammatically allow different types of changing word orders, such as object scrambling and topicalization. Scrambling and topicalization are more related to syntax and semantics/phonology, respectively. Here we hypothesized that scrambling should activate the left frontal regions, while topicalization would affect the bilateral temporal regions. To examine such distinct effects in our functional magnetic resonance imaging study, we targeted the Kaqchikel Maya language, a Mayan language spoken in Guatemala. In Kaqchikel, the syntactically canonical word order is verb-object-subject (VOS), but at least three non-canonical word orders (i.e., SVO, VSO, and OVS) are also grammatically allowed. We used a sentence-picture matching task, in which the participants listened to a short Kaqchikel sentence and judged whether a picture matched the meaning of the sentence. The advantage of applying this experimental paradigm to an understudied language such as Kaqchikel is that it will allow us to validate the universality of linguistic computation in the brain. We found that the conditions with scrambled sentences [+scrambling] elicited significant activation in the left inferior frontal gyrus and lateral premotor cortex, both of which have been proposed as grammar centers, indicating the effects of syntactic loads. In contrast, the conditions without topicalization [-topicalization] resulted in significant activation in bilateral Heschl's gyrus and superior temporal gyrus, demonstrating that the syntactic and phonological processes were clearly dissociated within the language areas. Moreover, the pre-supplementary motor area and left superior/middle temporal gyri were activated under relatively demanding conditions, suggesting their supportive roles in syntactic or semantic processing. To exclude any semantic/phonological effects of the object-subject word orders, we performed direct comparisons while making the factor of topicalization constant, and

  9. Spontaneous Activity Associated with Delusions of Schizophrenia in the Left Medial Superior Frontal Gyrus: A Resting-State fMRI Study.

    Directory of Open Access Journals (Sweden)

    Bin Gao

    Full Text Available Delusions of schizophrenia have been found to be associated with alterations of some brain regions in structure and task-induced activation. However, the relationship between spontaneously occurring symptoms and spontaneous brain activity remains unclear. In the current study, 14 schizophrenic patients with delusions and 14 healthy controls underwent a resting-state functional magnetic resonance imaging (RS-fMRI scan. Patients with delusions of schizophrenia patients were rated with Positive and Negative Syndrome Scale (PANSS and Characteristics of Delusional Rating Scale (CDRS. Regional homogeneity (ReHo was calculated to measure the local synchronization of the spontaneous activity in a voxel-wise way. A two-sample t-test showed that ReHo of the right anterior cingulate gyrus and left medial superior frontal gyrus were higher in patients, and ReHo of the left superior occipital gyrus was lower, compared to healthy controls. Further, among patients, correlation analysis showed a significant difference between delusion scores of CRDS and ReHo of brain regions. ReHo of the left medial superior frontal gyrus was negatively correlated with patients' CDRS scores but not with delusional PANSS scores. These results suggested that altered local synchronization of spontaneous brain activity may be related to the pathophysiology of delusion in schizophrenia.

  10. Spontaneous Activity Associated with Delusions of Schizophrenia in the Left Medial Superior Frontal Gyrus: A Resting-State fMRI Study.

    Science.gov (United States)

    Gao, Bin; Wang, Yiquan; Liu, Weibo; Chen, Zhiyu; Zhou, Heshan; Yang, Jinyu; Cohen, Zachary; Zhu, Yihong; Zang, Yufeng

    2015-01-01

    Delusions of schizophrenia have been found to be associated with alterations of some brain regions in structure and task-induced activation. However, the relationship between spontaneously occurring symptoms and spontaneous brain activity remains unclear. In the current study, 14 schizophrenic patients with delusions and 14 healthy controls underwent a resting-state functional magnetic resonance imaging (RS-fMRI) scan. Patients with delusions of schizophrenia patients were rated with Positive and Negative Syndrome Scale (PANSS) and Characteristics of Delusional Rating Scale (CDRS). Regional homogeneity (ReHo) was calculated to measure the local synchronization of the spontaneous activity in a voxel-wise way. A two-sample t-test showed that ReHo of the right anterior cingulate gyrus and left medial superior frontal gyrus were higher in patients, and ReHo of the left superior occipital gyrus was lower, compared to healthy controls. Further, among patients, correlation analysis showed a significant difference between delusion scores of CRDS and ReHo of brain regions. ReHo of the left medial superior frontal gyrus was negatively correlated with patients' CDRS scores but not with delusional PANSS scores. These results suggested that altered local synchronization of spontaneous brain activity may be related to the pathophysiology of delusion in schizophrenia.

  11. Greater pre-stimulus effective connectivity from the left inferior frontal area to other areas is associated with better phonological decoding in dyslexic readers

    Directory of Open Access Journals (Sweden)

    Richard E Frye

    2010-12-01

    Full Text Available Functional neuroimaging studies suggest that neural networks that subserve reading are organized differently in dyslexic readers (DRs and typical readers (TRs, yet the hierarchical structure of these networks has not been well studied. We used Granger Causality (GC to examine the effective connectivity of the preparatory network that occurs prior to viewing a non-word stimulus that requires phonological decoding in 7 DRs and 10 TRs who were young adults. The neuromagnetic activity that occurred 500 ms prior to each rhyme trial was analyzed from sensors overlying the left and right inferior frontal areas (IFA, temporoparietal areas (TPA, and ventral occipitotemporal areas (VOTA within the low, medium, and high beta and gamma sub-bands. A mixed-model analysis determined whether connectivity to or from the left and right IFAs differed across connectivity direction (into vs. out of the IFAs, brain areas, reading group, and/or performance. Results indicated that greater connectivity in the low beta sub-band from the left IFA to other cortical areas was significantly related to better non-word rhyme discrimination in DRs but not TRs. This suggests that the left IFA is an important cortical area involved in compensating for poor phonological function in DRs. We suggest that the left IFA activates a wider-than usual network prior to each trial in the service of supporting otherwise effortful phonological decoding in DRs. The fact that the left IFA provides top-down activation to both posterior left hemispheres areas used by typical readers for phonological decoding and homologous right hemisphere areas is discussed. In contrast, within the high gamma sub-band, better performance was associated with decreased connectivity between the left IFA and other brain areas, in both reading groups. Overly strong gamma connectivity during the pre-stimulus period may interfere with subsequent transient activation and deactivation of sub-networks once the non

  12. Subliminal and Supraliminal Processing of Facial Expression of Emotions: Brain Oscillation in the Left/Right Frontal Area

    OpenAIRE

    Balconi, Michela; Ferrari, Chiara

    2012-01-01

    The unconscious effects of an emotional stimulus have been highlighted by a vast amount of research, whereover it remains questionable whether it is possible to assign a specific function to cortical brain oscillations in the unconscious perception of facial expressions of emotions. Alpha band variation was monitored within the right- and left-cortical side when subjects consciously (supraliminal stimulation) or unconsciously (subliminal stimulation) processed facial patterns. Twenty subjects...

  13. Supplementation of Antipsychotic Treatment with the Amino Acid Sarcosine Influences Proton Magnetic Resonance Spectroscopy Parameters in Left Frontal White Matter in Patients with Schizophrenia

    Directory of Open Access Journals (Sweden)

    Dominik Strzelecki

    2015-10-01

    Full Text Available Dysfunction of the glutamatergic system, the main stimulating system in the brain, has a major role in pathogenesis of schizophrenia. The frontal white matter (WM is partially composed of axons from glutamatergic pyramidal neurons and glia with glutamatergic receptors. The natural amino acid sarcosine, a component of a normal diet, inhibits the glycine type 1 transporter, increasing the glycine level. Thus, it modulates glutamatergic transmission through the glutamatergic ionotropic NMDA (N-methyl-d-aspartate receptor, which requires glycine as a co-agonist. To evaluate the concentrations of brain metabolites (NAA, N-acetylaspartate; Glx, complex of glutamate, glutamine, and γ-aminobutyric acid (GABA; mI, myo-inositol; Cr, creatine; Cho, choline in the left frontal WM, Proton Nuclear Magnetic Resonance (1H-NMR spectroscopy was used. Twenty-five patients randomly chosen from a group of fifty with stable schizophrenia (DSM-IV-TR and dominant negative symptoms, who were receiving antipsychotic therapy, were administered 2 g of sarcosine daily for six months. The remaining 25 patients received placebo. Assignment was double blinded. 1H-NMR spectroscopy (1.5 T was performed twice: before and after the intervention. NAA, Glx and mI were evaluated as Cr and Cho ratios. All patients were also assessed twice with the Positive and Negative Syndrome Scale (PANSS. Results were compared between groups and in two time points in each group. The sarcosine group demonstrated a significant decrease in WM Glx/Cr and Glx/Cho ratios compared to controls after six months of therapy. In the experimental group, the final NAA/Cr ratio significantly increased and Glx/Cr ratio significantly decreased compared to baseline values. Improvement in the PANSS scores was significant only in the sarcosine group. In patients with schizophrenia, sarcosine augmentation can reverse the negative effect of glutamatergic system overstimulation, with a simultaneous beneficial increase

  14. Frontal Phonological Agraphia and Acalculia with Impaired Verbal Short-Term Memory due to Left Inferior Precentral Gyrus Lesion.

    Science.gov (United States)

    Sakurai, Yasuhisa; Furukawa, Emi; Kurihara, Masanori; Sugimoto, Izumi

    2018-01-01

    We report a patient with phonological agraphia (selective impairment of kana [Japanese phonetic writing] nonwords) and acalculia (mental arithmetic difficulties) with impaired verbal short-term memory after a cerebral hemorrhage in the opercular part of the left precentral gyrus (Brodmann area 6) and the adjacent postcentral gyrus. The patient showed phonemic paragraphia in five-character kana nonword writing, minimal acalculia, and reduced digit and letter span. Mental arithmetic normalized after 8 months and agraphia recovered to the normal range at 1 year after onset, in parallel with an improvement of the auditory letter span score from 4 to 6 over a period of 14 months and in the digit span score from 6 to 7 over 24 months. These results suggest a close relationship between the recovery of agraphia and acalculia and the improvement of verbal short-term memory. The present case also suggests that the opercular part of the precentral gyrus constitutes the phonological route in writing that conveys phonological information of syllable sequences, and its damage causes phonological agraphia and acalculia with reduced verbal short-term memory.

  15. Frontal Phonological Agraphia and Acalculia with Impaired Verbal Short-Term Memory due to Left Inferior Precentral Gyrus Lesion

    Directory of Open Access Journals (Sweden)

    Yasuhisa Sakurai

    2018-03-01

    Full Text Available We report a patient with phonological agraphia (selective impairment of kana [Japanese phonetic writing] nonwords and acalculia (mental arithmetic difficulties with impaired verbal short-term memory after a cerebral hemorrhage in the opercular part of the left precentral gyrus (Brodmann area 6 and the adjacent postcentral gyrus. The patient showed phonemic paragraphia in five-character kana nonword writing, minimal acalculia, and reduced digit and letter span. Mental arithmetic normalized after 8 months and agraphia recovered to the normal range at 1 year after onset, in parallel with an improvement of the auditory letter span score from 4 to 6 over a period of 14 months and in the digit span score from 6 to 7 over 24 months. These results suggest a close relationship between the recovery of agraphia and acalculia and the improvement of verbal short-term memory. The present case also suggests that the opercular part of the precentral gyrus constitutes the phonological route in writing that conveys phonological information of syllable sequences, and its damage causes phonological agraphia and acalculia with reduced verbal short-term memory.

  16. The Sport Expert's Attention Superiority on Skill-related Scene Dynamic by the Activation of left Medial Frontal Gyrus: An ERP and LORETA Study.

    Science.gov (United States)

    He, Mengyang; Qi, Changzhu; Lu, Yang; Song, Amanda; Hayat, Saba Z; Xu, Xia

    2018-05-21

    Extensive studies have shown that a sports expert is superior to a sports novice in visually perceptual-cognitive processes of sports scene information, however the attentional and neural basis of it has not been thoroughly explored. The present study examined whether a sport expert has the attentional superiority on scene information relevant to his/her sport skill, and explored what factor drives this superiority. To address this problem, EEGs were recorded as participants passively viewed sport scenes (tennis vs. non-tennis) and negative emotional faces in the context of a visual attention task, where the pictures of sport scenes or of negative emotional faces randomly followed the pictures with overlapping sport scenes and negative emotional faces. ERP results showed that for experts, the evoked potential of attentional competition elicited by the overlap of tennis scene was significantly larger than that evoked by the overlap of non-tennis scene, while this effect was absent for novices. The LORETA showed that the experts' left medial frontal gyrus (MFG) cortex was significantly more active as compared to the right MFG when processing the overlap of tennis scene, but the lateralization effect was not significant in novices. Those results indicate that experts have attentional superiority on skill-related scene information, despite intruding the scene through negative emotional faces that are prone to cause negativity bias toward their visual field as a strong distractor. This superiority is actuated by the activation of left MFG cortex and probably due to self-reference. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

  17. Context-dependent lexical ambiguity resolution: MEG evidence for the time-course of activity in left inferior frontal gyrus and posterior middle temporal gyrus.

    Science.gov (United States)

    Mollo, Giovanna; Jefferies, Elizabeth; Cornelissen, Piers; Gennari, Silvia P

    An MEG study investigated the role of context in semantic interpretation by examining the comprehension of ambiguous words in contexts leading to different interpretations. We compared high-ambiguity words in minimally different contexts (to bowl, the bowl) to low-ambiguity counterparts (the tray, to flog). Whole brain beamforming revealed the engagement of left inferior frontal gyrus (LIFG) and posterior middle temporal gyrus (LPMTG). Points of interest analyses showed that both these sites showed a stronger response to verb-contexts by 200 ms post-stimulus and displayed overlapping ambiguity effects that were sustained from 300 ms onwards. The effect of context was stronger for high-ambiguity words than for low-ambiguity words at several different time points, including within the first 100 ms post-stimulus. Unlike LIFG, LPMTG also showed stronger responses to verb than noun contexts in low-ambiguity trials. We argue that different functional roles previously attributed to LIFG and LPMTG are in fact played out at different periods during processing. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

  18. Self-reflection and the inner voice: activation of the left inferior frontal gyrus during perceptual and conceptual self-referential thinking.

    Science.gov (United States)

    Morin, Alain; Hamper, Breanne

    2012-01-01

    Inner speech involvement in self-reflection was examined by reviewing 130 studies assessing brain activation during self-referential processing in key self-domains: agency, self-recognition, emotions, personality traits, autobiographical memory, and miscellaneous (e.g., prospection, judgments). The left inferior frontal gyrus (LIFG) has been shown to be reliably recruited during inner speech production. The percentage of studies reporting LIFG activity for each self-dimension was calculated. Fifty five percent of all studies reviewed indicated LIFG (and presumably inner speech) activity during self-reflection tasks; on average LIFG activation is observed 16% of the time during completion of non-self tasks (e.g., attention, perception). The highest LIFG activation rate was observed during retrieval of autobiographical information. The LIFG was significantly more recruited during conceptual tasks (e.g., prospection, traits) than during perceptual tasks (agency and self-recognition). This constitutes additional evidence supporting the idea of a participation of inner speech in self-related thinking.

  19. TMS interferes with lexical-semantic retrieval in left inferior frontal gyrus and posterior middle temporal gyrus: Evidence from cyclical picture naming.

    Science.gov (United States)

    Krieger-Redwood, Katya; Jefferies, Elizabeth

    2014-11-01

    We used TMS to investigate the contribution of left inferior frontal gyrus (LIFG) and posterior middle temporal gyrus (pMTG) to lexical/semantic selection and retrieval processes using a cyclical naming paradigm. Participants named pictures that were presented repeatedly across six cycles, either in semantically related or unrelated sets. Previous research has suggested that selection demands are higher for related sets, especially after repetition, since participants experience competition from the activation of semantic neighbours. In contrast, retrieval demands are greater for unrelated sets in the absence of semantic priming, particularly on the first cycle when the target names have not been previously activated. Therefore, this paradigm can reveal independent effects of (i) retrieval demands (i.e., the ease of accessing picture names from visual input) and (ii) selection/competition. We found that rTMS to LIFG and pMTG produced similar behavioural effects: stimulation of both sites disrupted picture naming performance on early cycles (when participants were less practised at producing the picture names) and for semantically-related sets (when there was the potential for increased competition and yet also facilitation from semantic neighbours). There were no effects of TMS when either retrieval or selection requirements were maximal on their own. The data therefore support the view that both LIFG and pMTG contribute to picture name retrieval, with both sites playing a critical role in mediating the semantic facilitation of naming when retrieval demands are high. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Tell it to a child! A brain stimulation study of the role of left inferior frontal gyrus in emotion regulation during storytelling.

    Science.gov (United States)

    Urgesi, Cosimo; Mattiassi, Alan D A; Buiatti, Tania; Marini, Andrea

    2016-08-01

    In everyday life we need to continuously regulate our emotional responses according to their social context. Strategies of emotion regulation allow individuals to control time, intensity, nature and expression of emotional responses to environmental stimuli. The left inferior frontal gyrus (LIFG) is involved in the cognitive control of the selection of semantic content. We hypothesized that it might also be involved in the regulation of emotional feelings and expressions. We applied continuous theta burst stimulation (cTBS) over LIFG or a control site before a newly-developed ecological regulation task that required participants to produce storytelling of pictures with negative or neutral valence to either a peer (unregulated condition) or a child (regulated condition). Linguistic, expressive, and physiological responses were analyzed in order to assess the effects of LIFG-cTBS on emotion regulation. Results showed that the emotion regulation context modulated the emotional content of narrative productions, but not the physiologic orienting response or the early expressive behavior to negative stimuli. Furthermore, LIFG-cTBS disrupted the text-level structuring of negative picture storytelling and the early cardiac and muscular response to negative pictures; however, it did not affect the contextual emotional regulation of storytelling. These results may suggest that LIFG is involved in the initial detection of the affective arousal of emotional stimuli. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Fundamentals of convolutional coding

    CERN Document Server

    Johannesson, Rolf

    2015-01-01

    Fundamentals of Convolutional Coding, Second Edition, regarded as a bible of convolutional coding brings you a clear and comprehensive discussion of the basic principles of this field * Two new chapters on low-density parity-check (LDPC) convolutional codes and iterative coding * Viterbi, BCJR, BEAST, list, and sequential decoding of convolutional codes * Distance properties of convolutional codes * Includes a downloadable solutions manual

  2. Fast Convolution Module (Fast Convolution Module)

    National Research Council Canada - National Science Library

    Bierens, L

    1997-01-01

    This report describes the design and realisation of a real-time range azimuth compression module, the so-called 'Fast Convolution Module', based on the fast convolution algorithm developed at TNO-FEL...

  3. Electrical stimulation over the left inferior frontal gyrus (IFG) determines long-term effects in the recovery of speech apraxia in three chronic aphasics.

    Science.gov (United States)

    Marangolo, P; Marinelli, C V; Bonifazi, S; Fiori, V; Ceravolo, M G; Provinciali, L; Tomaiuolo, F

    2011-12-01

    A number of studies have shown that modulating cortical activity by means of transcranial direct current stimulation (tDCS) affects the performance of both healthy and brain-damaged subjects. In this study, we investigated the potential of tDCS for the recovery of apraxia of speech in 3 patients with stroke-induced aphasia. Over 2 weeks, three aphasic subjects participated in a randomized double-blinded experiment involving intensive language training for their articulatory difficulties in two tDCS conditions. Each subject participated in five consecutive daily sessions of anodic tDCS (20 min, 1 mA) and sham stimulation over the left inferior frontal gyrus (referred to as Broca's area) while they performed a repetition task. By the end of each week, a significant improvement was found in both conditions. However, all three subjects showed greater response accuracy in the anodic than in the sham condition. Moreover, results for transfer of treatment effects, although different across subjects, indicate a generalization of the recovery at the language test. Subjects 2 and 3 showed a significant improvement in oral production tasks, such as word repetition and reading, while Subjects 1 and 2 had an unexpected significant recovery in written naming and word writing under dictation tasks. At three follow-ups (1 week, 1 and 2 months after the end of treatment), response accuracy was still significantly better in the anodic than in sham condition, suggesting a long-term effect on the recovery of their articulatory gestures. Copyright © 2011 Elsevier B.V. All rights reserved.

  4. Resting-State Connectivity of the Left Frontal Cortex to the Default Mode and Dorsal Attention Network Supports Reserve in Mild Cognitive Impairment

    Directory of Open Access Journals (Sweden)

    Nicolai Franzmeier

    2017-08-01

    Full Text Available Reserve refers to the phenomenon of relatively preserved cognition in disproportion to the extent of neuropathology, e.g., in Alzheimer’s disease. A putative functional neural substrate underlying reserve is global functional connectivity of the left lateral frontal cortex (LFC, Brodmann Area 6/44. Resting-state fMRI-assessed global LFC-connectivity is associated with protective factors (education and better maintenance of memory in mild cognitive impairment (MCI. Since the LFC is a hub of the fronto-parietal control network that regulates the activity of other networks, the question arises whether LFC-connectivity to specific networks rather than the whole-brain may underlie reserve. We assessed resting-state fMRI in 24 MCI and 16 healthy controls (HC and in an independent validation sample (23 MCI/32 HC. Seed-based LFC-connectivity to seven major resting-state networks (i.e., fronto-parietal, limbic, dorsal-attention, somatomotor, default-mode, ventral-attention, visual was computed, reserve was quantified as residualized memory performance after accounting for age and hippocampal atrophy. In both samples of MCI, LFC-activity was anti-correlated with the default-mode network (DMN, but positively correlated with the dorsal-attention network (DAN. Greater education predicted stronger LFC-DMN-connectivity (anti-correlation and LFC-DAN-connectivity. Stronger LFC-DMN and LFC-DAN-connectivity each predicted higher reserve, consistently in both MCI samples. No associations were detected for LFC-connectivity to other networks. These novel results extend our previous findings on global functional connectivity of the LFC, showing that LFC-connectivity specifically to the DAN and DMN, two core memory networks, enhances reserve in the memory domain in MCI.

  5. An unusual association of headache, epilepsy, and late-onset Kleist’s pseudodepression syndrome in frontal lobe cavernoma of the cerebral left hemisphere

    Directory of Open Access Journals (Sweden)

    Chirchiglia D

    2017-05-01

    Full Text Available Domenico Chirchiglia,1 Attilio Della Torre,1 Domenico Murrone,2 Pasquale Chirchiglia,3 Rosa Marotta4 1Department of Neurosurgery, Neurophysiopathology Unit, University of Catanzaro “Magna Graecia”, Catanzaro, 2Neurosurgery Department, Di Venere Hospital, Bari, 3School of Medicine, University of Catanzaro, Catanzaro, 4Department of Medical and Surgical Sciences, University of Catanzaro, Catanzaro, Italy Abstract: Cerebral cavernous angioma or cavernoma is a benign vascular malformation, usually asymptomatic. It is infrequent and often its discovery is incidental, a so-called incidentaloma. However, these lesions can be symptomatic, causing headaches, epilepsy, cerebral hemorrhage and other neurological signs depending on the brain area involved. Frontal localization is responsible for psychiatric disorders, particularly the prefrontal region, leading to prefrontal syndrome, a condition common in all frontal lobe tumors. Psychopathological syndrome can be depression-type, pseudodepression syndrome or maniac-type, pseudomaniac syndrome. Surgical treatment of lesions like this may not always be possible due to their location in eloquent areas. In this study, we describe an unusual association of migraine-like headache, epilepsy and frontal lobe pseudodepression late-onset syndrome in the same patient. We have considered this case interesting mainly for the rarity of both a headache with migraine features and for the late onset of pseudodepression syndrome. Pathophysiology underlying migraine-like headache and that concerning the late-onset pseudodepression frontal lobe syndrome seems to be unclear. This case leads to further hypotheses about the mechanisms responsible for headache syndromes and psychopathological disorders, in the specific case when caused by a cerebral frontal lobe lesion. Keywords: cerebral cavernoma, cavernous angioma, headache, frontal syndrome, pseudodepression syndrome 

  6. Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain-computer interface: three-class classification of rest, right-, and left-hand motor execution.

    Science.gov (United States)

    Trakoolwilaiwan, Thanawin; Behboodi, Bahareh; Lee, Jaeseok; Kim, Kyungsoo; Choi, Ji-Woong

    2018-01-01

    The aim of this work is to develop an effective brain-computer interface (BCI) method based on functional near-infrared spectroscopy (fNIRS). In order to improve the performance of the BCI system in terms of accuracy, the ability to discriminate features from input signals and proper classification are desired. Previous studies have mainly extracted features from the signal manually, but proper features need to be selected carefully. To avoid performance degradation caused by manual feature selection, we applied convolutional neural networks (CNNs) as the automatic feature extractor and classifier for fNIRS-based BCI. In this study, the hemodynamic responses evoked by performing rest, right-, and left-hand motor execution tasks were measured on eight healthy subjects to compare performances. Our CNN-based method provided improvements in classification accuracy over conventional methods employing the most commonly used features of mean, peak, slope, variance, kurtosis, and skewness, classified by support vector machine (SVM) and artificial neural network (ANN). Specifically, up to 6.49% and 3.33% improvement in classification accuracy was achieved by CNN compared with SVM and ANN, respectively.

  7. Task-based and resting-state fMRI reveal compensatory network changes following damage to left inferior frontal gyrus.

    Science.gov (United States)

    Hallam, Glyn P; Thompson, Hannah E; Hymers, Mark; Millman, Rebecca E; Rodd, Jennifer M; Lambon Ralph, Matthew A; Smallwood, Jonathan; Jefferies, Elizabeth

    2018-02-01

    Damage to left inferior prefrontal cortex in stroke aphasia is associated with semantic deficits reflecting poor control over conceptual retrieval, as opposed to loss of knowledge. However, little is known about how functional recruitment within the semantic network changes in patients with executive-semantic deficits. The current study acquired functional magnetic resonance imaging (fMRI) data from 14 patients with semantic aphasia, who had difficulty with flexible semantic retrieval following left prefrontal damage, and 16 healthy age-matched controls, allowing us to examine activation and connectivity in the semantic network. We examined neural activity while participants listened to spoken sentences that varied in their levels of lexical ambiguity and during rest. We found group differences in two regions thought to be good candidates for functional compensation: ventral anterior temporal lobe (vATL), which is strongly implicated in comprehension, and posterior middle temporal gyrus (pMTG), which is hypothesized to work together with left inferior prefrontal cortex to support controlled aspects of semantic retrieval. The patients recruited both of these sites more than controls in response to meaningful sentences. Subsequent analysis identified that, in control participants, the recruitment of pMTG to ambiguous sentences was inversely related to functional coupling between pMTG and anterior superior temporal gyrus (aSTG) at rest, while the patients showed the opposite pattern. Moreover, stronger connectivity between pMTG and aSTG in patients was associated with better performance on a test of verbal semantic association, suggesting that this temporal lobe connection supports comprehension in the face of damage to left inferior prefrontal cortex. These results characterize network changes in patients with executive-semantic deficits and converge with studies of healthy participants in providing evidence for a distributed system underpinning semantic control that

  8. A Preliminary fMRI Study of a Novel Self-Paced Written Fluency Task: Observation of Left-Hemispheric Activation, and Increased Frontal Activation in Late vs. Early Task Phases

    Directory of Open Access Journals (Sweden)

    Laleh eGolestanirad

    2015-03-01

    Full Text Available Neuropsychological tests of verbal fluency are very widely used to characterize impaired cognitive function. For clinical neuroscience studies and potential medical applications, measuring the brain activity that underlies such tests with functional magnetic resonance imaging (fMRI is of significant interest - but a challenging proposition because overt speech can cause signal artifacts, which tend to worsen as the duration of speech tasks becomes longer. In a novel approach, we present the group brain activity of 12 subjects who performed a self-paced written version of phonemic fluency using fMRI-compatible tablet technology that recorded responses and provided task-related feedback on a projection screen display, over long-duration task blocks (60 s. As predicted, we observed robust activation in the left anterior inferior and medial frontal gyri, consisting with previously reported results of verbal fluency tasks which established the role of these areas in strategic word retrieval. In addition, the number of words produced in the late phase (last 30 s of written phonemic fluency was significantly less (p < 0.05 than the number produced in the early phase (first 30 s. Activation during the late phase vs. the early phase was also assessed from the first 20 s and last 20 s of task performance, which eliminated the possibility that the sluggish hemodynamic response from the early phase would affect the activation estimates of the late phase. The last 20 s produced greater activation maps covering extended areas in bilateral precuneus, cuneus, middle temporal gyrus, insula, middle frontal gyrus and cingulate gyrus. Among them, greater activation was observed in the bilateral middle frontal gyrus (Brodmann area BA 9 and cingulate gyrus (BA 24, 32 likely as part of the initiation, maintenance, and shifting of attentional resources.

  9. Supervised Convolutional Sparse Coding

    KAUST Repository

    Affara, Lama Ahmed

    2018-04-08

    Convolutional Sparse Coding (CSC) is a well-established image representation model especially suited for image restoration tasks. In this work, we extend the applicability of this model by proposing a supervised approach to convolutional sparse coding, which aims at learning discriminative dictionaries instead of purely reconstructive ones. We incorporate a supervised regularization term into the traditional unsupervised CSC objective to encourage the final dictionary elements to be discriminative. Experimental results show that using supervised convolutional learning results in two key advantages. First, we learn more semantically relevant filters in the dictionary and second, we achieve improved image reconstruction on unseen data.

  10. The roles of the Q (q) wave in lead I and QRS frontal axis for diagnosing loss of left ventricular capture during cardiac resynchronization therapy.

    Science.gov (United States)

    Cao, Yuan-Yuan; Su, Yan-Gang; Bai, Jin; Wang, Wei; Wang, Jing-Feng; Qin, Sheng-Mei; Ge, Jun-Bo

    2015-01-01

    Loss of left ventricular (LV) capture may lead to deterioration of heart failure in patients with cardiac resynchronization therapy (CRT). Recognition of loss of LV capture in time is important in clinical practice. A total of 422 electrocardiograms were acquired and analyzed from 53 CRT patients at 8 different pacing settings (LV only, right ventricle [RV] only, biventricular [BV] pacing with LV preactivation of 60, 40, 20, and 0 milliseconds and RV preactivation of 20 and 40 milliseconds). A modified Ammann algorithm by adding a third step-presence of Q (q, or QS) wave-to the original 2-step Ammann algorithm and a QRS axis shift method were devised to identify the loss of LV capture. The accuracy of modified Ammann algorithm was significantly higher than that of Ammann algorithm (78.9% vs. 69.1%, P capture. The LV preactivation, or simultaneous BV activation and LV lead positioned in nonposterior or noninferior wall can increase the diagnostic power of the modified Ammann algorithm and QRS axis shift method. © 2014 Wiley Periodicals, Inc.

  11. Convolution based profile fitting

    International Nuclear Information System (INIS)

    Kern, A.; Coelho, A.A.; Cheary, R.W.

    2002-01-01

    Full text: In convolution based profile fitting, profiles are generated by convoluting functions together to form the observed profile shape. For a convolution of 'n' functions this process can be written as, Y(2θ)=F 1 (2θ)x F 2 (2θ)x... x F i (2θ)x....xF n (2θ). In powder diffractometry the functions F i (2θ) can be interpreted as the aberration functions of the diffractometer, but in general any combination of appropriate functions for F i (2θ) may be used in this context. Most direct convolution fitting methods are restricted to combinations of F i (2θ) that can be convoluted analytically (e.g. GSAS) such as Lorentzians, Gaussians, the hat (impulse) function and the exponential function. However, software such as TOPAS is now available that can accurately convolute and refine a wide variety of profile shapes numerically, including user defined profiles, without the need to convolute analytically. Some of the most important advantages of modern convolution based profile fitting are: 1) virtually any peak shape and angle dependence can normally be described using minimal profile parameters in laboratory and synchrotron X-ray data as well as in CW and TOF neutron data. This is possible because numerical convolution and numerical differentiation is used within the refinement procedure so that a wide range of functions can easily be incorporated into the convolution equation; 2) it can use physically based diffractometer models by convoluting the instrument aberration functions. This can be done for most laboratory based X-ray powder diffractometer configurations including conventional divergent beam instruments, parallel beam instruments, and diffractometers used for asymmetric diffraction. It can also accommodate various optical elements (e.g. multilayers and monochromators) and detector systems (e.g. point and position sensitive detectors) and has already been applied to neutron powder diffraction systems (e.g. ANSTO) as well as synchrotron based

  12. The frontal lobes and inhibitory function

    International Nuclear Information System (INIS)

    Konishi, Seiki

    2011-01-01

    Neuropsychological studies using traditional tasks of inhibitory functions, such as the Wisconsin card sorting test (WCST) and the Go/No-Go Task have revealed that the frontal lobe is responsible for several types of inhibitory functions. However, the detailed psychological nature of the inhibitory functions and the precise location of their critical foci within the frontal lobe remain to be investigated. Functional magnetic resonance imaging provides spatial and temporal resolution that allowed us to illuminate at least 4 frontal regions involved in inhibitory functions: the dorsolateral, ventrolateral, and rostral parts of the frontal lobe and the presupplementary motor area (preSMA). The ventrolateral part of the frontal lobe in the right hemisphere was activated during response inhibition. The preSMA in the left hemisphere was activated during inhibition of proactive interference immediately after the dimension changes of the WCST. The rostral part of the frontal lobe in the left hemisphere was activated during inhibition long after the dimension changes. The dorsolateral part of the frontal lobe in the left hemisphere was activated at the dimension changes in the first time, but not in the second time. These findings provide clues to our understanding of functional differentiation of inhibitory functions and their localization in the frontal lobe. (author)

  13. Convolution copula econometrics

    CERN Document Server

    Cherubini, Umberto; Mulinacci, Sabrina

    2016-01-01

    This book presents a novel approach to time series econometrics, which studies the behavior of nonlinear stochastic processes. This approach allows for an arbitrary dependence structure in the increments and provides a generalization with respect to the standard linear independent increments assumption of classical time series models. The book offers a solution to the problem of a general semiparametric approach, which is given by a concept called C-convolution (convolution of dependent variables), and the corresponding theory of convolution-based copulas. Intended for econometrics and statistics scholars with a special interest in time series analysis and copula functions (or other nonparametric approaches), the book is also useful for doctoral students with a basic knowledge of copula functions wanting to learn about the latest research developments in the field.

  14. Efficient convolutional sparse coding

    Science.gov (United States)

    Wohlberg, Brendt

    2017-06-20

    Computationally efficient algorithms may be applied for fast dictionary learning solving the convolutional sparse coding problem in the Fourier domain. More specifically, efficient convolutional sparse coding may be derived within an alternating direction method of multipliers (ADMM) framework that utilizes fast Fourier transforms (FFT) to solve the main linear system in the frequency domain. Such algorithms may enable a significant reduction in computational cost over conventional approaches by implementing a linear solver for the most critical and computationally expensive component of the conventional iterative algorithm. The theoretical computational cost of the algorithm may be reduced from O(M.sup.3N) to O(MN log N), where N is the dimensionality of the data and M is the number of elements in the dictionary. This significant improvement in efficiency may greatly increase the range of problems that can practically be addressed via convolutional sparse representations.

  15. Multithreaded implicitly dealiased convolutions

    Science.gov (United States)

    Roberts, Malcolm; Bowman, John C.

    2018-03-01

    Implicit dealiasing is a method for computing in-place linear convolutions via fast Fourier transforms that decouples work memory from input data. It offers easier memory management and, for long one-dimensional input sequences, greater efficiency than conventional zero-padding. Furthermore, for convolutions of multidimensional data, the segregation of data and work buffers can be exploited to reduce memory usage and execution time significantly. This is accomplished by processing and discarding data as it is generated, allowing work memory to be reused, for greater data locality and performance. A multithreaded implementation of implicit dealiasing that accepts an arbitrary number of input and output vectors and a general multiplication operator is presented, along with an improved one-dimensional Hermitian convolution that avoids the loop dependency inherent in previous work. An alternate data format that can accommodate a Nyquist mode and enhance cache efficiency is also proposed.

  16. Impairments in proverb interpretation following focal frontal lobe lesions☆

    Science.gov (United States)

    Murphy, Patrick; Shallice, Tim; Robinson, Gail; MacPherson, Sarah E.; Turner, Martha; Woollett, Katherine; Bozzali, Marco; Cipolotti, Lisa

    2013-01-01

    The proverb interpretation task (PIT) is often used in clinical settings to evaluate frontal “executive” dysfunction. However, only a relatively small number of studies have investigated the relationship between frontal lobe lesions and performance on the PIT. We compared 52 patients with unselected focal frontal lobe lesions with 52 closely matched healthy controls on a proverb interpretation task. Participants also completed a battery of neuropsychological tests, including a fluid intelligence task (Raven’s Advanced Progressive Matrices). Lesions were firstly analysed according to a standard left/right sub-division. Secondly, a finer-grained analysis compared the performance of patients with medial, left lateral and right lateral lesions with healthy controls. Thirdly, a contrast of specific frontal subgroups compared the performance of patients with medial lesions with patients with lateral frontal lesions. The results showed that patients with left frontal lesions were significantly impaired on the PIT, while in patients with right frontal lesions the impairments approached significance. Medial frontal patients were the only frontal subgroup impaired on the PIT, relative to healthy controls and lateral frontal patients. Interestingly, an error analysis indicated that a significantly higher number of concrete responses were found in the left lateral subgroup compared to healthy controls. We found no correlation between scores on the PIT and on the fluid intelligence task. Overall our results suggest that specific regions of the frontal lobes contribute to the performance on the PIT. PMID:23850600

  17. Impairments in proverb interpretation following focal frontal lobe lesions.

    Science.gov (United States)

    Murphy, Patrick; Shallice, Tim; Robinson, Gail; MacPherson, Sarah E; Turner, Martha; Woollett, Katherine; Bozzali, Marco; Cipolotti, Lisa

    2013-09-01

    The proverb interpretation task (PIT) is often used in clinical settings to evaluate frontal "executive" dysfunction. However, only a relatively small number of studies have investigated the relationship between frontal lobe lesions and performance on the PIT. We compared 52 patients with unselected focal frontal lobe lesions with 52 closely matched healthy controls on a proverb interpretation task. Participants also completed a battery of neuropsychological tests, including a fluid intelligence task (Raven's Advanced Progressive Matrices). Lesions were firstly analysed according to a standard left/right sub-division. Secondly, a finer-grained analysis compared the performance of patients with medial, left lateral and right lateral lesions with healthy controls. Thirdly, a contrast of specific frontal subgroups compared the performance of patients with medial lesions with patients with lateral frontal lesions. The results showed that patients with left frontal lesions were significantly impaired on the PIT, while in patients with right frontal lesions the impairments approached significance. Medial frontal patients were the only frontal subgroup impaired on the PIT, relative to healthy controls and lateral frontal patients. Interestingly, an error analysis indicated that a significantly higher number of concrete responses were found in the left lateral subgroup compared to healthy controls. We found no correlation between scores on the PIT and on the fluid intelligence task. Overall our results suggest that specific regions of the frontal lobes contribute to the performance on the PIT. © 2013 The Authors. Published by Elsevier Ltd. All rights reserved.

  18. Mind the movement: Frontal asymmetry stands for behavioral motivation, bilateral frontal activation for behavior.

    Science.gov (United States)

    Rodrigues, Johannes; Müller, Mathias; Mühlberger, Andreas; Hewig, Johannes

    2018-01-01

    Frontal asymmetry has been investigated over the past 30 years, and several theories have been developed about its meaning. The original theory of Davidson and its diversification by Harmon-Jones & Allen allocated approach motivation to relative left frontal brain activity and withdrawal motivation to relative right frontal brain activity. Hewig and colleagues extended this theory by adding bilateral frontal activation representing a biological correlate of the behavioral activation system if actual behavior is shown. Wacker and colleagues formulated a theory related to the revised reinforcement sensitivity theory by Gray & McNaughton. Here, relative left frontal brain activation represents the revised behavioral activation system and behavior, while relative right frontal brain activation represents the revised behavioral inhibition system, representing the experience of conflict. These theories were investigated with a newly developed paradigm where participants were able to move around freely in a virtual T maze via joystick while having their EEG recorded. Analyzing the influence of frontal brain activation during this virtual reality task on observable behavior for 30 participants, we found more relative left frontal brain activation during approach behavior and more relative right brain activation for withdrawal behavior of any kind. Additionally, there was more bilateral frontal brain activation when participants were engaged in behavior compared to doing nothing. Hence, this study provides evidence for the idea that frontal asymmetry stands for behavioral approach or avoidance motivation, and bilateral frontal activation stands for behavior. Additionally, observable behavior is not only determined by frontal asymmetry, but also by relevant traits. © 2017 Society for Psychophysiological Research.

  19. Frontal ataxia in childhood.

    Science.gov (United States)

    Erasmus, C E; Beems, T; Rotteveel, J J

    2004-12-01

    Frontal ataxia may be the result of a unilateral frontal lesion. In this report three cases are presented with ataxia due to right frontal lesions. One case concerns a boy presenting with an unsteady gait and titubation of the trunk, mimicking developmental disequilibrium and with complex partial seizures. It proved to be caused by a small right-sided cavernoma in the middle frontal gyrus. After surgical intervention the symptoms and the seizures disappeared. Two subsequent cases concern teenage patients presenting with headache after an ENT infection and on physical examination mild dysmetric function of the upper limbs and slight disequilibrium, due to right-sided frontal lobe abscesses. After neurosurgical and antibiotic therapy the symptoms were relieved. The frontal origin of ataxia should be considered in children presenting with a "cerebellar syndrome". Frontal gait disorders consist of a clinical pattern of different gait disorders. The syndrome has been mentioned in the literature under different names. Our patients show signs compatible with the term frontal disequilibrium, a clinical pattern of frontal gait disorder. This assumes walking problems characterized by loss of control of motor planning, leading to imbalance. Remarkably, frontal ataxia may mimic developmental delay as demonstrated in the first case and may be the leading mild symptom in extensive frontal lobe damage as demonstrated by the two other cases. We suppose that frontal ataxia is the result of a disturbance in the cerebellar-frontal circuitries and an impairment of executive and planning functions of the basal ganglia-frontal lobe circuitry.

  20. Frontal Lobe Seizures

    Science.gov (United States)

    ... cause of frontal lobe epilepsy remains unknown. Complications Status epilepticus. Frontal lobe seizures tend to occur in clusters and may provoke a dangerous condition called status epilepticus — in which seizure activity lasts much longer than ...

  1. Frontal ataxia in childhood.

    OpenAIRE

    Erasmus, C.E.; Beems, T.; Rotteveel, J.J.

    2004-01-01

    Frontal ataxia may be the result of a unilateral frontal lesion. In this report three cases are presented with ataxia due to right frontal lesions. One case concerns a boy presenting with an unsteady gait and titubation of the trunk, mimicking developmental disequilibrium and with complex partial seizures. It proved to be caused by a small right-sided cavernoma in the middle frontal gyrus. After surgical intervention the symptoms and the seizures disappeared. Two subsequent cases concern teen...

  2. Frontal ataxia in childhood.

    NARCIS (Netherlands)

    Erasmus, C.E.; Beems, T.; Rotteveel, J.J.

    2004-01-01

    Frontal ataxia may be the result of a unilateral frontal lesion. In this report three cases are presented with ataxia due to right frontal lesions. One case concerns a boy presenting with an unsteady gait and titubation of the trunk, mimicking developmental disequilibrium and with complex partial

  3. Convolutional coding techniques for data protection

    Science.gov (United States)

    Massey, J. L.

    1975-01-01

    Results of research on the use of convolutional codes in data communications are presented. Convolutional coding fundamentals are discussed along with modulation and coding interaction. Concatenated coding systems and data compression with convolutional codes are described.

  4. The convolution transform

    CERN Document Server

    Hirschman, Isidore Isaac

    2005-01-01

    In studies of general operators of the same nature, general convolution transforms are immediately encountered as the objects of inversion. The relation between differential operators and integral transforms is the basic theme of this work, which is geared toward upper-level undergraduates and graduate students. It may be read easily by anyone with a working knowledge of real and complex variable theory. Topics include the finite and non-finite kernels, variation diminishing transforms, asymptotic behavior of kernels, real inversion theory, representation theory, the Weierstrass transform, and

  5. Separating Underdetermined Convolutive Speech Mixtures

    DEFF Research Database (Denmark)

    Pedersen, Michael Syskind; Wang, DeLiang; Larsen, Jan

    2006-01-01

    a method for underdetermined blind source separation of convolutive mixtures. The proposed framework is applicable for separation of instantaneous as well as convolutive speech mixtures. It is possible to iteratively extract each speech signal from the mixture by combining blind source separation...

  6. Strongly-MDS convolutional codes

    NARCIS (Netherlands)

    Gluesing-Luerssen, H; Rosenthal, J; Smarandache, R

    Maximum-distance separable (MDS) convolutional codes have the property that their free distance is maximal among all codes of the same rate and the same degree. In this paper, a class of MDS convolutional codes is introduced whose column distances reach the generalized Singleton bound at the

  7. Consensus Convolutional Sparse Coding

    KAUST Repository

    Choudhury, Biswarup

    2017-12-01

    Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high-dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaicing and 4D light field view synthesis.

  8. Consensus Convolutional Sparse Coding

    KAUST Repository

    Choudhury, Biswarup

    2017-04-11

    Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaickingand 4D light field view synthesis.

  9. Consensus Convolutional Sparse Coding

    KAUST Repository

    Choudhury, Biswarup; Swanson, Robin; Heide, Felix; Wetzstein, Gordon; Heidrich, Wolfgang

    2017-01-01

    Convolutional sparse coding (CSC) is a promising direction for unsupervised learning in computer vision. In contrast to recent supervised methods, CSC allows for convolutional image representations to be learned that are equally useful for high-level vision tasks and low-level image reconstruction and can be applied to a wide range of tasks without problem-specific retraining. Due to their extreme memory requirements, however, existing CSC solvers have so far been limited to low-dimensional problems and datasets using a handful of low-resolution example images at a time. In this paper, we propose a new approach to solving CSC as a consensus optimization problem, which lifts these limitations. By learning CSC features from large-scale image datasets for the first time, we achieve significant quality improvements in a number of imaging tasks. Moreover, the proposed method enables new applications in high-dimensional feature learning that has been intractable using existing CSC methods. This is demonstrated for a variety of reconstruction problems across diverse problem domains, including 3D multispectral demosaicing and 4D light field view synthesis.

  10. Frontal subregions mediating Elevator Counting task performance.

    Science.gov (United States)

    MacPherson, Sarah E; Turner, Martha S; Bozzali, Marco; Cipolotti, Lisa; Shallice, Tim

    2010-10-01

    Deficits in sustained attention may lead to action slips in everyday life as irrelevant action sequences are inappropriately triggered internally or by the environment. While deficits in sustained attention have been associated with damage to the frontal lobes of the brain, little is known about the role of the frontal lobes in the Elevator Counting subtest of the Test of Everyday Attention. In the current study, 55 frontal patients subdivided into medial, orbital and lateral subgroups, 18 patients with posterior lesions and 82 healthy controls performed the Elevator Counting task. The results revealed that patients with medial and left lateral prefrontal lesions were significantly impaired on the task compared to healthy controls. Research suggests that patients with medial lesions are susceptible to competition from task irrelevant schema; whereas the left lateral group in the current study may fail to keep track of the tones already presented. Copyright © 2010 Elsevier Ltd. All rights reserved.

  11. Dealiased convolutions for pseudospectral simulations

    International Nuclear Information System (INIS)

    Roberts, Malcolm; Bowman, John C

    2011-01-01

    Efficient algorithms have recently been developed for calculating dealiased linear convolution sums without the expense of conventional zero-padding or phase-shift techniques. For one-dimensional in-place convolutions, the memory requirements are identical with the zero-padding technique, with the important distinction that the additional work memory need not be contiguous with the input data. This decoupling of data and work arrays dramatically reduces the memory and computation time required to evaluate higher-dimensional in-place convolutions. The memory savings is achieved by computing the in-place Fourier transform of the data in blocks, rather than all at once. The technique also allows one to dealias the n-ary convolutions that arise on Fourier transforming cubic and higher powers. Implicitly dealiased convolutions can be built on top of state-of-the-art adaptive fast Fourier transform libraries like FFTW. Vectorized multidimensional implementations for the complex and centered Hermitian (pseudospectral) cases have already been implemented in the open-source software FFTW++. With the advent of this library, writing a high-performance dealiased pseudospectral code for solving nonlinear partial differential equations has now become a relatively straightforward exercise. New theoretical estimates of computational complexity and memory use are provided, including corrected timing results for 3D pruned convolutions and further consideration of higher-order convolutions.

  12. Regulatory behavior and frontal activity: Considering the role of revised-BIS in relative right frontal asymmetry.

    Science.gov (United States)

    Gable, Philip A; Neal, Lauren B; Threadgill, A Hunter

    2018-01-01

    Essential to human behavior are three core personality systems: approach, avoidance, and a regulatory system governing the two motivational systems. Decades of research has linked approach motivation with greater relative left frontal-cortical asymmetry. Other research has linked avoidance motivation with greater relative right frontal-cortical asymmetry. However, past work linking withdrawal motivation with greater relative right frontal asymmetry has been mixed. The current article reviews evidence suggesting that activation of the regulatory system (revised Behavioral Inhibition System [r-BIS]) may be more strongly related to greater relative right frontal asymmetry than withdrawal motivation. Specifically, research suggests that greater activation of the r-BIS is associated with greater relative right frontal activity, and reduced r-BIS activation is associated with reduced right frontal activity (greater relative left frontal activity). We review evidence examining trait and state frontal activity using EEG, source localization, lesion studies, neuronal stimulation, and fMRI supporting the idea that r-BIS may be the core personality system related to greater relative right frontal activity. In addition, the current review seeks to disentangle avoidance motivation and r-BIS as substrates of relative right frontal asymmetry. © 2017 Society for Psychophysiological Research.

  13. Is Kinesio Taping to Generate Skin Convolutions Effective for Increasing Local Blood Circulation?

    OpenAIRE

    Yang, Jae-Man; Lee, Jung-Hoon

    2018-01-01

    Background It is unclear whether traditional application of Kinesio taping, which produces wrinkles in the skin, is effective for improving blood circulation. This study investigated local skin temperature changes after the application of an elastic therapeutic tape using convolution and non-convolution taping methods (CTM/NCTM). Material/Methods Twenty-eight pain-free men underwent CTM and NCTM randomly applied to the right and left sides of the lower back. Using infrared thermography, skin ...

  14. Craniotomy Frontal Bone Defect

    African Journals Online (AJOL)

    2018-03-01

    Mar 1, 2018 ... Defect reconstruction and fixation of the graft: The defect of ... where all loose fragments of fractured frontal bone was removed via the ... Mandible. • Ilium. • Allograft ... pediatric patients owing to skull growth. Thus, autologous ...

  15. Design of convolutional tornado code

    Science.gov (United States)

    Zhou, Hui; Yang, Yao; Gao, Hongmin; Tan, Lu

    2017-09-01

    As a linear block code, the traditional tornado (tTN) code is inefficient in burst-erasure environment and its multi-level structure may lead to high encoding/decoding complexity. This paper presents a convolutional tornado (cTN) code which is able to improve the burst-erasure protection capability by applying the convolution property to the tTN code, and reduce computational complexity by abrogating the multi-level structure. The simulation results show that cTN code can provide a better packet loss protection performance with lower computation complexity than tTN code.

  16. Solutions to Arithmetic Convolution Equations

    Czech Academy of Sciences Publication Activity Database

    Glöckner, H.; Lucht, L.G.; Porubský, Štefan

    2007-01-01

    Roč. 135, č. 6 (2007), s. 1619-1629 ISSN 0002-9939 R&D Projects: GA ČR GA201/04/0381 Institutional research plan: CEZ:AV0Z10300504 Keywords : arithmetic functions * Dirichlet convolution * polynomial equations * analytic equations * topological algebras * holomorphic functional calculus Subject RIV: BA - General Mathematics Impact factor: 0.520, year: 2007

  17. Adaptive Graph Convolutional Neural Networks

    OpenAIRE

    Li, Ruoyu; Wang, Sheng; Zhu, Feiyun; Huang, Junzhou

    2018-01-01

    Graph Convolutional Neural Networks (Graph CNNs) are generalizations of classical CNNs to handle graph data such as molecular data, point could and social networks. Current filters in graph CNNs are built for fixed and shared graph structure. However, for most real data, the graph structures varies in both size and connectivity. The paper proposes a generalized and flexible graph CNN taking data of arbitrary graph structure as input. In that way a task-driven adaptive graph is learned for eac...

  18. Convolution of Distribution-Valued Functions. Applications.

    OpenAIRE

    BARGETZ, CHRISTIAN

    2011-01-01

    In this article we examine products and convolutions of vector-valued functions. For nuclear normal spaces of distributions Proposition 25 in [31,p. 120] yields a vector-valued product or convolution if there is a continuous product or convolution mapping in the range of the vector-valued functions. For specific spaces, we generalize this result to hypocontinuous bilinear maps at the expense of generality with respect to the function space. We consider holomorphic, meromorphic and differentia...

  19. Frontal Integration and Coping

    DEFF Research Database (Denmark)

    Larsen, Torben

    2012-01-01

    reciprocal to Mesolimbic dopamine activity (mood). The study aims to explore interpersonal differences in coping associated with neural properties. Method: Neuroeconomic literature search of how neural centers of Rc2/L shape risk attitude2 or coping. Results: General risk attitude is a right skewed...... to the classical tempers. In prospect, differentiating the Frontal integration pattern by temper (General risk attitude) opens an evidence-based pathway for individually tailored neural training towards advanced social objectives as multidisciplinary collaboration and healthy living. References 1. Larsen T...

  20. Incomplete convolutions in production and inventory models

    NARCIS (Netherlands)

    Houtum, van G.J.J.A.N.; Zijm, W.H.M.

    1997-01-01

    In this paper, we study incomplete convolutions of continuous distribution functions, as they appear in the analysis of (multi-stage) production and inventory systems. Three example systems are discussed where these incomplete convolutions naturally arise. We derive explicit, nonrecursive formulae

  1. A convolutional approach to reflection symmetry

    DEFF Research Database (Denmark)

    Cicconet, Marcelo; Birodkar, Vighnesh; Lund, Mads

    2017-01-01

    We present a convolutional approach to reflection symmetry detection in 2D. Our model, built on the products of complex-valued wavelet convolutions, simplifies previous edge-based pairwise methods. Being parameter-centered, as opposed to feature-centered, it has certain computational advantages w...

  2. Symbol synchronization in convolutionally coded systems

    Science.gov (United States)

    Baumert, L. D.; Mceliece, R. J.; Van Tilborg, H. C. A.

    1979-01-01

    Alternate symbol inversion is sometimes applied to the output of convolutional encoders to guarantee sufficient richness of symbol transition for the receiver symbol synchronizer. A bound is given for the length of the transition-free symbol stream in such systems, and those convolutional codes are characterized in which arbitrarily long transition free runs occur.

  3. The general theory of convolutional codes

    Science.gov (United States)

    Mceliece, R. J.; Stanley, R. P.

    1993-01-01

    This article presents a self-contained introduction to the algebraic theory of convolutional codes. This introduction is partly a tutorial, but at the same time contains a number of new results which will prove useful for designers of advanced telecommunication systems. Among the new concepts introduced here are the Hilbert series for a convolutional code and the class of compact codes.

  4. Pediatric frontal mucocele secondary to a bifid frontal sinus septum.

    Science.gov (United States)

    Plikaitis, Christina M; Purzycki, Adam R; Couture, Daniel; David, Lisa R

    2010-09-01

    A mucocele is a mucus-containing sac lined with epithelium that arises within a sinus when its drainage is compromised. The frontal sinus is the most common location, with frontal mucocele development occurring when the nasofrontal duct becomes obstructed because of polyps, bone tumors, prior surgery, sinusitis, trauma, or anatomic variation. We report an unusual case of a sterile pediatric frontal mucocele presenting as a slowly enlarging forehead mass due to a bifid frontal sinus septum. A 9-year-old girl presented to the craniofacial clinic for evaluation of a right frontal mass that had been slowly growing over the past year. She was otherwise healthy and had no history of previous trauma or sinus infections. Computed tomography (CT) scan results revealed a localized frontal fluid collection with protrusion and thinning of the anterior frontal bone between 2 midline bony septii. Surgical cranialization of the frontal sinus was performed. The anatomy of her lesion seen both on CT scan and intraoperatively likely explains this unusual case presentation. Instead of the usual inciting event of an intact frontal sinus drainage system becoming blocked, this patient seemed to have a primary developmental lack of any drainage system that led to her mucocele. During formation of her frontal sinus, she developed a bifid septum within the midline that excluded a portion of her frontal sinus from the lateral nasofrontal ducts. With mucus-producing epithelium trapped within these bony confines, pressure began to mount with expansion and thinning of the bone both anteriorly and posteriorly. The lack of any infectious symptoms and sterile culture results may support that this space developed primarily and was never in continuity with the external drainage system. Only 4 other patients have been reported with asymptomatic forehead swelling as the only presenting symptom, with the age ranging from 33 to 79 years. This patient represents the first clinical report of a congenital

  5. Convolution-deconvolution in DIGES

    International Nuclear Information System (INIS)

    Philippacopoulos, A.J.; Simos, N.

    1995-01-01

    Convolution and deconvolution operations is by all means a very important aspect of SSI analysis since it influences the input to the seismic analysis. This paper documents some of the convolution/deconvolution procedures which have been implemented into the DIGES code. The 1-D propagation of shear and dilatational waves in typical layered configurations involving a stack of layers overlying a rock is treated by DIGES in a similar fashion to that of available codes, e.g. CARES, SHAKE. For certain configurations, however, there is no need to perform such analyses since the corresponding solutions can be obtained in analytic form. Typical cases involve deposits which can be modeled by a uniform halfspace or simple layered halfspaces. For such cases DIGES uses closed-form solutions. These solutions are given for one as well as two dimensional deconvolution. The type of waves considered include P, SV and SH waves. The non-vertical incidence is given special attention since deconvolution can be defined differently depending on the problem of interest. For all wave cases considered, corresponding transfer functions are presented in closed-form. Transient solutions are obtained in the frequency domain. Finally, a variety of forms are considered for representing the free field motion both in terms of deterministic as well as probabilistic representations. These include (a) acceleration time histories, (b) response spectra (c) Fourier spectra and (d) cross-spectral densities

  6. Model structure selection in convolutive mixtures

    DEFF Research Database (Denmark)

    Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai

    2006-01-01

    The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious represent......The CICAAR algorithm (convolutive independent component analysis with an auto-regressive inverse model) allows separation of white (i.i.d) source signals from convolutive mixtures. We introduce a source color model as a simple extension to the CICAAR which allows for a more parsimonious...... representation in many practical mixtures. The new filter-CICAAR allows Bayesian model selection and can help answer questions like: ’Are we actually dealing with a convolutive mixture?’. We try to answer this question for EEG data....

  7. Convolutions

    Indian Academy of Sciences (India)

    President's Address to the Association of Mathematics Teachers of India, December 2011. I am expected to tell you, in 25 minutes, something that should interest you, excite you, pique your curiosity, and make you look for more. It is a tall order, but I will try. The word 'interactive' is in fashion these days. So I will leave a few ...

  8. Frontal alpha asymmetry neurofeedback for the reduction of negative affect and anxiety.

    Science.gov (United States)

    Mennella, Rocco; Patron, Elisabetta; Palomba, Daniela

    2017-05-01

    Frontal alpha asymmetry has been proposed to underlie the balance between approach and withdrawal motivation associated to each individual's affective style. Neurofeedback of EEG frontal alpha asymmetry represents a promising tool to reduce negative affect, although its specific effects on left/right frontal activity and approach/withdrawal motivation are still unclear. The present study employed a neurofeedback training to increase frontal alpha asymmetry (right - left), in order to evaluate discrete changes in alpha power at left and right sites, as well as in positive and negative affect, anxiety and depression. Thirty-two right-handed females were randomly assigned to receive either the neurofeedback on frontal alpha asymmetry, or an active control training (N = 16 in each group). The asymmetry group showed an increase in alpha asymmetry driven by higher alpha at the right site (p neurofeedback for the reduction of negative affect and anxiety in clinical settings. Copyright © 2017 Elsevier Ltd. All rights reserved.

  9. Adaptive decoding of convolutional codes

    Directory of Open Access Journals (Sweden)

    K. Hueske

    2007-06-01

    Full Text Available Convolutional codes, which are frequently used as error correction codes in digital transmission systems, are generally decoded using the Viterbi Decoder. On the one hand the Viterbi Decoder is an optimum maximum likelihood decoder, i.e. the most probable transmitted code sequence is obtained. On the other hand the mathematical complexity of the algorithm only depends on the used code, not on the number of transmission errors. To reduce the complexity of the decoding process for good transmission conditions, an alternative syndrome based decoder is presented. The reduction of complexity is realized by two different approaches, the syndrome zero sequence deactivation and the path metric equalization. The two approaches enable an easy adaptation of the decoding complexity for different transmission conditions, which results in a trade-off between decoding complexity and error correction performance.

  10. Adaptive decoding of convolutional codes

    Science.gov (United States)

    Hueske, K.; Geldmacher, J.; Götze, J.

    2007-06-01

    Convolutional codes, which are frequently used as error correction codes in digital transmission systems, are generally decoded using the Viterbi Decoder. On the one hand the Viterbi Decoder is an optimum maximum likelihood decoder, i.e. the most probable transmitted code sequence is obtained. On the other hand the mathematical complexity of the algorithm only depends on the used code, not on the number of transmission errors. To reduce the complexity of the decoding process for good transmission conditions, an alternative syndrome based decoder is presented. The reduction of complexity is realized by two different approaches, the syndrome zero sequence deactivation and the path metric equalization. The two approaches enable an easy adaptation of the decoding complexity for different transmission conditions, which results in a trade-off between decoding complexity and error correction performance.

  11. Origami by frontal photopolymerization.

    Science.gov (United States)

    Zhao, Zeang; Wu, Jiangtao; Mu, Xiaoming; Chen, Haosen; Qi, H Jerry; Fang, Daining

    2017-04-01

    Origami structures are of great interest in microelectronics, soft actuators, mechanical metamaterials, and biomedical devices. Current methods of fabricating origami structures still have several limitations, such as complex material systems or tedious processing steps. We present a simple approach for creating three-dimensional (3D) origami structures by the frontal photopolymerization method, which can be easily implemented by using a commercial projector. The concept of our method is based on the volume shrinkage during photopolymerization. By adding photoabsorbers into the polymer resin, an attenuated light field is created and leads to a nonuniform curing along the thickness direction. The layer directly exposed to light cures faster than the next layer; this nonuniform curing degree leads to nonuniform curing-induced volume shrinkage. This further introduces a nonuniform stress field, which drives the film to bend toward the newly formed side. The degree of bending can be controlled by adjusting the gray scale and the irradiation time, an easy approach for creating origami structures. The behavior is examined both experimentally and theoretically. Two methods are also proposed to create different types of 3D origami structures.

  12. Convolutional Neural Network for Image Recognition

    CERN Document Server

    Seifnashri, Sahand

    2015-01-01

    The aim of this project is to use machine learning techniques especially Convolutional Neural Networks for image processing. These techniques can be used for Quark-Gluon discrimination using calorimeters data, but unfortunately I didn’t manage to get the calorimeters data and I just used the Jet data fromminiaodsim(ak4 chs). The Jet data was not good enough for Convolutional Neural Network which is designed for ’image’ recognition. This report is made of twomain part, part one is mainly about implementing Convolutional Neural Network on unphysical data such as MNIST digits and CIFAR-10 dataset and part 2 is about the Jet data.

  13. Co-activation-based parcellation of the lateral prefrontal cortex delineates the inferior frontal junction area

    OpenAIRE

    Muhle-Karbe, Paul Simon; Derrfuss, Jan; Lynn, Maggie; Neubert, Franz Xaver; Fox, Peter; Brass, Marcel; Eickhoff, Simon

    2016-01-01

    The inferior frontal junction (IFJ) area, a small region in the posterior lateral prefrontal cortex (LPFC), has received increasing interest in recent years due to its central involvement in the control of action, attention, and memory. Yet, both its function and anatomy remain controversial. Here, we employed a meta-analytic parcellation of the left LPFC to show that the IFJ can be isolated based on its specific functional connections. A seed region, oriented along the left inferior frontal ...

  14. The validity of individual frontal alpha asymmetry EEG neurofeedback.

    Science.gov (United States)

    Quaedflieg, C W E M; Smulders, F T Y; Meyer, T; Peeters, F; Merckelbach, H; Smeets, T

    2016-01-01

    Frontal asymmetry in alpha oscillations is assumed to be associated with psychopathology and individual differences in emotional responding. Brain-activity-based feedback is a promising tool for the modulation of cortical activity. Here, we validated a neurofeedback protocol designed to change relative frontal asymmetry based on individual alpha peak frequencies, including real-time average referencing and eye-correction. Participants (N = 60) were randomly assigned to a right, left or placebo neurofeedback group. Results show a difference in trainability between groups, with a linear change in frontal alpha asymmetry over time for the right neurofeedback group during rest. Moreover, the asymmetry changes in the right group were frequency and location specific, even though trainability did not persist at 1 week and 1 month follow-ups. On the behavioral level, subjective stress on the second test day was reduced in the left and placebo neurofeedback groups, but not in the right neurofeedback group. We found individual differences in trainability that were dependent on training group, with participants in the right neurofeedback group being more likely to change their frontal asymmetry in the desired direction. Individual differences in trainability were also reflected in the ability to change frontal asymmetry during the feedback. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  15. A Note on Cubic Convolution Interpolation

    OpenAIRE

    Meijering, E.; Unser, M.

    2003-01-01

    We establish a link between classical osculatory interpolation and modern convolution-based interpolation and use it to show that two well-known cubic convolution schemes are formally equivalent to two osculatory interpolation schemes proposed in the actuarial literature about a century ago. We also discuss computational differences and give examples of other cubic interpolation schemes not previously studied in signal and image processing.

  16. The role of asymmetric frontal cortical activity in emotion-related phenomena: a review and update.

    Science.gov (United States)

    Harmon-Jones, Eddie; Gable, Philip A; Peterson, Carly K

    2010-07-01

    Conceptual and empirical approaches to the study of the role of asymmetric frontal cortical activity in emotional processes are reviewed. Although early research suggested that greater left than right frontal cortical activity was associated with positive affect, more recent research, primarily on anger, suggests that greater left than right frontal cortical activity is associated with approach motivation, which can be positive (e.g., enthusiasm) or negative in valence (e.g., anger). In addition to reviewing this research on anger, research on guilt, bipolar disorder, and various types of positive affect is reviewed with relation to their association with asymmetric frontal cortical activity. The reviewed research not only contributes to a more complete understanding of the emotive functions of asymmetric frontal cortical activity, but it also points to the importance of considering motivational direction as separate from affective valence in psychological models of emotional space. Copyright © 2009 Elsevier B.V. All rights reserved.

  17. The relation of hedonic hunger and restrained eating to lateralized frontal activation.

    Science.gov (United States)

    Winter, S R; Feig, E H; Kounios, J; Erickson, B; Berkowitz, S; Lowe, M R

    2016-09-01

    Asymmetrical alpha activation in the prefrontal cortex (frontal asymmetry) in electroencephalography (EEG) has been related to eating behavior. Prior studies linked dietary restraint with right frontal asymmetry [1] and disinhibition with left frontal asymmetry [2]. The current study simultaneously assessed restrained eating and hedonic hunger (drive for food reward in the absence of hunger) in relation to frontal asymmetry. Resting-state EEG and measures of restrained eating (Revised Restraint Scale; RRS) and hedonic hunger (Power of Food Scale; PFS) were assessed in 61 non-obese adults. Individually, hedonic hunger predicted left asymmetry. However, PFS and RRS were correlated (r=0.48, phunger exhibited left asymmetry irrespective of RRS scores; among those low in PFS, only those high in RRS showed right asymmetry. Results were consistent with literature linking avoidant behaviors (restraint) with right-frontal asymmetry and approach behaviors (binge eating) with left-frontal asymmetry. It appears that a strong drive toward palatable foods predominates at a neural level even when restraint is high. Findings suggest that lateralized frontal activity is an indicator of motivation both to consume and to avoid consuming highly palatable foods. Copyright © 2016 Elsevier Inc. All rights reserved.

  18. Frontal brain asymmetry as a marker of depression and effectiveness of TMS therapy

    International Nuclear Information System (INIS)

    Mani, D.; Lithgow, B.

    2010-01-01

    Full text: Resting frontal brain electroencephalography (EEG) asymmetry has been hypothesi sed as a diagnostic marker for depression. A number of studies have shown that depressed individuals are characterised by diminished left sided activation of the prefrontal cortex, which is indicated by greater left than right alpha-band power. Relative left frontal region activity is believed to be associated with positive approach related behaviour and relative right frontal activity is seen to be linked to negative withdrawal related behaviour. In this study, frontal brain EEG was recorded from 17 depressed and 19 control subjects, from which frontal brain asymmetry ratios were calculated. The results confirmed the trend of relative left anterior hypoaclivation for individuals with depression compared to the healthy controls. This study also looked at beta and theta band ratios and found theta for depressed is predominantly negative, while the control group dis played mainly positive values. Beta comparison showed little significant difference between control and depressed groups. In addition, there have been few studies that examined frontal brain asymmetry in depression soon after treatment to gauge its effectiv ness. In a very preliminary study, the effect of Transcranial Magnetic Stimulation (TMS) therapy on the alpha band frontal brain asymmetry ratio for 5 depl'essed subjects before and after treatment found a slight increase in FBA ratio for 4 subjects. Further research and a larger subject group is required to validate these results.

  19. Differences in the neural correlates of frontal lobe tests.

    Science.gov (United States)

    Matsuoka, Teruyuki; Kato, Yuka; Imai, Ayu; Fujimoto, Hiroshi; Shibata, Keisuke; Nakamura, Kaeko; Yamada, Kei; Narumoto, Jin

    2018-01-01

    The Executive Interview (EXIT25), the executive clock-drawing task (CLOX1), and the Frontal Assessment Battery (FAB) are used to assess executive function at the bedside. These tests assess distinct psychometric properties. The aim of this study was to examine differences in the neural correlates of the EXIT25, CLOX1, and FAB based on magnetic resonance imaging. Fifty-eight subjects (30 with Alzheimer's disease, 10 with mild cognitive impairment, and 18 healthy controls) participated in this study. Multiple regression analyses were performed to examine the brain regions correlated with the EXIT25, CLOX1, and FAB scores. Age, gender, and years of education were included as covariates. Statistical thresholds were set to uncorrected P-values of 0.001 at the voxel level and 0.05 at the cluster level. The EXIT25 score correlated inversely with the regional grey matter volume in the left lateral frontal lobe (Brodmann areas 6, 9, 44, and 45). The CLOX1 score correlated positively with the regional grey matter volume in the right orbitofrontal cortex (Brodmann area 11) and the left supramarginal gyrus (Brodmann area 40). The FAB score correlated positively with the regional grey matter volume in the right precentral gyrus (Brodmann area 6). The left lateral frontal lobe (Brodmann area 9) and the right lateral frontal lobe (Brodmann area 46) were identified as common brain regions that showed association with EXIT25, CLOX1, and FAB based only a voxel-level threshold. The results of this study suggest that the EXIT25, CLOX1, and FAB may be associated with the distinct neural correlates of the frontal cortex. © 2018 Japanese Psychogeriatric Society.

  20. Real Time Eye Detector with Cascaded Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Bin Li

    2018-01-01

    Full Text Available An accurate and efficient eye detector is essential for many computer vision applications. In this paper, we present an efficient method to evaluate the eye location from facial images. First, a group of candidate regions with regional extreme points is quickly proposed; then, a set of convolution neural networks (CNNs is adopted to determine the most likely eye region and classify the region as left or right eye; finally, the center of the eye is located with other CNNs. In the experiments using GI4E, BioID, and our datasets, our method attained a detection accuracy which is comparable to existing state-of-the-art methods; meanwhile, our method was faster and adaptable to variations of the images, including external light changes, facial occlusion, and changes in image modality.

  1. Frontal and subcortical grey matter reductions in PTSD.

    Science.gov (United States)

    O'Doherty, Daniel C M; Tickell, Ashleigh; Ryder, Will; Chan, Charles; Hermens, Daniel F; Bennett, Maxwell R; Lagopoulos, Jim

    2017-08-30

    Post-traumatic stress disorder (PTSD) is characterised by a range of debilitating psychological, physical and cognitive symptoms. PTSD has been associated with grey matter atrophy in limbic and frontal cortical brain regions. However, previous studies have reported heterogeneous findings, with grey matter changes observed beyond limbic/frontal areas. Seventy-five adults were recruited from the community, 25 diagnosed with PTSD along with 25 healthy and 25 trauma exposed age and gender matched controls. Participants underwent clinical assessment and magnetic resonance imaging. The data-analyses method Voxel Based Morphometry (VBM) was used to estimate cortical grey matter volumes. When compared to both healthy and trauma exposed controls, PTSD subjects demonstrated decreased grey matter volumes within subcortical brain regions-including the hippocampus and amygdala-along with reductions in the anterior cingulate cortex, frontal medial cortex, middle frontal gyrus, superior frontal gyrus, paracingulate gyrus, and precuneus cortex. Significant negative correlations were found between total CAPS lifetime clinical scores/sub-scores and GM volume of both the PTSD and TC groups. GM volumes of the left rACC and right amygdala showed a significant negative correlation within PTSD diagnosed subjects. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  2. Fully convolutional neural networks improve abdominal organ segmentation

    Science.gov (United States)

    Bobo, Meg F.; Bao, Shunxing; Huo, Yuankai; Yao, Yuang; Virostko, Jack; Plassard, Andrew J.; Lyu, Ilwoo; Assad, Albert; Abramson, Richard G.; Hilmes, Melissa A.; Landman, Bennett A.

    2018-03-01

    Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans. Yet, deep learning approaches have not been applied to whole abdomen magnetic resonance imaging (MRI) segmentation. Herein, we evaluate the applicability of an existing fully convolutional neural network (FCNN) designed for CT imaging to segment abdominal organs on T2 weighted (T2w) MRI's with two examples. In the primary example, we compare a classical multi-atlas approach with FCNN on forty-five T2w MRI's acquired from splenomegaly patients with five organs labeled (liver, spleen, left kidney, right kidney, and stomach). Thirty-six images were used for training while nine were used for testing. The FCNN resulted in a Dice similarity coefficient (DSC) of 0.930 in spleens, 0.730 in left kidneys, 0.780 in right kidneys, 0.913 in livers, and 0.556 in stomachs. The performance measures for livers, spleens, right kidneys, and stomachs were significantly better than multi-atlas (p < 0.05, Wilcoxon rank-sum test). In a secondary example, we compare the multi-atlas approach with FCNN on 138 distinct T2w MRI's with manually labeled pancreases (one label). On the pancreas dataset, the FCNN resulted in a median DSC of 0.691 in pancreases versus 0.287 for multi-atlas. The results are highly promising given relatively limited training data and without specific training of the FCNN model and illustrate the potential of deep learning approaches to transcend imaging modalities. 1

  3. Visuo-spatial construction in patients with frontal and parietal lobe lesions

    Directory of Open Access Journals (Sweden)

    Himani Kashyap

    2011-04-01

    Full Text Available Visuospatial construction, traditionally viewed as a putative parietal function, also requires sustained attention, planning, organization strategies and error correction, and hence frontal lobe mediation. The relative contributions of the frontal and parietal lobes are poorly understood. To examine the contributions of parietal, frontal lobes, as well as right and left cerebral hemispheres to visuospatial construction. The Stick Construction Test for two-dimensional construction and the Block Construction Test for three-dimensional construction were administered pre-surgically to patients with lesions in the parietal lobe (n =9 and the frontal lobe (n=11, along with normal control subjects (n =20 matched to the patients on age (+/- 3 years, gender, education (+/- 3 years and handedness. The patients were significantly slower than the controls on both two-dimensional and three-dimensional tests. Patients with parietal lesions were slower than those with frontal lesions on the test of three-dimensional construction. Within each lobe patients with right and left sided lesions did not differ significantly. It appears that tests of three-dimensional construction might be most sensitive to visuospatial construction deficits. Visuospatial construction involves the mediation of both frontal and parietal lobes. The function does not appear to be lateralized. The networks arising from the parieto-occipital areas and projecting to the frontal cortices (e.g., occipito-frontal fasciculus may be the basis of the mediation of both lobes in visuospatial construction. The present findings need replication from studies with larger sample sizes.

  4. The Role of Medial Frontal Cortex in Action Anticipation in Professional Badminton Players.

    Science.gov (United States)

    Xu, Huan; Wang, Pin; Ye, Zhuo'er; Di, Xin; Xu, Guiping; Mo, Lei; Lin, Huiyan; Rao, Hengyi; Jin, Hua

    2016-01-01

    Some studies show that the medial frontal cortex is associated with more skilled action anticipation, while similar findings are not observed in some other studies, possibly due to the stimuli employed and the participants used as the control group. In addition, no studies have investigated whether there is any functional connectivity between the medial frontal cortex and other brain regions in more skilled action anticipation. Therefore, the present study aimed to re-investigate how the medial frontal cortex is involved in more skilled action anticipation by circumventing the limitations of previous research and to investigate that the medial frontal cortex functionally connected with other brain regions involved in action processing in more skilled action anticipation. To this end, professional badminton players and novices were asked to anticipate the landing position of the shuttlecock while watching badminton match videos or to judge the gender of the players in the matches. The video clips ended right at the point that the shuttlecock and the racket came into contact to reduce the effect of information about the trajectory of the shuttlecock. Novices who lacked training and watching experience were recruited for the control group to reduce the effect of sport-related experience on the medial frontal cortex. Blood oxygenation level-dependent activation was assessed by means of functional magnetic resonance imaging. Compared to novices, badminton players exhibited stronger activation in the left medial frontal cortex during action anticipation and greater functional connectivity between left medial frontal cortex and some other brain regions (e.g., right posterior cingulate cortex). Therefore, the present study supports the position that the medial frontal cortex plays a role in more skilled action anticipation and that there is a specific brain network for more skilled action anticipation that involves right posterior cingulate cortex, right fusiform gyrus

  5. The role of medial frontal gyrus in action anticipation in professional badminton players

    Directory of Open Access Journals (Sweden)

    Huan Xu

    2016-11-01

    Full Text Available Some studies show that the medial frontal cortex is associated with more skilled action anticipation, while similar findings are not observed in some other studies, possibly due to the stimuli employed and the participants used as the control group. In addition, no studies have investigated whether there is any functional connectivity between the medial frontal cortex and other brain regions in more skilled action anticipation. Therefore, the present study aimed to re-investigate how the medial frontal cortex is involved in more skilled action anticipation by circumventing the limitations of previous research and to investigate that the medial frontal cortex functionally connected with other brain regions involved in action processing in more skilled action anticipation. To this end, professional badminton players and novices were asked to anticipate the landing position of the shuttlecock while watching badminton match videos or to judge the gender of the players in the matches. The video clips ended right at the point that the shuttlecock and the racket came into contact to reduce the effect of information about the trajectory of the shuttlecock. Novices who lacked training and watching experience were recruited for the control group to reduce the effect of sport-related experience on the medial frontal cortex. Blood oxygenation level-dependent (BOLD activation was assessed by means of functional magnetic resonance imaging (fMRI. Compared to novices, badminton players exhibited stronger activation in the left medial frontal cortex during action anticipation and greater functional connectivity between left medial frontal cortex and some other brain regions (e.g., right posterior cingulate cortex. Therefore, the present study supports the position that the medial frontal cortex plays a role in more skilled action anticipation and that there is a specific brain network for more skilled action anticipation that involves right posterior cingulate

  6. The Role of Medial Frontal Cortex in Action Anticipation in Professional Badminton Players

    Science.gov (United States)

    Xu, Huan; Wang, Pin; Ye, Zhuo’er; Di, Xin; Xu, Guiping; Mo, Lei; Lin, Huiyan; Rao, Hengyi; Jin, Hua

    2016-01-01

    Some studies show that the medial frontal cortex is associated with more skilled action anticipation, while similar findings are not observed in some other studies, possibly due to the stimuli employed and the participants used as the control group. In addition, no studies have investigated whether there is any functional connectivity between the medial frontal cortex and other brain regions in more skilled action anticipation. Therefore, the present study aimed to re-investigate how the medial frontal cortex is involved in more skilled action anticipation by circumventing the limitations of previous research and to investigate that the medial frontal cortex functionally connected with other brain regions involved in action processing in more skilled action anticipation. To this end, professional badminton players and novices were asked to anticipate the landing position of the shuttlecock while watching badminton match videos or to judge the gender of the players in the matches. The video clips ended right at the point that the shuttlecock and the racket came into contact to reduce the effect of information about the trajectory of the shuttlecock. Novices who lacked training and watching experience were recruited for the control group to reduce the effect of sport-related experience on the medial frontal cortex. Blood oxygenation level-dependent activation was assessed by means of functional magnetic resonance imaging. Compared to novices, badminton players exhibited stronger activation in the left medial frontal cortex during action anticipation and greater functional connectivity between left medial frontal cortex and some other brain regions (e.g., right posterior cingulate cortex). Therefore, the present study supports the position that the medial frontal cortex plays a role in more skilled action anticipation and that there is a specific brain network for more skilled action anticipation that involves right posterior cingulate cortex, right fusiform gyrus

  7. Spatial and Time Domain Feature of ERP Speller System Extracted via Convolutional Neural Network.

    Science.gov (United States)

    Yoon, Jaehong; Lee, Jungnyun; Whang, Mincheol

    2018-01-01

    Feature of event-related potential (ERP) has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain-computer interface applications, but subjects who do not show such peak are common. Recent development of convolutional neural network provides a way to analyze spatial and temporal features of ERP. Here, we train the convolutional neural network with 2 convolutional layers whose feature maps represented spatial and temporal features of event-related potential. We have found that nonilliterate subjects' ERP show high correlation between occipital lobe and parietal lobe, whereas illiterate subjects only show correlation between neural activities from frontal lobe and central lobe. The nonilliterates showed peaks in P300, P500, and P700, whereas illiterates mostly showed peaks in around P700. P700 was strong in both subjects. We found that P700 peak may be the key feature of ERP as it appears in both illiterate and nonilliterate subjects.

  8. Spatial and Time Domain Feature of ERP Speller System Extracted via Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Jaehong Yoon

    2018-01-01

    Full Text Available Feature of event-related potential (ERP has not been completely understood and illiteracy problem remains unsolved. To this end, P300 peak has been used as the feature of ERP in most brain–computer interface applications, but subjects who do not show such peak are common. Recent development of convolutional neural network provides a way to analyze spatial and temporal features of ERP. Here, we train the convolutional neural network with 2 convolutional layers whose feature maps represented spatial and temporal features of event-related potential. We have found that nonilliterate subjects’ ERP show high correlation between occipital lobe and parietal lobe, whereas illiterate subjects only show correlation between neural activities from frontal lobe and central lobe. The nonilliterates showed peaks in P300, P500, and P700, whereas illiterates mostly showed peaks in around P700. P700 was strong in both subjects. We found that P700 peak may be the key feature of ERP as it appears in both illiterate and nonilliterate subjects.

  9. Semantic segmentation of bioimages using convolutional neural networks

    CSIR Research Space (South Africa)

    Wiehman, S

    2016-07-01

    Full Text Available Convolutional neural networks have shown great promise in both general image segmentation problems as well as bioimage segmentation. In this paper, the application of different convolutional network architectures is explored on the C. elegans live...

  10. One weird trick for parallelizing convolutional neural networks

    OpenAIRE

    Krizhevsky, Alex

    2014-01-01

    I present a new way to parallelize the training of convolutional neural networks across multiple GPUs. The method scales significantly better than all alternatives when applied to modern convolutional neural networks.

  11. Gradient Flow Convolutive Blind Source Separation

    DEFF Research Database (Denmark)

    Pedersen, Michael Syskind; Nielsen, Chinton Møller

    2004-01-01

    Experiments have shown that the performance of instantaneous gradient flow beamforming by Cauwenberghs et al. is reduced significantly in reverberant conditions. By expanding the gradient flow principle to convolutive mixtures, separation in a reverberant environment is possible. By use...... of a circular four microphone array with a radius of 5 mm, and applying convolutive gradient flow instead of just applying instantaneous gradient flow, experimental results show an improvement of up to around 14 dB can be achieved for simulated impulse responses and up to around 10 dB for a hearing aid...

  12. Human Face Recognition Using Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Răzvan-Daniel Albu

    2009-10-01

    Full Text Available In this paper, I present a novel hybrid face recognition approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns. The convolutional network extracts successively larger features in a hierarchical set of layers. With the weights of the trained neural networks there are created kernel windows used for feature extraction in a 3-stage algorithm. I present experimental results illustrating the efficiency of the proposed approach. I use a database of 796 images of 159 individuals from Reims University which contains quite a high degree of variability in expression, pose, and facial details.

  13. CMOS Compressed Imaging by Random Convolution

    OpenAIRE

    Jacques, Laurent; Vandergheynst, Pierre; Bibet, Alexandre; Majidzadeh, Vahid; Schmid, Alexandre; Leblebici, Yusuf

    2009-01-01

    We present a CMOS imager with built-in capability to perform Compressed Sensing. The adopted sensing strategy is the random Convolution due to J. Romberg. It is achieved by a shift register set in a pseudo-random configuration. It acts as a convolutive filter on the imager focal plane, the current issued from each CMOS pixel undergoing a pseudo-random redirection controlled by each component of the filter sequence. A pseudo-random triggering of the ADC reading is finally applied to comp...

  14. Feedback equivalence of convolutional codes over finite rings

    Directory of Open Access Journals (Sweden)

    DeCastro-García Noemí

    2017-12-01

    Full Text Available The approach to convolutional codes from the linear systems point of view provides us with effective tools in order to construct convolutional codes with adequate properties that let us use them in many applications. In this work, we have generalized feedback equivalence between families of convolutional codes and linear systems over certain rings, and we show that every locally Brunovsky linear system may be considered as a representation of a code under feedback convolutional equivalence.

  15. [Mirror movement due to the medial frontal lobe lesion].

    Science.gov (United States)

    Takahashi, N; Kawamura, M; Hirayama, K

    1995-01-01

    We reported a case with acquired mirror movement in upper limbs due to the lesion of right medial frontal lobe including supplementary motor area, and also discussed a possible mechanism underlying it. A 59-year-old right-handed woman developed left hemiparesis caused by cerebral hemorrhage in the right frontoparietal lobe, on April 5, 1981. She had right hemiparesis and right hemianopsia due to cerebral hemorrhage in the left parieto-occipital lobe, 13 days later. As the patient was recovering from paresis, mirror movement appeared on upper limbs. The features of the mirror movement of this case are summarized as follows: (1) it appeared when using both proximal and distal region of upper limbs; (2) it appeared on left upper limb when the patient intended to move right upper limb or on right upper limb when intended to move left upper limb, while it appeared predominantly in the former; and (3) it was more remarkably found in habitual movement using gesture and pantomimic movement for the use of objects, and it was found in lower degree when actual object was used or when the patient tried to imitate the gesture of the examiner. The lesions in MRI were found in medial region of right frontal lobe (supplementary motor area, medial region of motor area, and cingulate gyrus), right medial parietal lobe, posterior region of right occipital lobe, and medial regions of left parietal and occipital lobes. There was no apparent abnormality in corpus callosum.(ABSTRACT TRUNCATED AT 250 WORDS)

  16. Discrete convolution-operators and radioactive disintegration. [Numerical solution

    Energy Technology Data Exchange (ETDEWEB)

    Kalla, S L; VALENTINUZZI, M E [UNIVERSIDAD NACIONAL DE TUCUMAN (ARGENTINA). FACULTAD DE CIENCIAS EXACTAS Y TECNOLOGIA

    1975-08-01

    The basic concepts of discrete convolution and discrete convolution-operators are briefly described. Then, using the discrete convolution - operators, the differential equations associated with the process of radioactive disintegration are numerically solved. The importance of the method is emphasized to solve numerically, differential and integral equations.

  17. The IMM Frontal Face Database

    DEFF Research Database (Denmark)

    Fagertun, Jens; Stegmann, Mikkel Bille

    2005-01-01

    This note describes a data set consisting of 120 annotated monocular images of 12 different frontal human faces. Points of correspondence are placed on each image so the data set can be readily used for building statistical models of shape. Format specifications and terms of use are also given...

  18. Auditory aura in nocturnal frontal lobe epilepsy: a red flag to suspect an extra-frontal epileptogenic zone.

    Science.gov (United States)

    Ferri, Lorenzo; Bisulli, Francesca; Nobili, Lino; Tassi, Laura; Licchetta, Laura; Mostacci, Barbara; Stipa, Carlotta; Mainieri, Greta; Bernabè, Giorgia; Provini, Federica; Tinuper, Paolo

    2014-11-01

    To describe the anatomo-electro-clinical findings of patients with nocturnal hypermotor seizures (NHS) preceded by auditory symptoms, to evaluate the localizing value of auditory aura. Our database of 165 patients with nocturnal frontal lobe epilepsy (NFLE) diagnosis confirmed by videopolysomnography (VPSG) was reviewed, selecting those who reported an auditory aura as the initial ictal symptom in at least two NHS during their lifetime. Eleven patients were selected (seven males, four females). According to the anatomo-electro-clinical data, three groups were identified. Group 1 [defined epileptogenic zone (EZ)]: three subjects were studied with stereo-EEG. The EZ lay in the left superior temporal gyrus in two cases, whereas in the third case seizures arose from a dysplastic lesion located in the left temporal lobe. One of these three patients underwent left Heschl's gyrus resection, and is currently seizure-free. Group 2 (presumed EZ): three cases in which a presumed EZ was identified; in the left temporal lobe in two cases and in the left temporal lobe extending to the insula in one subject. Group 3 (uncertain EZ): five cases had anatomo-electro-clinical correlations discordant. This work suggests that auditory aura may be a helpful anamnestic feature suggesting an extra-frontal seizure origin. This finding could guide secondary investigations to improve diagnostic definition and selection of candidates for surgical treatment. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

  19. Deformable image registration using convolutional neural networks

    NARCIS (Netherlands)

    Eppenhof, Koen A.J.; Lafarge, Maxime W.; Moeskops, Pim; Veta, Mitko; Pluim, Josien P.W.

    2018-01-01

    Deformable image registration can be time-consuming and often needs extensive parameterization to perform well on a specific application. We present a step towards a registration framework based on a three-dimensional convolutional neural network. The network directly learns transformations between

  20. Epileptiform spike detection via convolutional neural networks

    DEFF Research Database (Denmark)

    Johansen, Alexander Rosenberg; Jin, Jing; Maszczyk, Tomasz

    2016-01-01

    The EEG of epileptic patients often contains sharp waveforms called "spikes", occurring between seizures. Detecting such spikes is crucial for diagnosing epilepsy. In this paper, we develop a convolutional neural network (CNN) for detecting spikes in EEG of epileptic patients in an automated...

  1. Convolutional Neural Networks for SAR Image Segmentation

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Nobel-Jørgensen, Morten

    2015-01-01

    Segmentation of Synthetic Aperture Radar (SAR) images has several uses, but it is a difficult task due to a number of properties related to SAR images. In this article we show how Convolutional Neural Networks (CNNs) can easily be trained for SAR image segmentation with good results. Besides...

  2. Convolutional Neural Networks - Generalizability and Interpretations

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David

    from data despite it being limited in amount or context representation. Within Machine Learning this thesis focuses on Convolutional Neural Networks for Computer Vision. The research aims to answer how to explore a model's generalizability to the whole population of data samples and how to interpret...

  3. Towards dropout training for convolutional neural networks.

    Science.gov (United States)

    Wu, Haibing; Gu, Xiaodong

    2015-11-01

    Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demonstrates that max-pooling dropout is equivalent to randomly picking activation based on a multinomial distribution at training time. In light of this insight, we advocate employing our proposed probabilistic weighted pooling, instead of commonly used max-pooling, to act as model averaging at test time. Empirical evidence validates the superiority of probabilistic weighted pooling. We also empirically show that the effect of convolutional dropout is not trivial, despite the dramatically reduced possibility of over-fitting due to the convolutional architecture. Elaborately designing dropout training simultaneously in max-pooling and fully-connected layers, we achieve state-of-the-art performance on MNIST, and very competitive results on CIFAR-10 and CIFAR-100, relative to other approaches without data augmentation. Finally, we compare max-pooling dropout and stochastic pooling, both of which introduce stochasticity based on multinomial distributions at pooling stage. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. A locality aware convolutional neural networks accelerator

    NARCIS (Netherlands)

    Shi, R.; Xu, Z.; Sun, Z.; Peemen, M.C.J.; Li, A.; Corporaal, H.; Wu, D.

    2015-01-01

    The advantages of Convolutional Neural Networks (CNNs) with respect to traditional methods for visual pattern recognition have changed the field of machine vision. The main issue that hinders broad adoption of this technique is the massive computing workload in CNN that prevents real-time

  5. Frontal assessment battery and frontal atrophy in amyotrophic lateral sclerosis

    OpenAIRE

    Terada, Tatsuhiro; Miyata, Jun; Obi, Tomokazu; Kubota, Manabu; Yoshizumi, Miho; Yamazaki, Kinya; Mizoguchi, Kouichi; Murai, Toshiya

    2017-01-01

    Abstract Objectives To determine the potential utility of the frontal assessment battery (FAB) in assessing cognitive impairments in amyotrophic lateral sclerosis (ALS), we investigated the association between the FAB score and regional gray matter volume, and ascertained whether the regional brain alterations related to cognitive impairments occur in relatively mild stage of ALS. Materials and Methods Twenty?four ALS patients with a Mini?Mental State Examination score of >23, a normal score ...

  6. Frontal Brain Asymmetry in Depression with Comorbid Anxiety: A Neuropsychological Investigation

    OpenAIRE

    Nelson, Brady D.; Sarapas, Casey; Robison-Andrew, E. Jenna; Altman, Sarah E.; Campbell, Miranda L.; Shankman, Stewart A.

    2012-01-01

    The approach-withdrawal model posits that depression and anxiety are associated with a relative right asymmetry in frontal brain activity. Most studies have tested this model using measures of cortical brain activity such as electroencephalography. However, neuropsychological tasks that differentially employ left vs. right frontal cortical regions can also be used to test hypotheses from the model. In two independent samples (Study 1 and 2), the present study investigated the performance of c...

  7. Frontal fibrosing alopecia treatment options.

    Science.gov (United States)

    Fertig, Raymond; Tosti, Antonella

    2016-11-01

    Frontal fibrosing alopecia (FFA) is a rare dermatologic disease that causes scarring and hair loss and is increasing in prevalence worldwide. FFA patients typically present with hair loss in the frontal scalp region and eyebrows which may be associated with sensations of itching or burning. FFA is a clinically distinct variant of lichen planopilaris (LPP) that affects predominantly postmenopausal women, although men and premenopausal women may also be affected. Early diagnosis and prompt treatment are necessary to prevent definitive scarring and permanent hair loss. Data from retrospective studies indicate that 5-alpha-reductase inhibitors (5aRIs) are effective in stabilizing the disease. In our clinical experience, we have seen optimal results treating FFA patients with oral finasteride in conjunction with hydroxychloroquine, topical calcineurin inhibitors (tacrolimus) and excimer laser in patients with signs of active inflammation.

  8. Frontal and temporal volumes in Childhood Absence Epilepsy.

    Science.gov (United States)

    Caplan, Rochelle; Levitt, Jennifer; Siddarth, Prabha; Wu, Keng Nei; Gurbani, Suresh; Sankar, Raman; Shields, W Donald

    2009-11-01

    This study compared frontotemporal brain volumes in children with childhood absence epilepsy (CAE) to age- and gender-matched children without epilepsy. It also examined the association of these volumes with seizure, demographic, perinatal, intelligence quotient (IQ), and psychopathology variables. Twenty-six children with CAE, aged 7.5-11.8 years, and 37 children without epilepsy underwent brain magnetic resonance imaging (MRI) scans at 1.5 Tesla. Tissue was segmented, and total brain, frontal lobe, frontal parcellations, and temporal lobe volumes were computed. All children had IQ testing and structured psychiatric interviews. Parents provided seizure, perinatal, and behavioral information on each child. The CAE group had significantly smaller gray matter volumes of the left orbital frontal gyrus as well as both left and right temporal lobes compared to the age- and gender-matched children without epilepsy. In the CAE group these volumes were related to age, gender, ethnicity, and pregnancy complications but not to seizure, IQ, and psychopathology variables. In the group of children without epilepsy, however, the volumes were related to IQ. These findings suggest that CAE impacts brain development in regions implicated in behavior, cognition, and language. In addition to supporting the cortical focus theory of CAE, these findings also imply that CAE is not a benign disorder.

  9. Dysconnection of right parietal and frontal cortex in neglect syndrome

    DEFF Research Database (Denmark)

    Dietz, Martin; Nielsen, Jørgen Feldbæk; Roepstorff, Andreas

    2017-01-01

    A lesion to the right hemisphere of the brain often leads to perceptual neglect of the left side of the sensorium. The fact that lesions to different cortical regions lead to the same symptoms points to neglect as a dysconnection syndrome that may result from the dysconnection of a distributed...... network, rather than a disruption of computation in any particular brain region. To test this hypothesis, we used Bayesian analysis of effective connectivity based on electroencephalographic recordings in patients with left-sided neglect after a right-hemisphere lesion. While age-matched healthy controls...... connectivity in the left hemisphere when stimuli appeared on their right. Crucially, this parieto-frontal feedback connectivity was aggravated in patients with more severe symptoms. In contrast, patients and controls did not show differences in the local connectivity within regions. These findings suggest...

  10. DCMDN: Deep Convolutional Mixture Density Network

    Science.gov (United States)

    D'Isanto, Antonio; Polsterer, Kai Lars

    2017-09-01

    Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

  11. Gas Classification Using Deep Convolutional Neural Networks

    Science.gov (United States)

    Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

    2018-01-01

    In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP). PMID:29316723

  12. A convolutional neural network neutrino event classifier

    International Nuclear Information System (INIS)

    Aurisano, A.; Sousa, A.; Radovic, A.; Vahle, P.; Rocco, D.; Pawloski, G.; Himmel, A.; Niner, E.; Messier, M.D.; Psihas, F.

    2016-01-01

    Convolutional neural networks (CNNs) have been widely applied in the computer vision community to solve complex problems in image recognition and analysis. We describe an application of the CNN technology to the problem of identifying particle interactions in sampling calorimeters used commonly in high energy physics and high energy neutrino physics in particular. Following a discussion of the core concepts of CNNs and recent innovations in CNN architectures related to the field of deep learning, we outline a specific application to the NOvA neutrino detector. This algorithm, CVN (Convolutional Visual Network) identifies neutrino interactions based on their topology without the need for detailed reconstruction and outperforms algorithms currently in use by the NOvA collaboration.

  13. Gas Classification Using Deep Convolutional Neural Networks.

    Science.gov (United States)

    Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

    2018-01-08

    In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP).

  14. Quasi-cyclic unit memory convolutional codes

    DEFF Research Database (Denmark)

    Justesen, Jørn; Paaske, Erik; Ballan, Mark

    1990-01-01

    Unit memory convolutional codes with generator matrices, which are composed of circulant submatrices, are introduced. This structure facilitates the analysis of efficient search for good codes. Equivalences among such codes and some of the basic structural properties are discussed. In particular......, catastrophic encoders and minimal encoders are characterized and dual codes treated. Further, various distance measures are discussed, and a number of good codes, some of which result from efficient computer search and some of which result from known block codes, are presented...

  15. Applying Gradient Descent in Convolutional Neural Networks

    Science.gov (United States)

    Cui, Nan

    2018-04-01

    With the development of the integrated circuit and computer science, people become caring more about solving practical issues via information technologies. Along with that, a new subject called Artificial Intelligent (AI) comes up. One popular research interest of AI is about recognition algorithm. In this paper, one of the most common algorithms, Convolutional Neural Networks (CNNs) will be introduced, for image recognition. Understanding its theory and structure is of great significance for every scholar who is interested in this field. Convolution Neural Network is an artificial neural network which combines the mathematical method of convolution and neural network. The hieratical structure of CNN provides it reliable computer speed and reasonable error rate. The most significant characteristics of CNNs are feature extraction, weight sharing and dimension reduction. Meanwhile, combining with the Back Propagation (BP) mechanism and the Gradient Descent (GD) method, CNNs has the ability to self-study and in-depth learning. Basically, BP provides an opportunity for backwardfeedback for enhancing reliability and GD is used for self-training process. This paper mainly discusses the CNN and the related BP and GD algorithms, including the basic structure and function of CNN, details of each layer, the principles and features of BP and GD, and some examples in practice with a summary in the end.

  16. Phylogenetic convolutional neural networks in metagenomics.

    Science.gov (United States)

    Fioravanti, Diego; Giarratano, Ylenia; Maggio, Valerio; Agostinelli, Claudio; Chierici, Marco; Jurman, Giuseppe; Furlanello, Cesare

    2018-03-08

    Convolutional Neural Networks can be effectively used only when data are endowed with an intrinsic concept of neighbourhood in the input space, as is the case of pixels in images. We introduce here Ph-CNN, a novel deep learning architecture for the classification of metagenomics data based on the Convolutional Neural Networks, with the patristic distance defined on the phylogenetic tree being used as the proximity measure. The patristic distance between variables is used together with a sparsified version of MultiDimensional Scaling to embed the phylogenetic tree in a Euclidean space. Ph-CNN is tested with a domain adaptation approach on synthetic data and on a metagenomics collection of gut microbiota of 38 healthy subjects and 222 Inflammatory Bowel Disease patients, divided in 6 subclasses. Classification performance is promising when compared to classical algorithms like Support Vector Machines and Random Forest and a baseline fully connected neural network, e.g. the Multi-Layer Perceptron. Ph-CNN represents a novel deep learning approach for the classification of metagenomics data. Operatively, the algorithm has been implemented as a custom Keras layer taking care of passing to the following convolutional layer not only the data but also the ranked list of neighbourhood of each sample, thus mimicking the case of image data, transparently to the user.

  17. Image quality assessment using deep convolutional networks

    Science.gov (United States)

    Li, Yezhou; Ye, Xiang; Li, Yong

    2017-12-01

    This paper proposes a method of accurately assessing image quality without a reference image by using a deep convolutional neural network. Existing training based methods usually utilize a compact set of linear filters for learning features of images captured by different sensors to assess their quality. These methods may not be able to learn the semantic features that are intimately related with the features used in human subject assessment. Observing this drawback, this work proposes training a deep convolutional neural network (CNN) with labelled images for image quality assessment. The ReLU in the CNN allows non-linear transformations for extracting high-level image features, providing a more reliable assessment of image quality than linear filters. To enable the neural network to take images of any arbitrary size as input, the spatial pyramid pooling (SPP) is introduced connecting the top convolutional layer and the fully-connected layer. In addition, the SPP makes the CNN robust to object deformations to a certain extent. The proposed method taking an image as input carries out an end-to-end learning process, and outputs the quality of the image. It is tested on public datasets. Experimental results show that it outperforms existing methods by a large margin and can accurately assess the image quality on images taken by different sensors of varying sizes.

  18. Storage and executive processes in the frontal lobes.

    Science.gov (United States)

    Smith, E E; Jonides, J

    1999-03-12

    The human frontal cortex helps mediate working memory, a system that is used for temporary storage and manipulation of information and that is involved in many higher cognitive functions. Working memory includes two components: short-term storage (on the order of seconds) and executive processes that operate on the contents of storage. Recently, these two components have been investigated in functional neuroimaging studies. Studies of storage indicate that different frontal regions are activated for different kinds of information: storage for verbal materials activates Broca's area and left-hemisphere supplementary and premotor areas; storage of spatial information activates the right-hemisphere premotor cortex; and storage of object information activates other areas of the prefrontal cortex. Two of the fundamental executive processes are selective attention and task management. Both processes activate the anterior cingulate and dorsolateral prefrontal cortex.

  19. Bilingualism Alters Children's Frontal Lobe Functioning for Attentional Control

    Science.gov (United States)

    Arredondo, Maria M.; Hu, Xiao-Su; Satterfield, Teresa; Kovelman, Ioulia

    2017-01-01

    Bilingualism is a typical linguistic experience, yet relatively little is known about its impact on children's cognitive and brain development. Theories of bilingualism suggest early dual-language acquisition can improve children's cognitive abilities, specifically those relying on frontal lobe functioning. While behavioral findings present much conflicting evidence, little is known about its effects on children's frontal lobe development. Using functional Near-Infrared Spectroscopy (fNIRS), the findings suggest that Spanish-English bilingual children (n=13, ages 7-13) had greater activation in left prefrontal cortex during a non-verbal attentional control task relative to age-matched English monolinguals. In contrast, monolinguals (n=14) showed greater right prefrontal activation than bilinguals. The present findings suggest early bilingualism yields significant changes to the functional organization of children's prefrontal cortex for attentional control and carry implications for understanding how early life experiences impact cognition and brain development. PMID:26743118

  20. Secondary adult encephalocele with abscess formation of calcified frontal sinus mucocele.

    Science.gov (United States)

    Oh, Byeong Ho; Lee, Ok-Jun; Park, Young Seok

    2016-07-01

    Although encephalocele is a rare congenital abnormality, secondary encephalocele is extremely rare and can cause fatal complications. Here, we report a case of secondary encephalocele caused by frontal sinus wall defect due to chronic sinusitis, which was completely removed by cranialization with autologous bone graft. A 50-year-old man with a 10-year history of chronic sinusitis visited our hospital due to suddenly altered mentality characterized by stupor. Computerized tomography scanning and magnetic resonance imaging revealed an enlarged left frontal sinus with sinusitis. The frontal sinus cavity was calcified, and the left frontal lobe had herniated into the cavity accompanied by yellow pus. A large dural defect was also found around the frontal sinus area. After removal of the abscess and some of the frontal lobe, frontal skull base repair by cranialization was performed using autologous bone graft. Streptococcus pneumoniae was cultured from the cerebrospinal fluid (CSF), necessitating treatment with antibiotics. After the operation, the mental status of the patient improved and no CSF leakage was observed. In addition to correct diagnosis and early treatment including antibiotics, the surgical repair of defects is needed in patients with secondary encephalocele to prevent further episodes of meningitis. Surgical correction of frontal sinus encephalocele can be achieved through bifrontal craniotomy or endoscopic transnasal repair. If a patient has CSF leakage, open craniotomy may facilitate repair of the dural defect and allow for cranialization of the sinus. Removal of dysplastic herniated brain tissue and cranialization of the frontal sinus may be a good option for treating secondary encephalocele and its associated complications, including meningitis, abscess formation, and infarction of the herniated brain parenchyma.

  1. Frontal networks in adults with autism spectrum disorder.

    Science.gov (United States)

    Catani, Marco; Dell'Acqua, Flavio; Budisavljevic, Sanja; Howells, Henrietta; Thiebaut de Schotten, Michel; Froudist-Walsh, Seán; D'Anna, Lucio; Thompson, Abigail; Sandrone, Stefano; Bullmore, Edward T; Suckling, John; Baron-Cohen, Simon; Lombardo, Michael V; Wheelwright, Sally J; Chakrabarti, Bhismadev; Lai, Meng-Chuan; Ruigrok, Amber N V; Leemans, Alexander; Ecker, Christine; Consortium, Mrc Aims; Craig, Michael C; Murphy, Declan G M

    2016-02-01

    It has been postulated that autism spectrum disorder is underpinned by an 'atypical connectivity' involving higher-order association brain regions. To test this hypothesis in a large cohort of adults with autism spectrum disorder we compared the white matter networks of 61 adult males with autism spectrum disorder and 61 neurotypical controls, using two complementary approaches to diffusion tensor magnetic resonance imaging. First, we applied tract-based spatial statistics, a 'whole brain' non-hypothesis driven method, to identify differences in white matter networks in adults with autism spectrum disorder. Following this we used a tract-specific analysis, based on tractography, to carry out a more detailed analysis of individual tracts identified by tract-based spatial statistics. Finally, within the autism spectrum disorder group, we studied the relationship between diffusion measures and autistic symptom severity. Tract-based spatial statistics revealed that autism spectrum disorder was associated with significantly reduced fractional anisotropy in regions that included frontal lobe pathways. Tractography analysis of these specific pathways showed increased mean and perpendicular diffusivity, and reduced number of streamlines in the anterior and long segments of the arcuate fasciculus, cingulum and uncinate--predominantly in the left hemisphere. Abnormalities were also evident in the anterior portions of the corpus callosum connecting left and right frontal lobes. The degree of microstructural alteration of the arcuate and uncinate fasciculi was associated with severity of symptoms in language and social reciprocity in childhood. Our results indicated that autism spectrum disorder is a developmental condition associated with abnormal connectivity of the frontal lobes. Furthermore our findings showed that male adults with autism spectrum disorder have regional differences in brain anatomy, which correlate with specific aspects of autistic symptoms. Overall these

  2. Frontal and superior temporal auditory processing abnormalities in schizophrenia.

    Science.gov (United States)

    Chen, Yu-Han; Edgar, J Christopher; Huang, Mingxiong; Hunter, Michael A; Epstein, Emerson; Howell, Breannan; Lu, Brett Y; Bustillo, Juan; Miller, Gregory A; Cañive, José M

    2013-01-01

    Although magnetoencephalography (MEG) studies show superior temporal gyrus (STG) auditory processing abnormalities in schizophrenia at 50 and 100 ms, EEG and corticography studies suggest involvement of additional brain areas (e.g., frontal areas) during this interval. Study goals were to identify 30 to 130 ms auditory encoding processes in schizophrenia (SZ) and healthy controls (HC) and group differences throughout the cortex. The standard paired-click task was administered to 19 SZ and 21 HC subjects during MEG recording. Vector-based Spatial-temporal Analysis using L1-minimum-norm (VESTAL) provided 4D maps of activity from 30 to 130 ms. Within-group t-tests compared post-stimulus 50 ms and 100 ms activity to baseline. Between-group t-tests examined 50 and 100 ms group differences. Bilateral 50 and 100 ms STG activity was observed in both groups. HC had stronger bilateral 50 and 100 ms STG activity than SZ. In addition to the STG group difference, non-STG activity was also observed in both groups. For example, whereas HC had stronger left and right inferior frontal gyrus activity than SZ, SZ had stronger right superior frontal gyrus and left supramarginal gyrus activity than HC. Less STG activity was observed in SZ than HC, indicating encoding problems in SZ. Yet auditory encoding abnormalities are not specific to STG, as group differences were observed in frontal and SMG areas. Thus, present findings indicate that individuals with SZ show abnormalities in multiple nodes of a concurrently activated auditory network.

  3. An Algorithm for the Convolution of Legendre Series

    KAUST Repository

    Hale, Nicholas; Townsend, Alex

    2014-01-01

    An O(N2) algorithm for the convolution of compactly supported Legendre series is described. The algorithm is derived from the convolution theorem for Legendre polynomials and the recurrence relation satisfied by spherical Bessel functions. Combining with previous work yields an O(N 2) algorithm for the convolution of Chebyshev series. Numerical results are presented to demonstrate the improved efficiency over the existing algorithm. © 2014 Society for Industrial and Applied Mathematics.

  4. The Urbanik generalized convolutions in the non-commutative ...

    Indian Academy of Sciences (India)

    −sν(dx) < ∞. Now we apply this construction to the Kendall convolution case, starting with the weakly stable measure δ1. Example 1. Let △ be the Kendall convolution, i.e. the generalized convolution with the probability kernel: δ1△δa = (1 − a)δ1 + aπ2 for a ∈ [0, 1] and π2 be the Pareto distribution with the density π2(dx) =.

  5. [Neuroanatomy of Frontal Association Cortex].

    Science.gov (United States)

    Takada, Masahiko

    2016-11-01

    The frontal association cortex is composed of the prefrontal cortex and the motor-related areas except the primary motor cortex (i.e., the so-called higher motor areas), and is well-developed in primates, including humans. The prefrontal cortex receives and integrates large bits of diverse information from the parietal, temporal, and occipital association cortical areas (termed the posterior association cortex), and paralimbic association cortical areas. This information is then transmitted to the primary motor cortex via multiple motor-related areas. Given these facts, it is likely that the prefrontal cortex exerts executive functions for behavioral control. The functional input pathways from the posterior and paralimbic association cortical areas to the prefrontal cortex are classified primarily into six groups. Cognitive signals derived from the prefrontal cortex are conveyed to the rostral motor-related areas to transform them into motor signals, which finally enter the primary motor cortex via the caudal motor-related areas. Furthermore, it has been shown that, similar to the primary motor cortex, areas of the frontal association cortex form individual networks (known as "loop circuits") with the basal ganglia and cerebellum via the thalamus, and hence are extensively involved in the expression and control of behavioral actions.

  6. On a Generalized Hankel Type Convolution of Generalized Functions

    Indian Academy of Sciences (India)

    Generalized Hankel type transformation; Parserval relation; generalized ... The classical generalized Hankel type convolution are defined and extended to a class of generalized functions. ... Proceedings – Mathematical Sciences | News.

  7. Enhanced online convolutional neural networks for object tracking

    Science.gov (United States)

    Zhang, Dengzhuo; Gao, Yun; Zhou, Hao; Li, Tianwen

    2018-04-01

    In recent several years, object tracking based on convolution neural network has gained more and more attention. The initialization and update of convolution filters can directly affect the precision of object tracking effective. In this paper, a novel object tracking via an enhanced online convolution neural network without offline training is proposed, which initializes the convolution filters by a k-means++ algorithm and updates the filters by an error back-propagation. The comparative experiments of 7 trackers on 15 challenging sequences showed that our tracker can perform better than other trackers in terms of AUC and precision.

  8. Frontal alpha asymmetry in OCD patients and unaffected first-degree relatives.

    Science.gov (United States)

    Grützmann, Rosa; Riesel, Anja; Klawohn, Julia; Heinzel, Stephan; Kaufmann, Christian; Bey, Katharina; Lennertz, Leonard; Wagner, Michael; Kathmann, Norbert

    2017-08-01

    Frontal electroencephalographic alpha asymmetry as an indicator of trait approach and trait inhibition systems has previously been studied in individuals with obsessive-compulsive disorder (OCD) with mixed results. We explored frontal alpha asymmetry as a possible risk factor in OCD by investigating a large sample of OCD patients (n = 113), healthy control participants (n = 113), and unaffected 1st-degree relatives of OCD patients (n = 37). Additionally, the relationship between OCD symptom dimensions and frontal alpha asymmetry was explored. OCD patients and healthy control participants did not differ in alpha asymmetry scores. Hence, the current results do not support the notion that OCD as a diagnostic entity is associated with a shift in frontal cortical activity. Furthermore, alpha asymmetry scores were not statistically related to specific OCD symptom dimensions. Reasons for inconsistent results in OCD are discussed and should be explored in future studies. Compared to OCD patients and healthy control participants, unaffected 1st-degree relatives of OCD patients showed increased left frontal activity. Such asymmetry has previously been found to be associated with positive affect and adaptive emotion regulation under stress. Because stressful life events play an important role in the onset and exacerbation of OCD, increased left frontal activity might serve as a resilience factor in unaffected 1st-degree relatives. Future studies should follow up on these results with longitudinal risk studies and pre- and posttherapy assessments to further explore causality of this putative factor. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  9. Representation of cognitive reappraisal goals in frontal gamma oscillations.

    Science.gov (United States)

    Kang, Jae-Hwan; Jeong, Ji Woon; Kim, Hyun Taek; Kim, Sang Hee; Kim, Sung-Phil

    2014-01-01

    Recently, numerous efforts have been made to understand the neural mechanisms underlying cognitive regulation of emotion, such as cognitive reappraisal. Many studies have reported that cognitive control of emotion induces increases in neural activity of the control system, including the prefrontal cortex and the dorsal anterior cingulate cortex, and increases or decreases (depending upon the regulation goal) in neural activity of the appraisal system, including the amygdala and the insula. It has been hypothesized that information about regulation goals needs to be processed through interactions between the control and appraisal systems in order to support cognitive reappraisal. However, how this information is represented in the dynamics of cortical activity remains largely unknown. To address this, we investigated temporal changes in gamma band activity (35-55 Hz) in human electroencephalograms during a cognitive reappraisal task that was comprised of three reappraisal goals: to decease, maintain, or increase emotional responses modulated by affect-laden pictures. We examined how the characteristics of gamma oscillations, such as spectral power and large-scale phase synchronization, represented cognitive reappraisal goals. We found that left frontal gamma power decreased, was sustained, or increased when the participants suppressed, maintained, or amplified their emotions, respectively. This change in left frontal gamma power appeared during an interval of 1926 to 2453 ms after stimulus onset. We also found that the number of phase-synchronized pairs of gamma oscillations over the entire brain increased when participants regulated their emotions compared to when they maintained their emotions. These results suggest that left frontal gamma power may reflect cortical representation of emotional states modulated by cognitive reappraisal goals and gamma phase synchronization across whole brain regions may reflect emotional regulatory efforts to achieve these goals

  10. The classification of frontal sinus pneumatization patterns by CT-based volumetry.

    Science.gov (United States)

    Yüksel Aslier, Nesibe Gül; Karabay, Nuri; Zeybek, Gülşah; Keskinoğlu, Pembe; Kiray, Amaç; Sütay, Semih; Ecevit, Mustafa Cenk

    2016-10-01

    We aimed to define the classification of frontal sinus pneumatization patterns according to three-dimensional volume measurements. Datasets of 148 sides of 74 dry skulls were generated by the computerized tomography-based volumetry to measure frontal sinus volumes. The cutoff points for frontal sinus hypoplasia and hyperplasia were tested by ROC curve analysis and the validity of the diagnostic points was measured. The overall frequencies were 4.1, 14.2, 37.2 and 44.5 % for frontal sinus aplasia, hypoplasia, medium size and hyperplasia, respectively. The aplasia was bilateral in all three skulls. Hypoplasia was seen 76 % at the right side and hyperplasia was seen 56 % at the left side. The cutoff points for diagnosing frontal sinus hypoplasia and hyperplasia were '1131.25 mm(3)' (95.2 % sensitivity and 100 % specificity) and '3328.50 mm(3)' (88 % sensitivity and 86 % specificity), respectively. The findings provided in the present study, which define frontal sinus pneumatization patterns by CT-based volumetry, proved that two opposite sides of the frontal sinuses are asymmetric and three-dimensional classification should be developed by CT-based volumetry, because two-dimensional evaluations lack depth measurement.

  11. Pre-trained convolutional neural networks as feature extractors for tuberculosis detection.

    Science.gov (United States)

    Lopes, U K; Valiati, J F

    2017-10-01

    It is estimated that in 2015, approximately 1.8 million people infected by tuberculosis died, most of them in developing countries. Many of those deaths could have been prevented if the disease had been detected at an earlier stage, but the most advanced diagnosis methods are still cost prohibitive for mass adoption. One of the most popular tuberculosis diagnosis methods is the analysis of frontal thoracic radiographs; however, the impact of this method is diminished by the need for individual analysis of each radiography by properly trained radiologists. Significant research can be found on automating diagnosis by applying computational techniques to medical images, thereby eliminating the need for individual image analysis and greatly diminishing overall costs. In addition, recent improvements on deep learning accomplished excellent results classifying images on diverse domains, but its application for tuberculosis diagnosis remains limited. Thus, the focus of this work is to produce an investigation that will advance the research in the area, presenting three proposals to the application of pre-trained convolutional neural networks as feature extractors to detect the disease. The proposals presented in this work are implemented and compared to the current literature. The obtained results are competitive with published works demonstrating the potential of pre-trained convolutional networks as medical image feature extractors. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks.

    Science.gov (United States)

    Rajkomar, Alvin; Lingam, Sneha; Taylor, Andrew G; Blum, Michael; Mongan, John

    2017-02-01

    The study aimed to determine if computer vision techniques rooted in deep learning can use a small set of radiographs to perform clinically relevant image classification with high fidelity. One thousand eight hundred eighty-five chest radiographs on 909 patients obtained between January 2013 and July 2015 at our institution were retrieved and anonymized. The source images were manually annotated as frontal or lateral and randomly divided into training, validation, and test sets. Training and validation sets were augmented to over 150,000 images using standard image manipulations. We then pre-trained a series of deep convolutional networks based on the open-source GoogLeNet with various transformations of the open-source ImageNet (non-radiology) images. These trained networks were then fine-tuned using the original and augmented radiology images. The model with highest validation accuracy was applied to our institutional test set and a publicly available set. Accuracy was assessed by using the Youden Index to set a binary cutoff for frontal or lateral classification. This retrospective study was IRB approved prior to initiation. A network pre-trained on 1.2 million greyscale ImageNet images and fine-tuned on augmented radiographs was chosen. The binary classification method correctly classified 100 % (95 % CI 99.73-100 %) of both our test set and the publicly available images. Classification was rapid, at 38 images per second. A deep convolutional neural network created using non-radiological images, and an augmented set of radiographs is effective in highly accurate classification of chest radiograph view type and is a feasible, rapid method for high-throughput annotation.

  13. Convolutional neural networks and face recognition task

    Science.gov (United States)

    Sochenkova, A.; Sochenkov, I.; Makovetskii, A.; Vokhmintsev, A.; Melnikov, A.

    2017-09-01

    Computer vision tasks are remaining very important for the last couple of years. One of the most complicated problems in computer vision is face recognition that could be used in security systems to provide safety and to identify person among the others. There is a variety of different approaches to solve this task, but there is still no universal solution that would give adequate results in some cases. Current paper presents following approach. Firstly, we extract an area containing face, then we use Canny edge detector. On the next stage we use convolutional neural networks (CNN) to finally solve face recognition and person identification task.

  14. Decoding LDPC Convolutional Codes on Markov Channels

    Directory of Open Access Journals (Sweden)

    Kashyap Manohar

    2008-01-01

    Full Text Available Abstract This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveals that our pipelined algorithm reduces the number of operations per time step compared to LDPC block codes, at the expense of increased memory and latency. This tradeoff is favorable for low-power applications.

  15. Decoding LDPC Convolutional Codes on Markov Channels

    Directory of Open Access Journals (Sweden)

    Chris Winstead

    2008-04-01

    Full Text Available This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveals that our pipelined algorithm reduces the number of operations per time step compared to LDPC block codes, at the expense of increased memory and latency. This tradeoff is favorable for low-power applications.

  16. Fourier transforms and convolutions for the experimentalist

    CERN Document Server

    Jennison, RC

    1961-01-01

    Fourier Transforms and Convolutions for the Experimentalist provides the experimentalist with a guide to the principles and practical uses of the Fourier transformation. It aims to bridge the gap between the more abstract account of a purely mathematical approach and the rule of thumb calculation and intuition of the practical worker. The monograph springs from a lecture course which the author has given in recent years and for which he has drawn upon a number of sources, including a set of notes compiled by the late Dr. I. C. Browne from a series of lectures given by Mr. J . A. Ratcliffe of t

  17. Target recognition based on convolutional neural network

    Science.gov (United States)

    Wang, Liqiang; Wang, Xin; Xi, Fubiao; Dong, Jian

    2017-11-01

    One of the important part of object target recognition is the feature extraction, which can be classified into feature extraction and automatic feature extraction. The traditional neural network is one of the automatic feature extraction methods, while it causes high possibility of over-fitting due to the global connection. The deep learning algorithm used in this paper is a hierarchical automatic feature extraction method, trained with the layer-by-layer convolutional neural network (CNN), which can extract the features from lower layers to higher layers. The features are more discriminative and it is beneficial to the object target recognition.

  18. QCDNUM: Fast QCD evolution and convolution

    Science.gov (United States)

    Botje, M.

    2011-02-01

    The QCDNUM program numerically solves the evolution equations for parton densities and fragmentation functions in perturbative QCD. Un-polarised parton densities can be evolved up to next-to-next-to-leading order in powers of the strong coupling constant, while polarised densities or fragmentation functions can be evolved up to next-to-leading order. Other types of evolution can be accessed by feeding alternative sets of evolution kernels into the program. A versatile convolution engine provides tools to compute parton luminosities, cross-sections in hadron-hadron scattering, and deep inelastic structure functions in the zero-mass scheme or in generalised mass schemes. Input to these calculations are either the QCDNUM evolved densities, or those read in from an external parton density repository. Included in the software distribution are packages to calculate zero-mass structure functions in un-polarised deep inelastic scattering, and heavy flavour contributions to these structure functions in the fixed flavour number scheme. Program summaryProgram title: QCDNUM version: 17.00 Catalogue identifier: AEHV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEHV_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU Public Licence No. of lines in distributed program, including test data, etc.: 45 736 No. of bytes in distributed program, including test data, etc.: 911 569 Distribution format: tar.gz Programming language: Fortran-77 Computer: All Operating system: All RAM: Typically 3 Mbytes Classification: 11.5 Nature of problem: Evolution of the strong coupling constant and parton densities, up to next-to-next-to-leading order in perturbative QCD. Computation of observable quantities by Mellin convolution of the evolved densities with partonic cross-sections. Solution method: Parametrisation of the parton densities as linear or quadratic splines on a discrete grid, and evolution of the spline

  19. Innervation of the renal proximal convoluted tubule of the rat

    International Nuclear Information System (INIS)

    Barajas, L.; Powers, K.

    1989-01-01

    Experimental data suggest the proximal tubule as a major site of neurogenic influence on tubular function. The functional and anatomical axial heterogeneity of the proximal tubule prompted this study of the distribution of innervation sites along the early, mid, and late proximal convoluted tubule (PCT) of the rat. Serial section autoradiograms, with tritiated norepinephrine serving as a marker for monoaminergic nerves, were used in this study. Freehand clay models and graphic reconstructions of proximal tubules permitted a rough estimation of the location of the innervation sites along the PCT. In the subcapsular nephrons, the early PCT (first third) was devoid of innervation sites with most of the innervation occurring in the mid (middle third) and in the late (last third) PCT. Innervation sites were found in the early PCT in nephrons located deeper in the cortex. In juxtamedullary nephrons, innervation sites could be observed on the PCT as it left the glomerulus. This gradient of PCT innervation can be explained by the different tubulovascular relationships of nephrons at different levels of the cortex. The absence of innervation sites in the early PCT of subcapsular nephrons suggests that any influence of the renal nerves on the early PCT might be due to an effect of neurotransmitter released from renal nerves reaching the early PCT via the interstitium and/or capillaries

  20. DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs.

    Science.gov (United States)

    Chen, Liang-Chieh; Papandreou, George; Kokkinos, Iasonas; Murphy, Kevin; Yuille, Alan L

    2018-04-01

    In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are experimentally shown to have substantial practical merit. First, we highlight convolution with upsampled filters, or 'atrous convolution', as a powerful tool in dense prediction tasks. Atrous convolution allows us to explicitly control the resolution at which feature responses are computed within Deep Convolutional Neural Networks. It also allows us to effectively enlarge the field of view of filters to incorporate larger context without increasing the number of parameters or the amount of computation. Second, we propose atrous spatial pyramid pooling (ASPP) to robustly segment objects at multiple scales. ASPP probes an incoming convolutional feature layer with filters at multiple sampling rates and effective fields-of-views, thus capturing objects as well as image context at multiple scales. Third, we improve the localization of object boundaries by combining methods from DCNNs and probabilistic graphical models. The commonly deployed combination of max-pooling and downsampling in DCNNs achieves invariance but has a toll on localization accuracy. We overcome this by combining the responses at the final DCNN layer with a fully connected Conditional Random Field (CRF), which is shown both qualitatively and quantitatively to improve localization performance. Our proposed "DeepLab" system sets the new state-of-art at the PASCAL VOC-2012 semantic image segmentation task, reaching 79.7 percent mIOU in the test set, and advances the results on three other datasets: PASCAL-Context, PASCAL-Person-Part, and Cityscapes. All of our code is made publicly available online.

  1. Music increases frontal EEG coherence during verbal learning.

    Science.gov (United States)

    Peterson, David A; Thaut, Michael H

    2007-02-02

    Anecdotal and some empirical evidence suggests that music can enhance learning and memory. However, the mechanisms by which music modulates the neural activity associated with learning and memory remain largely unexplored. We evaluated coherent frontal oscillations in the electroencephalogram (EEG) while subjects were engaged in a modified version of Rey's Auditory Verbal Learning Test (AVLT). Subjects heard either a spoken version of the AVLT or the conventional AVLT word list sung. Learning-related changes in coherence (LRCC) were measured by comparing the EEG during word encoding on correctly recalled trials to the immediately preceding trial on which the same word was not recalled. There were no significant changes in coherence associated with conventional verbal learning. However, musical verbal learning was associated with increased coherence within and between left and right frontal areas in theta, alpha, and gamma frequency bands. It is unlikely that the different patterns of LRCC reflect general performance differences; the groups exhibited similar learning performance. The results suggest that verbal learning with a musical template strengthens coherent oscillations in frontal cortical networks involved in verbal encoding.

  2. Inferior Frontal Sensitivity to Common Speech Sounds Is Amplified by Increasing Word Intelligibility

    Science.gov (United States)

    Vaden, Kenneth I., Jr.; Kuchinsky, Stefanie E.; Keren, Noam I.; Harris, Kelly C.; Ahlstrom, Jayne B.; Dubno, Judy R.; Eckert, Mark A.

    2011-01-01

    The left inferior frontal gyrus (LIFG) exhibits increased responsiveness when people listen to words composed of speech sounds that frequently co-occur in the English language (Vaden, Piquado, & Hickok, 2011), termed high phonotactic frequency (Vitevitch & Luce, 1998). The current experiment aimed to further characterize the relation of…

  3. Dissociating Parieto-Frontal Networks for Phonological and Semantic Word Decisions

    DEFF Research Database (Denmark)

    Hartwigsen, Gesa; Weigel, Anni; Schuschan, Paul

    2016-01-01

    Left posterior inferior frontal gyrus (pIFG) and supramarginal gyrus (SMG) are key regions for phonological decisions, whereas angular gyrus (ANG) and anterior IFG (aIFG) are associated with semantics. However, it is less clear whether the functional contribution of one area changes in the presen...

  4. Synchronous retinotopic frontal-temporal activity during long-term memory for spatial location.

    Science.gov (United States)

    Slotnick, Scott D

    2010-05-12

    Early visual areas in occipital cortex are known to be retinotopic. Recently, retinotopic maps have been reported in frontal and parietal cortex during spatial attention and working memory. The present event-related potential (ERP) and functional magnetic resonance imaging (fMRI) study determined whether spatial long-term memory was associated with retinotopic activity in frontal and parietal regions, and assessed whether retinotopic activity in these higher level control regions was synchronous with retinotopic activity in lower level visual sensory regions. During encoding, abstract shapes were presented to the left or right of fixation. During retrieval, old and new shapes were presented at fixation and participants classified each shape as old and previously on the "left", old and previously on the "right", or "new". Retinotopic effects were manifested by accurate memory for items previously presented on the left producing activity in the right hemisphere and accurate memory for items previously presented on the right producing activity in the left hemisphere. Retinotopic ERP activity was observed in frontal regions and visual sensory (occipital and temporal) regions. In frontal cortex, retinotopic fMRI activity was localized to the frontal eye fields. There were no significant ERP or fMRI retinotopic memory effects in parietal regions. The present long-term memory retinotopic effects complement previous spatial attention and working memory findings (and suggest retinotopic activity in parietal cortex may require an external peripheral stimulus). Furthermore, ERP cross-correlogram analysis revealed that retinotopic activations in frontal and temporal regions were synchronous, indicating that these regions interact during retrieval of spatial information. (c) 2010 Elsevier B.V. All rights reserved.

  5. Convolutive ICA for Spatio-Temporal Analysis of EEG

    DEFF Research Database (Denmark)

    Dyrholm, Mads; Makeig, Scott; Hansen, Lars Kai

    2007-01-01

    in the convolutive model can be correctly detected using Bayesian model selection. We demonstrate a framework for deconvolving an EEG ICA subspace. Initial results suggest that in some cases convolutive mixing may be a more realistic model for EEG signals than the instantaneous ICA model....

  6. Modified Stieltjes Transform and Generalized Convolutions of Probability Distributions

    Directory of Open Access Journals (Sweden)

    Lev B. Klebanov

    2018-01-01

    Full Text Available The classical Stieltjes transform is modified in such a way as to generalize both Stieltjes and Fourier transforms. This transform allows the introduction of new classes of commutative and non-commutative generalized convolutions. A particular case of such a convolution for degenerate distributions appears to be the Wigner semicircle distribution.

  7. Nuclear norm regularized convolutional Max Pos@Top machine

    KAUST Repository

    Li, Qinfeng; Zhou, Xiaofeng; Gu, Aihua; Li, Zonghua; Liang, Ru-Ze

    2016-01-01

    , named as Pos@Top. Our proposed classification model has a convolutional structure that is composed by four layers, i.e., the convolutional layer, the activation layer, the max-pooling layer and the full connection layer. In this paper, we propose

  8. Spherical convolutions and their application in molecular modelling

    DEFF Research Database (Denmark)

    Boomsma, Wouter; Frellsen, Jes

    2017-01-01

    Convolutional neural networks are increasingly used outside the domain of image analysis, in particular in various areas of the natural sciences concerned with spatial data. Such networks often work out-of-the box, and in some cases entire model architectures from image analysis can be carried over...... to other problem domains almost unaltered. Unfortunately, this convenience does not trivially extend to data in non-euclidean spaces, such as spherical data. In this paper, we introduce two strategies for conducting convolutions on the sphere, using either a spherical-polar grid or a grid based...... of spherical convolutions in the context of molecular modelling, by considering structural environments within proteins. We show that the models are capable of learning non-trivial functions in these molecular environments, and that our spherical convolutions generally outperform standard 3D convolutions...

  9. Frontal anatomy and reaction time in Autism

    NARCIS (Netherlands)

    Schmitz, Nicole; Daly, Eileen; Murphy, Declan

    2007-01-01

    Widespread frontal lobe abnormalities, encompassing anatomy and function, are known to be implicated in Autistic Spectrum Disorders (ASD). The correlation between neurobiology and behaviour, however, is poorly understood in ASD. The aim of this study was to investigate frontal lobe anatomy and

  10. Asymmetric Frontal Brain Activity and Parental Rejection

    NARCIS (Netherlands)

    Huffmeijer, R.; Alink, L.R.A.; Tops, M.; Bakermans-Kranenburg, M.J.; van IJzendoorn, M.H.

    2013-01-01

    Asymmetric frontal brain activity has been widely implicated in reactions to emotional stimuli and is thought to reflect individual differences in approach-withdrawal motivation. Here, we investigate whether asymmetric frontal activity, as a measure of approach-withdrawal motivation, also predicts

  11. The Association Between Suicidal Behavior, Attentional Control, and Frontal Asymmetry

    Directory of Open Access Journals (Sweden)

    Catherine Thompson

    2018-03-01

    Full Text Available It can be difficult to identify those at risk of suicide because suicidal thoughts are often internalized and not shared with others. Yet to prevent suicide attempts it is crucial to identify suicidal thoughts and actions at an early stage. Past studies have suggested that deficits in attentional control are associated with suicide, with the argument that individuals are unable to inhibit negative thoughts and direct resources away from negative information. The current study aimed to investigate the association of suicidal behavior with neurological and behavioral markers, measuring attentional bias and inhibition in two Stroop tasks. Fifty-four participants responded to the color of color words in a standard Stroop task and the color of positive, negative, and neutral words in an emotional Stroop task. Electroencephalographic (EEG activity was recorded from frontal areas during each task and at resting. Participants were separated into a low-risk and high-risk group according to their self-reported suicidal behavior. Participants in the high-risk group showed slower response times in the color Stroop and reduced accuracy to incongruent trials, but faster response times in the emotional Stroop task. Response times to the word “suicide” were significantly slower for the high-risk group. This indicates an attentional bias toward specific negative stimuli and difficulties inhibiting information for those with high levels of suicidal behavior. In the emotional Stroop task the high-risk group showed reduced activity in leftward frontal areas, suggesting limitations in the ability to regulate emotional processing via the left frontal regions. The findings support the argument that deficits in attentional control are related to suicidal behavior. The research also suggests that under certain conditions frontal asymmetry may be associated with suicidal behavior.

  12. The Association Between Suicidal Behavior, Attentional Control, and Frontal Asymmetry

    Science.gov (United States)

    Thompson, Catherine; Ong, Elsie Li Chen

    2018-01-01

    It can be difficult to identify those at risk of suicide because suicidal thoughts are often internalized and not shared with others. Yet to prevent suicide attempts it is crucial to identify suicidal thoughts and actions at an early stage. Past studies have suggested that deficits in attentional control are associated with suicide, with the argument that individuals are unable to inhibit negative thoughts and direct resources away from negative information. The current study aimed to investigate the association of suicidal behavior with neurological and behavioral markers, measuring attentional bias and inhibition in two Stroop tasks. Fifty-four participants responded to the color of color words in a standard Stroop task and the color of positive, negative, and neutral words in an emotional Stroop task. Electroencephalographic (EEG) activity was recorded from frontal areas during each task and at resting. Participants were separated into a low-risk and high-risk group according to their self-reported suicidal behavior. Participants in the high-risk group showed slower response times in the color Stroop and reduced accuracy to incongruent trials, but faster response times in the emotional Stroop task. Response times to the word “suicide” were significantly slower for the high-risk group. This indicates an attentional bias toward specific negative stimuli and difficulties inhibiting information for those with high levels of suicidal behavior. In the emotional Stroop task the high-risk group showed reduced activity in leftward frontal areas, suggesting limitations in the ability to regulate emotional processing via the left frontal regions. The findings support the argument that deficits in attentional control are related to suicidal behavior. The research also suggests that under certain conditions frontal asymmetry may be associated with suicidal behavior. PMID:29593586

  13. Task-modulated activation and functional connectivity of the temporal and frontal areas during speech comprehension.

    Science.gov (United States)

    Yue, Q; Zhang, L; Xu, G; Shu, H; Li, P

    2013-05-01

    There is general consensus in the literature that a distributed network of temporal and frontal brain areas is involved in speech comprehension. However, how active versus passive tasks modulate the activation and the functional connectivity of the critical brain areas is not clearly understood. In this study, we used functional magnetic resonance imaging (fMRI) to identify intelligibility and task-related effects in speech comprehension. Participants performed a semantic judgment task on normal and time-reversed sentences, or passively listened to the sentences without making an overt response. The subtraction analysis demonstrated that passive sentence comprehension mainly engaged brain areas in the left anterior and posterior superior temporal sulcus and middle temporal gyrus (aSTS/MTG and pSTS/MTG), whereas active sentence comprehension recruited bilateral frontal regions in addition to the aSTS/MTG and pSTS/MTG regions. Functional connectivity analysis revealed that during passive sentence comprehension, the left aSTS/MTG was functionally connected with the left Heschl's gyrus (HG) and bilateral superior temporal gyrus (STG) but no area was functionally connected with the left pSTS/MTG; during active sentence comprehension, however, both the left aSTS/MTG and pSTS/MTG were functionally connected with bilateral superior temporal and inferior frontal areas. While these results are consistent with the view that the ventral stream of the temporo-frontal network subserves semantic processing, our findings further indicate that both the activation and the functional connectivity of the temporal and frontal areas are modulated by task demands. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.

  14. Deformable image registration using convolutional neural networks

    Science.gov (United States)

    Eppenhof, Koen A. J.; Lafarge, Maxime W.; Moeskops, Pim; Veta, Mitko; Pluim, Josien P. W.

    2018-03-01

    Deformable image registration can be time-consuming and often needs extensive parameterization to perform well on a specific application. We present a step towards a registration framework based on a three-dimensional convolutional neural network. The network directly learns transformations between pairs of three-dimensional images. The outputs of the network are three maps for the x, y, and z components of a thin plate spline transformation grid. The network is trained on synthetic random transformations, which are applied to a small set of representative images for the desired application. Training therefore does not require manually annotated ground truth deformation information. The methodology is demonstrated on public data sets of inspiration-expiration lung CT image pairs, which come with annotated corresponding landmarks for evaluation of the registration accuracy. Advantages of this methodology are its fast registration times and its minimal parameterization.

  15. Codeword Structure Analysis for LDPC Convolutional Codes

    Directory of Open Access Journals (Sweden)

    Hua Zhou

    2015-12-01

    Full Text Available The codewords of a low-density parity-check (LDPC convolutional code (LDPC-CC are characterised into structured and non-structured. The number of the structured codewords is dominated by the size of the polynomial syndrome former matrix H T ( D , while the number of the non-structured ones depends on the particular monomials or polynomials in H T ( D . By evaluating the relationship of the codewords between the mother code and its super codes, the low weight non-structured codewords in the super codes can be eliminated by appropriately choosing the monomials or polynomials in H T ( D , resulting in improved distance spectrum of the mother code.

  16. Measuring the volume of frontal lobe in healthy Chinese adults of the Han nationality on the high-resolution MRI

    International Nuclear Information System (INIS)

    Yin Lu; Liu Peifang; Ye Zhaoxiang; Chen Nan; Wang Xing; Li Kuncheng; Zhuo Yan; Chen Lin

    2010-01-01

    Objective: To explore the normal range of the volume of frontal lobe in Chinese adults of the Han nationality and provide morphological data for the construction of database for Chinese Standard Brain. Methods: This is a clinical multi-center study. Two hundred Chinese healthy volunteers (age range =18 to 70) recruited from 16 hospitals were divided into 5 groups, i.e., age range from 18 to 30, age range from 31 to 40, age range from 41 to 50, age range from 51 to 60, and age range from 61 to 70. Each group contained 20 males and 20 females. All of the volunteers were scanned by MR using T 1 weighted three- dimensional magnetization prepared rapid acquisition gradient echo sequence. We used the manual method to trace the region of interest and measured the left and right frontal lobe volumes separately. All the data were analyzed with SPSS (version 13.0). The sex differences in the frontal lobe volumes were analyzed by independent-samples t test, and the side differences were analyzed by paired-samples t test. Correlation and regression analysis was used between the age and the frontal lobe volumes. Results: In 200 healthy Chinese Han volunteers, the total frontal lobe volumes was (563±73) cm 3 . For male, the volumes of the left and the right frontal lobe were (288±42) cm 3 and (292±41) cm 3 , respectively. The volumes of the left and right frontal lobe in 100 women were (273±30)cm 3 and (274±30) cm 3 respectively. The differences of sex (t=3.334, P 0.05). There were negative correlations between the frontal lobe volumes and age in men and women (r=-0.586, -0.498, P< 0.01). Conclusions: The total frontal lobe volume of men was larger than that of women. The volume of the right frontal lobe was larger than the left frontal lobe in men, and the asymmetries didn't exist in women. The total frontal lobe volumes were both shrinking with age in men and women, which was more rapid in men than in women. (authors)

  17. Frontal alpha asymmetry predicts inhibitory processing in youth with attention deficit/hyperactivity disorder.

    Science.gov (United States)

    Ellis, Alissa J; Kinzel, Chantelle; Salgari, Giulia C; Loo, Sandra K

    2017-07-28

    Atypical asymmetry in brain activity has been implicated in the behavioral and attentional dysregulation observed in ADHD. Specifically, asymmetry in neural activity in the right versus left frontal regions has been linked to ADHD, as well as to symptoms often associated with ADHD such as heightened approach behaviors, impulsivity and difficulties with inhibition. Clarifying the role of frontal asymmetry in ADHD-like traits, such as disinhibition, may provide information on the neurophysiological processes underlying these behaviors. ADHD youth (ADHD: n = 25) and healthy, typically developing controls (TD: n = 25) underwent an electroencephalography (EEG) recording while completing a go/no-go task-a commonly used test measuring behavioral inhibition. In addition, advanced signal processing for source localization estimated the location of signal generators underlying frontal alpha asymmetry (FA) during correct and incorrect trials. This is the first study in ADHD to demonstrate that the dorsal-lateral prefrontal cortex (DLPFC) may be responsible for generating frontal alpha. During failed inhibition trials, ADHD youth displayed greater FA than TD youth. In addition, within the ADHD group, frontal asymmetry during later processing stages (i.e., 400-800ms after stimulus) predicted a higher number of commission errors throughout the task. These results suggest that frontal alpha asymmetry may be a specific biomarker of cognitive disinhibition among youth with ADHD. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. CE verbal episodic memory impairment in schizophrenia: a comparison with frontal lobe lesion patients.

    Science.gov (United States)

    Christensen, Bruce K; Patrick, Regan E; Stuss, Donald T; Gillingham, Susan; Zipursky, Robert B

    2013-01-01

    Schizophrenia (SCZ)-related verbal memory impairment is hypothesized to be mediated, in part, by frontal lobe (FTL) dysfunction. However, little research has contrasted the performance of SCZ patients with that of patients exhibiting circumscribed frontal lesions. The current study compared verbal episodic memory in patients with SCZ and focal FTL lesions (left frontal, LF; right frontal, RF; and bi-frontal, BF) on a four-trial list learning task consisting of three lists of varying semantic organizational structure. Each dependent variable was examined at two levels: scores collapsed across all four trials and learning scores (i.e., trial 4-trial 1). Performance deficits were observed in each patient group across most dependent measures at both levels. Regarding patient group differences, SCZ patients outperformed LF/BF patients (i.e., either learning scores or scores collapsed across trial) on free recall, primacy, primary memory, secondary memory, and subjective organization, whereas they only outperformed RF patients on the semantically blocked list on recency and primary memory. Collectively, these results indicate that the pattern of memory performance is largely similar between patients with SCZ and those with RF lesions. These data support tentative arguments that verbal episodic memory deficits in SCZ may be mediated by frontal dysfunction in the right hemisphere.

  19. Autobiographical memory of the recent past following frontal cortex or temporal lobe excisions.

    Science.gov (United States)

    Thaiss, Laila; Petrides, Michael

    2008-08-01

    Previous research has raised questions regarding the necessity of the frontal cortex in autobiographical memory and the role that it plays in actively retrieving contextual information associated with personally relevant events. Autobiographical memory was studied in patients with unilateral excisions restricted to the frontal cortex or temporal lobe involving the amygdalo-hippocampal region and in normal controls using an event-sampling method. We examined accuracy of free recall, use of strategies during retrieval and memory for specific aspects of the autobiographical events, including temporal order. Patients with temporal lobe excisions were impaired in autobiographical recall. By contrast, patients with frontal cortical excisions exhibited normal autobiographical recall but were less likely to use temporal order spontaneously to organize event retrieval. Instruction to organize retrieval by temporal order failed to improve recall in temporal lobe patients and increased the incidence of plausible intrusion errors in left temporal patients. In contrast, patients with frontal cortical excisions now surpassed control subjects in recall of autobiographical events. Furthermore, the retrieval accuracy for the temporal order of diary events was not impaired in these patients. In a subsequent cued recall test, temporal lobe patients were impaired in their memory for the details of the diary events and their context. In conclusion, a basic impairment in autobiographical memory (including memory for temporal context) results from damage to the temporal lobe and not the frontal cortex. Patients with frontal excisions fail to use organizational strategies spontaneously to aid retrieval but can use these effectively if instructed to do so.

  20. Vulnerability of the frontal and parietal regions in hypertensive patients during working memory task.

    Science.gov (United States)

    Li, Xin; Wang, Wenxiao; Wang, Ailin; Li, Peng; Zhang, Junying; Tao, Wuhai; Zhang, Zhanjun

    2017-05-01

    Hypertension is related with cognitive decline in the elderly. The frontal-parietal executive system plays an important role in cognitive aging and is also vulnerable to damage in elderly patients with hypertension. Examination of the brain's functional characteristics in frontal-parietal regions of hypertension is likely to be important for understanding the neural mechanisms of hypertension's effect on cognitive aging. We address this issue by comparing hypertension and control-performers in a functional MRI study. Twenty-eight hypertensive patients and 32 elderly controls were tested with n-back task with two load levels. The hypertensive patients exhibited worse executive and memory abilities than control subjects. The patterns of brain activation changed under different working memory loads in the hypertensive patients, who exhibited reduced activation only in the precentral gyrus under low loads and reduced activation in the middle frontal gyrus, left medial superior frontal gyrus and right precuneus under high loads. Thus, more regions of diminished activation were observed in the frontal and parietal regions with increasing task difficulty. More importantly, we found that lower activation in changed frontal and parietal regions was associated with worse cognitive function in high loads. The results demonstrate the relationship between cognitive function and frontoparietal functional activation in hypertension and their relevance to cognitive aging risk. Our findings provide a better understanding of the mechanism of cognitive decline in hypertension and highlight the importance of brain protection in hypertension.

  1. An Improved Convolutional Neural Network on Crowd Density Estimation

    Directory of Open Access Journals (Sweden)

    Pan Shao-Yun

    2016-01-01

    Full Text Available In this paper, a new method is proposed for crowd density estimation. An improved convolutional neural network is combined with traditional texture feature. The data calculated by the convolutional layer can be treated as a new kind of features.So more useful information of images can be extracted by different features.In the meantime, the size of image has little effect on the result of convolutional neural network. Experimental results indicate that our scheme has adequate performance to allow for its use in real world applications.

  2. Cranialization of the frontal sinus for secondary mucocele prevention following open surgery for benign frontal lesions.

    Directory of Open Access Journals (Sweden)

    Gilad Horowitz

    Full Text Available OBJECTIVE: To compare frontal sinus cranialization to obliteration for future prevention of secondary mucocele formation following open surgery for benign lesions of the frontal sinus. STUDY DESIGN: Retrospective case series. SETTING: Tertiary academic medical center. PATIENTS: Sixty-nine patients operated for benign frontal sinus pathology between 1994 and 2011. INTERVENTIONS: Open excision of benign frontal sinus pathology followed by either frontal obliteration (n = 41, 59% or frontal cranialization (n = 28, 41%. MAIN OUTCOME MEASURES: The prevalence of post-surgical complications and secondary mucocele formation were compiled. RESULTS: Pathologies included osteoma (n = 34, 49%, mucocele (n = 27, 39%, fibrous dysplasia (n = 6, 9%, and encephalocele (n = 2, 3%. Complications included skin infections (n = 6, postoperative cutaneous fistula (n = 1, telecanthus (n = 4, diplopia (n = 3, nasal deformity (n = 2 and epiphora (n = 1. None of the patients suffered from postoperative CSF leak, meningitis or pneumocephalus. Six patients, all of whom had previously undergone frontal sinus obliteration, required revision surgery due to secondary mucocele formation. Statistical analysis using non-inferiority test reveal that cranialization of the frontal sinus is non-inferior to obliteration for preventing secondary mucocele formation (P<0.0001. CONCLUSION: Cranialization of the frontal sinus appears to be a good option for prevention of secondary mucocele development after open excision of benign frontal sinus lesions.

  3. Corpus callosum lipoma with frontal encephalocele

    International Nuclear Information System (INIS)

    Srinivasa Rao, A.; Rao, V.R.K.; Ravi Mandalam, K.; Gupta, A.K.; Kumar, S.; Joseph, S.; Unni, M.

    1990-01-01

    Computed tomographic and plain X-ray observations in a patient with corpus callosum lipoma associated with frontal encephalocele are reported. The rarity of the lesion and the specific diagnostic criteria on CT are emphasised. (orig.)

  4. Errors on the Trail Making Test Are Associated with Right Hemispheric Frontal Lobe Damage in Stroke Patients

    Directory of Open Access Journals (Sweden)

    Bruno Kopp

    2015-01-01

    Full Text Available Measures of performance on the Trail Making Test (TMT are among the most popular neuropsychological assessment techniques. Completion time on TMT-A is considered to provide a measure of processing speed, whereas completion time on TMT-B is considered to constitute a behavioral measure of the ability to shift between cognitive sets (cognitive flexibility, commonly attributed to the frontal lobes. However, empirical evidence linking performance on the TMT-B to localized frontal lesions is mostly lacking. Here, we examined the association of frontal lesions following stroke with TMT-B performance measures (i.e., completion time and completion accuracy measures using voxel-based lesion-behavior mapping, with a focus on right hemispheric frontal lobe lesions. Our results suggest that the number of errors, but not completion time on the TMT-B, is associated with right hemispheric frontal lesions. This finding contradicts common clinical practice—the use of completion time on the TMT-B to measure cognitive flexibility, and it underscores the need for additional research on the association between cognitive flexibility and the frontal lobes. Further work in a larger sample, including left frontal lobe damage and with more power to detect effects of right posterior brain injury, is necessary to determine whether our observation is specific for right frontal lesions.

  5. Delusional misidentifications and duplications: right brain lesions, left brain delusions.

    Science.gov (United States)

    Devinsky, Orrin

    2009-01-06

    When the delusional misidentification syndromes reduplicative paramnesia and Capgras syndromes result from neurologic disease, lesions are usually bifrontal and/or right hemispheric. The related disorders of confabulation and anosognosis share overlapping mechanisms and anatomic pathology. A dual mechanism is postulated for the delusional misidentification syndromes: negative effects from right hemisphere and frontal lobe dysfunction as well as positive effects from release (i.e., overactivity) of preserved left hemisphere areas. Negative effects of right hemisphere injury impair self-monitoring, ego boundaries, and attaching emotional valence and familiarity to stimuli. The unchecked left hemisphere unleashes a creative narrator from the monitoring of self, memory, and reality by the frontal and right hemisphere areas, leading to excessive and false explanations. Further, the left hemisphere's cognitive style of categorization, often into dual categories, leads it to invent a duplicate or impostor to resolve conflicting information. Delusions result from right hemisphere lesions. But it is the left hemisphere that is deluded.

  6. Beyond the sniffer: frontal sinuses in Carnivora.

    Science.gov (United States)

    Curtis, Abigail A; Van Valkenburgh, Blaire

    2014-11-01

    Paranasal sinuses are some of the most poorly understood features of mammalian cranial anatomy. They are highly variable in presence and form among species, but their function is not well understood. The best-supported explanations for the function of sinuses is that they opportunistically fill mechanically unnecessary space, but that in some cases, sinuses in combination with the configuration of the frontal bone may improve skull performance by increasing skull strength and dissipating stresses more evenly. We used CT technology to investigate patterns in frontal sinus size and shape disparity among three families of carnivores: Canidae, Felidae, and Hyaenidae. We provide some of the first quantitative data on sinus morphology for these three families, and employ a novel method to quantify the relationship between three-dimensional sinus shape and skull shape. As expected, frontal sinus size and shape were more strongly correlated with frontal bone size and shape than with the morphology of the skull as a whole. However, sinus morphology was also related to allometric differences among families that are linked to biomechanical function. Our results support the hypothesis that frontal sinuses most often opportunistically fill space that is mechanically unnecessary, and they can facilitate cranial shape changes that reduce stress during feeding. Moreover, we suggest that the ability to form frontal sinuses allows species to modify skull function without compromising the performance of more functionally constrained regions such as the nasal chamber (heat/water conservation, olfaction), and braincase (housing the brain and sensory structures). © 2014 Wiley Periodicals, Inc.

  7. High Order Tensor Formulation for Convolutional Sparse Coding

    KAUST Repository

    Bibi, Adel Aamer; Ghanem, Bernard

    2017-01-01

    Convolutional sparse coding (CSC) has gained attention for its successful role as a reconstruction and a classification tool in the computer vision and machine learning community. Current CSC methods can only reconstruct singlefeature 2D images

  8. Adversarial training and dilated convolutions for brain MRI segmentation

    NARCIS (Netherlands)

    Moeskops, P.; Veta, M.; Lafarge, M.W.; Eppenhof, K.A.J.; Pluim, J.P.W.

    2017-01-01

    Convolutional neural networks (CNNs) have been applied to various automatic image segmentation tasks in medical image analysis, including brain MRI segmentation. Generative adversarial networks have recently gained popularity because of their power in generating images that are difficult to

  9. Classification of urine sediment based on convolution neural network

    Science.gov (United States)

    Pan, Jingjing; Jiang, Cunbo; Zhu, Tiantian

    2018-04-01

    By designing a new convolution neural network framework, this paper breaks the constraints of the original convolution neural network framework requiring large training samples and samples of the same size. Move and cropping the input images, generate the same size of the sub-graph. And then, the generated sub-graph uses the method of dropout, increasing the diversity of samples and preventing the fitting generation. Randomly select some proper subset in the sub-graphic set and ensure that the number of elements in the proper subset is same and the proper subset is not the same. The proper subsets are used as input layers for the convolution neural network. Through the convolution layer, the pooling, the full connection layer and output layer, we can obtained the classification loss rate of test set and training set. In the red blood cells, white blood cells, calcium oxalate crystallization classification experiment, the classification accuracy rate of 97% or more.

  10. Convolution of second order linear recursive sequences II.

    Directory of Open Access Journals (Sweden)

    Szakács Tamás

    2017-12-01

    Full Text Available We continue the investigation of convolutions of second order linear recursive sequences (see the first part in [1]. In this paper, we focus on the case when the characteristic polynomials of the sequences have common root.

  11. FPGA-based digital convolution for wireless applications

    CERN Document Server

    Guan, Lei

    2017-01-01

    This book presents essential perspectives on digital convolutions in wireless communications systems and illustrates their corresponding efficient real-time field-programmable gate array (FPGA) implementations. Covering these digital convolutions from basic concept to vivid simulation/illustration, the book is also supplemented with MS PowerPoint presentations to aid in comprehension. FPGAs or generic all programmable devices will soon become widespread, serving as the “brains” of all types of real-time smart signal processing systems, like smart networks, smart homes and smart cities. The book examines digital convolution by bringing together the following main elements: the fundamental theory behind the mathematical formulae together with corresponding physical phenomena; virtualized algorithm simulation together with benchmark real-time FPGA implementations; and detailed, state-of-the-art case studies on wireless applications, including popular linear convolution in digital front ends (DFEs); nonlinear...

  12. Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition

    OpenAIRE

    Zhang, Zewang; Sun, Zheng; Liu, Jiaqi; Chen, Jingwen; Huo, Zhao; Zhang, Xiao

    2016-01-01

    A deep learning approach has been widely applied in sequence modeling problems. In terms of automatic speech recognition (ASR), its performance has significantly been improved by increasing large speech corpus and deeper neural network. Especially, recurrent neural network and deep convolutional neural network have been applied in ASR successfully. Given the arising problem of training speed, we build a novel deep recurrent convolutional network for acoustic modeling and then apply deep resid...

  13. Traffic sign recognition with deep convolutional neural networks

    OpenAIRE

    Karamatić, Boris

    2016-01-01

    The problem of detection and recognition of traffic signs is becoming an important problem when it comes to the development of self driving cars and advanced driver assistance systems. In this thesis we will develop a system for detection and recognition of traffic signs. For the problem of detection we will use aggregate channel features and for the problem of recognition we will use a deep convolutional neural network. We will describe how convolutional neural networks work, how they are co...

  14. Convolutional Codes with Maximum Column Sum Rank for Network Streaming

    OpenAIRE

    Mahmood, Rafid; Badr, Ahmed; Khisti, Ashish

    2015-01-01

    The column Hamming distance of a convolutional code determines the error correction capability when streaming over a class of packet erasure channels. We introduce a metric known as the column sum rank, that parallels column Hamming distance when streaming over a network with link failures. We prove rank analogues of several known column Hamming distance properties and introduce a new family of convolutional codes that maximize the column sum rank up to the code memory. Our construction invol...

  15. Efficient and Invariant Convolutional Neural Networks for Dense Prediction

    OpenAIRE

    Gao, Hongyang; Ji, Shuiwang

    2017-01-01

    Convolutional neural networks have shown great success on feature extraction from raw input data such as images. Although convolutional neural networks are invariant to translations on the inputs, they are not invariant to other transformations, including rotation and flip. Recent attempts have been made to incorporate more invariance in image recognition applications, but they are not applicable to dense prediction tasks, such as image segmentation. In this paper, we propose a set of methods...

  16. Prediction of Electricity Usage Using Convolutional Neural Networks

    OpenAIRE

    Hansen, Martin

    2017-01-01

    Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Convolutional Neural Networks are overwhelmingly accurate when attempting to predict numbers using the famous MNIST-dataset. In this paper, we are attempting to transcend these results for time- series forecasting, and compare them with several regression mod- els. The Convolutional Neural Network model predicted the same value through the entire time lapse in contrast with the other ...

  17. Research of convolutional neural networks for traffic sign recognition

    OpenAIRE

    Stadalnikas, Kasparas

    2017-01-01

    In this thesis the convolutional neural networks application for traffic sign recognition is analyzed. Thesis describes the basic operations, techniques that are commonly used to apply in the image classification using convolutional neural networks. Also, this paper describes the data sets used for traffic sign recognition, their problems affecting the final training results. The paper reviews most popular existing technologies – frameworks for developing the solution for traffic sign recogni...

  18. On the Fresnel sine integral and the convolution

    Directory of Open Access Journals (Sweden)

    Adem Kılıçman

    2003-01-01

    Full Text Available The Fresnel sine integral S(x, the Fresnel cosine integral C(x, and the associated functions S+(x, S−(x, C+(x, and C−(x are defined as locally summable functions on the real line. Some convolutions and neutrix convolutions of the Fresnel sine integral and its associated functions with x+r, xr are evaluated.

  19. Developmental dyslexia: dysfunction of a left hemisphere reading network

    Directory of Open Access Journals (Sweden)

    Fabio eRichlan

    2012-05-01

    Full Text Available This mini-review summarizes and integrates findings from recent meta-analyses and original neuroimaging studies on functional brain abnormalities in dyslexic readers. Surprisingly, there is little empirical support for the standard neuroanatomical model of developmental dyslexia, which localizes the primary phonological decoding deficit in left temporo-parietal regions. Rather, recent evidence points to a dysfunction of a left hemisphere reading network, which includes occipito-temporal, inferior frontal, and inferior parietal regions.

  20. Radial Structure Scaffolds Convolution Patterns of Developing Cerebral Cortex

    Directory of Open Access Journals (Sweden)

    Mir Jalil Razavi

    2017-08-01

    Full Text Available Commonly-preserved radial convolution is a prominent characteristic of the mammalian cerebral cortex. Endeavors from multiple disciplines have been devoted for decades to explore the causes for this enigmatic structure. However, the underlying mechanisms that lead to consistent cortical convolution patterns still remain poorly understood. In this work, inspired by prior studies, we propose and evaluate a plausible theory that radial convolution during the early development of the brain is sculptured by radial structures consisting of radial glial cells (RGCs and maturing axons. Specifically, the regionally heterogeneous development and distribution of RGCs controlled by Trnp1 regulate the convex and concave convolution patterns (gyri and sulci in the radial direction, while the interplay of RGCs' effects on convolution and axons regulates the convex (gyral convolution patterns. This theory is assessed by observations and measurements in literature from multiple disciplines such as neurobiology, genetics, biomechanics, etc., at multiple scales to date. Particularly, this theory is further validated by multimodal imaging data analysis and computational simulations in this study. We offer a versatile and descriptive study model that can provide reasonable explanations of observations, experiments, and simulations of the characteristic mammalian cortical folding.

  1. Metaheuristic Algorithms for Convolution Neural Network.

    Science.gov (United States)

    Rere, L M Rasdi; Fanany, Mohamad Ivan; Arymurthy, Aniati Murni

    2016-01-01

    A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metaheuristic for accuracy improvement on convolution neural networks (CNN), a famous deep learning method, is still rarely investigated. Deep learning relates to a type of machine learning technique, where its aim is to move closer to the goal of artificial intelligence of creating a machine that could successfully perform any intellectual tasks that can be carried out by a human. In this paper, we propose the implementation strategy of three popular metaheuristic approaches, that is, simulated annealing, differential evolution, and harmony search, to optimize CNN. The performances of these metaheuristic methods in optimizing CNN on classifying MNIST and CIFAR dataset were evaluated and compared. Furthermore, the proposed methods are also compared with the original CNN. Although the proposed methods show an increase in the computation time, their accuracy has also been improved (up to 7.14 percent).

  2. Metaheuristic Algorithms for Convolution Neural Network

    Directory of Open Access Journals (Sweden)

    L. M. Rasdi Rere

    2016-01-01

    Full Text Available A typical modern optimization technique is usually either heuristic or metaheuristic. This technique has managed to solve some optimization problems in the research area of science, engineering, and industry. However, implementation strategy of metaheuristic for accuracy improvement on convolution neural networks (CNN, a famous deep learning method, is still rarely investigated. Deep learning relates to a type of machine learning technique, where its aim is to move closer to the goal of artificial intelligence of creating a machine that could successfully perform any intellectual tasks that can be carried out by a human. In this paper, we propose the implementation strategy of three popular metaheuristic approaches, that is, simulated annealing, differential evolution, and harmony search, to optimize CNN. The performances of these metaheuristic methods in optimizing CNN on classifying MNIST and CIFAR dataset were evaluated and compared. Furthermore, the proposed methods are also compared with the original CNN. Although the proposed methods show an increase in the computation time, their accuracy has also been improved (up to 7.14 percent.

  3. Do Convolutional Neural Networks Learn Class Hierarchy?

    Science.gov (United States)

    Bilal, Alsallakh; Jourabloo, Amin; Ye, Mao; Liu, Xiaoming; Ren, Liu

    2018-01-01

    Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of confusion increase. Interestingly, the class confusion patterns follow a hierarchical structure over the classes. We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data. We found that this hierarchy not only dictates the confusion patterns between the classes, it furthermore dictates the learning behavior of CNNs. In particular, the early layers in these networks develop feature detectors that can separate high-level groups of classes quite well, even after a few training epochs. In contrast, the latter layers require substantially more epochs to develop specialized feature detectors that can separate individual classes. We demonstrate how these insights are key to significant improvement in accuracy by designing hierarchy-aware CNNs that accelerate model convergence and alleviate overfitting. We further demonstrate how our methods help in identifying various quality issues in the training data.

  4. Microaneurysm detection using fully convolutional neural networks.

    Science.gov (United States)

    Chudzik, Piotr; Majumdar, Somshubra; Calivá, Francesco; Al-Diri, Bashir; Hunter, Andrew

    2018-05-01

    Diabetic retinopathy is a microvascular complication of diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the earliest clinical signs of diabetic retinopathy. This paper presents an automatic method for detecting microaneurysms in fundus photographies. A novel patch-based fully convolutional neural network with batch normalization layers and Dice loss function is proposed. Compared to other methods that require up to five processing stages, it requires only three. Furthermore, to the best of the authors' knowledge, this is the first paper that shows how to successfully transfer knowledge between datasets in the microaneurysm detection domain. The proposed method was evaluated using three publicly available and widely used datasets: E-Ophtha, DIARETDB1, and ROC. It achieved better results than state-of-the-art methods using the FROC metric. The proposed algorithm accomplished highest sensitivities for low false positive rates, which is particularly important for screening purposes. Performance, simplicity, and robustness of the proposed method demonstrates its suitability for diabetic retinopathy screening applications. Copyright © 2018 Elsevier B.V. All rights reserved.

  5. Multiscale Convolutional Neural Networks for Hand Detection

    Directory of Open Access Journals (Sweden)

    Shiyang Yan

    2017-01-01

    Full Text Available Unconstrained hand detection in still images plays an important role in many hand-related vision problems, for example, hand tracking, gesture analysis, human action recognition and human-machine interaction, and sign language recognition. Although hand detection has been extensively studied for decades, it is still a challenging task with many problems to be tackled. The contributing factors for this complexity include heavy occlusion, low resolution, varying illumination conditions, different hand gestures, and the complex interactions between hands and objects or other hands. In this paper, we propose a multiscale deep learning model for unconstrained hand detection in still images. Deep learning models, and deep convolutional neural networks (CNNs in particular, have achieved state-of-the-art performances in many vision benchmarks. Developed from the region-based CNN (R-CNN model, we propose a hand detection scheme based on candidate regions generated by a generic region proposal algorithm, followed by multiscale information fusion from the popular VGG16 model. Two benchmark datasets were applied to validate the proposed method, namely, the Oxford Hand Detection Dataset and the VIVA Hand Detection Challenge. We achieved state-of-the-art results on the Oxford Hand Detection Dataset and had satisfactory performance in the VIVA Hand Detection Challenge.

  6. Eye contact with neutral and smiling faces: effects on frontal EEG asymmetry and autonomic responses

    Directory of Open Access Journals (Sweden)

    Laura Maria Pönkänen

    2012-05-01

    Full Text Available In our previous studies we have shown that seeing another person live with a direct vs. averted gaze results in greater relative left-sided frontal asymmetry in the electroencephalography (EEG, associated with approach motivation, and in enhanced skin conductance responses indicating autonomic arousal. In our studies, however, the stimulus persons had a neutral expression. In real-life social interaction, eye contact is often associated with a smile, which is another signal of the sender’s approach-related motivation. A smile could therefore enhance the affective-motivational responses to eye contact. In the present study, we investigated whether the facial expression (neutral vs. smile would modulate the frontal EEG asymmetry and autonomic arousal to seeing a direct vs. an averted gaze in faces presented live through a liquid crystal shutter. The results showed that the skin conductance responses were greater for the direct than the averted gaze and that the effect of gaze direction was more pronounced for a smiling than a neutral face. However, the frontal EEG asymmetry results revealed a more complex pattern. Participants whose responses to seeing the other person were overall indicative of leftward frontal activity (indicative of approach showed greater relative left-sided asymmetry for the direct vs. averted gaze, whereas participants whose responses were overall indicative of rightward frontal activity (indicative of avoidance showed greater relative right-sided asymmetry to direct vs. averted gaze. The other person’s facial expression did not have an effect on the frontal EEG asymmetry. These findings may reflect that another’s direct gaze, as compared to their smile, has a more dominant role in regulating perceivers’ approach motivation.

  7. Frontal cephalometrics: practical applications, part 2.

    Science.gov (United States)

    Grummons, Duane; Ricketts, Robert M

    2004-01-01

    To (1) demonstrate the needs and benefits of three-dimensional diagnostic and treatment applications; (2) illustrate practical clinical applications of anteroposterior images and frontal analysis; and (3) enhance utilization of the Ricketts and Grummons frontal analyses. Frontal analysis methods and applications are specified and integrated into facial, smile, jaw, and occlusal therapies. Asymmetry conditions must be differentially diagnosed and effectively treated. Frontal and related image analysis and tracing steps are detailed. Asymmetry of facial parts is the rule, rather than the exception. Dental and facial midlines, occlusal plane, chin location, and smile esthetics are primarily emphasized. Beautiful facial proportions and smile harmony can be developed despite initial facial dysmorphosis and disproportions. Patients view themselves from the frontal perspective, so this carries priority when assessing problems. It is important to know the etiology of asymmetry to assist others with genetic counseling. Facial harmony and smile beauty are optimal when facial and maxillary dental midlines are aligned. The maxillary dentition width should be sufficiently wide to be in harmony with the individual patient facial morphology. The occlusal plane should be level and the chin centered as much as possible. Best facial development and proportionality exist when the skeletal and dental components are optimized transversely and are symmetric.

  8. Approach and withdrawal motivation in schizophrenia: an examination of frontal brain asymmetric activity.

    Science.gov (United States)

    Horan, William P; Wynn, Jonathan K; Mathis, Ian; Miller, Gregory A; Green, Michael F

    2014-01-01

    Although motivational disturbances are common in schizophrenia, their neurophysiological and psychological basis is poorly understood. This electroencephalography (EEG) study examined the well-established motivational direction model of asymmetric frontal brain activity in schizophrenia. According to this model, relative left frontal activity in the resting EEG reflects enhanced approach motivation tendencies, whereas relative right frontal activity reflects enhanced withdrawal motivation tendencies. Twenty-five schizophrenia outpatients and 25 healthy controls completed resting EEG assessments of frontal asymmetry in the alpha frequency band (8-12 Hz), as well as a self-report measure of behavioral activation and inhibition system (BIS/BAS) sensitivity. Patients showed an atypical pattern of differences from controls. On the EEG measure patients failed to show the left lateralized activity that was present in controls, suggesting diminished approach motivation. On the self-report measure, patients reported higher BIS sensitivity than controls, which is typically interpreted as heightened withdrawal motivation. EEG asymmetry scores did not significantly correlate with BIS/BAS scores or with clinical symptom ratings among patients. The overall pattern suggests a motivational disturbance in schizophrenia characterized by elements of both diminished approach and elevated withdrawal tendencies.

  9. Contrasting losses and gains increases the predictability of behavior by frontal EEG asymmetry

    Science.gov (United States)

    Telpaz, Ariel; Yechiam, Eldad

    2014-01-01

    Frontal asymmetry measured at rest using EEG is considered a stable marker of approach-avoidance behaviors and risk taking. We examined whether without salient cues of attention in the form of losses, predictability is reduced. Fifty-seven participants performed an experiential decision task in a gain-only, loss-only, and mixed (gains and losses) condition. Increased risk taking on the part of individuals with relatively high left frontal activation, as denoted by the Alpha band, was only observed in the task involving both gains and losses. Event-related potential analysis sheds light on the processes leading to this pattern. Left-frontal dominant individuals had increased fronto-central P300 activation following risky compared to safe outcomes, while right-frontal dominant individuals did not show a P300 difference following safe and risky outcomes. This interaction also only emerged when losses were contrasted with gains. The findings highlight the sensitivity of behavioral predictability to cues of valence. PMID:24817845

  10. Frontal and parietal theta burst TMS impairs working memory for visual-spatial conjunctions.

    Science.gov (United States)

    Morgan, Helen M; Jackson, Margaret C; van Koningsbruggen, Martijn G; Shapiro, Kimron L; Linden, David E J

    2013-03-01

    In tasks that selectively probe visual or spatial working memory (WM) frontal and posterior cortical areas show a segregation, with dorsal areas preferentially involved in spatial (e.g. location) WM and ventral areas in visual (e.g. object identity) WM. In a previous fMRI study [1], we showed that right parietal cortex (PC) was more active during WM for orientation, whereas left inferior frontal gyrus (IFG) was more active during colour WM. During WM for colour-orientation conjunctions, activity in these areas was intermediate to the level of activity for the single task preferred and non-preferred information. To examine whether these specialised areas play a critical role in coordinating visual and spatial WM to perform a conjunction task, we used theta burst transcranial magnetic stimulation (TMS) to induce a functional deficit. Compared to sham stimulation, TMS to right PC or left IFG selectively impaired WM for conjunctions but not single features. This is consistent with findings from visual search paradigms, in which frontal and parietal TMS selectively affects search for conjunctions compared to single features, and with combined TMS and functional imaging work suggesting that parietal and frontal regions are functionally coupled in tasks requiring integration of visual and spatial information. Our results thus elucidate mechanisms by which the brain coordinates spatially segregated processing streams and have implications beyond the field of working memory. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Tratamiento y complicaciones de las fracturas de seno frontal Frontal sinus fracture treatment and complications

    Directory of Open Access Journals (Sweden)

    S. Heredero Jung

    2007-06-01

    Full Text Available Introducción. Las fracturas de seno frontal se producen como resultado de impactos de alta energía. Un tratamiento inadecuado puede conducir a complicaciones serias incluso muchos años después del traumatismo. Objetivos. Evaluar los datos epidemiológicos y revisar las complicaciones asociadas. Estandarizar el protocolo de tratamiento. Materiales y métodos. Se revisaron 95 pacientes diagnosticados de fracturas de seno frontal pertenecientes al servicio de Cirugía Oral y Maxilofacial del Hospital Universitario 12 de Octubre de Madrid, entre enero de 1990 y diciembre de 2004. Resultados. La edad media de los pacientes revisados es de 34 años. La mayoría son hombres (78% y la causa más frecuente del traumatismo, los accidentes de tráfico. El patrón de fractura más común es el que afecta únicamente a la pared anterior del seno frontal. Las complicaciones descritas son: deformidad estética frontal, sinusitis frontal, mucocele frontal, celulitis fronto-orbitaria, intolerancia al material de osteosíntesis, complicaciones infecciosas del SNC y persistencia de fístula de líquido cefalorraquídeo. Conclusiones. El objetivo ha de estar encaminado a prevenir las complicaciones asociadas a los pacientes con fracturas de seno frontal. Hay que individualizar el protocolo de tratamiento en cada caso. Es recomendable un seguimiento a largo plazo para identificar precozmente las posibles complicaciones.Introduction. Frontal sinus fractures are caused by high velocity impacts. Inappropriate treatment can lead to serious complications, even many years after the trauma. Objectives. To evaluate epidemiological data and associated complications. To standardize the treatment protocol. Materials and methods. the clinical records of 95 patients with frontal sinus fractures treated between January 1990 and December 2004 at the Oral and Maxillofacial Surgery Department, "12 de Octubre" Hospital (Madrid, Spain, were reviewed. Results. The average age of

  12. Is Kinesio Taping to Generate Skin Convolutions Effective for Increasing Local Blood Circulation?

    Science.gov (United States)

    Yang, Jae-Man; Lee, Jung-Hoon

    2018-01-14

    BACKGROUND It is unclear whether traditional application of Kinesio taping, which produces wrinkles in the skin, is effective for improving blood circulation. This study investigated local skin temperature changes after the application of an elastic therapeutic tape using convolution and non-convolution taping methods (CTM/NCTM). MATERIAL AND METHODS Twenty-eight pain-free men underwent CTM and NCTM randomly applied to the right and left sides of the lower back. Using infrared thermography, skin temperature was measured before, immediately after application, 5 min later, 15 min later, and after the removal of the tape. RESULTS Both CTM and NCTM showed a slight, but significant, decrease in skin temperature for up to 5 min. The skin temperature at 15 min and after the removal of the tape was not significantly different from the initial temperature for CTM and NCTM. There were also no significant differences in the skin temperatures between CTM and NCTM. CONCLUSIONS Our findings do not support a therapeutic effect of wrinkling the skin with elastic tape application as a technique to increase local blood flow.

  13. Effects of Level of Retrieval Success on Recall-Related Frontal and Medial Temporal Lobe Activations

    Directory of Open Access Journals (Sweden)

    Daniela Montaldi

    2002-01-01

    Full Text Available Brain dedicated single photon emission computed tomography (SPECT was used to compare the neuroactivation produced by the cued recall of response words in a set of studied word pairs with that produced by the cued retrieval of words semantically related to unstudied stimulus words. Six of the 12 subjects scanned were extensively trained so as to have good memory of the studied pairs and the remaining six were minimally trained so as to have poor memory. When comparing episodic with semantic retrieval, the well-trained subjects showed significant left medial temporal lobe activation, which was also significantly greater than that shown by the poorly trained subjects, who failed to show significant medial temporal lobe activation. In contrast, the poorly trained subjects showed significant bilateral frontal lobe activation, which was significantly greater than that shown by the well-trained subjects who failed to show significant frontal lobe activation. The frontal activations occurred mainly in the dorsolateral region, but extended into the ventrolateral and, to a lesser extent, the frontal polar regions. It is argued that whereas the medial temporal lobe activation increased as the proportion of response words successfully recalled increased, the bilateral frontal lobe activation increased in proportion to retrieval effort, which was greater when learning had been less good.

  14. The effect of focal cortical frontal and posterior lesions on recollection and familiarity in recognition memory.

    Science.gov (United States)

    Stamenova, Vessela; Gao, Fuqiang; Black, Sandra E; Schwartz, Michael L; Kovacevic, Natasha; Alexander, Michael P; Levine, Brian

    2017-06-01

    Recognition memory can be subdivided into two processes: recollection (a contextually rich memory) and familiarity (a sense that an item is old). The brain network supporting recognition encompasses frontal, parietal and medial temporal regions. Which specific regions within the frontal lobe are critical for recollection vs. familiarity, however, are unknown; past studies of focal lesion patients have yielded conflicting results. We examined patients with focal lesions confined to medial polar (MP), right dorsal frontal (RDF), right frontotemporal (RFT), left dorsal frontal (LDF), temporal, and parietal regions and matched controls. A series of words and their humorous definitions were presented either auditorily or visually to all participants. Recall, recognition, and source memory were tested at 30 min and 24 h delay, along with "remember/know" judgments for recognized items. The MP, RDF, temporal and parietal groups were impaired on subjectively reported recollection; their intact recognition performance was supported by familiarity. None of the groups were impaired on cued recall, recognition familiarity or source memory. These findings suggest that the MP and RDF regions, along with parietal and temporal regions, are necessary for subjectively-reported recollection, while the LDF and right frontal ventral regions, as those affected in the RTF group, are not. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. [Language Functions in the Frontal Association Area: Brain Mechanisms That Create Language].

    Science.gov (United States)

    Yamamoto, Kayako; Sakai, Kuniyoshi L

    2016-11-01

    Broca's area is known to be critically involved in language processing for more than 150 years. Recent neuroimaging techniques, including functional magnetic resonance imaging (fMRI) and diffusion MRI, enabled the subdivision of Broca's area based on both functional and anatomical aspects. Networks among the frontal association areas, especially the left inferior frontal gyrus (IFG), and other cortical regions in the temporal/parietal association areas, are also important for language-related information processing. Here, we review how neuroimaging studies, combined with research paradigms based on theoretical linguistics, have contributed to clarifying the critical roles of the left IFG in syntactic processing and those of language-related networks, including cortical and cerebellar regions.

  16. The Right Posterior Inferior Frontal Gyrus Contributes to Phonological Word Decisions in the Healthy Brain: Evidence from Dual-Site TMS

    Science.gov (United States)

    Hartwigsen, Gesa; Price, Cathy J.; Baumgaertner, Annette; Geiss, Gesine; Koehnke, Maria; Ulmer, Stephan; Siebner, Hartwig R.

    2010-01-01

    There is consensus that the left hemisphere plays a dominant role in language processing, but functional imaging studies have shown that the right as well as the left posterior inferior frontal gyri (pIFG) are activated when healthy right-handed individuals make phonological word decisions. Here we used online transcranial magnetic stimulation…

  17. Injury risk functions for frontal oblique collisions.

    Science.gov (United States)

    Andricevic, Nino; Junge, Mirko; Krampe, Jonas

    2018-03-09

    The objective of this article was the construction of injury risk functions (IRFs) for front row occupants in oblique frontal crashes and a comparison to IRF of nonoblique frontal crashes from the same data set. Crashes of modern vehicles from GIDAS (German In-Depth Accident Study) were used as the basis for the construction of a logistic injury risk model. Static deformation, measured via displaced voxels on the postcrash vehicles, was used to calculate the energy dissipated in the crash. This measure of accident severity was termed objective equivalent speed (oEES) because it does not depend on the accident reconstruction and thus eliminates reconstruction biases like impact direction and vehicle model year. Imputation from property damage cases was used to describe underrepresented low-severity crashes-a known shortcoming of GIDAS. Binary logistic regression was used to relate the stimuli (oEES) to the binary outcome variable (injured or not injured). IRFs for the oblique frontal impact and nonoblique frontal impact were computed for the Maximum Abbreviated Injury Scale (MAIS) 2+ and 3+ levels for adults (18-64 years). For a given stimulus, the probability of injury for a belted driver was higher in oblique crashes than in nonoblique frontal crashes. For the 25% injury risk at MAIS 2+ level, the corresponding stimulus for oblique crashes was 40 km/h but it was 64 km/h for nonoblique frontal crashes. The risk of obtaining MAIS 2+ injuries is significantly higher in oblique crashes than in nonoblique crashes. In the real world, most MAIS 2+ injuries occur in an oEES range from 30 to 60 km/h.

  18. Reduced frontal and occipital lobe asymmetry on the CT-scans of schizophrenic patients. Its specificity and clinical significance

    International Nuclear Information System (INIS)

    Falkai, P.; Schneider, T.; Greve, B.; Klieser, E.; Bogerts, B.

    1995-01-01

    Frontal and occipital lobe widths were determined in the computed tomographic (CT) scans of 135 schizophrenic patients, 158 neuro psychiatrically healthy and 102 psychiatric control subjects, including patients with affective psychosis, neurosis and schizoaffective psychosis. Most healthy right-handed subjects demonstrate a relative enlargement of the right frontal as well as left occipital lobe compared to the opposite hemisphere. These normal frontal and occipital lobe asymmetries were selectively reduced in schizophrenics (f.: 5%, p < .0005; o.: 3%, p < .05), irrespective of the pathophysiological subgroup. Schizophrenic neuroleptic non-responders revealed a significant reduction of frontal lobe asymmetry (3%, p < .05), while no correlation between BPRS-sub scores and disturbed cerebral laterality could be detected. In sum the present study demonstrates the disturbed cerebral lateralisation in schizophrenic patients supporting the hypothesis of interrupted early brain development in schizophrenia. (author)

  19. The effects of gender and age on forensic personal identification from frontal sinus in a Turkish population.

    Science.gov (United States)

    Tatlisumak, Ertugrul; Asirdizer, Mahmut; Bora, Aydin; Hekimoglu, Yavuz; Etli, Yasin; Gumus, Orhan; Keskin, Siddik

    2017-01-01

    To define the dimensions of the frontal sinus in groups standardized for age and gender and to discuss the reasons and the effects of the variations. Methods: Frontal sinus measurements were obtained from paranasal CTscans of 180 males and 180 females in the Radiology Department of Dursun Odabas Medical Center of Yuzuncu Yil University, Van, which is located in Eastern Turkey, between February and March 2016. The width and height of sinuses were measured on a coronal plane, and the anteroposterior length was measured on an axial plane. Volumes were calculated using the Hospital Information Management Systems and Image Archiving and Management Systemprogram. The Statistical Package of the Social Science version 13 was used for statistical analyses.  Results: We determined differences in the frontal sinus measurements of different age groups in a Turkish adult population. Frontal sinus dimensions were usually higher in females and lower in males after 40-49 years of age than their younger counterparts, but the measurements were lower in females and higher in males in 70≤ years of age group than 60-69 years of age. Left frontal sinus was dominant in young age groups but right frontal sinus was dominant in groups 40-49 years of age or older.  Conclusion: We observed crossing of the measurements between the different age groups, which we could not find clear explanations. The results of such studies may affect forensic identification from frontal sinus measurements.

  20. Convolutional Dictionary Learning: Acceleration and Convergence

    Science.gov (United States)

    Chun, Il Yong; Fessler, Jeffrey A.

    2018-04-01

    Convolutional dictionary learning (CDL or sparsifying CDL) has many applications in image processing and computer vision. There has been growing interest in developing efficient algorithms for CDL, mostly relying on the augmented Lagrangian (AL) method or the variant alternating direction method of multipliers (ADMM). When their parameters are properly tuned, AL methods have shown fast convergence in CDL. However, the parameter tuning process is not trivial due to its data dependence and, in practice, the convergence of AL methods depends on the AL parameters for nonconvex CDL problems. To moderate these problems, this paper proposes a new practically feasible and convergent Block Proximal Gradient method using a Majorizer (BPG-M) for CDL. The BPG-M-based CDL is investigated with different block updating schemes and majorization matrix designs, and further accelerated by incorporating some momentum coefficient formulas and restarting techniques. All of the methods investigated incorporate a boundary artifacts removal (or, more generally, sampling) operator in the learning model. Numerical experiments show that, without needing any parameter tuning process, the proposed BPG-M approach converges more stably to desirable solutions of lower objective values than the existing state-of-the-art ADMM algorithm and its memory-efficient variant do. Compared to the ADMM approaches, the BPG-M method using a multi-block updating scheme is particularly useful in single-threaded CDL algorithm handling large datasets, due to its lower memory requirement and no polynomial computational complexity. Image denoising experiments show that, for relatively strong additive white Gaussian noise, the filters learned by BPG-M-based CDL outperform those trained by the ADMM approach.

  1. Lidar Cloud Detection with Fully Convolutional Networks

    Science.gov (United States)

    Cromwell, E.; Flynn, D.

    2017-12-01

    The vertical distribution of clouds from active remote sensing instrumentation is a widely used data product from global atmospheric measuring sites. The presence of clouds can be expressed as a binary cloud mask and is a primary input for climate modeling efforts and cloud formation studies. Current cloud detection algorithms producing these masks do not accurately identify the cloud boundaries and tend to oversample or over-represent the cloud. This translates as uncertainty for assessing the radiative impact of clouds and tracking changes in cloud climatologies. The Atmospheric Radiation Measurement (ARM) program has over 20 years of micro-pulse lidar (MPL) and High Spectral Resolution Lidar (HSRL) instrument data and companion automated cloud mask product at the mid-latitude Southern Great Plains (SGP) and the polar North Slope of Alaska (NSA) atmospheric observatory. Using this data, we train a fully convolutional network (FCN) with semi-supervised learning to segment lidar imagery into geometric time-height cloud locations for the SGP site and MPL instrument. We then use transfer learning to train a FCN for (1) the MPL instrument at the NSA site and (2) for the HSRL. In our semi-supervised approach, we pre-train the classification layers of the FCN with weakly labeled lidar data. Then, we facilitate end-to-end unsupervised pre-training and transition to fully supervised learning with ground truth labeled data. Our goal is to improve the cloud mask accuracy and precision for the MPL instrument to 95% and 80%, respectively, compared to the current cloud mask algorithms of 89% and 50%. For the transfer learning based FCN for the HSRL instrument, our goal is to achieve a cloud mask accuracy of 90% and a precision of 80%.

  2. The frontal method in hydrodynamics simulations

    Science.gov (United States)

    Walters, R.A.

    1980-01-01

    The frontal solution method has proven to be an effective means of solving the matrix equations resulting from the application of the finite element method to a variety of problems. In this study, several versions of the frontal method were compared in efficiency for several hydrodynamics problems. Three basic modifications were shown to be of value: 1. Elimination of equations with boundary conditions beforehand, 2. Modification of the pivoting procedures to allow dynamic management of the equation size, and 3. Storage of the eliminated equations in a vector. These modifications are sufficiently general to be applied to other classes of problems. ?? 1980.

  3. Frontal lobe atrophy in motor neuron diseases.

    Science.gov (United States)

    Kiernan, J A; Hudson, A J

    1994-08-01

    Neuronal degeneration in the precentral gyrus alone cannot account for the occurrence of spastic paresis in motor neuron diseases. To look for more extensive cortical atrophy we measured MRIs of the upper parts of the frontal and parietal lobes in 11 sporadic cases of classical amyotrophic lateral sclerosis (ALS), eight patients with primary lateral sclerosis (PLS) and an age- and sex-matched group of 49 neurologically normal people. None of the patients had overt dementia or other mental diseases. In PLS there is progressive spastic paresis but in contrast to ALS there is no lower motor neuron degeneration. The surface area of the precentral gyri and the amount of underlying white matter in PLS were consistently approximately 75% of the normal size. By contrast, there was some shrinkage of the precentral gyri in some of the ALS patients but the mean measurements for the group did not differ significantly from the controls. Anterior to the precentral sulci, the cortical surface area in PLS was approximately 85% of that of the controls, with correspondingly reduced white matter. In ALS the cortical surface areas of the anterior frontal lobes did not differ from those of the controls, but the amount of underlying white matter was reduced almost as much in ALS as it was in PLS. The measured changes in the frontal lobes suggest that in PLS there is simultaneous atrophy of the primary, premotor and supplementary motor areas of the cortex, with consequent degeneration of corticospinal and corticoreticular axons descending through the underlying white matter. These changes could account for the progressive upper motor neuron syndrome. In ALS, with no significant frontal cortical atrophy, the shrinkage of the white matter may be due to degeneration of axons projecting to the frontal cortex from elsewhere. Deprivation of afferents could explain the diminution of motor functions of the frontal lobes in ALS and also the changes in word fluency, judgement and attention that

  4. Let's inhibit our excitement: the relationships between Stroop, behavioral disinhibition, and the frontal lobes.

    Science.gov (United States)

    Heflin, Lara H; Laluz, Victor; Jang, Jung; Ketelle, Robin; Miller, Bruce L; Kramer, Joel H

    2011-09-01

    The Stroop (Stroop, 1935) is a frequently used neuropsychological test, with poor performance typically interpreted as indicative of disinhibition and frontal lobe damage. This study tested those interpretations by examining relationships between Stroop performance, behavioral disinhibition, and frontal lobe atrophy. Participants were 112 patients with mild cognitive impairment or dementia, recruited through UCSF's Memory and Aging Center. Participants received comprehensive dementia evaluations including structural MRI, neuropsychological testing, and informant interviews. Freesurfer, a semiautomated parcellation program, was used to analyze 1.5T MRI scans. Behavioral disinhibition was measured using the Neuropsychiatric Inventory (Cummings, 1997; Cummings et al., 1994) Disinhibition Scale. The sample (n = 112) mean age was 65.40 (SD = 8.60) years, education was 16.64 (SD = 2.54) years, and Mini-Mental State Examination (MMSE; Folstein et al., 1975) was 26.63 (SD = 3.32). Hierarchical linear regressions were used for data analysis. Controlling for age, MMSE, and color naming, Stroop performance was not significantly associated with disinhibition (β = 0.01, ΔR² = 0.01, p = .29). Hierarchical regressions controlling for age, MMSE, color naming, intracranial volume, and temporal and parietal lobes, examined whether left or right hemisphere regions predict Stroop performance. Bilaterally, parietal lobe atrophy best predicted poorer Stroop (left: β = 0.0004, ΔR² = 0.02, p = .002; right: β = 0.0004, ΔR² = 0.02, p = .002). Of frontal regions, only dorsolateral prefrontal cortex atrophy predicted poorer Stroop (β = 0.001, ΔR² = 0.01, p = .03); left and right anterior cingulate cortex atrophy predicted better Stroop (left: β = -0.003, ΔR² = 0.01, p = .02; right: β = -0.004, ΔR² = 0.01, p = .02). These findings suggest Stroop performance is a poor measure of behavioral disinhibition and frontal lobe atrophy even among a relatively high-risk population

  5. Retinopathy after low dose irradiation for an intracranial tumor of the frontal lobe

    International Nuclear Information System (INIS)

    Elsaas, T.; Thorud, E.; Jetne, V.; Conradi, I.S.

    1988-01-01

    A 32-year-old man underwent an operation for an oligodendroglioma of the left frontal lobe. Postoperatively he was irradiated to a target dose of 54 Gy. One year later hedeveloped bilateral retinopathy quite similar to diabetic retinopathy. There were no clinical or biochemical signs of diabetes or hematological disease. The calcultated maximum dose to the retina was 11 Gy. This is to our knowledge the lowest retinal dose of ionizing radiation reported to produce retinopathy. (author)

  6. Significant decreases in frontal and temporal [11C]-raclopride binding after THC challenge.

    Science.gov (United States)

    Stokes, Paul R A; Egerton, Alice; Watson, Ben; Reid, Alistair; Breen, Gerome; Lingford-Hughes, Anne; Nutt, David J; Mehta, Mitul A

    2010-10-01

    Delta9-tetrahydrocannabinol (THC) increases prefrontal cortical dopamine release in animals, but this is yet to be examined in humans. In man, striatal dopamine release can be indexed using [11C]-raclopride positron emission tomography (PET), and recent reports suggest that cortical [11C]-raclopride binding may also be sensitive to dopaminergic challenges. Using an existing dataset we examined whether THC alters [11C]-raclopride binding potential (BP(ND)) in cortical regions. Thirteen healthy volunteers underwent two [11C]-raclopride PET scans following either oral 10 mg THC or placebo. Significant areas of decreased cortical [11C]-raclopride BP(ND) were identified using whole brain voxel-wise analysis and quantified using a region of interest (ROI) ratio analysis. Effect of blood flow on binding was estimated using a simplified reference tissue model analysis. Results were compared to [11C]-raclopride test-retest reliability in the ROIs identified using a separate cohort of volunteers. Voxel-wise analysis identified three significant clusters of decreased [11C]-raclopride BP(ND) after THC in the right middle frontal gyrus, left superior frontal gyrus and left superior temporal gyrus. Decreases in [11C]-raclopride BPND following THC were greater than test-retest variability in these ROIs. R1, an estimate of blood flow, significantly decreased in the left superior frontal gyrus in the THC condition but was unchanged in the other ROIs. Decreased frontal binding significantly correlated to catechol-o-methyl transferase (COMT) val108 status. We have demonstrated for the first time significant decreases in bilateral frontopolar cortical and left superior temporal gyrus [11C]-raclopride binding after THC. The interpretation of these findings in relation to prefrontal dopamine release is discussed. Copyright 2010 Elsevier Inc. All rights reserved.

  7. Detecting atrial fibrillation by deep convolutional neural networks.

    Science.gov (United States)

    Xia, Yong; Wulan, Naren; Wang, Kuanquan; Zhang, Henggui

    2018-02-01

    Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of AF increases with age, causing high risks of stroke and increased morbidity and mortality. Efficient and accurate diagnosis of AF based on the ECG is valuable in clinical settings and remains challenging. In this paper, we proposed a novel method with high reliability and accuracy for AF detection via deep learning. The short-term Fourier transform (STFT) and stationary wavelet transform (SWT) were used to analyze ECG segments to obtain two-dimensional (2-D) matrix input suitable for deep convolutional neural networks. Then, two different deep convolutional neural network models corresponding to STFT output and SWT output were developed. Our new method did not require detection of P or R peaks, nor feature designs for classification, in contrast to existing algorithms. Finally, the performances of the two models were evaluated and compared with those of existing algorithms. Our proposed method demonstrated favorable performances on ECG segments as short as 5 s. The deep convolutional neural network using input generated by STFT, presented a sensitivity of 98.34%, specificity of 98.24% and accuracy of 98.29%. For the deep convolutional neural network using input generated by SWT, a sensitivity of 98.79%, specificity of 97.87% and accuracy of 98.63% was achieved. The proposed method using deep convolutional neural networks shows high sensitivity, specificity and accuracy, and, therefore, is a valuable tool for AF detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Video Super-Resolution via Bidirectional Recurrent Convolutional Networks.

    Science.gov (United States)

    Huang, Yan; Wang, Wei; Wang, Liang

    2018-04-01

    Super resolving a low-resolution video, namely video super-resolution (SR), is usually handled by either single-image SR or multi-frame SR. Single-Image SR deals with each video frame independently, and ignores intrinsic temporal dependency of video frames which actually plays a very important role in video SR. Multi-Frame SR generally extracts motion information, e.g., optical flow, to model the temporal dependency, but often shows high computational cost. Considering that recurrent neural networks (RNNs) can model long-term temporal dependency of video sequences well, we propose a fully convolutional RNN named bidirectional recurrent convolutional network for efficient multi-frame SR. Different from vanilla RNNs, 1) the commonly-used full feedforward and recurrent connections are replaced with weight-sharing convolutional connections. So they can greatly reduce the large number of network parameters and well model the temporal dependency in a finer level, i.e., patch-based rather than frame-based, and 2) connections from input layers at previous timesteps to the current hidden layer are added by 3D feedforward convolutions, which aim to capture discriminate spatio-temporal patterns for short-term fast-varying motions in local adjacent frames. Due to the cheap convolutional operations, our model has a low computational complexity and runs orders of magnitude faster than other multi-frame SR methods. With the powerful temporal dependency modeling, our model can super resolve videos with complex motions and achieve well performance.

  9. Interrelations between motivational stance, cortical excitability, and the frontal electroencephalogram asymmetry of emotion: A Transcranial magnetic stimulation study

    NARCIS (Netherlands)

    Schutter, D.J.L.G.; Weijer, A.D. de; Meuwese, J.D.I.; Morgan, B.E.; Honk, E.J. van

    2008-01-01

    everal electrophysiological studies have provided evidence for the frontal asymmetry of emotion. In this model the motivation to approach is lateralized to the left, whereas the motivation to avoidance is lateralized to the right hemisphere. The aim of the present experiment was to seek evidence for

  10. Invariant moments based convolutional neural networks for image analysis

    Directory of Open Access Journals (Sweden)

    Vijayalakshmi G.V. Mahesh

    2017-01-01

    Full Text Available The paper proposes a method using convolutional neural network to effectively evaluate the discrimination between face and non face patterns, gender classification using facial images and facial expression recognition. The novelty of the method lies in the utilization of the initial trainable convolution kernels coefficients derived from the zernike moments by varying the moment order. The performance of the proposed method was compared with the convolutional neural network architecture that used random kernels as initial training parameters. The multilevel configuration of zernike moments was significant in extracting the shape information suitable for hierarchical feature learning to carry out image analysis and classification. Furthermore the results showed an outstanding performance of zernike moment based kernels in terms of the computation time and classification accuracy.

  11. Single image super-resolution based on convolutional neural networks

    Science.gov (United States)

    Zou, Lamei; Luo, Ming; Yang, Weidong; Li, Peng; Jin, Liujia

    2018-03-01

    We present a deep learning method for single image super-resolution (SISR). The proposed approach learns end-to-end mapping between low-resolution (LR) images and high-resolution (HR) images. The mapping is represented as a deep convolutional neural network which inputs the LR image and outputs the HR image. Our network uses 5 convolution layers, which kernels size include 5×5, 3×3 and 1×1. In our proposed network, we use residual-learning and combine different sizes of convolution kernels at the same layer. The experiment results show that our proposed method performs better than the existing methods in reconstructing quality index and human visual effects on benchmarked images.

  12. Hemichorea and dystonia due to frontal lobe meningioma

    Directory of Open Access Journals (Sweden)

    Abdul Qayyum Rana

    2014-01-01

    Full Text Available Tumors originating from the meninges, also known as meningiomas, have rarely been known to cause parkinsonian symptoms and other movement disorders. Although some cases of AV malformations causing movement disorders have been described in the literature, not much has been reported about meningiomas in this regard. The aim of this case report is to further highlight the importance of brain imaging in patients with movement disorders for even a benign tumor; and also emphasize the need for a careful movement disorder examination because more than one phenomenology of movement disorders may result from the mechanical pressure caused by a tumor. We present a case report of a patient with a heavily calcified right frontal lobe meningioma. Our patient had irregular, involuntary, brief, fleeting and unpredictable movements of her left upper and lower extremities, consistent with chorea. The patient also had abnormal dystonic posturing of her left arm while walking. This case report highlights the importance of brain imaging as well as careful neurological examinations of patients with benign meningiomas. Moreover, it illustrates the remarkable specificity yet clinical diversity of meningiomas in presentation through movement disorders.

  13. Spacings and pair correlations for finite Bernoulli convolutions

    International Nuclear Information System (INIS)

    Benjamini, Itai; Solomyak, Boris

    2009-01-01

    We consider finite Bernoulli convolutions with a parameter 1/2 N . These sequences are uniformly distributed with respect to the infinite Bernoulli convolution measure ν λ , as N → ∞. Numerical evidence suggests that for a generic λ, the distribution of spacings between appropriately rescaled points is Poissonian. We obtain some partial results in this direction; for instance, we show that, on average, the pair correlations do not exhibit attraction or repulsion in the limit. On the other hand, for certain algebraic λ the behaviour is totally different

  14. A New Reverberator Based on Variable Sparsity Convolution

    DEFF Research Database (Denmark)

    Holm-Rasmussen, Bo; Lehtonen, Heidi-Maria; Välimäki, Vesa

    2013-01-01

    FIR filter coefficients are selected from a velvet noise sequence, which consists of ones, minus ones, and zeros only. In this application, it is sufficient perceptually to use very sparse velvet noise sequences having only about 0.1 to 0.2% non-zero elements, with increasing sparsity along...... the impulse response. The algorithm yields a parametric approximation of the late part of the impulse response, which is more than 100 times more efficient computationally than the direct convolution. The computational load of the proposed algorithm is comparable to that of FFT-based partitioned convolution...

  15. Convolutional cylinder-type block-circulant cycle codes

    Directory of Open Access Journals (Sweden)

    Mohammad Gholami

    2013-06-01

    Full Text Available In this paper, we consider a class of column-weight two quasi-cyclic low-density paritycheck codes in which the girth can be large enough, as an arbitrary multiple of 8. Then we devote a convolutional form to these codes, such that their generator matrix can be obtained by elementary row and column operations on the parity-check matrix. Finally, we show that the free distance of the convolutional codes is equal to the minimum distance of their block counterparts.

  16. Weed Growth Stage Estimator Using Deep Convolutional Neural Networks

    DEFF Research Database (Denmark)

    Teimouri, Nima; Dyrmann, Mads; Nielsen, Per Rydahl

    2018-01-01

    conditions with regards to soil types, resolution and light settings. Then, 9649 of these images were used for training the computer, which automatically divided the weeds into nine growth classes. The performance of this proposed convolutional neural network approach was evaluated on a further set of 2516...... in estimating the number of leaves and 96% accuracy when accepting a deviation of two leaves. These results show that this new method of using deep convolutional neural networks has a relatively high ability to estimate early growth stages across a wide variety of weed species....

  17. Deep Convolutional Neural Networks: Structure, Feature Extraction and Training

    Directory of Open Access Journals (Sweden)

    Namatēvs Ivars

    2017-12-01

    Full Text Available Deep convolutional neural networks (CNNs are aimed at processing data that have a known network like topology. They are widely used to recognise objects in images and diagnose patterns in time series data as well as in sensor data classification. The aim of the paper is to present theoretical and practical aspects of deep CNNs in terms of convolution operation, typical layers and basic methods to be used for training and learning. Some practical applications are included for signal and image classification. Finally, the present paper describes the proposed block structure of CNN for classifying crucial features from 3D sensor data.

  18. Very deep recurrent convolutional neural network for object recognition

    Science.gov (United States)

    Brahimi, Sourour; Ben Aoun, Najib; Ben Amar, Chokri

    2017-03-01

    In recent years, Computer vision has become a very active field. This field includes methods for processing, analyzing, and understanding images. The most challenging problems in computer vision are image classification and object recognition. This paper presents a new approach for object recognition task. This approach exploits the success of the Very Deep Convolutional Neural Network for object recognition. In fact, it improves the convolutional layers by adding recurrent connections. This proposed approach was evaluated on two object recognition benchmarks: Pascal VOC 2007 and CIFAR-10. The experimental results prove the efficiency of our method in comparison with the state of the art methods.

  19. Spectral interpolation - Zero fill or convolution. [image processing

    Science.gov (United States)

    Forman, M. L.

    1977-01-01

    Zero fill, or augmentation by zeros, is a method used in conjunction with fast Fourier transforms to obtain spectral spacing at intervals closer than obtainable from the original input data set. In the present paper, an interpolation technique (interpolation by repetitive convolution) is proposed which yields values accurate enough for plotting purposes and which lie within the limits of calibration accuracies. The technique is shown to operate faster than zero fill, since fewer operations are required. The major advantages of interpolation by repetitive convolution are that efficient use of memory is possible (thus avoiding the difficulties encountered in decimation in time FFTs) and that is is easy to implement.

  20. [Trauma induced left maxillary sinus dislocation of eyeball--a case report].

    Science.gov (United States)

    Chen, Yu; Liu, Cuiping; Cui, Liping

    2013-01-01

    Patient male, 27 year old. Left facial and head trauma for 6 hours, due to motor vehicle accident. Patient state of mind was clear at arrival to hospital. Body temperature: 36C; Pulse: 80 Time/Minute; Breath: 20 Time/Minute; Blood pressure: 120/80 mm Hg. An irregular, horizontal laceration at arch of left eyebrow, approximately 8-10 cm. A laceration on left wing of nose skin, approximately 1 cm. A laceration also under lower eyelid skin of right eye, approximately 2 cm. Left blepharedema and enophthalmos. Orbital and nasal sinuses CT indications:contusion and laceration of the left frontal lobe of brain; fracture of the left orbital frontal, ethmoid, sphenoid bone, left nasal, maxillary sinus and zygoma with soft tissue contusion and laceration; the left eyeball and optic nerve sunk into the maxillary sinus (See figure 1). (1) Multiple orbital fractures; (2) Left maxillary sinus dislocation of eyeball; (3) The left frontal lobe contusion and laceration of brain.

  1. Preservation of Frontal Sinus Anatomy and Outflow Tract Following Frontal Trauma with Dural Defect

    Directory of Open Access Journals (Sweden)

    James Wei Ming Kwek, MBBS, MRCS

    2015-02-01

    Full Text Available Summary: Our case report describes a young male mechanic who was hit in his face by a spring while repairing a car, resulting in traumatic injury to the frontal sinus, with fractures of both the anterior and the posterior tables with dural defect and cerebrospinal fluid leak. Current guidelines recommend that comminuted and/or displaced fractures of the posterior table of the frontal sinus with dural defects should be either cranialized or obliterated. In this patient, instead of cranializing or obliterating the frontal sinus, we managed to preserve the frontal sinus anatomy and its outflow tract using a combined open bicoronal and nasoendoscopic approach. This avoids the long-term complications associated with cranialization or obliteration including mucocele formation and frontocutaneous fistula.

  2. Medial frontal cortex and response conflict: Evidence from human intracranial EEG and medial frontal cortex lesion

    NARCIS (Netherlands)

    Cohen, M.X.; Ridderinkhof, K.R.; Haupt, S.; Elger, C.E.; Fell, J.

    2008-01-01

    The medial frontal cortex (MFC) has been implicated in the monitoring and selection of actions in the face of competing alternatives, but much remains unknown about its functional properties, including electrophysiological oscillations, during response conflict tasks. Here, we recorded intracranial

  3. Left-handedness and language lateralization in children.

    Science.gov (United States)

    Szaflarski, Jerzy P; Rajagopal, Akila; Altaye, Mekibib; Byars, Anna W; Jacola, Lisa; Schmithorst, Vincent J; Schapiro, Mark B; Plante, Elena; Holland, Scott K

    2012-01-18

    This fMRI study investigated the development of language lateralization in left- and righthanded children between 5 and 18 years of age. Twenty-seven left-handed children (17 boys, 10 girls) and 54 age- and gender-matched right-handed children were included. We used functional MRI at 3T and a verb generation task to measure hemispheric language dominance based on either frontal or temporo-parietal regions of interest (ROIs) defined for the entire group and applied on an individual basis. Based on the frontal ROI, in the left-handed group, 23 participants (85%) demonstrated left-hemispheric language lateralization, 3 (11%) demonstrated symmetric activation, and 1 (4%) demonstrated right-hemispheric lateralization. In contrast, 50 (93%) of the right-handed children showed left-hemispheric lateralization and 3 (6%) demonstrated a symmetric activation pattern, while one (2%) demonstrated a right-hemispheric lateralization. The corresponding values for the temporo-parietal ROI for the left-handed children were 18 (67%) left-dominant, 6 (22%) symmetric, 3 (11%) right-dominant and for the right-handed children 49 (91%), 4 (7%), 1 (2%), respectively. Left-hemispheric language lateralization increased with age in both groups but somewhat different lateralization trajectories were observed in girls when compared to boys. The incidence of atypical language lateralization in left-handed children in this study was similar to that reported in adults. We also found similar rates of increase in left-hemispheric language lateralization with age between groups (i.e., independent of handedness) indicating the presence of similar mechanisms for language lateralization in left- and right-handed children. Copyright © 2011 Elsevier B.V. All rights reserved.

  4. Intraoperative subcortical mapping of a language-associated deep frontal tract connecting the superior frontal gyrus to Broca's area in the dominant hemisphere of patients with glioma.

    Science.gov (United States)

    Fujii, Masazumi; Maesawa, Satoshi; Motomura, Kazuya; Futamura, Miyako; Hayashi, Yuichiro; Koba, Itsuko; Wakabayashi, Toshihiko

    2015-06-01

    The deep frontal pathway connecting the superior frontal gyrus to Broca's area, recently named the frontal aslant tract (FAT), is assumed to be associated with language functions, especially speech initiation and spontaneity. Injury to the deep frontal lobe is known to cause aphasia that mimics the aphasia caused by damage to the supplementary motor area. Although fiber dissection and tractography have revealed the existence of the tract, little is known about its function. The aim of this study was to determine the function of the FAT via electrical stimulation in patients with glioma who underwent awake surgery. The authors analyzed the data from subcortical mapping with electrical stimulation in 5 consecutive cases (3 males and 2 females, age range 40-54 years) with gliomas in the left frontal lobe. Diffusion tensor imaging (DTI) and tractography of the FAT were performed in all cases. A navigation system and intraoperative MRI were used in all cases. During the awake phase of the surgery, cortical mapping was performed to find the precentral gyrus and Broca's area, followed by tumor resection. After the cortical layer was removed, subcortical mapping was performed to assess language-associated fibers in the white matter. In all 5 cases, positive responses were obtained at the stimulation sites in the subcortical area adjacent to the FAT, which was visualized by the navigation system. Speech arrest was observed in 4 cases, and remarkably slow speech and conversation was observed in 1 case. The location of these sites was also determined on intraoperative MR images and estimated on preoperative MR images with DTI tractography, confirming the spatial relationships among the stimulation sites and white matter tracts. Tumor removal was successfully performed without damage to this tract, and language function did not deteriorate in any of the cases postoperatively. The authors identified the left FAT and confirmed that it was associated with language functions. This

  5. Efficient forward propagation of time-sequences in convolutional neural networks using Deep Shifting

    NARCIS (Netherlands)

    K.L. Groenland (Koen); S.M. Bohte (Sander)

    2016-01-01

    textabstractWhen a Convolutional Neural Network is used for on-the-fly evaluation of continuously updating time-sequences, many redundant convolution operations are performed. We propose the method of Deep Shifting, which remembers previously calculated results of convolution operations in order

  6. Automated mammographic breast density estimation using a fully convolutional network.

    Science.gov (United States)

    Lee, Juhun; Nishikawa, Robert M

    2018-03-01

    The purpose of this study was to develop a fully automated algorithm for mammographic breast density estimation using deep learning. Our algorithm used a fully convolutional network, which is a deep learning framework for image segmentation, to segment both the breast and the dense fibroglandular areas on mammographic images. Using the segmented breast and dense areas, our algorithm computed the breast percent density (PD), which is the faction of dense area in a breast. Our dataset included full-field digital screening mammograms of 604 women, which included 1208 mediolateral oblique (MLO) and 1208 craniocaudal (CC) views. We allocated 455, 58, and 91 of 604 women and their exams into training, testing, and validation datasets, respectively. We established ground truth for the breast and the dense fibroglandular areas via manual segmentation and segmentation using a simple thresholding based on BI-RADS density assessments by radiologists, respectively. Using the mammograms and ground truth, we fine-tuned a pretrained deep learning network to train the network to segment both the breast and the fibroglandular areas. Using the validation dataset, we evaluated the performance of the proposed algorithm against radiologists' BI-RADS density assessments. Specifically, we conducted a correlation analysis between a BI-RADS density assessment of a given breast and its corresponding PD estimate by the proposed algorithm. In addition, we evaluated our algorithm in terms of its ability to classify the BI-RADS density using PD estimates, and its ability to provide consistent PD estimates for the left and the right breast and the MLO and CC views of the same women. To show the effectiveness of our algorithm, we compared the performance of our algorithm against a state of the art algorithm, laboratory for individualized breast radiodensity assessment (LIBRA). The PD estimated by our algorithm correlated well with BI-RADS density ratings by radiologists. Pearson's rho values of

  7. Minimally invasive approach for lesions involving the frontal sinus

    African Journals Online (AJOL)

    risk of future meningitis. The frontal ... Traditional open surgery for frontal sinus pathology and cerebrospinal fluid (CSF) leaks is complex and involves a ... sinus. The wound is closed in two layers ... He had noted displacement of his right eye.

  8. Frontal lobe epilepsy and EEG: Neurophysiological approach

    OpenAIRE

    García López, Beatriz

    2015-01-01

    La epilepsia del lóbulo frontal es la segunda más frecuente en la mayoría de las series publicadas, después de la epilepsia temporal. Sus características clínicas y electroencefalográficas son muy variadas, lo que hace de su diagnóstico y tratamiento un reto en la práctica clínica. Las crisis frontales suelen aparecen en "clusters", con frecuencia generalizan y el aspecto electroencefalográfico de la actividad intercrítica y crítica suele ser difícil de interpretar por la gran difusión que su...

  9. Discrete singular convolution for the generalized variable-coefficient ...

    African Journals Online (AJOL)

    Numerical solutions of the generalized variable-coefficient Korteweg-de Vries equation are obtained using a discrete singular convolution and a fourth order singly diagonally implicit Runge-Kutta method for space and time discretisation, respectively. The theoretical convergence of the proposed method is rigorously ...

  10. Down image recognition based on deep convolutional neural network

    Directory of Open Access Journals (Sweden)

    Wenzhu Yang

    2018-06-01

    Full Text Available Since of the scale and the various shapes of down in the image, it is difficult for traditional image recognition method to correctly recognize the type of down image and get the required recognition accuracy, even for the Traditional Convolutional Neural Network (TCNN. To deal with the above problems, a Deep Convolutional Neural Network (DCNN for down image classification is constructed, and a new weight initialization method is proposed. Firstly, the salient regions of a down image were cut from the image using the visual saliency model. Then, these salient regions of the image were used to train a sparse autoencoder and get a collection of convolutional filters, which accord with the statistical characteristics of dataset. At last, a DCNN with Inception module and its variants was constructed. To improve the recognition accuracy, the depth of the network is deepened. The experiment results indicate that the constructed DCNN increases the recognition accuracy by 2.7% compared to TCNN, when recognizing the down in the images. The convergence rate of the proposed DCNN with the new weight initialization method is improved by 25.5% compared to TCNN. Keywords: Deep convolutional neural network, Weight initialization, Sparse autoencoder, Visual saliency model, Image recognition

  11. Face recognition: a convolutional neural-network approach.

    Science.gov (United States)

    Lawrence, S; Giles, C L; Tsoi, A C; Back, A D

    1997-01-01

    We present a hybrid neural-network for human face recognition which compares favourably with other methods. The system combines local image sampling, a self-organizing map (SOM) neural network, and a convolutional neural network. The SOM provides a quantization of the image samples into a topological space where inputs that are nearby in the original space are also nearby in the output space, thereby providing dimensionality reduction and invariance to minor changes in the image sample, and the convolutional neural network provides partial invariance to translation, rotation, scale, and deformation. The convolutional network extracts successively larger features in a hierarchical set of layers. We present results using the Karhunen-Loeve transform in place of the SOM, and a multilayer perceptron (MLP) in place of the convolutional network for comparison. We use a database of 400 images of 40 individuals which contains quite a high degree of variability in expression, pose, and facial details. We analyze the computational complexity and discuss how new classes could be added to the trained recognizer.

  12. Training Convolutional Neural Networks for Translational Invariance on SAR ATR

    DEFF Research Database (Denmark)

    Malmgren-Hansen, David; Engholm, Rasmus; Østergaard Pedersen, Morten

    2016-01-01

    In this paper we present a comparison of the robustness of Convolutional Neural Networks (CNN) to other classifiers in the presence of uncertainty of the objects localization in SAR image. We present a framework for simulating simple SAR images, translating the object of interest systematically...

  13. An Interactive Graphics Program for Assistance in Learning Convolution.

    Science.gov (United States)

    Frederick, Dean K.; Waag, Gary L.

    1980-01-01

    A program has been written for the interactive computer graphics facility at Rensselaer Polytechnic Institute that is designed to assist the user in learning the mathematical technique of convolving two functions. Because convolution can be represented graphically by a sequence of steps involving folding, shifting, multiplying, and integration, it…

  14. Diffraction and Dirchlet problem for parameter-elliptic convolution ...

    African Journals Online (AJOL)

    In this paper we evaluate the difference between the inverse operators of a Dirichlet problem and of a diffraction problem for parameter-elliptic convolution operators with constant symbols. We prove that the inverse operator of a Dirichlet problem can be obtained as a limit case of such a diffraction problem. Quaestiones ...

  15. Review of the convolution algorithm for evaluating service integrated systems

    DEFF Research Database (Denmark)

    Iversen, Villy Bæk

    1997-01-01

    In this paper we give a review of the applicability of the convolution algorithm. By this we are able to evaluate communication networks end--to--end with e.g. BPP multi-ratetraffic models insensitive to the holding time distribution. Rearrangement, minimum allocation, and maximum allocation...

  16. A convolutional neural network to filter artifacts in spectroscopic MRI.

    Science.gov (United States)

    Gurbani, Saumya S; Schreibmann, Eduard; Maudsley, Andrew A; Cordova, James Scott; Soher, Brian J; Poptani, Harish; Verma, Gaurav; Barker, Peter B; Shim, Hyunsuk; Cooper, Lee A D

    2018-03-09

    Proton MRSI is a noninvasive modality capable of generating volumetric maps of in vivo tissue metabolism without the need for ionizing radiation or injected contrast agent. Magnetic resonance spectroscopic imaging has been shown to be a viable imaging modality for studying several neuropathologies. However, a key hurdle in the routine clinical adoption of MRSI is the presence of spectral artifacts that can arise from a number of sources, possibly leading to false information. A deep learning model was developed that was capable of identifying and filtering out poor quality spectra. The core of the model used a tiled convolutional neural network that analyzed frequency-domain spectra to detect artifacts. When compared with a panel of MRS experts, our convolutional neural network achieved high sensitivity and specificity with an area under the curve of 0.95. A visualization scheme was implemented to better understand how the convolutional neural network made its judgement on single-voxel or multivoxel MRSI, and the convolutional neural network was embedded into a pipeline capable of producing whole-brain spectroscopic MRI volumes in real time. The fully automated method for assessment of spectral quality provides a valuable tool to support clinical MRSI or spectroscopic MRI studies for use in fields such as adaptive radiation therapy planning. © 2018 International Society for Magnetic Resonance in Medicine.

  17. Deep convolutional neural networks for detection of rail surface defects

    NARCIS (Netherlands)

    Faghih Roohi, S.; Hajizadeh, S.; Nunez Vicencio, Alfredo; Babuska, R.; De Schutter, B.H.K.; Estevez, Pablo A.; Angelov, Plamen P.; Del Moral Hernandez, Emilio

    2016-01-01

    In this paper, we propose a deep convolutional neural network solution to the analysis of image data for the detection of rail surface defects. The images are obtained from many hours of automated video recordings. This huge amount of data makes it impossible to manually inspect the images and

  18. Symbol Stream Combining in a Convolutionally Coded System

    Science.gov (United States)

    Mceliece, R. J.; Pollara, F.; Swanson, L.

    1985-01-01

    Symbol stream combining has been proposed as a method for arraying signals received at different antennas. If convolutional coding and Viterbi decoding are used, it is shown that a Viterbi decoder based on the proposed weighted sum of symbol streams yields maximum likelihood decisions.

  19. Two-level convolution formula for nuclear structure function

    Science.gov (United States)

    Ma, Boqiang

    1990-05-01

    A two-level convolution formula for the nuclear structure function is derived in considering the nucleus as a composite system of baryon-mesons which are also composite systems of quark-gluons again. The results show that the European Muon Colaboration effect can not be explained by the nuclear effects as nucleon Fermi motion and nuclear binding contributions.

  20. Two-level convolution formula for nuclear structure function

    International Nuclear Information System (INIS)

    Ma Boqiang

    1990-01-01

    A two-level convolution formula for the nuclear structure function is derived in considering the nucleus as a composite system of baryon-mesons which are also composite systems of quark-gluons again. The results show that the European Muon Colaboration effect can not be explained by the nuclear effects as nucleon Fermi motion and nuclear binding contributions

  1. Plant species classification using deep convolutional neural network

    DEFF Research Database (Denmark)

    Dyrmann, Mads; Karstoft, Henrik; Midtiby, Henrik Skov

    2016-01-01

    Information on which weed species are present within agricultural fields is important for site specific weed management. This paper presents a method that is capable of recognising plant species in colour images by using a convolutional neural network. The network is built from scratch trained an...

  2. Confabulation and memory impairments following frontal lobe lesions

    OpenAIRE

    Turner, Martha

    2005-01-01

    Neuroimaging studies have provided considerable evidence for frontal lobe involvement in memory processing. Memory impairments arc also frequently reported in patients with frontal lobe lesions. However detailed anatomical localisation is rare, making integration of lesion and imaging findings difficult. An investigation of the functional and anatomical contributions of the frontal lobes to memory was conducted in 42 patients with frontal lobe lesions, examining memory processes identified in...

  3. Intraparenchymal schwannoma of the frontal lobe.

    Directory of Open Access Journals (Sweden)

    Deogaonkar M

    1994-10-01

    Full Text Available A 45 year old woman with bifrontal headaches and progressive diminution in vision over 6 months was found to have bilateral papilloedema. CT scan showed large right frontal lesion with surrounding oedema. Right basal frontotemporal craniotomy was performed to excise the multinodular, intraparenchymatous tumor. Hispathology confirmed the diagnosis of schwannoma. Post-operative course was uneventful with disappearance of pre-operative signs and symptoms.

  4. Study of asymmetry in motor areas related to handedness using the fMRI BOLD response Gaussian convolution model

    International Nuclear Information System (INIS)

    Gao Qing; Chen Huafu; Gong Qiyong

    2009-01-01

    Brain asymmetry is a phenomenon well known for handedness, and has been studied in the motor cortex. However, few studies have quantitatively assessed the asymmetrical cortical activities for handedness in motor areas. In the present study, we systematically and quantitatively investigated asymmetry in the left and right primary motor cortices during sequential finger movements using the Gaussian convolution model approach based on the functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) response. Six right-handed and six left-handed subjects were recruited to perform three types of hand movement tasks. The results for the expected value of the Gaussian convolution model showed that it took the dominant hand a longer average interval of response delay regardless of the handedness and bi- or uni-manual performance. The results for the standard deviation of the Gaussian model suggested that in the mass neurons, these intervals of the dominant hand were much more variable than those of the non-dominant hand. When comparing bi-manual movement conditions with uni-manual movement conditions in the primary motor cortex (PMC), both the expected value and standard deviation in the Gaussian function were significantly smaller (p < 0.05) in the bi-manual conditions, showing that the movement of the non-dominant hand influenced that of the dominant hand.

  5. Study of asymmetry in motor areas related to handedness using the fMRI BOLD response Gaussian convolution model

    Energy Technology Data Exchange (ETDEWEB)

    Gao Qing [School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054 (China); School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu 610054 (China); Chen Huafu [School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054 (China); School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu 610054 (China)], E-mail: Chenhf@uestc.edu.cn; Gong Qiyong [Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041 (China)

    2009-10-30

    Brain asymmetry is a phenomenon well known for handedness, and has been studied in the motor cortex. However, few studies have quantitatively assessed the asymmetrical cortical activities for handedness in motor areas. In the present study, we systematically and quantitatively investigated asymmetry in the left and right primary motor cortices during sequential finger movements using the Gaussian convolution model approach based on the functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) response. Six right-handed and six left-handed subjects were recruited to perform three types of hand movement tasks. The results for the expected value of the Gaussian convolution model showed that it took the dominant hand a longer average interval of response delay regardless of the handedness and bi- or uni-manual performance. The results for the standard deviation of the Gaussian model suggested that in the mass neurons, these intervals of the dominant hand were much more variable than those of the non-dominant hand. When comparing bi-manual movement conditions with uni-manual movement conditions in the primary motor cortex (PMC), both the expected value and standard deviation in the Gaussian function were significantly smaller (p < 0.05) in the bi-manual conditions, showing that the movement of the non-dominant hand influenced that of the dominant hand.

  6. Inferior frontal gyrus activation predicts individual differences in perceptual learning of cochlear-implant simulations.

    Science.gov (United States)

    Eisner, Frank; McGettigan, Carolyn; Faulkner, Andrew; Rosen, Stuart; Scott, Sophie K

    2010-05-26

    This study investigated the neural plasticity associated with perceptual learning of a cochlear implant (CI) simulation. Normal-hearing listeners were trained with vocoded and spectrally shifted speech simulating a CI while cortical responses were measured with functional magnetic resonance imaging (fMRI). A condition in which the vocoded speech was spectrally inverted provided a control for learnability and adaptation. Behavioral measures showed considerable individual variability both in the ability to learn to understand the degraded speech, and in phonological working memory capacity. Neurally, left-lateralized regions in superior temporal sulcus and inferior frontal gyrus (IFG) were sensitive to the learnability of the simulations, but only the activity in prefrontal cortex correlated with interindividual variation in intelligibility scores and phonological working memory. A region in left angular gyrus (AG) showed an activation pattern that reflected learning over the course of the experiment, and covariation of activity in AG and IFG was modulated by the learnability of the stimuli. These results suggest that variation in listeners' ability to adjust to vocoded and spectrally shifted speech is partly reflected in differences in the recruitment of higher-level language processes in prefrontal cortex, and that this variability may further depend on functional links between the left inferior frontal gyrus and angular gyrus. Differences in the engagement of left inferior prefrontal cortex, and its covariation with posterior parietal areas, may thus underlie some of the variation in speech perception skills that have been observed in clinical populations of CI users.

  7. Frontal lobe function in temporal lobe epilepsy

    Science.gov (United States)

    Stretton, J.; Thompson, P.J.

    2012-01-01

    Summary Temporal lobe epilepsy (TLE) is typically associated with long-term memory dysfunction. The frontal lobes support high-level cognition comprising executive skills and working memory that is vital for daily life functioning. Deficits in these functions have been increasingly reported in TLE. Evidence from both the neuropsychological and neuroimaging literature suggests both executive function and working memory are compromised in the presence of TLE. In relation to executive impairment, particular focus has been paid to set shifting as measured by the Wisconsin Card Sorting Task. Other discrete executive functions such as decision-making and theory of mind also appear vulnerable but have received little attention. With regard to working memory, the medial temporal lobe structures appear have a more critical role, but with emerging evidence of hippocampal dependent and independent processes. The relative role of underlying pathology and seizure spread is likely to have considerable bearing upon the cognitive phenotype and trajectory in TLE. The identification of the nature of frontal lobe dysfunction in TLE thus has important clinical implications for prognosis and surgical management. Longitudinal neuropsychological and neuroimaging studies assessing frontal lobe function in TLE patients pre- and postoperatively will improve our understanding further. PMID:22100147

  8. Role of Frontal Alpha Oscillations in Creativity

    Science.gov (United States)

    Lustenberger, Caroline; Boyle, Michael R.; Foulser, A. Alban; Mellin, Juliann M.; Fröhlich, Flavio

    2015-01-01

    Creativity, the ability to produce innovative ideas, is a key higher-order cognitive function that is poorly understood. At the level of macroscopic cortical network dynamics, recent EEG data suggests that cortical oscillations in the alpha frequency band (8 – 12 Hz) are correlated with creative thinking. However, whether alpha oscillations play a fundamental role in creativity has remained unknown. Here we show that creativity is increased by enhancing alpha power using 10 Hz transcranial alternating current stimulation (10Hz-tACS) of the frontal cortex. In a study of 20 healthy participants with a randomized, balanced cross-over design, we found a significant improvement of 7.4% in the Creativity Index measured by the Torrance Test of Creative Thinking, a comprehensive and most frequently used assay of creative potential and strengths. In a second similar study with 20 subjects, 40Hz-tACS was used in instead of 10Hz-tACS to rule out a general “electrical stimulation” effect. No significant change in the Creativity Index was found for such frontal gamma stimulation. Our results suggest that alpha activity in frontal brain areas is selectively involved in creativity; this enhancement represents the first demonstration of specific neuronal dynamics that drive creativity and can be modulated by non-invasive brain stimulation. Our findings agree with the model that alpha recruitment increases with internal processing demands and is involved in inhibitory top-down control, which is an important requirement for creative ideation. PMID:25913062

  9. The frontal-anatomic specificity of design fluency repetitions and their diagnostic relevance for behavioral variant frontotemporal dementia.

    Science.gov (United States)

    Possin, Katherine L; Chester, Serana K; Laluz, Victor; Bostrom, Alan; Rosen, Howard J; Miller, Bruce L; Kramer, Joel H

    2012-09-01

    On tests of design fluency, an examinee draws as many different designs as possible in a specified time limit while avoiding repetition. The neuroanatomical substrates and diagnostic group differences of design fluency repetition errors and total correct scores were examined in 110 individuals diagnosed with dementia, 53 with mild cognitive impairment (MCI), and 37 neurologically healthy controls. The errors correlated significantly with volumes in the right and left orbitofrontal cortex (OFC), the right and left superior frontal gyrus, the right inferior frontal gyrus, and the right striatum, but did not correlate with volumes in any parietal or temporal lobe regions. Regression analyses indicated that the lateral OFC may be particularly crucial for preventing these errors, even after excluding patients with behavioral variant frontotemporal dementia (bvFTD) from the analysis. Total correct correlated more diffusely with volumes in the right and left frontal and parietal cortex, the right temporal cortex, and the right striatum and thalamus. Patients diagnosed with bvFTD made significantly more repetition errors than patients diagnosed with MCI, Alzheimer's disease, semantic dementia, progressive supranuclear palsy, or corticobasal syndrome. In contrast, total correct design scores did not differentiate the dementia patients. These results highlight the frontal-anatomic specificity of design fluency repetitions. In addition, the results indicate that the propensity to make these errors supports the diagnosis of bvFTD. (JINS, 2012, 18, 1-11).

  10. Frontal brain activation in young children during picture book reading with their mothers.

    Science.gov (United States)

    Ohgi, S; Loo, K K; Mizuike, C

    2010-02-01

    This study was to measure changes in frontal brain activation in young children during picture book reading with their mothers. The cross-sectional sample consisted of 15 young Japanese children (eight girls and seven boys, mean age 23.1 +/- 3.4). Two experimental tasks were presented as follows: Task 1 (picture book reading with their mothers); Task 2 (viewing of book-on-video). Duration of task stimulus was 180-sec and the 60-sec interval was filled. Brain activation was measured using an optical topography system. Significant increases in oxy-Hb were observed in both right and left frontal areas in response to Task 1 compared with Task 2. There were significant correlations between child's brain activity and mothers' and children's verbal-nonverbal behaviours. There was greater frontal lobe activation in children when they were engaged in a picture book reading task with their mothers, as opposed to passive viewing of a videotape in which the story was read to them. Social and verbal engagement of the mother in reading picture books with her young child may mediate frontal brain activity in the child.

  11. Virtual endoscopy and 3D volume rendering in the management of frontal sinus fractures.

    Science.gov (United States)

    Belina, Stanko; Cuk, Viseslav; Klapan, Ivica

    2009-12-01

    Frontal sinus fractures (FSF) are commonly caused by traffic accidents, assaults, industrial accidents and gunshot wounds. Classical roentgenography has high proportion of false negative findings in cases of FSF and is not particularly useful in examining the severity of damage to the frontal sinus posterior table and the nasofrontal duct region. High resolution computed tomography was inavoidable during the management of such patients but it may produce large quantity of 2D images. Postprocessing of datasets acquired by high resolution computer tomography from patients with severe head trauma may offer a valuable additional help in diagnostics and surgery planning. We performed virtual endoscopy (VE) and 3D volume rendering (3DVR) on high resolution CT data acquired from a 54-year-old man with with both anterior and posterior frontal sinus wall fracture in order to demonstrate advantages and disadvantages of these methods. Data acquisition was done by Siemens Somatom Emotion scanner and postprocessing was performed with Syngo 2006G software. VE and 3DVR were performed in a man who suffered blunt trauma to his forehead and nose in an traffic accident. Left frontal sinus anterior wall fracture without dislocation and fracture of tabula interna with dislocation were found. 3D position and orientation of fracture lines were shown in by 3D rendering software. We concluded that VE and 3DVR can clearly display the anatomic structure of the paranasal sinuses and nasopharyngeal cavity, revealing damage to the sinus wall caused by a fracture and its relationship to surrounding anatomical structures.

  12. Frontal cortical asymmetry may partially mediate the influence of social power on anger expression

    Directory of Open Access Journals (Sweden)

    Dongdong eLi

    2016-02-01

    Full Text Available When irritated by other people, powerful people usually tend to express their anger explicitly and directly, whereas people in less powerful positions are more likely not to show their feelings freely. The neural mechanism behind power and its influence on expression tendency has been scarcely explored. This study recorded frontal EEG activity at rest and frontal EEG activation while participants were engaged in a writing task describing an anger-eliciting event, in which they were irritated by people with higher or lower social power. Participants’ anger levels and expression inclination levels were self-reported on nine-point visual analog Likert scales, and also rated by independent raters based on the essays they had written. The results showed that high social power was indeed associated with greater anger expression tendency and greater left frontal activation than low social power. This is in line with the approach-inhibition theory of power. The mid-frontal asymmetric activation served as a partial mediator between social power and expression inclination. This effect may relate to the functions of the prefrontal cortex, which is in charge of information integration and evaluation and the control of motivation direction, as reported by previous studies.

  13. Less efficient and costly processes of frontal cortex in childhood chronic fatigue syndrome

    Science.gov (United States)

    Mizuno, Kei; Tanaka, Masaaki; Tanabe, Hiroki C.; Joudoi, Takako; Kawatani, Junko; Shigihara, Yoshihito; Tomoda, Akemi; Miike, Teruhisa; Imai-Matsumura, Kyoko; Sadato, Norihiro; Watanabe, Yasuyoshi

    2015-01-01

    The ability to divide one's attention deteriorates in patients with childhood chronic fatigue syndrome (CCFS). We conducted a study using a dual verbal task to assess allocation of attentional resources to two simultaneous activities (picking out vowels and reading for story comprehension) and functional magnetic resonance imaging. Patients exhibited a much larger area of activation, recruiting additional frontal areas. The right middle frontal gyrus (MFG), which is included in the dorsolateral prefrontal cortex, of CCFS patients was specifically activated in both the single and dual tasks; this activation level was positively correlated with motivation scores for the tasks and accuracy of story comprehension. In addition, in patients, the dorsal anterior cingulate gyrus (dACC) and left MFG were activated only in the dual task, and activation levels of the dACC and left MFG were positively associated with the motivation and fatigue scores, respectively. Patients with CCFS exhibited a wider area of activated frontal regions related to attentional resources in order to increase their poorer task performance with massive mental effort. This is likely to be less efficient and costly in terms of energy requirements. It seems to be related to the pathophysiology of patients with CCFS and to cause a vicious cycle of further increases in fatigue. PMID:26594619

  14. Less efficient and costly processes of frontal cortex in childhood chronic fatigue syndrome.

    Science.gov (United States)

    Mizuno, Kei; Tanaka, Masaaki; Tanabe, Hiroki C; Joudoi, Takako; Kawatani, Junko; Shigihara, Yoshihito; Tomoda, Akemi; Miike, Teruhisa; Imai-Matsumura, Kyoko; Sadato, Norihiro; Watanabe, Yasuyoshi

    2015-01-01

    The ability to divide one's attention deteriorates in patients with childhood chronic fatigue syndrome (CCFS). We conducted a study using a dual verbal task to assess allocation of attentional resources to two simultaneous activities (picking out vowels and reading for story comprehension) and functional magnetic resonance imaging. Patients exhibited a much larger area of activation, recruiting additional frontal areas. The right middle frontal gyrus (MFG), which is included in the dorsolateral prefrontal cortex, of CCFS patients was specifically activated in both the single and dual tasks; this activation level was positively correlated with motivation scores for the tasks and accuracy of story comprehension. In addition, in patients, the dorsal anterior cingulate gyrus (dACC) and left MFG were activated only in the dual task, and activation levels of the dACC and left MFG were positively associated with the motivation and fatigue scores, respectively. Patients with CCFS exhibited a wider area of activated frontal regions related to attentional resources in order to increase their poorer task performance with massive mental effort. This is likely to be less efficient and costly in terms of energy requirements. It seems to be related to the pathophysiology of patients with CCFS and to cause a vicious cycle of further increases in fatigue.

  15. Less efficient and costly processes of frontal cortex in childhood chronic fatigue syndrome

    Directory of Open Access Journals (Sweden)

    Kei Mizuno

    2015-01-01

    Full Text Available The ability to divide one's attention deteriorates in patients with childhood chronic fatigue syndrome (CCFS. We conducted a study using a dual verbal task to assess allocation of attentional resources to two simultaneous activities (picking out vowels and reading for story comprehension and functional magnetic resonance imaging. Patients exhibited a much larger area of activation, recruiting additional frontal areas. The right middle frontal gyrus (MFG, which is included in the dorsolateral prefrontal cortex, of CCFS patients was specifically activated in both the single and dual tasks; this activation level was positively correlated with motivation scores for the tasks and accuracy of story comprehension. In addition, in patients, the dorsal anterior cingulate gyrus (dACC and left MFG were activated only in the dual task, and activation levels of the dACC and left MFG were positively associated with the motivation and fatigue scores, respectively. Patients with CCFS exhibited a wider area of activated frontal regions related to attentional resources in order to increase their poorer task performance with massive mental effort. This is likely to be less efficient and costly in terms of energy requirements. It seems to be related to the pathophysiology of patients with CCFS and to cause a vicious cycle of further increases in fatigue.

  16. Anodal Transcranial Direct Current Stimulation Promotes Frontal Compensatory Mechanisms in Healthy Elderly Subjects.

    Science.gov (United States)

    Cespón, Jesús; Rodella, Claudia; Rossini, Paolo M; Miniussi, Carlo; Pellicciari, Maria C

    2017-01-01

    Recent studies have demonstrated that transcranial direct current stimulation (tDCS) is potentially useful to improve working memory. In the present study, young and elderly subjects performed a working memory task ( n -back task) during an electroencephalogram recording before and after receiving anodal, cathodal, and sham tDCS over the left dorsolateral prefrontal cortex (DLPFC). We investigated modulations of behavioral performance and electrophysiological correlates of working memory processes (frontal and parietal P300 event-related potentials). A strong tendency to modulated working memory performance was observed after the application of tDCS. In detail, young, but not elderly, subjects benefited from additional practice in the absence of real tDCS, as indicated by their more accurate responses after sham tDCS. The cathodal tDCS had no effect in any group of participants. Importantly, anodal tDCS improved accuracy in elderly. Moreover, increased accuracy after anodal tDCS was correlated with a larger frontal P300 amplitude. These findings suggest that, in elderly subjects, improved working memory after anodal tDCS applied over the left DLPFC may be related to the promotion of frontal compensatory mechanisms, which are related to attentional processes.

  17. Anodal Transcranial Direct Current Stimulation Promotes Frontal Compensatory Mechanisms in Healthy Elderly Subjects

    Directory of Open Access Journals (Sweden)

    Jesús Cespón

    2017-12-01

    Full Text Available Recent studies have demonstrated that transcranial direct current stimulation (tDCS is potentially useful to improve working memory. In the present study, young and elderly subjects performed a working memory task (n-back task during an electroencephalogram recording before and after receiving anodal, cathodal, and sham tDCS over the left dorsolateral prefrontal cortex (DLPFC. We investigated modulations of behavioral performance and electrophysiological correlates of working memory processes (frontal and parietal P300 event-related potentials. A strong tendency to modulated working memory performance was observed after the application of tDCS. In detail, young, but not elderly, subjects benefited from additional practice in the absence of real tDCS, as indicated by their more accurate responses after sham tDCS. The cathodal tDCS had no effect in any group of participants. Importantly, anodal tDCS improved accuracy in elderly. Moreover, increased accuracy after anodal tDCS was correlated with a larger frontal P300 amplitude. These findings suggest that, in elderly subjects, improved working memory after anodal tDCS applied over the left DLPFC may be related to the promotion of frontal compensatory mechanisms, which are related to attentional processes.

  18. An Implementation of Error Minimization Data Transmission in OFDM using Modified Convolutional Code

    Directory of Open Access Journals (Sweden)

    Hendy Briantoro

    2016-04-01

    Full Text Available This paper presents about error minimization in OFDM system. In conventional system, usually using channel coding such as BCH Code or Convolutional Code. But, performance BCH Code or Convolutional Code is not good in implementation of OFDM System. Error bits of OFDM system without channel coding is 5.77%. Then, we used convolutional code with code rate 1/2, it can reduce error bitsonly up to 3.85%. So, we proposed OFDM system with Modified Convolutional Code. In this implementation, we used Software Define Radio (SDR, namely Universal Software Radio Peripheral (USRP NI 2920 as the transmitter and receiver. The result of OFDM system using Modified Convolutional Code with code rate is able recover all character received so can decrease until 0% error bit. Increasing performance of Modified Convolutional Code is about 1 dB in BER of 10-4 from BCH Code and Convolutional Code. So, performance of Modified Convolutional better than BCH Code or Convolutional Code. Keywords: OFDM, BCH Code, Convolutional Code, Modified Convolutional Code, SDR, USRP

  19. Left frontal eye field remembers “where” but not “what”

    NARCIS (Netherlands)

    Campana, G.; Cowey, A.; Casco, C.; Oudsen, G.J.M.; Walsh, V.

    2007-01-01

    Short-term memory of basic stimulus features seems to rely upon low-level functional components of the visual pathways. By using a repetition priming paradigm, we previously showed that visual area V5/MT is important for holding motion direction information, but not spatial position information.

  20. How Left Inferior Frontal Cortex Participates in Syntactic Processing: Evidence from Aphasia

    Science.gov (United States)

    Love, Tracy; Swinney, David; Walenski, Matthew; Zurif, Edgar

    2008-01-01

    We report on three experiments that provide a real-time processing perspective on the poor comprehension of Broca's aphasic patients for non-canonically structured sentences. In the first experiment we presented sentences (via a Cross Modal Lexical Priming (CMLP) paradigm) to Broca's patients at a normal rate of speech. Unlike the pattern found…

  1. Behavioral Approach System Sensitivity and Risk Taking Interact to Predict Left-Frontal EEG Asymmetry

    OpenAIRE

    Black, Chelsea L.; Goldstein, Kim E.; LaBelle, Denise R.; Brown, Christopher W.; Harmon-Jones, Eddie; Abramson, Lyn Y.; Alloy, Lauren B.

    2014-01-01

    The Behavioral Approach System (BAS) hypersensitivity theory of bipolar disorder (BD; Alloy & Abramson, 2010; Depue & Iacono, 1989) suggests that hyperreactivity in the BAS results in the extreme fluctuations of mood characteristic of BD. In addition to risk conferred by BAS hypersensitivity, cognitive and personality variables may play a role in determining risk. We evaluated relationships among BAS sensitivity, risk taking, and an electrophysiological correlate of approach motivation, relat...

  2. The right posterior inferior frontal gyrus contributes to phonological word decisions in the healthy brain

    DEFF Research Database (Denmark)

    Hartwigsen, Gesa; Price, Cathy J; Baumgaertner, Annette

    2010-01-01

    There is consensus that the left hemisphere plays a dominant role in language processing, but functional imaging studies have shown that the right as well as the left posterior inferior frontal gyri (pIFG) are activated when healthy right-handed individuals make phonological word decisions. Here we...... used online transcranial magnetic stimulation (TMS) to examine the functional relevance of the right pIFG for auditory and visual phonological decisions. Healthy right-handed individuals made phonological or semantic word judgements on the same set of auditorily and visually presented words while......IFG impaired reaction times and accuracy of phonological but not semantic decisions for visually and auditorily presented words. TMS over left, right or bilateral pIFG disrupted phonological processing to a similar degree. In a follow-up experiment, the intensity threshold for delaying phonological judgements...

  3. Extravascular lung water: its measurement by simultaneous pulmonary and aortic sampling and iterative convolution

    International Nuclear Information System (INIS)

    Giuntini, C.; Fazio, F.

    1975-01-01

    The inadequacy of the apparent distribution volume of THO during the first passage dilution curve (a) to account for the total lung water in in-vitro measurements in dogs and (b) to measure any increase in lung water, even in patients with obvious clinical pulmonary oedema, prompted the present investigation. Tritiated water, THO, as diffusible indicator, and human serum albumin labelled with 131 I, ALB, as intravascular tracer, are injected into the superior vena cava at the junction with the right atrium. In order to clear the aortic blood samples of recirculation, the recirculating tracers must be determined. This is accomplished by pulmonary artery sampling. Iterative convolution of the pulmonary artery dilution curves with suitable test functions eventually yields products of convolution that fit well the corresponding aortic dilution curves of THO and ALB. The test functions that yield the best fit are taken to represent the frequency functions of the transit time from pulmonary artery to aorta of THO and ALB, respectively. By applying the same procedure of iterative convolution to these frequency functions, we obtain the dilution curve of THO in the extravascular lung space. As a result of this analysis: (a) forward extrapolation is less subject to systematic errors such as overestimation of the mean transit time of ALB, i.e. of the tracer that recirculates more; and (b) the distribution volume of THO can be better defined since the dilution of THO in the extravascular lung space may be followed beyond the point of recirculation. The results indicate that both in normal subjects and in patients with left ventricular insufficiency the computed dilution curves of THO in the extravascular lung space have a long tail which is more pronounced in the patients. These findings suggest the existence in the lungs of extravascular water pools that are slowly exchanging with pulmonary water flow. This may depend both on inhomogeneities of perfusion, with lack of it at

  4. Brain Abscess Associated with Isolated Left Superior Vena Cava Draining into the Left Atrium in the Absence of Coronary Sinus and Atrial Septal Defect

    International Nuclear Information System (INIS)

    Erol, Ilknur; Cetin, I. Ilker; Alehan, Fuesun; Varan, Birguel; Ozkan, Sueleyman; Agildere, A. Muhtesem; Tokel, Kursad

    2006-01-01

    A previously healthy 12-year-old girl presented with severe headache for 2 weeks. On physical examination, there was finger clubbing without apparent cyanosis. Neurological examination revealed only papiledema without focal neurologic signs. Cerebral magnetic resonance imaging showed the characteristic features of brain abscess in the left frontal lobe. Cardiologic workup to exclude a right-to-left shunt showed an abnormality of the systemic venous drainage: presence of isolated left superior vena cava draining into the left atrium in the absence of coronary sinus and atrial septal defect. This anomaly is rare, because only a few other cases have been reported

  5. Automated EEG-based screening of depression using deep convolutional neural network.

    Science.gov (United States)

    Acharya, U Rajendra; Oh, Shu Lih; Hagiwara, Yuki; Tan, Jen Hong; Adeli, Hojjat; Subha, D P

    2018-07-01

    In recent years, advanced neurocomputing and machine learning techniques have been used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In this paper, a novel computer model is presented for EEG-based screening of depression using a deep neural network machine learning approach, known as Convolutional Neural Network (CNN). The proposed technique does not require a semi-manually-selected set of features to be fed into a classifier for classification. It learns automatically and adaptively from the input EEG signals to differentiate EEGs obtained from depressive and normal subjects. The model was tested using EEGs obtained from 15 normal and 15 depressed patients. The algorithm attained accuracies of 93.5% and 96.0% using EEG signals from the left and right hemisphere, respectively. It was discovered in this research that the EEG signals from the right hemisphere are more distinctive in depression than those from the left hemisphere. This discovery is consistent with recent research and revelation that the depression is associated with a hyperactive right hemisphere. An exciting extension of this research would be diagnosis of different stages and severity of depression and development of a Depression Severity Index (DSI). Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Golden Proportion in Frontal Social Smile from Orthodontic Viewpoint

    Directory of Open Access Journals (Sweden)

    z Tabatabaei

    2011-09-01

    Full Text Available Introduction: Physical attraction has a significant effect on all aspects of personal life, and in this category facial appearance is the most important part of the body in prediction of attractiveness. In the face, mouth and specially shape and size of anterior teeth is important to gain dental and facial esthetic. The aim of this study is evaluation of golden proportion from orthodontic view in maxillary anterior teeth in both sexes. Methods: Considering inclusion and exclusion criteria, 100 students of Rafsanjan University of Medical Sciences were selected, and photographs of their frontal social smile were taken by a standard method from 30cm distance. Then visible part of central, lateral and canine teeth was measured by Photoshop software (Adobe Photoshop ver8 with 0.1mm precision. Data was evaluated by descriptive statistical analysis and sample T-test using SPSS. Results: According to descriptive statistical analysis and sample T- test, mean ratio of central to lateral teeth in the left side in men and women was 1.209±0.199 and 1.157±0.156 and in the right side in men and women was 1.179± 0.27 and 1.158± 0.145, respectively. The ratio of lateral to canine teeth in the left side in men and women was 1.522±0.146 and 1.494±0.127 and in the right side in men and women was 1.55±0.164 and 1.51±0.114, respectively. Golden proportion was seen between central and lateral teeth in 16% in the right side and 3.4% in the left side only in men. Conclusion: Golden proportion was seen between central and lateral in the left side and right side in men, but due to large canine in men, this proportion was not seen between lateral and canine teeth and so due to small lateral in women, it was not seen between anterior teeth.

  7. 47-year-old man with left leg numbness.

    Science.gov (United States)

    Mahta, Ali; Kim, Ryan Y; Saad, Ali G; Kesari, Santosh

    2013-03-01

    A 47-year-old white male with a history of uveitis, hypercalcemia and nephrolithiasis presented with acute onset partial seizure. On exam he had decreased sensation to light touch on his left lower extremity. A Brain MRI revealed a right frontal mass, which was initially thought to be a metastatic lesion or a primary brain tumor. However, biopsy of the lesion revealed it to be a non-caseating granulomatous lesion consistent with neurosarcoidosis.

  8. Dyslexic children lack word selectivity gradients in occipito-temporal and inferior frontal cortex

    Directory of Open Access Journals (Sweden)

    O.A. Olulade

    2015-01-01

    Full Text Available fMRI studies using a region-of-interest approach have revealed that the ventral portion of the left occipito-temporal cortex, which is specialized for orthographic processing of visually presented words (and includes the so-called “visual word form area”, VWFA, is characterized by a posterior-to-anterior gradient of increasing selectivity for words in typically reading adults, adolescents, and children (e.g. Brem et al., 2006, 2009. Similarly, the left inferior frontal cortex (IFC has been shown to exhibit a medial-to-lateral gradient of print selectivity in typically reading adults (Vinckier et al., 2007. Functional brain imaging studies of dyslexia have reported relative underactivity in left hemisphere occipito-temporal and inferior frontal regions using whole-brain analyses during word processing tasks. Hence, the question arises whether gradient sensitivities in these regions are altered in dyslexia. Indeed, a region-of-interest analysis revealed the gradient-specific functional specialization in the occipito-temporal cortex to be disrupted in dyslexic children (van der Mark et al., 2009. Building on these studies, we here (1 investigate if a word-selective gradient exists in the inferior frontal cortex in addition to the occipito-temporal cortex in normally reading children, (2 compare typically reading with dyslexic children, and (3 examine functional connections between these regions in both groups. We replicated the previously reported anterior-to-posterior gradient of increasing selectivity for words in the left occipito-temporal cortex in typically reading children, and its absence in the dyslexic children. Our novel finding is the detection of a pattern of increasing selectivity for words along the medial-to-lateral axis of the left inferior frontal cortex in typically reading children and evidence of functional connectivity between the most lateral aspect of this area and the anterior aspects of the occipito-temporal cortex. We

  9. Alopecia frontal fibrosante: una enfermedad en auge

    OpenAIRE

    Quintana-Sancho, A. de; Piris-García, X.; Valle-García, N.; Hierro-Cámara, M.

    2016-01-01

    La alopecia frontal fibrosante (AFF) es un tipo de alopecia cicatricial cuya incidencia está aumentando de forma significativa en nuestro país. Se caracteriza por un retroceso en la línea de implantación del pelo a nivel frontotemporal que afecta mayoritariamente a mujeres postmenopaúsicas, con un impacto negativo en su calidad de vida. Se asocia a menopausia precoz en un 14% de los casos y a hipotiroidismo en un 15%. Con respecto al tratamiento, son los inhibidores de la 5alfa-reductasa, los...

  10. Effects of positive emotion, extraversion, and dopamine on cognitive stability-flexibility and frontal EEG asymmetry.

    Science.gov (United States)

    Wacker, Jan

    2018-01-01

    The influence of positive emotions on the balance between cognitive stability and flexibility has been suggested to (a) differ among various positive emotional/motivational states (e.g., of varying approach motivation intensity), and (b) be mediated by brain dopamine (DA). Frontal EEG alpha asymmetry (ASY) is considered an indicator of approach motivational states and may be modulated by DA. The personality trait of extraversion is strongly linked to positive emotions and is now thought to reflect DA-based individual differences in incentive/approach motivation. The present study independently manipulated positive emotion (high approach wanting-expectancy [WE] vs. low approach warmth-liking [WL]) and dopamine (placebo vs. DA D2 blocker sulpiride) to examine their effects on both cognitive stability-flexibility and emotion-related ASY changes. The results showed numerically lower stability-flexibility in WE versus WL under placebo and a complete reversal of this effect under the D2 blocker, no differentiation between WE and WL groups in terms of emotion-related ASY change, but an association between self-reported WE and WL and ASY changes toward left and right frontal cortical activity, respectively. Finally, extraversion was positively associated with both stability-flexibility and ASY changes toward left frontal cortical activity under placebo, and these associations were completely reversed under the D2 blocker. The results (a) support a dopaminergic basis for frontal EEG asymmetry, extraversion, and the modulating effect of positive emotions on stability-flexibility, and (b) extend previous reports of cognitive differences between introverts and extraverts. © 2017 Society for Psychophysiological Research.

  11. Structural connectivity of right frontal hyperactive areas scales with stuttering severity.

    Science.gov (United States)

    Neef, Nicole E; Anwander, Alfred; Bütfering, Christoph; Schmidt-Samoa, Carsten; Friederici, Angela D; Paulus, Walter; Sommer, Martin

    2018-01-01

    A neuronal sign of persistent developmental stuttering is the magnified coactivation of right frontal brain regions during speech production. Whether and how stuttering severity relates to the connection strength of these hyperactive right frontal areas to other brain areas is an open question. Scrutinizing such brain-behaviour and structure-function relationships aims at disentangling suspected underlying neuronal mechanisms of stuttering. Here, we acquired diffusion-weighted and functional images from 31 adults who stutter and 34 matched control participants. Using a newly developed structural connectivity measure, we calculated voxel-wise correlations between connection strength and stuttering severity within tract volumes that originated from functionally hyperactive right frontal regions. Correlation analyses revealed that with increasing speech motor deficits the connection strength increased in the right frontal aslant tract, the right anterior thalamic radiation, and in U-shaped projections underneath the right precentral sulcus. In contrast, with decreasing speech motor deficits connection strength increased in the right uncinate fasciculus. Additional group comparisons of whole-brain white matter skeletons replicated the previously reported reduction of fractional anisotropy in the left and right superior longitudinal fasciculus as well as at the junction of right frontal aslant tract and right superior longitudinal fasciculus in adults who stutter compared to control participants. Overall, our investigation suggests that right fronto-temporal networks play a compensatory role as a fluency enhancing mechanism. In contrast, the increased connection strength within subcortical-cortical pathways may be implied in an overly active global response suppression mechanism in stuttering. Altogether, this combined functional MRI-diffusion tensor imaging study disentangles different networks involved in the neuronal underpinnings of the speech motor deficit in

  12. Structural connectivity of right frontal hyperactive areas scales with stuttering severity

    Science.gov (United States)

    Neef, Nicole E; Bütfering, Christoph; Schmidt-Samoa, Carsten; Friederici, Angela D; Paulus, Walter; Sommer, Martin

    2018-01-01

    Abstract A neuronal sign of persistent developmental stuttering is the magnified coactivation of right frontal brain regions during speech production. Whether and how stuttering severity relates to the connection strength of these hyperactive right frontal areas to other brain areas is an open question. Scrutinizing such brain–behaviour and structure–function relationships aims at disentangling suspected underlying neuronal mechanisms of stuttering. Here, we acquired diffusion-weighted and functional images from 31 adults who stutter and 34 matched control participants. Using a newly developed structural connectivity measure, we calculated voxel-wise correlations between connection strength and stuttering severity within tract volumes that originated from functionally hyperactive right frontal regions. Correlation analyses revealed that with increasing speech motor deficits the connection strength increased in the right frontal aslant tract, the right anterior thalamic radiation, and in U-shaped projections underneath the right precentral sulcus. In contrast, with decreasing speech motor deficits connection strength increased in the right uncinate fasciculus. Additional group comparisons of whole-brain white matter skeletons replicated the previously reported reduction of fractional anisotropy in the left and right superior longitudinal fasciculus as well as at the junction of right frontal aslant tract and right superior longitudinal fasciculus in adults who stutter compared to control participants. Overall, our investigation suggests that right fronto-temporal networks play a compensatory role as a fluency enhancing mechanism. In contrast, the increased connection strength within subcortical-cortical pathways may be implied in an overly active global response suppression mechanism in stuttering. Altogether, this combined functional MRI–diffusion tensor imaging study disentangles different networks involved in the neuronal underpinnings of the speech motor

  13. Posterior paralimbic and frontal metabolite impairments in asymptomatic hypertension with different treatment outcomes

    International Nuclear Information System (INIS)

    Garcia Santos, J.M.; Fuentes, L.J.; Vidal, J.B.

    2010-01-01

    Hypertension is associated with cognitive decline in elderly persons. We studied asymptomatic hypertensive subjects using brain magnetic resonance (MR) spectroscopy to evaluate metabolite impairments before the appearance of symptoms in patients with different treatment outcomes. In all, 14 healthy controls and 37 asymptomatic hypertensive patients (17 controlled and 20 resistant) underwent brain structural MR and MR spectroscopy of the posterior paralimbic (PPL) area and left frontal white matter. Ischemic burden (IB), global cortical atrophy and microbleeds were analyzed with visual scales. Metabolite ratios involving N-acetyl-aspartate (NAA), creatine (Cr), choline (Cho) and myoinositol (ml) were computed. Ultrasound measurements, including intima-media thickness, plaques and hemodynamic ratios, were obtained. Intergroup differences in IB, atrophy and metabolite ratios, and the atrophy and IB relationship were assessed with parametric and nonparametric statistical tests. In addition, the impacts of demographic, analytic and clinical factors, ischemia and atrophy, and ultrasound measurements on metabolite ratios were assessed. The significance level was set at P≤0.05. Higher atrophy scores presented with higher total or frontal IB (P<0.05). However, there was no intergroup difference in atrophy and IB. PPL ml/Cr was increased in resistant hypertension (P<0.021), whereas frontal NAA/Cr (P<0.007) showed opposite trends between controlled (increased ratios) and resistant (decreased ratios) hypertension. Unlike PPL ml/Cr, frontal NAA/Cr showed significant correlations with the lipid profile and ultrasound measurements. PPL ml/Cr increases in resistant hypertension, and frontal NAA/Cr diverges between controlled and resistant hypertension before physical and neuropsychological symptoms appear. (author)

  14. Combining morphometric features and convolutional networks fusion for glaucoma diagnosis

    Science.gov (United States)

    Perdomo, Oscar; Arevalo, John; González, Fabio A.

    2017-11-01

    Glaucoma is an eye condition that leads to loss of vision and blindness. Ophthalmoscopy exam evaluates the shape, color and proportion between the optic disc and physiologic cup, but the lack of agreement among experts is still the main diagnosis problem. The application of deep convolutional neural networks combined with automatic extraction of features such as: the cup-to-disc distance in the four quadrants, the perimeter, area, eccentricity, the major radio, the minor radio in optic disc and cup, in addition to all the ratios among the previous parameters may help with a better automatic grading of glaucoma. This paper presents a strategy to merge morphological features and deep convolutional neural networks as a novel methodology to support the glaucoma diagnosis in eye fundus images.

  15. Improving deep convolutional neural networks with mixed maxout units.

    Directory of Open Access Journals (Sweden)

    Hui-Zhen Zhao

    Full Text Available Motivated by insights from the maxout-units-based deep Convolutional Neural Network (CNN that "non-maximal features are unable to deliver" and "feature mapping subspace pooling is insufficient," we present a novel mixed variant of the recently introduced maxout unit called a mixout unit. Specifically, we do so by calculating the exponential probabilities of feature mappings gained by applying different convolutional transformations over the same input and then calculating the expected values according to their exponential probabilities. Moreover, we introduce the Bernoulli distribution to balance the maximum values with the expected values of the feature mappings subspace. Finally, we design a simple model to verify the pooling ability of mixout units and a Mixout-units-based Network-in-Network (NiN model to analyze the feature learning ability of the mixout models. We argue that our proposed units improve the pooling ability and that mixout models can achieve better feature learning and classification performance.

  16. Convolutional over Recurrent Encoder for Neural Machine Translation

    Directory of Open Access Journals (Sweden)

    Dakwale Praveen

    2017-06-01

    Full Text Available Neural machine translation is a recently proposed approach which has shown competitive results to traditional MT approaches. Standard neural MT is an end-to-end neural network where the source sentence is encoded by a recurrent neural network (RNN called encoder and the target words are predicted using another RNN known as decoder. Recently, various models have been proposed which replace the RNN encoder with a convolutional neural network (CNN. In this paper, we propose to augment the standard RNN encoder in NMT with additional convolutional layers in order to capture wider context in the encoder output. Experiments on English to German translation demonstrate that our approach can achieve significant improvements over a standard RNN-based baseline.

  17. Infimal Convolution Regularisation Functionals of BV and Lp Spaces

    KAUST Repository

    Burger, Martin

    2016-02-03

    We study a general class of infimal convolution type regularisation functionals suitable for applications in image processing. These functionals incorporate a combination of the total variation seminorm and Lp norms. A unified well-posedness analysis is presented and a detailed study of the one-dimensional model is performed, by computing exact solutions for the corresponding denoising problem and the case p=2. Furthermore, the dependency of the regularisation properties of this infimal convolution approach to the choice of p is studied. It turns out that in the case p=2 this regulariser is equivalent to the Huber-type variant of total variation regularisation. We provide numerical examples for image decomposition as well as for image denoising. We show that our model is capable of eliminating the staircasing effect, a well-known disadvantage of total variation regularisation. Moreover as p increases we obtain almost piecewise affine reconstructions, leading also to a better preservation of hat-like structures.

  18. 3D Medical Image Interpolation Based on Parametric Cubic Convolution

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    In the process of display, manipulation and analysis of biomedical image data, they usually need to be converted to data of isotropic discretization through the process of interpolation, while the cubic convolution interpolation is widely used due to its good tradeoff between computational cost and accuracy. In this paper, we present a whole concept for the 3D medical image interpolation based on cubic convolution, and the six methods, with the different sharp control parameter, which are formulated in details. Furthermore, we also give an objective comparison for these methods using data sets with the different slice spacing. Each slice in these data sets is estimated by each interpolation method and compared with the original slice using three measures: mean-squared difference, number of sites of disagreement, and largest difference. According to the experimental results, we present a recommendation for 3D medical images under the different situations in the end.

  19. Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks.

    Science.gov (United States)

    Yu, Haiyang; Wu, Zhihai; Wang, Shuqin; Wang, Yunpeng; Ma, Xiaolei

    2017-06-26

    Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs), for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

  20. Deep learning for steganalysis via convolutional neural networks

    Science.gov (United States)

    Qian, Yinlong; Dong, Jing; Wang, Wei; Tan, Tieniu

    2015-03-01

    Current work on steganalysis for digital images is focused on the construction of complex handcrafted features. This paper proposes a new paradigm for steganalysis to learn features automatically via deep learning models. We novelly propose a customized Convolutional Neural Network for steganalysis. The proposed model can capture the complex dependencies that are useful for steganalysis. Compared with existing schemes, this model can automatically learn feature representations with several convolutional layers. The feature extraction and classification steps are unified under a single architecture, which means the guidance of classification can be used during the feature extraction step. We demonstrate the effectiveness of the proposed model on three state-of-theart spatial domain steganographic algorithms - HUGO, WOW, and S-UNIWARD. Compared to the Spatial Rich Model (SRM), our model achieves comparable performance on BOSSbase and the realistic and large ImageNet database.

  1. ID card number detection algorithm based on convolutional neural network

    Science.gov (United States)

    Zhu, Jian; Ma, Hanjie; Feng, Jie; Dai, Leiyan

    2018-04-01

    In this paper, a new detection algorithm based on Convolutional Neural Network is presented in order to realize the fast and convenient ID information extraction in multiple scenarios. The algorithm uses the mobile device equipped with Android operating system to locate and extract the ID number; Use the special color distribution of the ID card, select the appropriate channel component; Use the image threshold segmentation, noise processing and morphological processing to take the binary processing for image; At the same time, the image rotation and projection method are used for horizontal correction when image was tilting; Finally, the single character is extracted by the projection method, and recognized by using Convolutional Neural Network. Through test shows that, A single ID number image from the extraction to the identification time is about 80ms, the accuracy rate is about 99%, It can be applied to the actual production and living environment.

  2. Trajectory Generation Method with Convolution Operation on Velocity Profile

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Geon [Hanyang Univ., Seoul (Korea, Republic of); Kim, Doik [Korea Institute of Science and Technology, Daejeon (Korea, Republic of)

    2014-03-15

    The use of robots is no longer limited to the field of industrial robots and is now expanding into the fields of service and medical robots. In this light, a trajectory generation method that can respond instantaneously to the external environment is strongly required. Toward this end, this study proposes a method that enables a robot to change its trajectory in real-time using a convolution operation. The proposed method generates a trajectory in real time and satisfies the physical limits of the robot system such as acceleration and velocity limit. Moreover, a new way to improve the previous method, which generates inefficient trajectories in some cases owing to the characteristics of the trapezoidal shape of trajectories, is proposed by introducing a triangle shape. The validity and effectiveness of the proposed method is shown through a numerical simulation and a comparison with the previous convolution method.

  3. Airplane detection in remote sensing images using convolutional neural networks

    Science.gov (United States)

    Ouyang, Chao; Chen, Zhong; Zhang, Feng; Zhang, Yifei

    2018-03-01

    Airplane detection in remote sensing images remains a challenging problem and has also been taking a great interest to researchers. In this paper we propose an effective method to detect airplanes in remote sensing images using convolutional neural networks. Deep learning methods show greater advantages than the traditional methods with the rise of deep neural networks in target detection, and we give an explanation why this happens. To improve the performance on detection of airplane, we combine a region proposal algorithm with convolutional neural networks. And in the training phase, we divide the background into multi classes rather than one class, which can reduce false alarms. Our experimental results show that the proposed method is effective and robust in detecting airplane.

  4. Rock images classification by using deep convolution neural network

    Science.gov (United States)

    Cheng, Guojian; Guo, Wenhui

    2017-08-01

    Granularity analysis is one of the most essential issues in authenticate under microscope. To improve the efficiency and accuracy of traditional manual work, an convolutional neural network based method is proposed for granularity analysis from thin section image, which chooses and extracts features from image samples while build classifier to recognize granularity of input image samples. 4800 samples from Ordos basin are used for experiments under colour spaces of HSV, YCbCr and RGB respectively. On the test dataset, the correct rate in RGB colour space is 98.5%, and it is believable in HSV and YCbCr colour space. The results show that the convolution neural network can classify the rock images with high reliability.

  5. User-generated content curation with deep convolutional neural networks

    OpenAIRE

    Tous Liesa, Rubén; Wust, Otto; Gómez, Mauro; Poveda, Jonatan; Elena, Marc; Torres Viñals, Jordi; Makni, Mouna; Ayguadé Parra, Eduard

    2016-01-01

    In this paper, we report a work consisting in using deep convolutional neural networks (CNNs) for curating and filtering photos posted by social media users (Instagram and Twitter). The final goal is to facilitate searching and discovering user-generated content (UGC) with potential value for digital marketing tasks. The images are captured in real time and automatically annotated with multiple CNNs. Some of the CNNs perform generic object recognition tasks while others perform what we call v...

  6. A quantum algorithm for Viterbi decoding of classical convolutional codes

    OpenAIRE

    Grice, Jon R.; Meyer, David A.

    2014-01-01

    We present a quantum Viterbi algorithm (QVA) with better than classical performance under certain conditions. In this paper the proposed algorithm is applied to decoding classical convolutional codes, for instance; large constraint length $Q$ and short decode frames $N$. Other applications of the classical Viterbi algorithm where $Q$ is large (e.g. speech processing) could experience significant speedup with the QVA. The QVA exploits the fact that the decoding trellis is similar to the butter...

  7. Abnormality Detection in Mammography using Deep Convolutional Neural Networks

    OpenAIRE

    Xi, Pengcheng; Shu, Chang; Goubran, Rafik

    2018-01-01

    Breast cancer is the most common cancer in women worldwide. The most common screening technology is mammography. To reduce the cost and workload of radiologists, we propose a computer aided detection approach for classifying and localizing calcifications and masses in mammogram images. To improve on conventional approaches, we apply deep convolutional neural networks (CNN) for automatic feature learning and classifier building. In computer-aided mammography, deep CNN classifiers cannot be tra...

  8. Quantifying Translation-Invariance in Convolutional Neural Networks

    OpenAIRE

    Kauderer-Abrams, Eric

    2017-01-01

    A fundamental problem in object recognition is the development of image representations that are invariant to common transformations such as translation, rotation, and small deformations. There are multiple hypotheses regarding the source of translation invariance in CNNs. One idea is that translation invariance is due to the increasing receptive field size of neurons in successive convolution layers. Another possibility is that invariance is due to the pooling operation. We develop a simple ...

  9. Fast convolutional sparse coding using matrix inversion lemma

    Czech Academy of Sciences Publication Activity Database

    Šorel, Michal; Šroubek, Filip

    2016-01-01

    Roč. 55, č. 1 (2016), s. 44-51 ISSN 1051-2004 R&D Projects: GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : Convolutional sparse coding * Feature learning * Deconvolution networks * Shift-invariant sparse coding Subject RIV: JD - Computer Applications, Robotics Impact factor: 2.337, year: 2016 http://library.utia.cas.cz/separaty/2016/ZOI/sorel-0459332.pdf

  10. Learning Convolutional Text Representations for Visual Question Answering

    OpenAIRE

    Wang, Zhengyang; Ji, Shuiwang

    2017-01-01

    Visual question answering is a recently proposed artificial intelligence task that requires a deep understanding of both images and texts. In deep learning, images are typically modeled through convolutional neural networks, and texts are typically modeled through recurrent neural networks. While the requirement for modeling images is similar to traditional computer vision tasks, such as object recognition and image classification, visual question answering raises a different need for textual...

  11. Shallow and deep convolutional networks for saliency prediction

    OpenAIRE

    Pan, Junting; Sayrol Clols, Elisa; Giró Nieto, Xavier; McGuinness, Kevin; O'Connor, Noel

    2016-01-01

    The prediction of salient areas in images has been traditionally addressed with hand-crafted features based on neuroscience principles. This paper, however, addresses the problem with a completely data-driven approach by training a convolutional neural network (convnet). The learning process is formulated as a minimization of a loss function that measures the Euclidean distance of the predicted saliency map with the provided ground truth. The recent publication of large datasets of saliency p...

  12. Production and reception of meaningful sound in Foville's 'encompassing convolution'.

    Science.gov (United States)

    Schiller, F

    1999-04-01

    In the history of neurology. Achille Louis Foville (1799-1879) is a name deserving to be remembered. In the course of time, his circonvolution d'enceinte of 1844 (surrounding the Sylvian fissure) became the 'convolution encompassing' every aspect of aphasiology, including amusia, ie., the localization in a coherent semicircle of semicircle of cerebral cortext serving the production and perception of language, song and instrumental music in health and disease.

  13. Relay Backpropagation for Effective Learning of Deep Convolutional Neural Networks

    OpenAIRE

    Shen, Li; Lin, Zhouchen; Huang, Qingming

    2015-01-01

    Learning deeper convolutional neural networks becomes a tendency in recent years. However, many empirical evidences suggest that performance improvement cannot be gained by simply stacking more layers. In this paper, we consider the issue from an information theoretical perspective, and propose a novel method Relay Backpropagation, that encourages the propagation of effective information through the network in training stage. By virtue of the method, we achieved the first place in ILSVRC 2015...

  14. Maximum likelihood convolutional decoding (MCD) performance due to system losses

    Science.gov (United States)

    Webster, L.

    1976-01-01

    A model for predicting the computational performance of a maximum likelihood convolutional decoder (MCD) operating in a noisy carrier reference environment is described. This model is used to develop a subroutine that will be utilized by the Telemetry Analysis Program to compute the MCD bit error rate. When this computational model is averaged over noisy reference phase errors using a high-rate interpolation scheme, the results are found to agree quite favorably with experimental measurements.

  15. General Dirichlet Series, Arithmetic Convolution Equations and Laplace Transforms

    Czech Academy of Sciences Publication Activity Database

    Glöckner, H.; Lucht, L.G.; Porubský, Štefan

    2009-01-01

    Roč. 193, č. 2 (2009), s. 109-129 ISSN 0039-3223 R&D Projects: GA ČR GA201/07/0191 Institutional research plan: CEZ:AV0Z10300504 Keywords : arithmetic function * Dirichlet convolution * polynomial equation * analytic equation * topological algebra * holomorphic functional calculus * implicit function theorem * Laplace transform * semigroup * complex measure Subject RIV: BA - General Mathematics Impact factor: 0.645, year: 2009 http://arxiv.org/abs/0712.3172

  16. Solving singular convolution equations using the inverse fast Fourier transform

    Czech Academy of Sciences Publication Activity Database

    Krajník, E.; Montesinos, V.; Zizler, P.; Zizler, Václav

    2012-01-01

    Roč. 57, č. 5 (2012), s. 543-550 ISSN 0862-7940 R&D Projects: GA AV ČR IAA100190901 Institutional research plan: CEZ:AV0Z10190503 Keywords : singular convolution equations * fast Fourier transform * tempered distribution Subject RIV: BA - General Mathematics Impact factor: 0.222, year: 2012 http://www.springerlink.com/content/m8437t3563214048/

  17. CICAAR - Convolutive ICA with an Auto-Regressive Inverse Model

    DEFF Research Database (Denmark)

    Dyrholm, Mads; Hansen, Lars Kai

    2004-01-01

    We invoke an auto-regressive IIR inverse model for convolutive ICA and derive expressions for the likelihood and its gradient. We argue that optimization will give a stable inverse. When there are more sensors than sources the mixing model parameters are estimated in a second step by least square...... estimation. We demonstrate the method on synthetic data and finally separate speech and music in a real room recording....

  18. Lateral frontal cortex volume reduction in Tourette syndrome revealed by VBM

    Directory of Open Access Journals (Sweden)

    Wittfoth Matthias

    2012-02-01

    Full Text Available Abstract Background Structural changes have been found predominantly in the frontal cortex and in the striatum in children and adolescents with Gilles de la Tourette syndrome (GTS. The influence of comorbid symptomatology is unclear. Here we sought to address the question of gray matter abnormalities in GTS patients with co-morbid obsessive-compulsive disorder (OCD and/or attention deficit hyperactivity disorder (ADHD using voxel-based morphometry (VBM in twenty-nine adult actually unmedicated GTS patients and twenty-five healthy control subjects. Results In GTS we detected a cluster of decreased gray matter volume in the left inferior frontal gyrus (IFG, but no regions demonstrating volume increases. By comparing subgroups of GTS with comorbid ADHD to the subgroup with comorbid OCD, we found a left-sided amygdalar volume increase. Conclusions From our results it is suggested that the left IFG may constitute a common underlying structural correlate of GTS with co-morbid OCD/ADHD. A volume reduction in this brain region that has been previously identified as a key region in OCD and was associated with the active inhibition of attentional processes may reflect the failure to control behavior. Amygdala volume increase is discussed on the background of a linkage of this structure with ADHD symptomatology. Correlations with clinical data revealed gray matter volume changes in specific brain areas that have been described in these conditions each.

  19. Better without (lateral) frontal cortex? Insight problems solved by frontal patients.

    Science.gov (United States)

    Reverberi, Carlo; Toraldo, Alessio; D'Agostini, Serena; Skrap, Miran

    2005-12-01

    A recently proposed theory on frontal lobe functions claims that the prefrontal cortex, particularly its dorso-lateral aspect, is crucial in defining a set of responses suitable for a particular task, and biasing these for selection. This activity is carried out for virtually any kind of non-routine tasks, without distinction of content. The aim of this study is to test the prediction of Frith's 'sculpting the response space' hypothesis by means of an 'insight' problem-solving task, namely the matchstick arithmetic task. Starting from Knoblich et al.'s interpretation for the failure of healthy controls to solve the matchstick problem, and Frith's theory on the role of dorsolateral frontal cortex, we derived the counterintuitive prediction that patients with focal damage to the lateral frontal cortex should perform better than a group of healthy participants on this rather difficult task. We administered the matchstick task to 35 patients (aged 26-65 years) with a single focal brain lesion as determined by a CT or an MRI scan, and to 23 healthy participants (aged 34-62 years). The findings seemed in line with theoretical predictions. While only 43% of healthy participants could solve the most difficult matchstick problems ('type C'), 82% of lateral frontal patients did so (Fisher's exact test, P < 0.05). In conclusion, the combination of Frith's and Knoblich et al.'s theories was corroborated.

  20. AFM tip-sample convolution effects for cylinder protrusions

    Science.gov (United States)

    Shen, Jian; Zhang, Dan; Zhang, Fei-Hu; Gan, Yang

    2017-11-01

    A thorough understanding about the AFM tip geometry dependent artifacts and tip-sample convolution effect is essential for reliable AFM topographic characterization and dimensional metrology. Using rigid sapphire cylinder protrusions (diameter: 2.25 μm, height: 575 nm) as the model system, a systematic and quantitative study about the imaging artifacts of four types of tips-two different pyramidal tips, one tetrahedral tip and one super sharp whisker tip-is carried out through comparing tip geometry dependent variations in AFM topography of cylinders and constructing the rigid tip-cylinder convolution models. We found that the imaging artifacts and the tip-sample convolution effect are critically related to the actual inclination of the working cantilever, the tip geometry, and the obstructive contacts between the working tip's planes/edges and the cylinder. Artifact-free images can only be obtained provided that all planes and edges of the working tip are steeper than the cylinder sidewalls. The findings reported here will contribute to reliable AFM characterization of surface features of micron or hundreds of nanometers in height that are frequently met in semiconductor, biology and materials fields.

  1. Edgeworth Expansion Based Model for the Convolutional Noise pdf

    Directory of Open Access Journals (Sweden)

    Yonatan Rivlin

    2014-01-01

    Full Text Available Recently, the Edgeworth expansion up to order 4 was used to represent the convolutional noise probability density function (pdf in the conditional expectation calculations where the source pdf was modeled with the maximum entropy density approximation technique. However, the applied Lagrange multipliers were not the appropriate ones for the chosen model for the convolutional noise pdf. In this paper we use the Edgeworth expansion up to order 4 and up to order 6 to model the convolutional noise pdf. We derive the appropriate Lagrange multipliers, thus obtaining new closed-form approximated expressions for the conditional expectation and mean square error (MSE as a byproduct. Simulation results indicate hardly any equalization improvement with Edgeworth expansion up to order 4 when using optimal Lagrange multipliers over a nonoptimal set. In addition, there is no justification for using the Edgeworth expansion up to order 6 over the Edgeworth expansion up to order 4 for the 16QAM and easy channel case. However, Edgeworth expansion up to order 6 leads to improved equalization performance compared to the Edgeworth expansion up to order 4 for the 16QAM and hard channel case as well as for the case where the 64QAM is sent via an easy channel.

  2. Traffic sign recognition based on deep convolutional neural network

    Science.gov (United States)

    Yin, Shi-hao; Deng, Ji-cai; Zhang, Da-wei; Du, Jing-yuan

    2017-11-01

    Traffic sign recognition (TSR) is an important component of automated driving systems. It is a rather challenging task to design a high-performance classifier for the TSR system. In this paper, we propose a new method for TSR system based on deep convolutional neural network. In order to enhance the expression of the network, a novel structure (dubbed block-layer below) which combines network-in-network and residual connection is designed. Our network has 10 layers with parameters (block-layer seen as a single layer): the first seven are alternate convolutional layers and block-layers, and the remaining three are fully-connected layers. We train our TSR network on the German traffic sign recognition benchmark (GTSRB) dataset. To reduce overfitting, we perform data augmentation on the training images and employ a regularization method named "dropout". The activation function we employ in our network adopts scaled exponential linear units (SELUs), which can induce self-normalizing properties. To speed up the training, we use an efficient GPU to accelerate the convolutional operation. On the test dataset of GTSRB, we achieve the accuracy rate of 99.67%, exceeding the state-of-the-art results.

  3. Face recognition via Gabor and convolutional neural network

    Science.gov (United States)

    Lu, Tongwei; Wu, Menglu; Lu, Tao

    2018-04-01

    In recent years, the powerful feature learning and classification ability of convolutional neural network have attracted widely attention. Compared with the deep learning, the traditional machine learning algorithm has a good explanatory which deep learning does not have. Thus, In this paper, we propose a method to extract the feature of the traditional algorithm as the input of convolution neural network. In order to reduce the complexity of the network, the kernel function of Gabor wavelet is used to extract the feature from different position, frequency and direction of target image. It is sensitive to edge of image which can provide good direction and scale selection. The extraction of the image from eight directions on a scale are as the input of network that we proposed. The network have the advantage of weight sharing and local connection and texture feature of the input image can reduce the influence of facial expression, gesture and illumination. At the same time, we introduced a layer which combined the results of the pooling and convolution can extract deeper features. The training network used the open source caffe framework which is beneficial to feature extraction. The experiment results of the proposed method proved that the network structure effectively overcame the barrier of illumination and had a good robustness as well as more accurate and rapid than the traditional algorithm.

  4. Nuclear norm regularized convolutional Max Pos@Top machine

    KAUST Repository

    Li, Qinfeng

    2016-11-18

    In this paper, we propose a novel classification model for the multiple instance data, which aims to maximize the number of positive instances ranked before the top-ranked negative instances. This method belongs to a recently emerged performance, named as Pos@Top. Our proposed classification model has a convolutional structure that is composed by four layers, i.e., the convolutional layer, the activation layer, the max-pooling layer and the full connection layer. In this paper, we propose an algorithm to learn the convolutional filters and the full connection weights to maximize the Pos@Top measure over the training set. Also, we try to minimize the rank of the filter matrix to explore the low-dimensional space of the instances in conjunction with the classification results. The rank minimization is conducted by the nuclear norm minimization of the filter matrix. In addition, we develop an iterative algorithm to solve the corresponding problem. We test our method on several benchmark datasets. The experimental results show the superiority of our method compared with other state-of-the-art Pos@Top maximization methods.

  5. Measurements of the frontal and prefrontal lobe volumes by three dimensional magnetic resonance imaging scan. III. Analysis of sex differences with advanced age

    Energy Technology Data Exchange (ETDEWEB)

    Kanemura, Hideaki; Aihara, Masao; Nakazawa, Shinpei [Yamanashi Medical Univ., Tamaho (Japan)

    2002-09-01

    To determine whether there is sex difference in the growth of the frontal and prefrontal lobes, we quantitatively measured the volume of these lobes by three dimensional (3-D) MRI in healthy 12 males (5 months to 39 years) and six females (1 year 11 months to 27 years). The left and right lobes were studied separately. The 3-D MRI data were acquired by the fast spoiled gradient recalled (SPGR) sequence using a 1.5 T MR imager. The frontal and prefrontal lobe volumes were measured by the volume measurement function of the Workstation. In males, the left to right ratio (L/R ratio) of the frontal and prefrontal lobes increased with age. On the contrary, in females, L/R ratio of the frontal and prefrontal lobes showed no significant change with advancing age. These results highlighted sex-specific maturational changes of the frontal and prefrontal lobes and suggested that quantitative data on the frontal and prefrontal lobe are important in interpreting brain abnormalities in children with developmental disorders. (author)

  6. Measurements of the frontal and prefrontal lobe volumes by three dimensional magnetic resonance imaging scan. III. Analysis of sex differences with advanced age

    International Nuclear Information System (INIS)

    Kanemura, Hideaki; Aihara, Masao; Nakazawa, Shinpei

    2002-01-01

    To determine whether there is sex difference in the growth of the frontal and prefrontal lobes, we quantitatively measured the volume of these lobes by three dimensional (3-D) MRI in healthy 12 males (5 months to 39 years) and six females (1 year 11 months to 27 years). The left and right lobes were studied separately. The 3-D MRI data were acquired by the fast spoiled gradient recalled (SPGR) sequence using a 1.5 T MR imager. The frontal and prefrontal lobe volumes were measured by the volume measurement function of the Workstation. In males, the left to right ratio (L/R ratio) of the frontal and prefrontal lobes increased with age. On the contrary, in females, L/R ratio of the frontal and prefrontal lobes showed no significant change with advancing age. These results highlighted sex-specific maturational changes of the frontal and prefrontal lobes and suggested that quantitative data on the frontal and prefrontal lobe are important in interpreting brain abnormalities in children with developmental disorders. (author)

  7. Electrophysiological and behavioral effects of frontal transcranial direct current stimulation on cognitive fatigue in multiple sclerosis.

    Science.gov (United States)

    Fiene, Marina; Rufener, Katharina S; Kuehne, Maria; Matzke, Mike; Heinze, Hans-Jochen; Zaehle, Tino

    2018-03-01

    Fatigue is one of the most common and debilitating symptoms affecting patients with multiple sclerosis (MS). Sustained cognitive effort induces cognitive fatigue, operationalized as subjective exhaustion and fatigue-related objective alertness decrements with time-on-task. During prolonged cognitive testing, MS patients show increased simple reaction times (RT) accompanied by lower amplitudes and prolonged latencies of the P300 event-related potential. Previous studies suggested a major role of structural and functional abnormalities in the frontal cortex including a frontal hypo-activation in fatigue pathogenesis. In the present study we investigated the neuromodulatory effect of transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (DLPFC) on objective measures of fatigue-related decrements in cognitive performance in MS patients. P300 during an auditory oddball task and simple reaction times in an alertness test were recorded at baseline, during and after stimulation. Compared to sham, anodal tDCS caused an increase in P300 amplitude that persisted after the end of stimulation and eliminated the fatigue-related increase in RT over the course of a testing session. Our findings demonstrate that anodal tDCS over the left DLPFC can counteract performance decrements associated with fatigue thereby leading to an improvement in the patient's ability to cope with sustained cognitive demands. This provides causal evidence for the functional relevance of the left DLPFC in fatigue pathophysiology. The results indicate that tDCS-induced modulations of frontal activity can be an effective therapeutic option for the treatment of fatigue-related declines in cognitive performance in MS patients.

  8. Amygdala-frontal connectivity predicts internalizing symptom recovery among inpatient adolescents.

    Science.gov (United States)

    Venta, Amanda; Sharp, Carla; Patriquin, Michelle; Salas, Ramiro; Newlin, Elizabeth; Curtis, Kaylah; Baldwin, Philip; Fowler, Christopher; Frueh, B Christopher

    2018-01-01

    The possibility of using biological measures to predict the trajectory of symptoms among adolescent psychiatric inpatients has important implications. This study aimed to examine emotion regulation ability (measured via self-report) and a hypothesized proxy in resting-state functional connectivity [RSFC] between the amygdala and frontal brain regions as baseline predictors of internalizing symptom recovery during inpatient care. 196 adolescents (61% female; Mage = 15.20; SD = 1.48) completed the Achenbach Brief Problem Monitor (BPM) each week during their inpatient care. RSFC (n = 45) and self-report data of emotion regulation (n = 196) were collected at baseline. The average internalizing symptom score at admission was high (α 0 = 66.52), exceeding the BPM's clinical cut off score of 65. On average, internalizing symptom scores declined significantly, by 0.40 points per week (p = 0.004). While self-reported emotion regulation was associated with admission levels of internalizing problems, it did not predict change in symptoms. RSFC between left amygdala and left superior frontal gyrus was significantly associated with the intercept-higher connectivity was associated with higher internalizing at admission-and the slope- higher connectivity was associated with a more positive slope (i.e., less decline in symptoms). RSFC between the right amygdala and the left superior frontal gyrus was significantly, positively correlated with the slope parameter. Results indicate the potential of biologically-based measures that can be developed further for personalized care in adolescent psychiatry. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Frontal sinus asymmetry: Is it an effect of cranial asymmetry? X-ray analysis of 469 normal adult human frontal sinus

    Directory of Open Access Journals (Sweden)

    Ayhan Kanat

    2015-01-01

    Full Text Available Background and Aims: There is no study in the literature that investigates an asymmetric morphological feature of the frontal sinus (FS. Materials and Methods: Four hundred and sixty-nine consecutive direct X-rays of FSs were analyzed for the asymmetry between the right and left sides. When an asymmetry in the height and contour of the FS existed, this difference was quantified. Results: Of the 469 patients, X-rays of 402 patients (85.7%, there was an asymmetry between right and left sides of the FS. Of these 235 (50.1% were dominant on the left side, whereas 167 (35.6% were dominant on the right, the sinuses of remaining 67 patients (14.3% was symmetric. Statistical Analysis: The comparisons between parameters were performed using Wilkinson signed rank test. The relationship between handedness and sinus asymmetry was also examined by two proportions test. There is statistically significant difference between the dominance of left and right FS. Conclusions: Hemispheric dominance may have some effect (s of on sinus asymmetry of the human cranium. Surgeons sometimes enter the cranium through the FS and knowledge of asymmetric FS is important to minimize surgical complications.

  10. Selective activation of the superior frontal gyrus in task-switching: an event-related fNIRS study.

    Science.gov (United States)

    Cutini, Simone; Scatturin, Pietro; Menon, Enrica; Bisiacchi, Patrizia Silvia; Gamberini, Luciano; Zorzi, Marco; Dell'Acqua, Roberto

    2008-08-15

    In the task-switching paradigm, reaction time is longer and accuracy is worse in switch trials relative to repetition trials. This so-called switch cost has been ascribed to the engagement of control processes required to alternate between distinct stimulus-response mapping rules. Neuroimaging studies have reported an enhanced activation of the human lateral prefrontal cortex and the superior frontal gyrus during the task-switching paradigm. Whether neural activation in these regions is dissociable and associated with separable cognitive components of task switching has been a matter of recent debate. We used multi-channel near-infrared spectroscopy (fNIRS) to measure brain cortical activity in a task-switching paradigm designed to avoid task differences, order predictability, and frequency effects. The results showed a generalized bilateral activation of the lateral prefrontal cortex and the superior frontal gyrus in both switch trials and repetition trials. To isolate the activity selectively associated with the task-switch, the overall activity recorded during repetition trials was subtracted from the activity recorded during switch trials. Following subtraction, the remaining activity was entirely confined to the left portion of the superior frontal gyrus. The present results suggest that factors associated with load and maintenance of distinct stimulus-response mapping rules in working memory are likely contributors to the activation of the lateral prefrontal cortex, whereas only activity in the left superior frontal gyrus can be linked unequivocally to switching between distinct cognitive tasks.

  11. Diagnostic electrocardiographic dyad criteria of emphysema in left ventricular hypertrophy.

    Science.gov (United States)

    Lanjewar, Swapnil S; Chhabra, Lovely; Chaubey, Vinod K; Joshi, Saurabh; Kulkarni, Ganesh; Kothagundla, Chandrasekhar; Kaul, Sudesh; Spodick, David H

    2013-01-01

    The electrocardiographic diagnostic dyad of emphysema, namely a combination of the frontal vertical P-vector and a narrow QRS duration, can serve as a quasidiagnostic marker for emphysema, with specificity close to 100%. We postulated that the presence of left ventricular hypertrophy in emphysema may affect the sensitivity of this electrocardiographic criterion given that left ventricular hypertrophy generates prominent left ventricular forces and may increase the QRS duration. We reviewed the electrocardiograms and echocardiograms for 73 patients with emphysema. The patients were divided into two groups based on the presence or absence of echocardiographic evidence of left ventricular hypertrophy. The P-vector, QRS duration, and forced expiratory volume in one second (FEV1) were computed and compared between the two subgroups. There was no statistically significant difference in qualitative lung function (FEV1) between the subgroups. There was no statistically significant difference in mean P-vector between the subgroups. The mean QRS duration was significantly longer in patients with left ventricular hypertrophy as compared with those without left ventricular hypertrophy. The presence of left ventricular hypertrophy may not affect the sensitivity of the P-vector verticalization when used as a lone criterion for diagnosing emphysema. However, the presence of left ventricular hypertrophy may significantly reduce the sensitivity of the electrocardiographic diagnostic dyad in emphysema, as it causes a widening of the QRS duration.

  12. Frontal sinus revision rate after nasal polyposis surgery including frontal recess clearance and middle turbinectomy: A long-term analysis.

    Science.gov (United States)

    Benkhatar, Hakim; Khettab, Idir; Sultanik, Philippe; Laccourreye, Ollivier; Bonfils, Pierre

    2018-08-01

    To determine the frontal sinus revision rate after nasal polyposis (NP) surgery including frontal recess clearance (FRC) and middle turbinectomy (MT), to search for predictive factors and to analyse surgical management. Longitudinal analysis of 153 patients who consecutively underwent bilateral sphenoethmoidectomy with FRC and MT for NP with a minimum follow-up of 7 years. Decision of revision surgery was made in case of medically refractory chronic frontal sinusitis or frontal mucocele. Univariate and multivariate analysis incorporating clinical and radiological variables were performed. The frontal sinus revision rate was 6.5% (10/153). The mean time between the initial procedure and revision surgery was 3 years, 10 months. Osteitis around the frontal sinus outflow tract (FSOT) was associated with a higher risk of frontal sinus revision surgery (p=0.01). Asthma and aspirin intolerance did not increase the risk, as well as frontal sinus ostium diameter or residual frontoethmoid cells. Among revised patients, 60% required multiple procedures and 70% required frontal sinus ostium enlargement. Our long-term study reports that NP surgery including FRC and MT is associated with a low frontal sinus revision rate (6.5%). Patients developing osteitis around the FSOT have a higher risk of frontal sinus revision surgery. As mucosal damage can lead to osteitis, FSOT mucosa should be preserved during initial NP surgery. However, as multiple procedures are common among NP patients requiring frontal sinus revision, frontal sinus ostium enlargement should be considered during first revision in the hope of reducing the need of further revisions. Copyright © 2018 Elsevier B.V. All rights reserved.

  13. Influence of trait behavioral inhibition and behavioral approach motivation systems on the LPP and frontal asymmetry to anger pictures.

    Science.gov (United States)

    Gable, Philip A; Poole, Bryan D

    2014-02-01

    Behavioral approach and avoidance are fundamental to the experience of emotion and motivation, but the motivational system associated with anger is not well established. Some theories posit that approach motivational processes underlie anger, whereas others posit that avoidance motivational processes underlie anger. The current experiment sought to address whether traits related to behavioral approach or avoidance influence responses to anger stimuli using multiple measures: ERP, electroencephalographic (EEG) α-asymmetry and self-report. After completing the behavioral inhibition system/behavioral approach system (BIS/BAS) scales, participants viewed anger pictures and neutral pictures. BAS predicted larger late positive potentials (LPPs) to anger pictures, but not to neutral pictures. In addition, BAS predicted greater left-frontal asymmetry to anger pictures. Moreover, larger LPPs to anger pictures related to greater left-frontal EEG asymmetry during anger pictures. These results suggest that trait approach motivation relates to neurophysiological responses of anger.

  14. Pott's Puffy Tumor Arising from Frontal Sinusitis

    Energy Technology Data Exchange (ETDEWEB)

    Lim, Ji Yeon; Kang, Hyun Koo [Seoul Veterans Hospital, Seoul (Korea, Republic of)

    2010-02-15

    Pott's puffy tumor is an extremely rare and potentially life-threatening complication of frontal sinusitis. We report a case of a 64-year-old man who presented at our emergency department with mild tenderness on the glabellar area and diplopia. Computed Tomography (CT) revealed frontal sinusitis and osteomyelitis of the frontal bone. Following sinus trephination and long-term antibiotic therapy, the patient achieved a complete recovery.

  15. Convolution equations on lattices: periodic solutions with values in a prime characteristic field

    OpenAIRE

    Zaidenberg, Mikhail

    2006-01-01

    These notes are inspired by the theory of cellular automata. A linear cellular automaton on a lattice of finite rank or on a toric grid is a discrete dinamical system generated by a convolution operator with kernel concentrated in the nearest neighborhood of the origin. In the present paper we deal with general convolution operators. We propose an approach via harmonic analysis which works over a field of positive characteristic. It occurs that a standard spectral problem for a convolution op...

  16. Left heart ventricular angiography

    Science.gov (United States)

    ... blood vessels. These x-ray pictures create a "movie" of the left ventricle as it contracts rhythmically. ... 22578925 www.ncbi.nlm.nih.gov/pubmed/22578925 . Review Date 9/26/2016 Updated by: Michael A. ...

  17. Left heart catheterization

    Science.gov (United States)

    Catheterization - left heart ... to help guide the catheters up into your heart and arteries. Dye (sometimes called "contrast") will be ... in the blood vessels that lead to your heart. The catheter is then moved through the aortic ...

  18. Study on the development of frontal sinuses by morphometric analysis of the skull - doi: 10.4025/actascibiolsci.v35i2.13334

    Directory of Open Access Journals (Sweden)

    Carolina Peixoto Magalhães

    2013-05-01

    Full Text Available The frontal sinuses are cranial areas of clinical, forensic and pathology importance whose development mechanisms are still poorly defined. Nasal airflow and brain development are two of the main theories. Current analysis debates whether they are the real determinants of frontal sinuses growth, which may be proved by the skull’s morphometric analysis. Four groups of measures related to the external cranial architecture, the pyriform aperture, orbital cavities and frontal sinuses were defined. Thirty-three skulls of individuals, mean age 68 years, from the Laboratory of Anatomy of the Academic Centre of Victoria – UFPE – Brazil, were used. Statistical analysis showed total agenesis of the frontal sinus in 18.2% of the skulls. There was significant correlation between the development of the right frontal sinus and the pyriform aperture, and between the left frontal sinus and two cranial measurements (p ≤ 0.05. Significant differences between mean of pyriform aperture areas of the skulls with or without sinuses were also reported (p ≤ 0.01. Results supported the fact that there was a modulation activity by nasal aeration and brain formation in the development of frontal sinuses.

  19. Frontal Lobe Function in Chess Players

    Directory of Open Access Journals (Sweden)

    Vahid Nejati

    2012-05-01

    Full Text Available Chess is considered as a cognitive game because of severe engagement of the mental resources during playing. The purpose of this study is evaluation of frontal lobe function of chess players with matched non-players. Wisconsin Card Sorting Test (WCST data showed no difference between the player and non-player groups in preservation error and completed categories but surprisingly showed significantly lower grade of the player group in correct response. Our data reveal that chess players dont have any preference in any stage of Stroop test. Chess players dont have any preference in selective attention, inhibition and executive cognitive function. Chess players' have lower shifting abilities than non-players.

  20. Frontal lobe function in chess players.

    Science.gov (United States)

    Nejati, Majid; Nejati, Vahid

    2012-01-01

    Chess is considered as a cognitive game because of severe engagement of the mental resources during playing. The purpose of this study is evaluation of frontal lobe function of chess players with matched non-players. Wisconsin Card Sorting Test (WCST) data showed no difference between the player and non-player groups in preservation error and completed categories but surprisingly showed significantly lower grade of the player group in correct response. Our data reveal that chess players don't have any preference in any stage of Stroop test. Chess players don't have any preference in selective attention, inhibition and executive cognitive function. Chess players' have lower shifting abilities than non-players.

  1. Conceptual control across modalities: graded specialisation for pictures and words in inferior frontal and posterior temporal cortex

    OpenAIRE

    Krieger-Redwood, Katya; Teige, Catarina; Davey, James; Hymers, Mark; Jefferies, Elizabeth

    2015-01-01

    Controlled semantic retrieval to words elicits co-activation of inferior frontal (IFG) and left posterior temporal cortex (pMTG), but research has not yet established (i) the distinct contributions of these regions or (ii) whether the same processes are recruited for non-verbal stimuli. Words have relatively flexible meanings – as a consequence, identifying the context that links two specific words is relatively demanding. In contrast, pictures are richer stimuli and their precise meaning is ...

  2. Frontal parenchymal atrophy measures in multiple sclerosis.

    Science.gov (United States)

    Locatelli, Laura; Zivadinov, Robert; Grop, Attilio; Zorzon, Marino

    2004-10-01

    The aim of this study was to establish whether, in a cross-sectional study, the normalized measures of whole and regional brain atrophy correlate better with tests assessing the cognitive function than the absolute brain atrophy measures. The neuropsychological performances and disability have been assessed in 39 patients with relapsing-remitting multiple sclerosis (MS). T1- and T2-lesion load (LL) of total brain and frontal lobes (FLs) were measured using a reproducible semiautomated technique. The whole brain volume and the regional brain parenchymal volume (RBPV) of FLs were obtained using a computerized interactive program, which incorporates semiautomated and automated segmentation processes. Normalized measures of brain atrophy, i.e., brain parenchymal fraction (BPF) and regional brain parenchymal fraction (RBPF) of FLs, were calculated. The scan-rescan, inter- and intrarater coefficient of variation (COV) and intraclass correlation coefficient (ICC) have been estimated. The RBPF of FLs showed an acceptable level of reproducibility which ranged from 1.7% for intrarater variability to 3.2% for scan-rescan variability. The mean ICC was 0.88 (CI 0.82-0.93). The RBPF of FLs demonstrated stronger magnitudes of correlation with neuropsychological functioning, disability and quantitative MRI lesion measures than RBPV. These differences were statistically significant: PColor Word Interference test, Pcognitive functions, whereas BPAV did not. The correlation analysis results were supported by the results of multiple regression analysis which showed that only the normalized brain atrophy measures were associated with tests exploring the cognitive functions. These data suggest that RBPF is a reproducible and sensitive method for measuring frontal parenchymal atrophy. The normalized measures of whole and regional brain parenchymal atrophy should be preferred to absolute measures in future studies that correlate neuropsychological performances and brain atrophy measures

  3. Performance Analysis of DPSK Signals with Selection Combining and Convolutional Coding in Fading Channel

    National Research Council Canada - National Science Library

    Ong, Choon

    1998-01-01

    The performance analysis of a differential phase shift keyed (DPSK) communications system, operating in a Rayleigh fading environment, employing convolutional coding and diversity processing is presented...

  4. Model selection for convolutive ICA with an application to spatiotemporal analysis of EEG

    DEFF Research Database (Denmark)

    Dyrholm, Mads; Makeig, S.; Hansen, Lars Kai

    2007-01-01

    We present a new algorithm for maximum likelihood convolutive independent component analysis (ICA) in which components are unmixed using stable autoregressive filters determined implicitly by estimating a convolutive model of the mixing process. By introducing a convolutive mixing model...... for the components, we show how the order of the filters in the model can be correctly detected using Bayesian model selection. We demonstrate a framework for deconvolving a subspace of independent components in electroencephalography (EEG). Initial results suggest that in some cases, convolutive mixing may...

  5. Use of Frontal Sinus and Nasal Septum Pattern as an Aid in Personal Identification and Determination of Gender: A Radiographic Study.

    Science.gov (United States)

    Verma, Kavita; Nahar, Prashant; Singh, Mohit Pal; Mathur, Hemant; Bhuvaneshwari, S

    2017-01-01

    Personal identification and gender determination of unknown person has a vital importance in forensic investigation. Human skull radiography is a useful tool in human identification in natural disaster, in any accidents such as fire accident and road traffic accident where body remains become degraded or severely destroyed. Present study was performed to evaluate the measurement of frontal sinus, uniqueness of various pattern of nasal septum when combined with frontal sinus observed on posterio anterior cephalogram for sex determination as well as personal identification. A total of 80 individuals, 40 males and 40 females, between the age ranges of 18-30 years were selected. The selected individuals had their Posterio Anterior (PA) cephalogram performed after taking their informed consent. Right and left areas and the maximum height and width of the frontal sinus were determined and septum patterns were evaluated and both patterns were also combined and compared. The radiographs were taken on Xtropan 2000 OPG X-ray machine with cephalography attachment and KODAK CR 7400 digital radiography system. Mean and SD values of the greatest height and width of frontal sinus in male and female patients were thus evaluated. The mean values of the frontal sinus were greater in males and the left area was larger than the right area, based on student's t-test at the 5% level of significance. The combination of Frontal Sinus Patterns and Nasal Septum Patterns (FP+NSP) were assessed and found that there were nine classifiable patterns in 26 (32.5%) individuals (12 males and 14 females), each of which had common representations in more than one individual. Besides these patterns, there were unique unclassifiable patterns in 54 (67.5%) individuals. The present study supports the use of radiographic evaluation of frontal sinus dimensions, frontal sinus patterns, nasal septum deviations and the combination FP+NSP patterns for personal identification and gender determination in

  6. Frontal-insula gray matter deficits in first-episode medication-naïve patients with major depressive disorder.

    Science.gov (United States)

    Lai, Chien-Han; Wu, Yu-Te

    2014-05-01

    This study is designed to investigate the gray matter volume (GMV) deficits in patients with first-episode medication-naïve major depressive disorder (MDD). We enrolled 38 patients with first-episode medication-naïve MDD and 27 controls in this project. Voxel-based morphometry was used to compare GMV differences between two groups. Besides, the relationship between GMV of patients and the severity of clinical symptoms was estimated to confirm the role of GMV deficits in clinical symptoms. The correlation between total GMV and illness duration was also performed to elucidate the impacts of untreated duration on the GMV. We found that first-episode medication-naïve MDD patients had significant GMV deficits in bilateral superior frontal gyri, left middle frontal gyrus, left medial frontal gyrus and left insula. The GMV of patient group was negatively correlated with the severity of clinical symptoms and the illness duration. A pattern of GMV deficits in fronto-insula might represent the biomarker for first-episode medication-naïve MDD. Copyright © 2014 Elsevier B.V. All rights reserved.

  7. Are personality traits of juvenile myoclonic epilepsy related to frontal lobe dysfunctions? A proton MRS study.

    Science.gov (United States)

    de Araújo Filho, Gerardo Maria; Lin, Katia; Lin, Jaime; Peruchi, Mirella M; Caboclo, Luís Otávio S F; Guaranha, Mirian S B; Guilhoto, Laura M F F; Carrete, Henrique; Yacubian, Elza Márcia T

    2009-05-01

    Personality traits characterized by emotional instability and immaturity, unsteadiness, lack of discipline, hedonism, frequent and rapid mood changes, and indifference toward one's disease have been associated with patients who have juvenile myoclonic epilepsy (JME). Literature data demonstrate worse seizure control and more psychosocial dysfunctions among patients with JME who have those traits. In this controlled study we performed a correlation analysis of psychiatric scores with magnetic resonance spectroscopy (MRS) values across JME patients, aiming to verify the existence of a possible relation between frontal lobe dysfunction and the prevalence of personality disorders (PDs) in JME. Sixteen JME patients with cluster B PDs, 41 JME patients without any psychiatric disorder, and 30 healthy controls were submitted to a psychiatric evaluation and to a quantitative multivoxel MRS of thalamus; insula; cingulate gyrus; striatum; and frontal, parietal, and occipital lobes. Groups were homogeneous according to age, gender, and manual dominance. Psychiatric evaluation was performed through the Scheduled Clinical Interview for DSM-IV, Axis I and II (SCID I and II, respectively). A significant reduction of N-acetyl-aspartate over creatinine (NAA/Cr) ratio was observed mainly in the left frontal lobe in the JME and PD group. In addition, a significant increase in the glutamate-glutamine over creatinine GLX/Cr ratio was also observed in this referred region in the same group. These data support the hypothesis that PDs in JME could represent neuronal dysfunction and possibly a more severe form of this epileptic syndrome.

  8. A Postmortem Study of Frontal and Temporal Gyri Thickness and Cell Number in Human Obesity.

    Science.gov (United States)

    Gómez-Apo, Erick; García-Sierra, Adrián; Silva-Pereyra, Juan; Soto-Abraham, Virgilia; Mondragón-Maya, Alejandra; Velasco-Vales, Verónica; Pescatello, Linda S

    2018-01-01

    This study aimed to compare cortex thickness and neuronal cell density in postmortem brain tissue from people with overweight or obesity and normal weight. The cortex thickness and neuron density of eight donors with overweight or obesity (mean = 31.6 kg/m 2 ; SD = 4.35; n = 8; 6 male) and eight donors with normal weight (mean = 21.8 kg/m 2 ; SD = 1.5; n = 8; 5 male) were compared. All participants were Mexican and lived in Mexico City. Randomly selected thickness measures of different cortex areas from the frontal and temporal lobes were analyzed based on high-resolution real-size photographs. A histological analysis of systematic-random fields was used to quantify the number of neurons in postmortem left and right of the first, second, and third gyri of frontal and temporal lobe brain samples. No statistical difference was found in cortical thickness between donors with overweight or obesity and individuals with normal weight. A smaller number of neurons was found among the donors with overweight or obesity than the donors with normal weight at different frontal and temporal areas. A lower density of neurons is associated with overweight or obesity. The morphological basis for structural brain changes in obesity requires further investigation. © 2017 The Obesity Society.

  9. Motivated malleability: Frontal cortical asymmetry predicts the susceptibility to social influence.

    Science.gov (United States)

    Schnuerch, Robert; Pfattheicher, Stefan

    2017-07-16

    Humans, just as many other animals, regulate their behavior in terms of approaching stimuli associated with pleasure and avoiding stimuli linked to harm. A person's current and chronic motivational direction - that is, approach versus avoidance orientation - is reliably reflected in the asymmetry of frontal cortical low-frequency oscillations. Using resting electroencephalography (EEG), we show that frontal asymmetry is predictive of the tendency to yield to social influence: Stronger right- than left-side frontolateral activation during a resting-state session prior to the experiment was robustly associated with a stronger inclination to adopt a peer group's judgments during perceptual decision-making (Study 1). We posit that this reflects the role of a person's chronic avoidance orientation in socially adjusted behavior. This claim was strongly supported by additional survey investigations (Studies 2a, 2b, 2c), all of which consistently revealed that trait avoidance was positively linked to the susceptibility to social influence. The present contribution thus stresses the relevance of chronic avoidance orientation in social conformity, refining (yet not contradicting) the longstanding view that socially influenced behavior is motivated by approach-related goals. Moreover, our findings valuably underscore and extend our knowledge on the association between frontal cortical asymmetry and a variety of psychological variables.

  10. Occipital cortex of blind individuals is functionally coupled with executive control areas of frontal cortex.

    Science.gov (United States)

    Deen, Ben; Saxe, Rebecca; Bedny, Marina

    2015-08-01

    In congenital blindness, the occipital cortex responds to a range of nonvisual inputs, including tactile, auditory, and linguistic stimuli. Are these changes in functional responses to stimuli accompanied by altered interactions with nonvisual functional networks? To answer this question, we introduce a data-driven method that searches across cortex for functional connectivity differences across groups. Replicating prior work, we find increased fronto-occipital functional connectivity in congenitally blind relative to blindfolded sighted participants. We demonstrate that this heightened connectivity extends over most of occipital cortex but is specific to a subset of regions in the inferior, dorsal, and medial frontal lobe. To assess the functional profile of these frontal areas, we used an n-back working memory task and a sentence comprehension task. We find that, among prefrontal areas with overconnectivity to occipital cortex, one left inferior frontal region responds to language over music. By contrast, the majority of these regions responded to working memory load but not language. These results suggest that in blindness occipital cortex interacts more with working memory systems and raise new questions about the function and mechanism of occipital plasticity.

  11. Effective Connectivity Hierarchically Links Temporoparietal and Frontal Areas of the Auditory Dorsal Stream with the Motor Cortex Lip Area during Speech Perception

    Science.gov (United States)

    Murakami, Takenobu; Restle, Julia; Ziemann, Ulf

    2012-01-01

    A left-hemispheric cortico-cortical network involving areas of the temporoparietal junction (Tpj) and the posterior inferior frontal gyrus (pIFG) is thought to support sensorimotor integration of speech perception into articulatory motor activation, but how this network links with the lip area of the primary motor cortex (M1) during speech…

  12. Results of a pilot study on the involvement of bilateral inferior frontal gyri in emotional prosody perception: an rTMS study

    NARCIS (Netherlands)

    Hoekert, Marjolijn; Vingerhoets, Guy; Aleman, Andre

    2010-01-01

    Background: The right hemisphere may play an important role in paralinguistic features such as the emotional melody in speech. The extent of this involvement however is unclear. Imaging studies have shown involvement of both left and right inferior frontal gyri in emotional prosody perception. The

  13. SPM analysis of brain perfusion SPECT and F-18 FDG PET in the Korean autosomal dominant nocturnal frontal lobe epilepsy family

    International Nuclear Information System (INIS)

    Won, Kyoung Sook; Zeon, Seok Kil

    2004-01-01

    This study attempted to investigate the specific pattern of brain perfusion and glucose metabolism in the Korean autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE) family. Using Tc-99m ECD brain perfusion SPECT. we assessed brain perfusion in 6 patients at interictal period and 5 patients at ictal period. Interictal F-18 FDG PET was performed on 6 affected family members. The scans were statistically analyzed by using statistical parametric mapping (SPM99). The data of the affected family members were compared to those of the control subjects. Interictal F-18 FDG PET SPM group analysis showed decreased glucose metabolism over the left middle and superior frontal gyri and the left central regions including the anterior parietal lobe. There was a less pronounced decrease in glucose uptake in the right anterior superior frontal gyrus. Interictal brain perfusion SPECT SPM group analysis showed similar pattern of decreased perfusion compared to those of interictal F-18 FDG PET. Ictal brain perfusion SPECT SPM group analysis revealed increased perfusion over the left pre-and postcentral gyri and less pronounced increased perfusion in the right postcentral gyrus. lnterictal F -18 PET and brain perfusion SPECT SPM group analysis suggest that major abnormalities of ADNFLE family are in the left frontal lobe. These findings may be helpful to elucidate the pathophysiological mechanism of this rare disease entity

  14. SPM analysis of brain perfusion SPECT and F-18 FDG PET in the Korean autosomal dominant nocturnal frontal lobe epilepsy family

    Energy Technology Data Exchange (ETDEWEB)

    Won, Kyoung Sook; Zeon, Seok Kil [Keimyung University Dongsan Medical Center, Daegu (Korea, Republic of)

    2004-07-01

    This study attempted to investigate the specific pattern of brain perfusion and glucose metabolism in the Korean autosomal dominant nocturnal frontal lobe epilepsy (ADNFLE) family. Using Tc-99m ECD brain perfusion SPECT. we assessed brain perfusion in 6 patients at interictal period and 5 patients at ictal period. Interictal F-18 FDG PET was performed on 6 affected family members. The scans were statistically analyzed by using statistical parametric mapping (SPM99). The data of the affected family members were compared to those of the control subjects. Interictal F-18 FDG PET SPM group analysis showed decreased glucose metabolism over the left middle and superior frontal gyri and the left central regions including the anterior parietal lobe. There was a less pronounced decrease in glucose uptake in the right anterior superior frontal gyrus. Interictal brain perfusion SPECT SPM group analysis showed similar pattern of decreased perfusion compared to those of interictal F-18 FDG PET. Ictal brain perfusion SPECT SPM group analysis revealed increased perfusion over the left pre-and postcentral gyri and less pronounced increased perfusion in the right postcentral gyrus. lnterictal F -18 PET and brain perfusion SPECT SPM group analysis suggest that major abnormalities of ADNFLE family are in the left frontal lobe. These findings may be helpful to elucidate the pathophysiological mechanism of this rare disease entity.

  15. Accelerated Time-Domain Modeling of Electromagnetic Pulse Excitation of Finite-Length Dissipative Conductors over a Ground Plane via Function Fitting and Recursive Convolution

    Energy Technology Data Exchange (ETDEWEB)

    Campione, Salvatore [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Warne, Larry K. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sainath, Kamalesh [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Basilio, Lorena I. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-10-01

    In this report we overview the fundamental concepts for a pair of techniques which together greatly hasten computational predictions of electromagnetic pulse (EMP) excitation of finite-length dissipative conductors over a ground plane. In a time- domain, transmission line (TL) model implementation, predictions are computationally bottlenecked time-wise, either for late-time predictions (about 100ns-10000ns range) or predictions concerning EMP excitation of long TLs (order of kilometers or more ). This is because the method requires a temporal convolution to account for the losses in the ground. Addressing this to facilitate practical simulation of EMP excitation of TLs, we first apply a technique to extract an (approximate) complex exponential function basis-fit to the ground/Earth's impedance function, followed by incorporating this into a recursion-based convolution acceleration technique. Because the recursion-based method only requires the evaluation of the most recent voltage history data (versus the entire history in a "brute-force" convolution evaluation), we achieve necessary time speed- ups across a variety of TL/Earth geometry/material scenarios. Intentionally Left Blank

  16. What makes a frontal area of primate brain the frontal eye field?

    Directory of Open Access Journals (Sweden)

    Pierre ePouget

    2015-05-01

    Full Text Available The frontal eye field region (FEF of the oculomotor pathways has been intensely studied. The primary goal of this review is to illustrate the phylogenetic displacement of the FEF locus in primate species. The locus is arrayed along the arcuate sulcus in monkeys and abuts into the primary motor strip region in humans. The strengths and limitations of the various functional, anatomical and histological methodologies used to identify such regions are also discussed.

  17. Frontal Fibers Connecting the Superior Frontal Gyrus to Broca Area: A Corticocortical Evoked Potential Study.

    Science.gov (United States)

    Ookawa, Satoshi; Enatsu, Rei; Kanno, Aya; Ochi, Satoko; Akiyama, Yukinori; Kobayashi, Tamaki; Yamao, Yukihiro; Kikuchi, Takayuki; Matsumoto, Riki; Kunieda, Takeharu; Mikuni, Nobuhiro

    2017-11-01

    The frontal aslant tract is a deep frontal pathway connecting the superior frontal gyrus (SFG) to Broca area. This fiber is assumed to be associated with language functions, especially speech initiation and spontaneity. The aim of this study was to electrophysiologically investigate this network using corticocortical evoked potentials (CCEPs). This study enrolled 8 patients with brain tumors or medically intractable focal epilepsies who underwent frontal craniotomy over the language-dominant side. All patients underwent CCEP recordings during tumor resection or during invasive evaluation for epilepsy surgery. Alternating 1-Hz electrical stimuli were delivered to pars opercularis (pO) and pars triangularis (pT), corresponding to Broca area, and SFG via the subdural grid electrodes with intensity of 10 mA. Electrocorticograms from SFG and pO/pT time-locked to 50 stimuli were averaged in each trial to obtain CCEP responses. In all patients, stimulation of pO/pT induced CCEP responses in SFG. CCEP responses were recorded in lateral SFG in 5 patients and in supplementary motor areas in 4 patients. Reciprocality was observed in 7 patients in the stimulation of SFG. CCEP responses were significantly faster at SFG from pO/pT than at pO/pT from SFG (Wilcoxon signed rank test, P = 0.028). The present study demonstrated a corticocortical network connecting Broca areas and SFG in a reciprocal manner. Our findings might provide new insight into language and motor integration. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Activation of extrastriate and frontal cortical areas by visual words and word-like stimuli

    International Nuclear Information System (INIS)

    Petersen, S.E.; Fox, P.T.; Snyder, A.Z.; Raichle, M.E.

    1990-01-01

    Visual presentation of words activates extrastriate regions of the occipital lobes of the brain. When analyzed by positron emission tomography (PET), certain areas in the left, medial extrastriate visual cortex were activated by visually presented pseudowords that obey English spelling rules, as well as by actual words. These areas were not activated by nonsense strings of letters or letter-like forms. Thus visual word form computations are based on learned distinctions between words and nonwords. In addition, during passive presentation of words, but not pseudowords, activation occurred in a left frontal area that is related to semantic processing. These findings support distinctions made in cognitive psychology and computational modeling between high-level visual and semantic computations on single words and describe the anatomy that may underlie these distinctions

  19. Frontally confined versus frontally emergent submarine landslides: A 3D seismic characterisation

    Energy Technology Data Exchange (ETDEWEB)

    Frey-Martinez, Jose; Cartwright, Joe; James, David [3DLab. School of Earth, Ocean and Planetary Sciences, Cardiff University, P.O. Box 914, Cardiff CF10 3YE (United Kingdom)

    2006-06-15

    Three-dimensional (3D) seismic data from the continental margin offshore Israel (Eastern Mediterranean) have been used to analyse the compressional structures within the toe regions of two major buried submarine landslides: the ISC and the T20. Both landslides are developed within a Plio-Pleistocene slope succession composed predominately of claystones, limestones and siltstones. The high spatial resolution provided by the seismic data has allowed a detailed analysis of the geometries and deformational structures within the toe regions of the two landslides, and this has been used to develop a mechanical model for their development. Importantly, it has been recognised that submarine landslides may be divided into two main types according to their form of frontal emplacement: frontally confined and frontally emergent. In the former, the landslide undergoes a restricted downslope translation and does not overrun the undeformed downslope strata. In the latter, much larger downslope translation occurs because the landslide is able to ramp up from its original basal shear surface and translate in an unconfined manner over the seafloor. We propose that these two types of submarine landslides are end members of a continuum of gravity-driven slope failure processes, which extends from landslides where the headscarp is completely evacuated, to landslides where the material remains entirely within the headscarp. The differentiation of these two end members is of critical importance as their respective mechanisms of formation, downslope propagation and emplacement are significantly different, and hence need to be taken into consideration when analysing their respective kinematics. (author)

  20. Finding strong lenses in CFHTLS using convolutional neural networks

    Science.gov (United States)

    Jacobs, C.; Glazebrook, K.; Collett, T.; More, A.; McCarthy, C.

    2017-10-01

    We train and apply convolutional neural networks, a machine learning technique developed to learn from and classify image data, to Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging for the identification of potential strong lensing systems. An ensemble of four convolutional neural networks was trained on images of simulated galaxy-galaxy lenses. The training sets consisted of a total of 62 406 simulated lenses and 64 673 non-lens negative examples generated with two different methodologies. An ensemble of trained networks was applied to all of the 171 deg2 of the CFHTLS wide field image data, identifying 18 861 candidates including 63 known and 139 other potential lens candidates. A second search of 1.4 million early-type galaxies selected from the survey catalogue as potential deflectors, identified 2465 candidates including 117 previously known lens candidates, 29 confirmed lenses/high-quality lens candidates, 266 novel probable or potential lenses and 2097 candidates we classify as false positives. For the catalogue-based search we estimate a completeness of 21-28 per cent with respect to detectable lenses and a purity of 15 per cent, with a false-positive rate of 1 in 671 images tested. We predict a human astronomer reviewing candidates produced by the system would identify 20 probable lenses and 100 possible lenses per hour in a sample selected by the robot. Convolutional neural networks are therefore a promising tool for use in the search for lenses in current and forthcoming surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope.

  1. Left insular cortex and left SFG underlie prismatic adaptation effects on time perception: evidence from fMRI.

    Science.gov (United States)

    Magnani, Barbara; Frassinetti, Francesca; Ditye, Thomas; Oliveri, Massimiliano; Costantini, Marcello; Walsh, Vincent

    2014-05-15

    Prismatic adaptation (PA) has been shown to affect left-to-right spatial representations of temporal durations. A leftward aftereffect usually distorts time representation toward an underestimation, while rightward aftereffect usually results in an overestimation of temporal durations. Here, we used functional magnetic resonance imaging (fMRI) to study the neural mechanisms that underlie PA effects on time perception. Additionally, we investigated whether the effect of PA on time is transient or stable and, in the case of stability, which cortical areas are responsible of its maintenance. Functional brain images were acquired while participants (n=17) performed a time reproduction task and a control-task before, immediately after and 30 min after PA inducing a leftward aftereffect, administered outside the scanner. The leftward aftereffect induced an underestimation of time intervals that lasted for at least 30 min. The left anterior insula and the left superior frontal gyrus showed increased functional activation immediately after versus before PA in the time versus the control-task, suggesting these brain areas to be involved in the executive spatial manipulation of the representation of time. The left middle frontal gyrus showed an increase of activation after 30 min with respect to before PA. This suggests that this brain region may play a key role in the maintenance of the PA effect over time. Copyright © 2014. Published by Elsevier Inc.

  2. Fast space-varying convolution using matrix source coding with applications to camera stray light reduction.

    Science.gov (United States)

    Wei, Jianing; Bouman, Charles A; Allebach, Jan P

    2014-05-01

    Many imaging applications require the implementation of space-varying convolution for accurate restoration and reconstruction of images. Here, we use the term space-varying convolution to refer to linear operators whose impulse response has slow spatial variation. In addition, these space-varying convolution operators are often dense, so direct implementation of the convolution operator is typically computationally impractical. One such example is the problem of stray light reduction in digital cameras, which requires the implementation of a dense space-varying deconvolution operator. However, other inverse problems, such as iterative tomographic reconstruction, can also depend on the implementation of dense space-varying convolution. While space-invariant convolution can be efficiently implemented with the fast Fourier transform, this approach does not work for space-varying operators. So direct convolution is often the only option for implementing space-varying convolution. In this paper, we develop a general approach to the efficient implementation of space-varying convolution, and demonstrate its use in the application of stray light reduction. Our approach, which we call matrix source coding, is based on lossy source coding of the dense space-varying convolution matrix. Importantly, by coding the transformation matrix, we not only reduce the memory required to store it; we also dramatically reduce the computation required to implement matrix-vector products. Our algorithm is able to reduce computation by approximately factoring the dense space-varying convolution operator into a product of sparse transforms. Experimental results show that our method can dramatically reduce the computation required for stray light reduction while maintaining high accuracy.

  3. Is the Frontal Assessment Battery reliable in ALS patients?

    NARCIS (Netherlands)

    Raaphorst, J.; Beeldman, E.; Jaeger, B.; Schmand, B.A.; Berg, L.H. van den; Weikamp, J.G.; Schelhaas, H.J.; Visser, M. de; Haan, R.J. de

    2013-01-01

    The assessment of frontal functions in ALS patients is important because of the overlap with the behavioural variant of frontotemporal dementia (bvFTD). We investigated the applicability and reliability of the Frontal Assessment Battery (FAB) within a cohort of predominantly prevalent ALS patients.

  4. Non-frontal Model Based Approach to Forensic Face Recognition

    NARCIS (Netherlands)

    Dutta, A.; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    2012-01-01

    In this paper, we propose a non-frontal model based approach which ensures that a face recognition system always gets to compare images having similar view (or pose). This requires a virtual suspect reference set that consists of non-frontal suspect images having pose similar to the surveillance

  5. Fast Convolutional Sparse Coding in the Dual Domain

    KAUST Repository

    Affara, Lama Ahmed

    2017-09-27

    Convolutional sparse coding (CSC) is an important building block of many computer vision applications ranging from image and video compression to deep learning. We present two contributions to the state of the art in CSC. First, we significantly speed up the computation by proposing a new optimization framework that tackles the problem in the dual domain. Second, we extend the original formulation to higher dimensions in order to process a wider range of inputs, such as color inputs, or HOG features. Our results show a significant speedup compared to the current state of the art in CSC.

  6. Phase transitions in glassy systems via convolutional neural networks

    Science.gov (United States)

    Fang, Chao

    Machine learning is a powerful approach commonplace in industry to tackle large data sets. Most recently, it has found its way into condensed matter physics, allowing for the first time the study of, e.g., topological phase transitions and strongly-correlated electron systems. The study of spin glasses is plagued by finite-size effects due to the long thermalization times needed. Here we use convolutional neural networks in an attempt to detect a phase transition in three-dimensional Ising spin glasses. Our results are compared to traditional approaches.

  7. Visualizing Vector Fields Using Line Integral Convolution and Dye Advection

    Science.gov (United States)

    Shen, Han-Wei; Johnson, Christopher R.; Ma, Kwan-Liu

    1996-01-01

    We present local and global techniques to visualize three-dimensional vector field data. Using the Line Integral Convolution (LIC) method to image the global vector field, our new algorithm allows the user to introduce colored 'dye' into the vector field to highlight local flow features. A fast algorithm is proposed that quickly recomputes the dyed LIC images. In addition, we introduce volume rendering methods that can map the LIC texture on any contour surface and/or translucent region defined by additional scalar quantities, and can follow the advection of colored dye throughout the volume.

  8. Fast Convolutional Sparse Coding in the Dual Domain

    KAUST Repository

    Affara, Lama Ahmed; Ghanem, Bernard; Wonka, Peter

    2017-01-01

    Convolutional sparse coding (CSC) is an important building block of many computer vision applications ranging from image and video compression to deep learning. We present two contributions to the state of the art in CSC. First, we significantly speed up the computation by proposing a new optimization framework that tackles the problem in the dual domain. Second, we extend the original formulation to higher dimensions in order to process a wider range of inputs, such as color inputs, or HOG features. Our results show a significant speedup compared to the current state of the art in CSC.

  9. Salient regions detection using convolutional neural networks and color volume

    Science.gov (United States)

    Liu, Guang-Hai; Hou, Yingkun

    2018-03-01

    Convolutional neural network is an important technique in machine learning, pattern recognition and image processing. In order to reduce the computational burden and extend the classical LeNet-5 model to the field of saliency detection, we propose a simple and novel computing model based on LeNet-5 network. In the proposed model, hue, saturation and intensity are utilized to extract depth cues, and then we integrate depth cues and color volume to saliency detection following the basic structure of the feature integration theory. Experimental results show that the proposed computing model outperforms some existing state-of-the-art methods on MSRA1000 and ECSSD datasets.

  10. Traffic sign classification with dataset augmentation and convolutional neural network

    Science.gov (United States)

    Tang, Qing; Kurnianggoro, Laksono; Jo, Kang-Hyun

    2018-04-01

    This paper presents a method for traffic sign classification using a convolutional neural network (CNN). In this method, firstly we transfer a color image into grayscale, and then normalize it in the range (-1,1) as the preprocessing step. To increase robustness of classification model, we apply a dataset augmentation algorithm and create new images to train the model. To avoid overfitting, we utilize a dropout module before the last fully connection layer. To assess the performance of the proposed method, the German traffic sign recognition benchmark (GTSRB) dataset is utilized. Experimental results show that the method is effective in classifying traffic signs.

  11. Tandem mass spectrometry data quality assessment by self-convolution

    Directory of Open Access Journals (Sweden)

    Tham Wai

    2007-09-01

    Full Text Available Abstract Background Many algorithms have been developed for deciphering the tandem mass spectrometry (MS data sets. They can be essentially clustered into two classes. The first performs searches on theoretical mass spectrum database, while the second based itself on de novo sequencing from raw mass spectrometry data. It was noted that the quality of mass spectra affects significantly the protein identification processes in both instances. This prompted the authors to explore ways to measure the quality of MS data sets before subjecting them to the protein identification algorithms, thus allowing for more meaningful searches and increased confidence level of proteins identified. Results The proposed method measures the qualities of MS data sets based on the symmetric property of b- and y-ion peaks present in a MS spectrum. Self-convolution on MS data and its time-reversal copy was employed. Due to the symmetric nature of b-ions and y-ions peaks, the self-convolution result of a good spectrum would produce a highest mid point intensity peak. To reduce processing time, self-convolution was achieved using Fast Fourier Transform and its inverse transform, followed by the removal of the "DC" (Direct Current component and the normalisation of the data set. The quality score was defined as the ratio of the intensity at the mid point to the remaining peaks of the convolution result. The method was validated using both theoretical mass spectra, with various permutations, and several real MS data sets. The results were encouraging, revealing a high percentage of positive prediction rates for spectra with good quality scores. Conclusion We have demonstrated in this work a method for determining the quality of tandem MS data set. By pre-determining the quality of tandem MS data before subjecting them to protein identification algorithms, spurious protein predictions due to poor tandem MS data are avoided, giving scientists greater confidence in the

  12. The Use of Finite Fields and Rings to Compute Convolutions

    Science.gov (United States)

    1975-06-06

    showed in Ref. 1 that the convolution of two finite sequences of integers (a, ) and (b, ) for k = 1, 2, . . ., d can be obtained as the inverse transform of...since the T.’S are all distinct. Thus T~ exists and (7) can be solved as a = T A the inverse " transform .𔃻 Next let us impose on (7) the...the inverse transform d-1 Cn= (d) I Cka k=0 If an a can be found so that multiplications by powers of a are simple in hardware, the

  13. Tandem mass spectrometry data quality assessment by self-convolution.

    Science.gov (United States)

    Choo, Keng Wah; Tham, Wai Mun

    2007-09-20

    Many algorithms have been developed for deciphering the tandem mass spectrometry (MS) data sets. They can be essentially clustered into two classes. The first performs searches on theoretical mass spectrum database, while the second based itself on de novo sequencing from raw mass spectrometry data. It was noted that the quality of mass spectra affects significantly the protein identification processes in both instances. This prompted the authors to explore ways to measure the quality of MS data sets before subjecting them to the protein identification algorithms, thus allowing for more meaningful searches and increased confidence level of proteins identified. The proposed method measures the qualities of MS data sets based on the symmetric property of b- and y-ion peaks present in a MS spectrum. Self-convolution on MS data and its time-reversal copy was employed. Due to the symmetric nature of b-ions and y-ions peaks, the self-convolution result of a good spectrum would produce a highest mid point intensity peak. To reduce processing time, self-convolution was achieved using Fast Fourier Transform and its inverse transform, followed by the removal of the "DC" (Direct Current) component and the normalisation of the data set. The quality score was defined as the ratio of the intensity at the mid point to the remaining peaks of the convolution result. The method was validated using both theoretical mass spectra, with various permutations, and several real MS data sets. The results were encouraging, revealing a high percentage of positive prediction rates for spectra with good quality scores. We have demonstrated in this work a method for determining the quality of tandem MS data set. By pre-determining the quality of tandem MS data before subjecting them to protein identification algorithms, spurious protein predictions due to poor tandem MS data are avoided, giving scientists greater confidence in the predicted results. We conclude that the algorithm performs well

  14. Classifying medical relations in clinical text via convolutional neural networks.

    Science.gov (United States)

    He, Bin; Guan, Yi; Dai, Rui

    2018-05-16

    Deep learning research on relation classification has achieved solid performance in the general domain. This study proposes a convolutional neural network (CNN) architecture with a multi-pooling operation for medical relation classification on clinical records and explores a loss function with a category-level constraint matrix. Experiments using the 2010 i2b2/VA relation corpus demonstrate these models, which do not depend on any external features, outperform previous single-model methods and our best model is competitive with the existing ensemble-based method. Copyright © 2018. Published by Elsevier B.V.

  15. Weed Growth Stage Estimator Using Deep Convolutional Neural Networks

    DEFF Research Database (Denmark)

    Teimouri, Nima; Dyrmann, Mads; Nielsen, Per Rydahl

    2018-01-01

    This study outlines a new method of automatically estimating weed species and growth stages (from cotyledon until eight leaves are visible) of in situ images covering 18 weed species or families. Images of weeds growing within a variety of crops were gathered across variable environmental conditi...... in estimating the number of leaves and 96% accuracy when accepting a deviation of two leaves. These results show that this new method of using deep convolutional neural networks has a relatively high ability to estimate early growth stages across a wide variety of weed species....

  16. The statistical neuroanatomy of frontal networks in the macaque.

    Directory of Open Access Journals (Sweden)

    Bruno B Averbeck

    2008-04-01

    Full Text Available We were interested in gaining insight into the functional properties of frontal networks based upon their anatomical inputs. We took a neuroinformatics approach, carrying out maximum likelihood hierarchical cluster analysis on 25 frontal cortical areas based upon their anatomical connections, with 68 input areas representing exterosensory, chemosensory, motor, limbic, and other frontal inputs. The analysis revealed a set of statistically robust clusters. We used these clusters to divide the frontal areas into 5 groups, including ventral-lateral, ventral-medial, dorsal-medial, dorsal-lateral, and caudal-orbital groups. Each of these groups was defined by a unique set of inputs. This organization provides insight into the differential roles of each group of areas and suggests a gradient by which orbital and ventral-medial areas may be responsible for decision-making processes based on emotion and primary reinforcers, and lateral frontal areas are more involved in integrating affective and rational information into a common framework.

  17. Frontal EEG asymmetry as a moderator and mediator of emotion.

    Science.gov (United States)

    Coan, James A; Allen, John J B

    2004-10-01

    Frontal EEG asymmetry appears to serve as (1) an individual difference variable related to emotional responding and emotional disorders, and (2) a state-dependent concomitant of emotional responding. Such findings, highlighted in this review, suggest that frontal EEG asymmetry may serve as both a moderator and a mediator of emotion- and motivation-related constructs. Unequivocal evidence supporting frontal EEG asymmetry as a moderator and/or mediator of emotion is lacking, as insufficient attention has been given to analyzing the frontal EEG asymmetries in terms of moderators and mediators. The present report reviews the frontal EEG asymmetry literature from the framework of moderators and mediators, and overviews data analytic strategies that would support claims of moderation and mediation.

  18. Why do patients with neurodegenerative frontal syndrome fail to answer: 'In what way are an orange and a banana alike?'.

    Science.gov (United States)

    Lagarde, Julien; Valabrègue, Romain; Corvol, Jean-Christophe; Garcin, Béatrice; Volle, Emmanuelle; Le Ber, Isabelle; Vidailhet, Marie; Dubois, Bruno; Levy, Richard

    2015-02-01

    in the frontal-basal-ganglion network. Two types of errors were observed in frontal patients. The most frequent was discriminating instead of grouping items ('linking deficit'). Patients also linked items on a concrete instead of an abstract basis ('abstraction deficit'). Linking and abstraction deficits were related to partially different areas: the linking deficit to the dorsal anterior cingulate cortex, right middle frontal gyrus and both inferior parietal lobules and the abstraction deficit to the head of the caudate nuclei and the left superior frontal gyrus. These data suggest that verbal concept formation requires the integrity of the prefrontal-basal-ganglion functional network. In addition, it can be divided into two distinct cognitive processes, which are underlain by two partially different neural networks. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  19. The association between aerobic fitness and cognitive function in older men mediated by frontal lateralization.

    Science.gov (United States)

    Hyodo, Kazuki; Dan, Ippeita; Kyutoku, Yasushi; Suwabe, Kazuya; Byun, Kyeongho; Ochi, Genta; Kato, Morimasa; Soya, Hideaki

    2016-01-15

    Previous studies have shown that higher aerobic fitness is related to higher cognitive function and higher task-related prefrontal activation in older adults. However, a holistic picture of these factors has yet to be presented. As a typical age-related change of brain activation, less lateralized activity in the prefrontal cortex during cognitive tasks has been observed in various neuroimaging studies. Thus, this study aimed to reveal the relationship between aerobic fitness, cognitive function, and frontal lateralization. Sixty male older adults each performed a submaximal incremental exercise test to determine their oxygen intake (V·O2) at ventilatory threshold (VT) in order to index their aerobic fitness. They performed a color-word Stroop task while prefrontal activation was monitored using functional near infrared spectroscopy. As an index of cognitive function, Stroop interference time was analyzed. Partial correlation analyses revealed significant correlations among higher VT, shorter Stroop interference time and greater left-lateralized dorsolateral prefrontal cortex (DLPFC) activation when adjusting for education. Moreover, mediation analyses showed that left-lateralized DLPFC activation significantly mediated the association between VT and Stroop interference time. These results suggest that higher aerobic fitness is associated with cognitive function via lateralized frontal activation in older adults. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. DETERMINATION OF CLINICALLY RELEVANT DIFFERENCES IN FRONTAL PLANE HOP TESTS IN WOMEN'S COLLEGIATE BASKETBALL AND SOCCER PLAYERS

    Science.gov (United States)

    Hardesty, Kelly; Hegedus, Eric J.; Ford, Kevin R.; Nguyen, Anh‐Dung

    2017-01-01

    Background ACL injury prevention programs are less successful in female basketball players than in soccer players. Previous authors have identified anthropometric and biomechanical differences between the athletes and different sport‐specific demands, including a higher frequency of frontal plane activities in basketball. Current injury risk screening and preventive training practices do not place a strong emphasis on frontal plane activities. The medial and lateral triple hop for distance tests may be beneficial for use in the basketball population. Hypothesis/Purpose To 1) establish normative values for the medial and lateral triple hop tests in healthy female collegiate athletes, and 2) analyze differences in test scores between female basketball and soccer players. It was hypothesized that due to the frequent frontal plane demands of their sport, basketball players would exhibit greater performance during these frontal plane performance tests. Study Design Cross‐sectional. Methods Thirty‐two NCAA Division‐1 female athletes (20 soccer, 12 basketball) performed three trials each of a medial and lateral triple hop for distance test. Distances were normalized to height and mass in order to account for anthropometric differences. Repeated measures ANOVAs were performed to identify statistically significant main effects of sport (basketball vs. soccer), and side (right vs. left), and sport x side interactions. Results After accounting for anthropometric differences, soccer players exhibited significantly better performance than basketball players in the medial and lateral triple hop tests (p jumped farther on their left (400.3 ± 41.5 cm) than right (387.9 ± 43.4 cm) limbs, but no side differences were identified in the lateral triple hop. No significant side x sport interactions were identified. Conclusions Women's basketball players exhibit decreased performance of frontal plane hop tests when compared to women's soccer players. Additionally

  1. Reduced right frontal fractional anisotropy correlated with early elevated plasma LDL levels in obese young adults.

    Directory of Open Access Journals (Sweden)

    Baohui Lou

    Full Text Available OBJECTIVE: To investigate the underlying physiological mechanisms of the structural differences in gray matter (GM and white matter (WM associated with obesity in young Chinese adults. MATERIALS AND METHODS: A total of 49 right-handed obese or overweight (n = 22, mean age 31.72±8.04 years and normal weight (n = 27, mean age 29.04±7.32 years Han Chinese individuals were recruited. All participants underwent voxel-based morphometry analysis of T1-weighted MRI and tract-based spatial statistics analysis of diffusion tensor imaging. Partial correlation analysis was performed between the physiological data obtained and the abnormal structural alterations. RESULTS: In the OO group, GM atrophy occurred in the left prefrontal cortex, bilateral cingulate gyrus, and the right temporal lobe, while enlargement was observed in the bilateral putamen. WM atrophy was observed predominantly in the regions that regulate food intake, such as the bilateral basal ganglia, the right amygdala, and the left insula. The OO group exhibited lower fractional anisotropy (FA in bilateral frontal corticospinal tracts and the right brainstem. Significant negative correlations were observed between FA values of those three clusters and BMI, and waist circumference, while the volume of bilateral putamen positively correlated with both BMI and waist circumference. High plasma LDL levels were correlated with low FA values in the right frontal corticospinal tract. Interestingly, the negative correlation was limited to male participants. CONCLUSIONS: Obesity-related alterations of GM and WM volumes were observed predominantly in food reward circuit, which may motivate abnormal dietary intake. Further, early elevated plasma LDL might contribute to low right frontal FA values of male adults, which requires further demonstration by larger-scale and longitudinal studies.

  2. Emotional Responses to Music: Shifts in Frontal Brain Asymmetry Mark Periods of Musical Change.

    Science.gov (United States)

    Arjmand, Hussain-Abdulah; Hohagen, Jesper; Paton, Bryan; Rickard, Nikki S

    2017-01-01

    Recent studies have demonstrated increased activity in brain regions associated with emotion and reward when listening to pleasurable music. Unexpected change in musical features intensity and tempo - and thereby enhanced tension and anticipation - is proposed to be one of the primary mechanisms by which music induces a strong emotional response in listeners. Whether such musical features coincide with central measures of emotional response has not, however, been extensively examined. In this study, subjective and physiological measures of experienced emotion were obtained continuously from 18 participants (12 females, 6 males; 18-38 years) who listened to four stimuli-pleasant music, unpleasant music (dissonant manipulations of their own music), neutral music, and no music, in a counter-balanced order. Each stimulus was presented twice: electroencephalograph (EEG) data were collected during the first, while participants continuously subjectively rated the stimuli during the second presentation. Frontal asymmetry (FA) indices from frontal and temporal sites were calculated, and peak periods of bias toward the left (indicating a shift toward positive affect) were identified across the sample. The music pieces were also examined to define the temporal onset of key musical features. Subjective reports of emotional experience averaged across the condition confirmed participants rated their music selection as very positive, the scrambled music as negative, and the neutral music and silence as neither positive nor negative. Significant effects in FA were observed in the frontal electrode pair FC3-FC4, and the greatest increase in left bias from baseline was observed in response to pleasurable music. These results are consistent with findings from previous research. Peak FA responses at this site were also found to co-occur with key musical events relating to change, for instance, the introduction of a new motif, or an instrument change, or a change in low level acoustic

  3. Electrophysiological evidence for right frontal lobe dominance in spatial visuomotor learning.

    Science.gov (United States)

    Lang, W; Lang, M; Kornhuber, A; Kornhuber, H H

    1986-02-01

    Slow negative potential shifts were recorded together with the error made in motor performance when two different groups of 14 students tracked visual stimuli with their right hand. Various visuomotor tasks were compared. A tracking task (T) in which subjects had to track the stimulus directly, showed no decrease of error in motor performance during the experiment. In a distorted tracking task (DT) a continuous horizontal distortion of the visual feedback had to be compensated. The additional demands of this task required visuomotor learning. Another learning condition was a mirrored-tracking task (horizontally inverted tracking, hIT), i.e. an elementary function, such as the concept of changing left and right was interposed between perception and action. In addition, subjects performed a no-tracking control task (NT) in which they started the visual stimulus without tracking it. A slow negative potential shift was associated with the visuomotor performance (TP: tracking potential). In the learning tasks (DT and hIT) this negativity was significantly enhanced over the anterior midline and in hIT frontally and precentrally over both hemispheres. Comparing hIT and T for every subject, the enhancement of the tracking potential in hIT was correlated with the success in motor learning in frontomedial and bilaterally in frontolateral recordings (r = 0.81-0.88). However, comparing DT and T, such a correlation was only found in frontomedial and right frontolateral electrodes (r = 0.5-0.61), but not at the left frontolateral electrode. These experiments are consistent with previous findings and give further neurophysiological evidence for frontal lobe activity in visuomotor learning. The hemispherical asymmetry is discussed in respect to hemispherical specialization (right frontal lobe dominance in spatial visuomotor learning).

  4. Reduced frontal-subcortical white matter connectivity in association with suicidal ideation in major depressive disorder

    Science.gov (United States)

    Myung, W; Han, C E; Fava, M; Mischoulon, D; Papakostas, G I; Heo, J-Y; Kim, K W; Kim, S T; Kim, D J H; Kim, D K; Seo, S W; Seong, J-K; Jeon, H J

    2016-01-01

    Major depressive disorder (MDD) and suicidal behavior have been associated with structural and functional changes in the brain. However, little is known regarding alterations of brain networks in MDD patients with suicidal ideation. We investigated whether or not MDD patients with suicidal ideation have different topological organizations of white matter networks compared with MDD patients without suicidal ideation. Participants consisted of 24 patients with MDD and suicidal ideation, 25 age- and gender-matched MDD patients without suicidal ideation and 31 healthy subjects. A network-based statistics (NBS) and a graph theoretical analysis were performed to assess differences in the inter-regional connectivity. Diffusion tensor imaging (DTI) was performed to assess topological changes according to suicidal ideation in MDD patients. The Scale for Suicide Ideation (SSI) and the Korean version of the Barrett Impulsiveness Scale (BIS) were used to assess the severity of suicidal ideation and impulsivity, respectively. Reduced structural connectivity in a characterized subnetwork was found in patients with MDD and suicidal ideation by utilizing NBS analysis. The subnetwork included the regions of the frontosubcortical circuits and the regions involved in executive function in the left hemisphere (rostral middle frontal, pallidum, superior parietal, frontal pole, caudate, putamen and thalamus). The graph theoretical analysis demonstrated that network measures of the left rostral middle frontal had a significant positive correlation with severity of SSI (r=0.59, P=0.02) and BIS (r=0.59, P=0.01). The total edge strength that was significantly associated with suicidal ideation did not differ between MDD patients without suicidal ideation and healthy subjects. Our findings suggest that the reduced frontosubcortical circuit of structural connectivity, which includes regions associated with executive function and impulsivity, appears to have a role in the emergence of suicidal

  5. Frontal Brain Asymmetry and Willingness to Pay.

    Science.gov (United States)

    Ramsøy, Thomas Z; Skov, Martin; Christensen, Maiken K; Stahlhut, Carsten

    2018-01-01

    Consumers frequently make decisions about how much they are willing to pay (WTP) for specific products and services, but little is known about the neural mechanisms underlying such calculations. In this study, we were interested in testing whether specific brain activation-the asymmetry in engagement of the prefrontal cortex-would be related to consumer choice. Subjects saw products and subsequently decided how much they were willing to pay for each product, while undergoing neuroimaging using electroencephalography. Our results demonstrate that prefrontal asymmetry in the gamma frequency band, and a trend in the beta frequency band that was recorded during product viewing was significantly related to subsequent WTP responses. Frontal asymmetry in the alpha band was not related to WTP decisions. Besides suggesting separate neuropsychological mechanisms of consumer choice, we find that one specific measure-the prefrontal gamma asymmetry-was most strongly related to WTP responses, and was most coupled to the actual decision phase. These findings are discussed in light of the psychology of WTP calculations, and in relation to the recent emergence of consumer neuroscience and neuromarketing.

  6. Frontal Brain Asymmetry and Willingness to Pay

    Directory of Open Access Journals (Sweden)

    Thomas Z. Ramsøy

    2018-03-01

    Full Text Available Consumers frequently make decisions about how much they are willing to pay (WTP for specific products and services, but little is known about the neural mechanisms underlying such calculations. In this study, we were interested in testing whether specific brain activation—the asymmetry in engagement of the prefrontal cortex—would be related to consumer choice. Subjects saw products and subsequently decided how much they were willing to pay for each product, while undergoing neuroimaging using electroencephalography. Our results demonstrate that prefrontal asymmetry in the gamma frequency band, and a trend in the beta frequency band that was recorded during product viewing was significantly related to subsequent WTP responses. Frontal asymmetry in the alpha band was not related to WTP decisions. Besides suggesting separate neuropsychological mechanisms of consumer choice, we find that one specific measure—the prefrontal gamma asymmetry—was most strongly related to WTP responses, and was most coupled to the actual decision phase. These findings are discussed in light of the psychology of WTP calculations, and in relation to the recent emergence of consumer neuroscience and neuromarketing.

  7. Frontal Brain Asymmetry and Willingness to Pay

    Science.gov (United States)

    Ramsøy, Thomas Z.; Skov, Martin; Christensen, Maiken K.; Stahlhut, Carsten

    2018-01-01

    Consumers frequently make decisions about how much they are willing to pay (WTP) for specific products and services, but little is known about the neural mechanisms underlying such calculations. In this study, we were interested in testing whether specific brain activation—the asymmetry in engagement of the prefrontal cortex—would be related to consumer choice. Subjects saw products and subsequently decided how much they were willing to pay for each product, while undergoing neuroimaging using electroencephalography. Our results demonstrate that prefrontal asymmetry in the gamma frequency band, and a trend in the beta frequency band that was recorded during product viewing was significantly related to subsequent WTP responses. Frontal asymmetry in the alpha band was not related to WTP decisions. Besides suggesting separate neuropsychological mechanisms of consumer choice, we find that one specific measure—the prefrontal gamma asymmetry—was most strongly related to WTP responses, and was most coupled to the actual decision phase. These findings are discussed in light of the psychology of WTP calculations, and in relation to the recent emergence of consumer neuroscience and neuromarketing. PMID:29662432

  8. Trauma of the Frontal Region Is Influenced by the Volume of Frontal Sinuses. A Finite Element Study

    Directory of Open Access Journals (Sweden)

    Srbislav S. Pajic

    2017-07-01

    Full Text Available Anatomy of frontal sinuses varies individually, from differences in volume and shape to a rare case when the sinuses are absent. However, there are scarce data related to influence of these variations on impact generated fracture pattern. Therefore, the aim of this study was to analyse the influence of frontal sinus volume on the stress distribution and fracture pattern in the frontal region. The study included four representative Finite Element models of the skull. Reference model was built on the basis of computed tomography scans of a human head with normally developed frontal sinuses. By modifying the reference model, three additional models were generated: a model without sinuses, with hypoplasic, and with hyperplasic sinuses. A 7.7 kN force was applied perpendicularly to the forehead of each model, in order to simulate a frontal impact. The results demonstrated that the distribution of impact stress in frontal region depends on the frontal sinus volume. The anterior sinus wall showed the highest fragility in case with hyperplasic sinuses, whereas posterior wall/inner plate showed more fragility in cases with hypoplasic and undeveloped sinuses. Well-developed frontal sinuses might, through absorption of the impact energy by anterior wall, protect the posterior wall and intracranial contents.

  9. A MacWilliams Identity for Convolutional Codes: The General Case

    OpenAIRE

    Gluesing-Luerssen, Heide; Schneider, Gert

    2008-01-01

    A MacWilliams Identity for convolutional codes will be established. It makes use of the weight adjacency matrices of the code and its dual, based on state space realizations (the controller canonical form) of the codes in question. The MacWilliams Identity applies to various notions of duality appearing in the literature on convolutional coding theory.

  10. Isointense infant brain MRI segmentation with a dilated convolutional neural network

    NARCIS (Netherlands)

    Moeskops, P.; Pluim, J.P.W.

    2017-01-01

    Quantitative analysis of brain MRI at the age of 6 months is difficult because of the limited contrast between white matter and gray matter. In this study, we use a dilated triplanar convolutional neural network in combination with a non-dilated 3D convolutional neural network for the segmentation

  11. An upper bound on the number of errors corrected by a convolutional code

    DEFF Research Database (Denmark)

    Justesen, Jørn

    2000-01-01

    The number of errors that a convolutional codes can correct in a segment of the encoded sequence is upper bounded by the number of distinct syndrome sequences of the relevant length.......The number of errors that a convolutional codes can correct in a segment of the encoded sequence is upper bounded by the number of distinct syndrome sequences of the relevant length....

  12. Linear diffusion-wave channel routing using a discrete Hayami convolution method

    Science.gov (United States)

    Li Wang; Joan Q. Wu; William J. Elliot; Fritz R. Feidler; Sergey. Lapin

    2014-01-01

    The convolution of an input with a response function has been widely used in hydrology as a means to solve various problems analytically. Due to the high computation demand in solving the functions using numerical integration, it is often advantageous to use the discrete convolution instead of the integration of the continuous functions. This approach greatly reduces...

  13. Using convolutional decoding to improve time delay and phase estimation in digital communications

    Science.gov (United States)

    Ormesher, Richard C [Albuquerque, NM; Mason, John J [Albuquerque, NM

    2010-01-26

    The time delay and/or phase of a communication signal received by a digital communication receiver can be estimated based on a convolutional decoding operation that the communication receiver performs on the received communication signal. If the original transmitted communication signal has been spread according to a spreading operation, a corresponding despreading operation can be integrated into the convolutional decoding operation.

  14. Frontal EEG delta/alpha ratio and screening for post-stroke cognitive deficits: the power of four electrodes.

    Science.gov (United States)

    Schleiger, Emma; Sheikh, Nabeel; Rowland, Tennille; Wong, Andrew; Read, Stephen; Finnigan, Simon

    2014-10-01

    This study analysed correlations between post-stroke, quantitative electroencephalographic (QEEG) indices, and cognition-specific, functional outcome measures. Results were compared between QEEG indices calculated from the standard 19 versus 4 frontal (or 4 posterior) electrodes to assess the feasibility and efficacy of employing a reduced electrode montage. Resting-state EEG was recorded at the bedside within 62-101 h after onset of symptoms of middle cerebral artery, ischaemic stroke (confirmed radiologically). Relative power for delta, theta, alpha and beta, delta/alpha ratio (DAR) and pairwise-derived brain symmetry index (pdBSI) were averaged; over all electrodes (global), over F3, F4, F7, F8 (frontal) and P3, P4, T5, T6 (posterior). The functional independence measure and functional assessment measure (FIM-FAM) was administered at mean 105 days post-stroke. Total (30 items) and cognition-specific (5 items) FIM-FAM scores were correlated with QEEG indices using Spearman's coefficient, with a Bonferroni correction. Twenty-five patients were recruited, 4 died within 3 months and 1 was lost to follow-up. Hence 20 cases (10 female; 9 left hemisphere; mean age 68 years, range 38-84) were analysed. Two QEEG indices demonstrated highly-significant correlations with cognitive outcomes: frontal DAR (ρ = -0.664, p ≤ 0.001) and global, relative alpha power (ρ = 0.67, p ≤ 0.001). After correction there were no other significant correlations. Alpha activity - particularly frontally - may index post-stroke attentional capacity, which appears to be a key determinant of functional and cognitive outcomes. Likewise frontal delta pathophysiology influences such outcomes. Pending further studies, DAR from 4 frontal electrodes may inform early screening for post-MCA stroke cognitive deficits, and thereby, clinical decisions. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. Frontal dysconnectivity in 22q11.2 deletion syndrome: an atlas-based functional connectivity analysis.

    Science.gov (United States)

    Mattiaccio, Leah M; Coman, Ioana L; Thompson, Carlie A; Fremont, Wanda P; Antshel, Kevin M; Kates, Wendy R

    2018-01-20

    22q11.2 deletion syndrome (22q11DS) is a neurodevelopmental syndrome associated with deficits in cognitive and emotional processing. This syndrome represents one of the highest risk factors for the development of schizophrenia. Previous studies of functional connectivity (FC) in 22q11DS report aberrant connectivity patterns in large-scale networks that are associated with the development of psychotic symptoms. In this study, we performed a functional connectivity analysis using the CONN toolbox to test for differential connectivity patterns between 54 individuals with 22q11DS and 30 healthy controls, between the ages of 17-25 years old. We mapped resting-state fMRI data onto 68 atlas-based regions of interest (ROIs) generated by the Desikan-Killany atlas in FreeSurfer, resulting in 2278 ROI-to-ROI connections for which we determined total linear temporal associations between each. Within the group with 22q11DS only, we further tested the association between prodromal symptoms of psychosis and FC. We observed that relative to controls, individuals with 22q11DS displayed increased FC in lobar networks involving the frontal-frontal, frontal-parietal, and frontal-occipital ROIs. In contrast, FC between ROIs in the parietal-temporal and occipital lobes was reduced in the 22q11DS group relative to healthy controls. Moreover, positive psychotic symptoms were positively associated with increased functional connections between the left precuneus and right superior frontal gyrus, as well as reduced functional connectivity between the bilateral pericalcarine. Positive symptoms were negatively associated with increased functional connectivity between the right pericalcarine and right postcentral gyrus. Our results suggest that functional organization may be altered in 22q11DS, leading to disruption in connectivity between frontal and other lobar substructures, and potentially increasing risk for prodromal psychosis.

  16. Social modeling of eating mediated by mirror neuron activity: A causal model moderated by frontal asymmetry and BMI.

    Science.gov (United States)

    McGeown, Laura; Davis, Ron

    2018-02-15

    The social modeling of eating effect refers to the consistently demonstrated phenomenon that individuals tend to match their quantity of food intake to their eating companion. The current study sought to explore whether activity within the mirror neuron system (MNS) mediates the social modeling of eating effect as a function of EEG frontal asymmetry and body mass index (BMI). Under the guise of rating empathy, 93 female undergraduates viewed a female video confederate "incidentally" consume either a low or high intake of chips while electroencephalogram (EEG) activity was recorded. Subsequent ad libitum chip consumption was quantified. A first- and second-stage dual moderation model revealed that frontal asymmetry and BMI moderated an indirect effect of model consumption on participants' food consumption as mediated by MNS activity at electrode site C3, a 3 b 3 =-0.718, SE=0.365, 95% CI [-1.632, -0.161]. Left frontal asymmetry was associated with greater mu activity and a positive association between model and participant chip consumption, while right frontal asymmetry was associated with less mu activity and a negative association between model and participant consumption. Across all levels of frontal asymmetry, the effect was only significant among those with a BMI at the 50th percentile or lower. Thus, among leaner individuals, the MNS was demonstrated to mediate social modeling of eating, as moderated by frontal asymmetry. These findings are integrated within the normative account of social modeling of eating. It is proposed that the normative framework may benefit from consideration of both conscious and unconscious operation of intake norms. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. No Community Left Behind

    Science.gov (United States)

    Schlechty, Phillip C.

    2008-01-01

    The debate over the reauthorization of No Child Left Behind (NCLB) generally overlooks--or looks past--what may be the most fundamental flaw in that legislation. As the law is now written, decisions regarding what the young should know and be able to do are removed from the hands of parents and local community leaders and turned over to officials…

  18. The Children Left Behind

    Science.gov (United States)

    Gillard, Sarah A.; Gillard, Sharlett

    2012-01-01

    This article explores some of the deficits in our educational system in regard to non-hearing students. It has become agonizingly clear that non-hearing students are being left out of the gallant sweep to enrich our children's educations. The big five areas of literacy, at best, present unique challenges for non-hearing students and, in some…

  19. Left atrial appendage occlusion

    Directory of Open Access Journals (Sweden)

    Ahmad Mirdamadi

    2013-01-01

    Full Text Available Left atrial appendage (LAA occlusion is a treatment strategy to prevent blood clot formation in atrial appendage. Although, LAA occlusion usually was done by catheter-based techniques, especially percutaneous trans-luminal mitral commissurotomy (PTMC, it can be done during closed and open mitral valve commissurotomy (CMVC, OMVC and mitral valve replacement (MVR too. Nowadays, PTMC is performed as an optimal management of severe mitral stenosis (MS and many patients currently are treated by PTMC instead of previous surgical methods. One of the most important contraindications of PTMC is presence of clot in LAA. So, each patient who suffers of severe MS is evaluated by Trans-Esophageal Echocardiogram to rule out thrombus in LAA before PTMC. At open heart surgery, replacement of the mitral valve was performed for 49-year-old woman. Also, left atrial appendage occlusion was done during surgery. Immediately after surgery, echocardiography demonstrates an echo imitated the presence of a thrombus in left atrial appendage area, although there was not any evidence of thrombus in pre-pump TEE. We can conclude from this case report that when we suspect of thrombus of left atrial, we should obtain exact history of previous surgery of mitral valve to avoid misdiagnosis clotted LAA, instead of obliterated LAA. Consequently, it can prevent additional evaluations and treatments such as oral anticoagulation and exclusion or postponing surgeries including PTMC.

  20. Classifying images using restricted Boltzmann machines and convolutional neural networks

    Science.gov (United States)

    Zhao, Zhijun; Xu, Tongde; Dai, Chenyu

    2017-07-01

    To improve the feature recognition ability of deep model transfer learning, we propose a hybrid deep transfer learning method for image classification based on restricted Boltzmann machines (RBM) and convolutional neural networks (CNNs). It integrates learning abilities of two models, which conducts subject classification by exacting structural higher-order statistics features of images. While the method transfers the trained convolutional neural networks to the target datasets, fully-connected layers can be replaced by restricted Boltzmann machine layers; then the restricted Boltzmann machine layers and Softmax classifier are retrained, and BP neural network can be used to fine-tuned the hybrid model. The restricted Boltzmann machine layers has not only fully integrated the whole feature maps, but also learns the statistical features of target datasets in the view of the biggest logarithmic likelihood, thus removing the effects caused by the content differences between datasets. The experimental results show that the proposed method has improved the accuracy of image classification, outperforming other methods on Pascal VOC2007 and Caltech101 datasets.

  1. Cloud Detection by Fusing Multi-Scale Convolutional Features

    Science.gov (United States)

    Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

    2018-04-01

    Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

  2. Real-Time Video Convolutional Face Finder on Embedded Platforms

    Directory of Open Access Journals (Sweden)

    Mamalet Franck

    2007-01-01

    Full Text Available A high-level optimization methodology is applied for implementing the well-known convolutional face finder (CFF algorithm for real-time applications on mobile phones, such as teleconferencing, advanced user interfaces, image indexing, and security access control. CFF is based on a feature extraction and classification technique which consists of a pipeline of convolutions and subsampling operations. The design of embedded systems requires a good trade-off between performance and code size due to the limited amount of available resources. The followed methodology copes with the main drawbacks of the original implementation of CFF such as floating-point computation and memory allocation, in order to allow parallelism exploitation and perform algorithm optimizations. Experimental results show that our embedded face detection system can accurately locate faces with less computational load and memory cost. It runs on a 275 MHz Starcore DSP at 35 QCIF images/s with state-of-the-art detection rates and very low false alarm rates.

  3. Enhancing neutron beam production with a convoluted moderator

    Energy Technology Data Exchange (ETDEWEB)

    Iverson, E.B., E-mail: iversoneb@ornl.gov [Spallation Neutron Source, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Baxter, D.V. [Center for the Exploration of Energy and Matter, Indiana University, Bloomington, IN 47408 (United States); Muhrer, G. [Lujan Neutron Scattering Center, Los Alamos National Laboratory, P.O. Box 1663, Los Alamos, NM 87545 (United States); Ansell, S.; Dalgliesh, R. [ISIS Facility, Rutherford Appleton Laboratory, Chilton (United Kingdom); Gallmeier, F.X. [Spallation Neutron Source, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Kaiser, H. [Center for the Exploration of Energy and Matter, Indiana University, Bloomington, IN 47408 (United States); Lu, W. [Spallation Neutron Source, Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)

    2014-10-21

    We describe a new concept for a neutron moderating assembly resulting in the more efficient production of slow neutron beams. The Convoluted Moderator, a heterogeneous stack of interleaved moderating material and nearly transparent single-crystal spacers, is a directionally enhanced neutron beam source, improving beam emission over an angular range comparable to the range accepted by neutron beam lines and guides. We have demonstrated gains of 50% in slow neutron intensity for a given fast neutron production rate while simultaneously reducing the wavelength-dependent emission time dispersion by 25%, both coming from a geometric effect in which the neutron beam lines view a large surface area of moderating material in a relatively small volume. Additionally, we have confirmed a Bragg-enhancement effect arising from coherent scattering within the single-crystal spacers. We have not observed hypothesized refractive effects leading to additional gains at long wavelength. In addition to confirmation of the validity of the Convoluted Moderator concept, our measurements provide a series of benchmark experiments suitable for developing simulation and analysis techniques for practical optimization and eventual implementation at slow neutron source facilities.

  4. Photon beam convolution using polyenergetic energy deposition kernels

    International Nuclear Information System (INIS)

    Hoban, P.W.; Murray, D.C.; Round, W.H.

    1994-01-01

    In photon beam convolution calculations where polyenergetic energy deposition kernels (EDKs) are used, the primary photon energy spectrum should be correctly accounted for in Monte Carlo generation of EDKs. This requires the probability of interaction, determined by the linear attenuation coefficient, μ, to be taken into account when primary photon interactions are forced to occur at the EDK origin. The use of primary and scattered EDKs generated with a fixed photon spectrum can give rise to an error in the dose calculation due to neglecting the effects of beam hardening with depth. The proportion of primary photon energy that is transferred to secondary electrons increases with depth of interaction, due to the increase in the ratio μ ab /μ as the beam hardens. Convolution depth-dose curves calculated using polyenergetic EDKs generated for the primary photon spectra which exist at depths of 0, 20 and 40 cm in water, show a fall-off which is too steep when compared with EGS4 Monte Carlo results. A beam hardening correction factor applied to primary and scattered 0 cm EDKs, based on the ratio of kerma to terma at each depth, gives primary, scattered and total dose in good agreement with Monte Carlo results. (Author)

  5. Multi-Branch Fully Convolutional Network for Face Detection

    KAUST Repository

    Bai, Yancheng

    2017-07-20

    Face detection is a fundamental problem in computer vision. It is still a challenging task in unconstrained conditions due to significant variations in scale, pose, expressions, and occlusion. In this paper, we propose a multi-branch fully convolutional network (MB-FCN) for face detection, which considers both efficiency and effectiveness in the design process. Our MB-FCN detector can deal with faces at all scale ranges with only a single pass through the backbone network. As such, our MB-FCN model saves computation and thus is more efficient, compared to previous methods that make multiple passes. For each branch, the specific skip connections of the convolutional feature maps at different layers are exploited to represent faces in specific scale ranges. Specifically, small faces can be represented with both shallow fine-grained and deep powerful coarse features. With this representation, superior improvement in performance is registered for the task of detecting small faces. We test our MB-FCN detector on two public face detection benchmarks, including FDDB and WIDER FACE. Extensive experiments show that our detector outperforms state-of-the-art methods on all these datasets in general and by a substantial margin on the most challenging among them (e.g. WIDER FACE Hard subset). Also, MB-FCN runs at 15 FPS on a GPU for images of size 640 x 480 with no assumption on the minimum detectable face size.

  6. Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks

    Directory of Open Access Journals (Sweden)

    Haiyang Yu

    2017-06-01

    Full Text Available Predicting large-scale transportation network traffic has become an important and challenging topic in recent decades. Inspired by the domain knowledge of motion prediction, in which the future motion of an object can be predicted based on previous scenes, we propose a network grid representation method that can retain the fine-scale structure of a transportation network. Network-wide traffic speeds are converted into a series of static images and input into a novel deep architecture, namely, spatiotemporal recurrent convolutional networks (SRCNs, for traffic forecasting. The proposed SRCNs inherit the advantages of deep convolutional neural networks (DCNNs and long short-term memory (LSTM neural networks. The spatial dependencies of network-wide traffic can be captured by DCNNs, and the temporal dynamics can be learned by LSTMs. An experiment on a Beijing transportation network with 278 links demonstrates that SRCNs outperform other deep learning-based algorithms in both short-term and long-term traffic prediction.

  7. Convolutional Neural Network for Histopathological Analysis of Osteosarcoma.

    Science.gov (United States)

    Mishra, Rashika; Daescu, Ovidiu; Leavey, Patrick; Rakheja, Dinesh; Sengupta, Anita

    2018-03-01

    Pathologists often deal with high complexity and sometimes disagreement over osteosarcoma tumor classification due to cellular heterogeneity in the dataset. Segmentation and classification of histology tissue in H&E stained tumor image datasets is a challenging task because of intra-class variations, inter-class similarity, crowded context, and noisy data. In recent years, deep learning approaches have led to encouraging results in breast cancer and prostate cancer analysis. In this article, we propose convolutional neural network (CNN) as a tool to improve efficiency and accuracy of osteosarcoma tumor classification into tumor classes (viable tumor, necrosis) versus nontumor. The proposed CNN architecture contains eight learned layers: three sets of stacked two convolutional layers interspersed with max pooling layers for feature extraction and two fully connected layers with data augmentation strategies to boost performance. The use of a neural network results in higher accuracy of average 92% for the classification. We compare the proposed architecture with three existing and proven CNN architectures for image classification: AlexNet, LeNet, and VGGNet. We also provide a pipeline to calculate percentage necrosis in a given whole slide image. We conclude that the use of neural networks can assure both high accuracy and efficiency in osteosarcoma classification.

  8. Multi-Input Convolutional Neural Network for Flower Grading

    Directory of Open Access Journals (Sweden)

    Yu Sun

    2017-01-01

    Full Text Available Flower grading is a significant task because it is extremely convenient for managing the flowers in greenhouse and market. With the development of computer vision, flower grading has become an interdisciplinary focus in both botany and computer vision. A new dataset named BjfuGloxinia contains three quality grades; each grade consists of 107 samples and 321 images. A multi-input convolutional neural network is designed for large scale flower grading. Multi-input CNN achieves a satisfactory accuracy of 89.6% on the BjfuGloxinia after data augmentation. Compared with a single-input CNN, the accuracy of multi-input CNN is increased by 5% on average, demonstrating that multi-input convolutional neural network is a promising model for flower grading. Although data augmentation contributes to the model, the accuracy is still limited by lack of samples diversity. Majority of misclassification is derived from the medium class. The image processing based bud detection is useful for reducing the misclassification, increasing the accuracy of flower grading to approximately 93.9%.

  9. Convolutional neural network architectures for predicting DNA–protein binding

    Science.gov (United States)

    Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

    2016-01-01

    Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

  10. Transforming Musical Signals through a Genre Classifying Convolutional Neural Network

    Science.gov (United States)

    Geng, S.; Ren, G.; Ogihara, M.

    2017-05-01

    Convolutional neural networks (CNNs) have been successfully applied on both discriminative and generative modeling for music-related tasks. For a particular task, the trained CNN contains information representing the decision making or the abstracting process. One can hope to manipulate existing music based on this 'informed' network and create music with new features corresponding to the knowledge obtained by the network. In this paper, we propose a method to utilize the stored information from a CNN trained on musical genre classification task. The network was composed of three convolutional layers, and was trained to classify five-second song clips into five different genres. After training, randomly selected clips were modified by maximizing the sum of outputs from the network layers. In addition to the potential of such CNNs to produce interesting audio transformation, more information about the network and the original music could be obtained from the analysis of the generated features since these features indicate how the network 'understands' the music.

  11. Siamese convolutional networks for tracking the spine motion

    Science.gov (United States)

    Liu, Yuan; Sui, Xiubao; Sun, Yicheng; Liu, Chengwei; Hu, Yong

    2017-09-01

    Deep learning models have demonstrated great success in various computer vision tasks such as image classification and object tracking. However, tracking the lumbar spine by digitalized video fluoroscopic imaging (DVFI), which can quantitatively analyze the motion mode of spine to diagnose lumbar instability, has not yet been well developed due to the lack of steady and robust tracking method. In this paper, we propose a novel visual tracking algorithm of the lumbar vertebra motion based on a Siamese convolutional neural network (CNN) model. We train a full-convolutional neural network offline to learn generic image features. The network is trained to learn a similarity function that compares the labeled target in the first frame with the candidate patches in the current frame. The similarity function returns a high score if the two images depict the same object. Once learned, the similarity function is used to track a previously unseen object without any adapting online. In the current frame, our tracker is performed by evaluating the candidate rotated patches sampled around the previous frame target position and presents a rotated bounding box to locate the predicted target precisely. Results indicate that the proposed tracking method can detect the lumbar vertebra steadily and robustly. Especially for images with low contrast and cluttered background, the presented tracker can still achieve good tracking performance. Further, the proposed algorithm operates at high speed for real time tracking.

  12. Real-Time Video Convolutional Face Finder on Embedded Platforms

    Directory of Open Access Journals (Sweden)

    Franck Mamalet

    2007-03-01

    Full Text Available A high-level optimization methodology is applied for implementing the well-known convolutional face finder (CFF algorithm for real-time applications on mobile phones, such as teleconferencing, advanced user interfaces, image indexing, and security access control. CFF is based on a feature extraction and classification technique which consists of a pipeline of convolutions and subsampling operations. The design of embedded systems requires a good trade-off between performance and code size due to the limited amount of available resources. The followed methodology copes with the main drawbacks of the original implementation of CFF such as floating-point computation and memory allocation, in order to allow parallelism exploitation and perform algorithm optimizations. Experimental results show that our embedded face detection system can accurately locate faces with less computational load and memory cost. It runs on a 275 MHz Starcore DSP at 35 QCIF images/s with state-of-the-art detection rates and very low false alarm rates.

  13. Digital image correlation based on a fast convolution strategy

    Science.gov (United States)

    Yuan, Yuan; Zhan, Qin; Xiong, Chunyang; Huang, Jianyong

    2017-10-01

    In recent years, the efficiency of digital image correlation (DIC) methods has attracted increasing attention because of its increasing importance for many engineering applications. Based on the classical affine optical flow (AOF) algorithm and the well-established inverse compositional Gauss-Newton algorithm, which is essentially a natural extension of the AOF algorithm under a nonlinear iterative framework, this paper develops a set of fast convolution-based DIC algorithms for high-efficiency subpixel image registration. Using a well-developed fast convolution technique, the set of algorithms establishes a series of global data tables (GDTs) over the digital images, which allows the reduction of the computational complexity of DIC significantly. Using the pre-calculated GDTs, the subpixel registration calculations can be implemented efficiently in a look-up-table fashion. Both numerical simulation and experimental verification indicate that the set of algorithms significantly enhances the computational efficiency of DIC, especially in the case of a dense data sampling for the digital images. Because the GDTs need to be computed only once, the algorithms are also suitable for efficiently coping with image sequences that record the time-varying dynamics of specimen deformations.

  14. Convolutional neural network features based change detection in satellite images

    Science.gov (United States)

    Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

    2016-07-01

    With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

  15. Classification of stroke disease using convolutional neural network

    Science.gov (United States)

    Marbun, J. T.; Seniman; Andayani, U.

    2018-03-01

    Stroke is a condition that occurs when the blood supply stop flowing to the brain because of a blockage or a broken blood vessel. A symptoms that happen when experiencing stroke, some of them is a dropped consciousness, disrupted vision and paralyzed body. The general examination is being done to get a picture of the brain part that have stroke using Computerized Tomography (CT) Scan. The image produced from CT will be manually checked and need a proper lighting by doctor to get a type of stroke. That is why it needs a method to classify stroke from CT image automatically. A method proposed in this research is Convolutional Neural Network. CT image of the brain is used as the input for image processing. The stage before classification are image processing (Grayscaling, Scaling, Contrast Limited Adaptive Histogram Equalization, then the image being classified with Convolutional Neural Network. The result then showed that the method significantly conducted was able to be used as a tool to classify stroke disease in order to distinguish the type of stroke from CT image.

  16. Image Classification Based on Convolutional Denoising Sparse Autoencoder

    Directory of Open Access Journals (Sweden)

    Shuangshuang Chen

    2017-01-01

    Full Text Available Image classification aims to group images into corresponding semantic categories. Due to the difficulties of interclass similarity and intraclass variability, it is a challenging issue in computer vision. In this paper, an unsupervised feature learning approach called convolutional denoising sparse autoencoder (CDSAE is proposed based on the theory of visual attention mechanism and deep learning methods. Firstly, saliency detection method is utilized to get training samples for unsupervised feature learning. Next, these samples are sent to the denoising sparse autoencoder (DSAE, followed by convolutional layer and local contrast normalization layer. Generally, prior in a specific task is helpful for the task solution. Therefore, a new pooling strategy—spatial pyramid pooling (SPP fused with center-bias prior—is introduced into our approach. Experimental results on the common two image datasets (STL-10 and CIFAR-10 demonstrate that our approach is effective in image classification. They also demonstrate that none of these three components: local contrast normalization, SPP fused with center-prior, and l2 vector normalization can be excluded from our proposed approach. They jointly improve image representation and classification performance.

  17. Weed Growth Stage Estimator Using Deep Convolutional Neural Networks.

    Science.gov (United States)

    Teimouri, Nima; Dyrmann, Mads; Nielsen, Per Rydahl; Mathiassen, Solvejg Kopp; Somerville, Gayle J; Jørgensen, Rasmus Nyholm

    2018-05-16

    This study outlines a new method of automatically estimating weed species and growth stages (from cotyledon until eight leaves are visible) of in situ images covering 18 weed species or families. Images of weeds growing within a variety of crops were gathered across variable environmental conditions with regards to soil types, resolution and light settings. Then, 9649 of these images were used for training the computer, which automatically divided the weeds into nine growth classes. The performance of this proposed convolutional neural network approach was evaluated on a further set of 2516 images, which also varied in term of crop, soil type, image resolution and light conditions. The overall performance of this approach achieved a maximum accuracy of 78% for identifying Polygonum spp. and a minimum accuracy of 46% for blackgrass. In addition, it achieved an average 70% accuracy rate in estimating the number of leaves and 96% accuracy when accepting a deviation of two leaves. These results show that this new method of using deep convolutional neural networks has a relatively high ability to estimate early growth stages across a wide variety of weed species.

  18. Convolutional neural networks for vibrational spectroscopic data analysis.

    Science.gov (United States)

    Acquarelli, Jacopo; van Laarhoven, Twan; Gerretzen, Jan; Tran, Thanh N; Buydens, Lutgarde M C; Marchiori, Elena

    2017-02-15

    In this work we show that convolutional neural networks (CNNs) can be efficiently used to classify vibrational spectroscopic data and identify important spectral regions. CNNs are the current state-of-the-art in image classification and speech recognition and can learn interpretable representations of the data. These characteristics make CNNs a good candidate for reducing the need for preprocessing and for highlighting important spectral regions, both of which are crucial steps in the analysis of vibrational spectroscopic data. Chemometric analysis of vibrational spectroscopic data often relies on preprocessing methods involving baseline correction, scatter correction and noise removal, which are applied to the spectra prior to model building. Preprocessing is a critical step because even in simple problems using 'reasonable' preprocessing methods may decrease the performance of the final model. We develop a new CNN based method and provide an accompanying publicly available software. It is based on a simple CNN architecture with a single convolutional layer (a so-called shallow CNN). Our method outperforms standard classification algorithms used in chemometrics (e.g. PLS) in terms of accuracy when applied to non-preprocessed test data (86% average accuracy compared to the 62% achieved by PLS), and it achieves better performance even on preprocessed test data (96% average accuracy compared to the 89% achieved by PLS). For interpretability purposes, our method includes a procedure for finding important spectral regions, thereby facilitating qualitative interpretation of results. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. sEMG-Based Gesture Recognition with Convolution Neural Networks

    Directory of Open Access Journals (Sweden)

    Zhen Ding

    2018-06-01

    Full Text Available The traditional classification methods for limb motion recognition based on sEMG have been deeply researched and shown promising results. However, information loss during feature extraction reduces the recognition accuracy. To obtain higher accuracy, the deep learning method was introduced. In this paper, we propose a parallel multiple-scale convolution architecture. Compared with the state-of-art methods, the proposed architecture fully considers the characteristics of the sEMG signal. Larger sizes of kernel filter than commonly used in other CNN-based hand recognition methods are adopted. Meanwhile, the characteristics of the sEMG signal, that is, muscle independence, is considered when designing the architecture. All the classification methods were evaluated on the NinaPro database. The results show that the proposed architecture has the highest recognition accuracy. Furthermore, the results indicate that parallel multiple-scale convolution architecture with larger size of kernel filter and considering muscle independence can significantly increase the classification accuracy.

  20. Development of a morphological convolution operator for bearing fault detection

    Science.gov (United States)

    Li, Yifan; Liang, Xihui; Liu, Weiwei; Wang, Yan

    2018-05-01

    This paper presents a novel signal processing scheme, namely morphological convolution operator (MCO) lifted morphological undecimated wavelet (MUDW), for rolling element bearing fault detection. In this scheme, a MCO is first designed to fully utilize the advantage of the closing & opening gradient operator and the closing-opening & opening-closing gradient operator for feature extraction as well as the merit of excellent denoising characteristics of the convolution operator. The MCO is then introduced into MUDW for the purpose of improving the fault detection ability of the reported MUDWs. Experimental vibration signals collected from a train wheelset test rig and the bearing data center of Case Western Reserve University are employed to evaluate the effectiveness of the proposed MCO lifted MUDW on fault detection of rolling element bearings. The results show that the proposed approach has a superior performance in extracting fault features of defective rolling element bearings. In addition, comparisons are performed between two reported MUDWs and the proposed MCO lifted MUDW. The MCO lifted MUDW outperforms both of them in detection of outer race faults and inner race faults of rolling element bearings.

  1. Fluence-convolution broad-beam (FCBB) dose calculation

    Energy Technology Data Exchange (ETDEWEB)

    Lu Weiguo; Chen Mingli, E-mail: wlu@tomotherapy.co [TomoTherapy Inc., 1240 Deming Way, Madison, WI 53717 (United States)

    2010-12-07

    IMRT optimization requires a fast yet relatively accurate algorithm to calculate the iteration dose with small memory demand. In this paper, we present a dose calculation algorithm that approaches these goals. By decomposing the infinitesimal pencil beam (IPB) kernel into the central axis (CAX) component and lateral spread function (LSF) and taking the beam's eye view (BEV), we established a non-voxel and non-beamlet-based dose calculation formula. Both LSF and CAX are determined by a commissioning procedure using the collapsed-cone convolution/superposition (CCCS) method as the standard dose engine. The proposed dose calculation involves a 2D convolution of a fluence map with LSF followed by ray tracing based on the CAX lookup table with radiological distance and divergence correction, resulting in complexity of O(N{sup 3}) both spatially and temporally. This simple algorithm is orders of magnitude faster than the CCCS method. Without pre-calculation of beamlets, its implementation is also orders of magnitude smaller than the conventional voxel-based beamlet-superposition (VBS) approach. We compared the presented algorithm with the CCCS method using simulated and clinical cases. The agreement was generally within 3% for a homogeneous phantom and 5% for heterogeneous and clinical cases. Combined with the 'adaptive full dose correction', the algorithm is well suitable for calculating the iteration dose during IMRT optimization.

  2. Deep multi-scale convolutional neural network for hyperspectral image classification

    Science.gov (United States)

    Zhang, Feng-zhe; Yang, Xia

    2018-04-01

    In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

  3. Object Detection Based on Fast/Faster RCNN Employing Fully Convolutional Architectures

    Directory of Open Access Journals (Sweden)

    Yun Ren

    2018-01-01

    Full Text Available Modern object detectors always include two major parts: a feature extractor and a feature classifier as same as traditional object detectors. The deeper and wider convolutional architectures are adopted as the feature extractor at present. However, many notable object detection systems such as Fast/Faster RCNN only consider simple fully connected layers as the feature classifier. In this paper, we declare that it is beneficial for the detection performance to elaboratively design deep convolutional networks (ConvNets of various depths for feature classification, especially using the fully convolutional architectures. In addition, this paper also demonstrates how to employ the fully convolutional architectures in the Fast/Faster RCNN. Experimental results show that a classifier based on convolutional layer is more effective for object detection than that based on fully connected layer and that the better detection performance can be achieved by employing deeper ConvNets as the feature classifier.

  4. Hypoplastic left heart syndrome

    Directory of Open Access Journals (Sweden)

    Thiagarajan Ravi

    2007-05-01

    Full Text Available Abstract Hypoplastic left heart syndrome(HLHS refers to the abnormal development of the left-sided cardiac structures, resulting in obstruction to blood flow from the left ventricular outflow tract. In addition, the syndrome includes underdevelopment of the left ventricle, aorta, and aortic arch, as well as mitral atresia or stenosis. HLHS has been reported to occur in approximately 0.016 to 0.036% of all live births. Newborn infants with the condition generally are born at full term and initially appear healthy. As the arterial duct closes, the systemic perfusion becomes decreased, resulting in hypoxemia, acidosis, and shock. Usually, no heart murmur, or a non-specific heart murmur, may be detected. The second heart sound is loud and single because of aortic atresia. Often the liver is enlarged secondary to congestive heart failure. The embryologic cause of the disease, as in the case of most congenital cardiac defects, is not fully known. The most useful diagnostic modality is the echocardiogram. The syndrome can be diagnosed by fetal echocardiography between 18 and 22 weeks of gestation. Differential diagnosis includes other left-sided obstructive lesions where the systemic circulation is dependent on ductal flow (critical aortic stenosis, coarctation of the aorta, interrupted aortic arch. Children with the syndrome require surgery as neonates, as they have duct-dependent systemic circulation. Currently, there are two major modalities, primary cardiac transplantation or a series of staged functionally univentricular palliations. The treatment chosen is dependent on the preference of the institution, its experience, and also preference. Although survival following initial surgical intervention has improved significantly over the last 20 years, significant mortality and morbidity are present for both surgical strategies. As a result pediatric cardiologists continue to be challenged by discussions with families regarding initial decision

  5. Cirurgia de osteoma de seio frontal Surgery of frontal sinus osteoma

    Directory of Open Access Journals (Sweden)

    Lisete Pessoa de Oliveira Fobe

    2002-03-01

    Full Text Available Os osteomas do seio frontal correspondem a 57% dos osteomas dos seios paranasais, com incidência variando de 0,01% a 3%. A remoção cirúrgica nos osteomas frontais é indicada nos pacientes sintomáticos. Nos pacientes assintomáticos pode-se adotar a conduta conservadora ou cirúrgica em todos os pacientes independente da sua localização ou extensão. Cinco pacientes com diagnóstico de osteoma de seio frontal foram operados entre 1995 e 1999. A idade média foi 38,4 anos (extremos de 12 a 55 anos, sendo 3 homens e 2 mulheres. O período de sintomatologia variou de 6 meses a 3 anos com média de 10,5 meses. Quatro pacientes apresentaram cefaléia. Um paciente apresentou epistaxe. Os exames complementares realizados foram: radiografia simples e tomografia computadorizada de seios paranasais com cortes axiais e coronais. Em dois pacientes o diâmetro do osteoma foi maior que 3 cm, e menor que 3 cm em três. A decisão da técnica cirúrgica entre coronal e supraciliar foi estética, reservando-se a abordagem supraciliar para um paciente com calvície, apesar do tumor ser volumoso com extensão para seio etmoidal. Nenhuma dificuldade técnica intra-operatória foi atribuída à escolha da abordagem. O óstio nasofrontal não foi obstruído no intra-operatório. O seguimento pós-operatório mínimo foi de dois anos. Em todos os casos a remoção foi total sem recidiva ou resíduos tumorais. Os sintomas clínicos, achados radiológicos e abordagens cirúrgicas são discutidos. Não ocorreram complicações pós-operatórias.Frontal sinus osteomas are 57% of all paranasal sinus osteomas, with an incidence of 00.1 to 3%. Surgical removal of the frontal sinus osteomas is done in symptomatic patients. Asymptomatic patients can be managed conservatively or submitted to surgery in spite of its location or extension. Five patients having the diagnosis of frontal sinus osteoma were operated on between 1995 and 1999. Medium age was 38.4 years (from 12

  6. Analisis Penyerapan Energi Crash Box Pola Origami pada Pengujian Frontal Impact Posisi Angular Frontal

    Directory of Open Access Journals (Sweden)

    Redi Bintarto

    2017-05-01

    Full Text Available In the car, the body structure is designed in such a way so as to transfer and absorb energy. This serves to minimize the result of this accident related to kinetic energy. This needs a system to absorb the kinetic energy maximally, so as a result of a frontal collision events that can be reduced optimally and kinetic energy can be absorbed by a front body structure. Devices used for absorbing kinetic energy in the car is usually called a crash box, which is located between the main structure and bumper. Crash Box generally tubular thin shaped. It has been a lot of research about the crash box. In this study using crash box origami patterns and using methods taguchi orthogonal array L9 (34. AA7003-T7 aluminum material modeled as bilinear isotropic hardening, the loading method is Frontal Impact Frontal Angular Position with impact angles of 5, 15 and 30 degree by using the finite element software simulation methods. The simulation results showed that the crash box in the lowest possible energy absorption were happened at crash box with 5 degree, with 683 153 Joule energy absorbsion. The highest result was happened to crash box number 5 with the results of 3,140.778 Joule. Lowest absorption on impact of 15 degree and 30 degree were happened to crash box number 1 and number 3 with a value of 245 685 Joule and 174 845 Joule, while the highest absorption at mumber 3 with each value 1,708.521 Joule and 1,750.872 Joule.

  7. Analyzing Brain Functions by Subject Classification of Functional Near-Infrared Spectroscopy Data Using Convolutional Neural Networks Analysis

    Directory of Open Access Journals (Sweden)

    Satoru Hiwa

    2016-01-01

    Full Text Available Functional near-infrared spectroscopy (fNIRS is suitable for noninvasive mapping of relative changes in regional cortical activity but is limited for quantitative comparisons among cortical sites, subjects, and populations. We have developed a convolutional neural network (CNN analysis method that learns feature vectors for accurate identification of group differences in fNIRS responses. In this study, subject gender was classified using CNN analysis of fNIRS data. fNIRS data were acquired from male and female subjects during a visual number memory task performed in a white noise environment because previous studies had revealed that the pattern of cortical blood flow during the task differed between males and females. A learned classifier accurately distinguished males from females based on distinct fNIRS signals from regions of interest (ROI including the inferior frontal gyrus and premotor areas that were identified by the learning algorithm. These cortical regions are associated with memory storage, attention, and task motor response. The accuracy of the classifier suggests stable gender-based differences in cerebral blood flow during this task. The proposed CNN analysis method can objectively identify ROIs using fNIRS time series data for machine learning to distinguish features between groups.

  8. Reduced frontal brain volume in non-treatment-seeking cocaine-dependent individuals: exploring the role of impulsivity, depression, and smoking.

    Science.gov (United States)

    Crunelle, Cleo L; Kaag, Anne Marije; van Wingen, Guido; van den Munkhof, Hanna E; Homberg, Judith R; Reneman, Liesbeth; van den Brink, Wim

    2014-01-01

    In cocaine-dependent patients, gray matter (GM) volume reductions have been observed in the frontal lobes that are associated with the duration of cocaine use. Studies are mostly restricted to treatment-seekers and studies in non-treatment-seeking cocaine abusers are sparse. Here, we assessed GM volume differences between 30 non-treatment-seeking cocaine-dependent individuals and 33 non-drug using controls using voxel-based morphometry. Additionally, within the group of non-treatment-seeking cocaine-dependent individuals, we explored the role of frequently co-occurring features such as trait impulsivity (Barratt Impulsivity Scale, BIS), smoking, and depressive symptoms (Beck Depression Inventory), as well as the role of cocaine use duration, on frontal GM volume. Smaller GM volumes in non-treatment-seeking cocaine-dependent individuals were observed in the left middle frontal gyrus. Moreover, within the group of cocaine users, trait impulsivity was associated with reduced GM volume in the right orbitofrontal cortex, the left precentral gyrus, and the right superior frontal gyrus, whereas no effect of smoking severity, depressive symptoms, or duration of cocaine use was observed on regional GM volumes. Our data show an important association between trait impulsivity and frontal GM volumes in cocaine-dependent individuals. In contrast to previous studies with treatment-seeking cocaine-dependent patients, no significant effects of smoking severity, depressive symptoms, or duration of cocaine use on frontal GM volume were observed. Reduced frontal GM volumes in non-treatment-seeking cocaine-dependent subjects are associated with trait impulsivity and are not associated with co-occurring nicotine dependence or depression.

  9. [A case of crossed aphasia with echolalia after the resection of tumor in the right medial frontal lobe].

    Science.gov (United States)

    Endo, K; Suzuki, K; Yamadori, A; Kumabe, T; Seki, K; Fujii, T

    2001-03-01

    We report a right-handed woman, who developed a non-fluent aphasia after resection of astrocytoma (grade III) in the right medial frontal lobe. On admission to the rehabilitation department, neurological examination revealed mild left hemiparesis, hyperreflexia on the left side and grasp reflex on the left hand. Neuropsychologically she showed general inattention, non-fluent aphasia, acalculia, constructional disability, and mild buccofacial apraxia. No other apraxia, unilateral spatial neglect or extinction phenomena were observed. An MRI demonstrated resected areas in the right superior frontal gyrus, subcortical region in the right middle frontal gyrus, anterior part of the cingulate gyrus, a part of supplementary motor area. Surrounding area in the right frontal lobe showed diffuse signal change. She demonstrated non-fluent aprosodic speech with word finding difficulty. No phonemic paraphasia, or anarthria was observed. Auditory comprehension was fair with some difficulty in comprehending complex commands. Naming was good, but verbal fluency tests for a category or phonemic cuing was severely impaired. She could repeat words but not sentences. Reading comprehension was disturbed by semantic paralexia and writing words was poor for both Kana (syllabogram) and Kanji(logogram) characters. A significant feature of her speech was mitigated echolalia. In both free conversation and examination setting, she often repeated phrases spoken to her which she used to start her speech. In addition, she repeated words spoken to others which were totally irrelevant to her conversation. She was aware of her echoing, which always embarrassed her. She described her echolalic tendency as a great nuisance. However, once echoing being forbidden, she could not initiate her speech and made incorrect responses after long delay. Thus, her compulsive echolalia helped to start her speech. Only four patients with crossed aphasia demonstrated echolalia in the literature. They showed severe

  10. Obsessive-compulsive disorder and ventromedial frontal lesions

    DEFF Research Database (Denmark)

    Irle, E; Exner, C; Thielen, K

    1998-01-01

    subjects who had undergone ventromedial frontal leukotomy were evaluated clinically and neuropsychologically and compared to seven well comparison OCD subjects without leukotomy. The 16 leukotomized subjects were divided into three groups according to the main lesion sites as determined by current magnetic...... on the Wisconsin Card Sorting Test. Subjects with lesions of the dorsolateral frontal convexity also showed memory problems, attentional slowing, and lower performance IQ. CONCLUSIONS: Restricted ventromedial frontal leukotomy should be discussed as a last-resort treatment for severe and refractory OCD...

  11. Alteraciones de memoria en daño cerebral frontal

    OpenAIRE

    Vega Rodríguez, Irene de la; Noreña, David de

    2007-01-01

    El córtex frontal está implicado en importantes procesos de memoria, pero tiene un papel diferente al de las estructuras temporales y diencefálicas mediales. Mientras que el daño en estas estructuras produce una grave amnesia anterógrada, en el daño frontal se manifiestan una serie de problemas y distorsiones concretas como las fabulaciones, la amnesia de la fuente, el déficit de memoria prospectiva o las alteraciones en el recuerdo libre. El lóbulo frontal no está implicado en el almacenamie...

  12. Issues in localization of brain function: The case of lateralized frontal cortex in cognition, emotion, and psychopathology.

    Science.gov (United States)

    Miller, Gregory A; Crocker, Laura D; Spielberg, Jeffrey M; Infantolino, Zachary P; Heller, Wendy

    2013-01-01

    The appeal of simple, sweeping portraits of large-scale brain mechanisms relevant to psychological phenomena competes with a rich, complex research base. As a prominent example, two views of frontal brain organization have emphasized dichotomous lateralization as a function of either emotional valence (positive/negative) or approach/avoidance motivation. Compelling findings support each. The literature has struggled to choose between them for three decades, without success. Both views are proving untenable as comprehensive models. Evidence of other frontal lateralizations, involving distinctions among dimensions of depression and anxiety, make a dichotomous view even more problematic. Recent evidence indicates that positive valence and approach motivation are associated with different areas in the left-hemisphere. Findings that appear contradictory at the level of frontal lobes as the units of analysis can be accommodated because hemodynamic and electromagnetic neuroimaging studies suggest considerable functional differentiation, in specialization and activation, of subregions of frontal cortex, including their connectivity to each other and to other regions. Such findings contribute to a more nuanced understanding of functional localization that accommodates aspects of multiple theoretical perspectives.

  13. Diagnostic electrocardiographic dyad criteria of emphysema in left ventricular hypertrophy

    Directory of Open Access Journals (Sweden)

    Lanjewar SS

    2013-11-01

    Full Text Available Swapnil S Lanjewar,1 Lovely Chhabra,1 Vinod K Chaubey,1 Saurabh Joshi,1 Ganesh Kulkarni,1 Chandrasekhar Kothagundla,1 Sudesh Kaul,1 David H Spodick21Department of Internal Medicine, 2Department of Cardiovascular Medicine, Saint Vincent Hospital, University of Massachusetts Medical School, Worcester, MA, USABackground: The electrocardiographic diagnostic dyad of emphysema, namely a combination of the frontal vertical P-vector and a narrow QRS duration, can serve as a quasidiagnostic marker for emphysema, with specificity close to 100%. We postulated that the presence of left ventricular hypertrophy in emphysema may affect the sensitivity of this electrocardiographic criterion given that left ventricular hypertrophy generates prominent left ventricular forces and may increase the QRS duration.Methods: We reviewed the electrocardiograms and echocardiograms for 73 patients with emphysema. The patients were divided into two groups based on the presence or absence of echocardiographic evidence of left ventricular hypertrophy. The P-vector, QRS duration, and forced expiratory volume in one second (FEV1 were computed and compared between the two subgroups.Results: There was no statistically significant difference in qualitative lung function (FEV1 between the subgroups. There was no statistically significant difference in mean P-vector between the subgroups. The mean QRS duration was significantly longer in patients with left ventricular hypertrophy as compared with those without left ventricular hypertrophy.Conclusion: The presence of left ventricular hypertrophy may not affect the sensitivity of the P-vector verticalization when used as a lone criterion for diagnosing emphysema. However, the presence of left ventricular hypertrophy may significantly reduce the sensitivity of the electrocardiographic diagnostic dyad in emphysema, as it causes a widening of the QRS duration.Keywords: emphysema, electrocardiogram, left ventricular hypertrophy, chronic

  14. Left Ventricular Assist Devices

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    Khuansiri Narajeenron

    2017-04-01

    Full Text Available Audience: The audience for this classic team-based learning (cTBL session is emergency medicine residents, faculty, and students; although this topic is applicable to internal medicine and family medicine residents. Introduction: A left ventricular assist device (LVAD is a mechanical circulatory support device that can be placed in critically-ill patients who have poor left ventricular function. After LVAD implantation, patients have improved quality of life.1 The number of LVAD patients worldwide continues to rise. Left-ventricular assist device patients may present to the emergency department (ED with severe, life-threatening conditions. It is essential that emergency physicians have a good understanding of LVADs and their complications. Objectives: Upon completion of this cTBL module, the learner will be able to: 1 Properly assess LVAD patients’ circulatory status; 2 appropriately resuscitate LVAD patients; 3 identify common LVAD complications; 4 evaluate and appropriately manage patients with LVAD malfunctions. Method: The method for this didactic session is cTBL.

  15. Roles of frontal and temporal regions in reinterpreting semantically ambiguous sentences

    Directory of Open Access Journals (Sweden)

    Sylvia eVitello

    2014-07-01

    Full Text Available Semantic ambiguity resolution is an essential and frequent part of speech comprehension because many words map onto multiple meanings (e.g., bark, bank. Neuroimaging research highlights the importance of the left inferior frontal gyrus (LIFG and the left posterior temporal cortex in this process but the roles they serve in ambiguity resolution are uncertain. One possibility is that both regions are engaged in the processes of semantic reinterpretation that follows incorrect interpretation of an ambiguous word. Here we used fMRI to investigate this hypothesis. 20 native British English monolinguals were scanned whilst listening to sentences that contained an ambiguous word. To induce semantic reinterpretation, the disambiguating information was presented after the ambiguous word and delayed until the end of the sentence (e.g., the teacher explained that the BARK was going to be very damp. These sentences were compared to well-matched unambiguous sentences. Supporting the reinterpretation hypothesis, these ambiguous sentences produced more activation in both the LIFG and the left posterior inferior temporal cortex. Importantly, all but one subject showed ambiguity-related peaks within both regions, demonstrating that the group-level results were driven by high inter-subject consistency. Further support came from the finding that activation in both regions was modulated by meaning dominance. Specifically, sentences containing biased ambiguous words, which have one more dominant meaning, produced greater activation than those with balanced ambiguous words, which have two equally frequent meanings. Because the context always supported the less frequent meaning, the biased words require reinterpretation more often than balanced words. This is the first evidence of dominance effects in the spoken modality and provides strong support that frontal and temporal regions support the updating of semantic representations during speech comprehension.

  16. Differential involvement of left prefrontal cortex in inductive and deductive reasoning.

    Science.gov (United States)

    Goel, Vinod; Dolan, Raymond J

    2004-10-01

    While inductive and deductive reasoning are considered distinct logical and psychological processes, little is known about their respective neural basis. To address this issue we scanned 16 subjects with fMRI, using an event-related design, while they engaged in inductive and deductive reasoning tasks. Both types of reasoning were characterized by activation of left lateral prefrontal and bilateral dorsal frontal, parietal, and occipital cortices. Neural responses unique to each type of reasoning determined from the Reasoning Type (deduction and induction) by Task (reasoning and baseline) interaction indicated greater involvement of left inferior frontal gyrus (BA 44) in deduction than induction, while left dorsolateral (BA 8/9) prefrontal gyrus showed greater activity during induction than deduction. This pattern suggests a dissociation within prefrontal cortex for deductive and inductive reasoning.

  17. Increased frontal electroencephalogram theta amplitude in patients with anorexia nervosa compared to healthy controls

    Directory of Open Access Journals (Sweden)

    Hestad KA

    2016-09-01

    Full Text Available Knut A Hestad,1–3 Siri Weider,3,4 Kristian Bernhard Nilsen,5–7 Marit Sæbø Indredavik,8,9 Trond Sand7,10 1Department of Research, Innlandet Hospital Trust, Brumunddal, Norway; 2Department of Public Health, Hedmark University of Applied Sciences, Elverum, Norway; 3Department of Psychology, Faculty of Social Sciences and Technology Management, Norwegian University of Science and Technology (NTNU, Trondheim, Norway; 4Department of Psychiatry, Specialised Unit for Eating Disorder Patients, Levanger Hospital, Health Trust Nord-Trøndelag, Levanger, Norway; 5Department of Neuroscience, Norwegian University of Science and Technology (NTNU, Trondheim, Norway; 6Department of Work Psychology and Physiology, National Institute of Occupational Health, Oslo, Norway; 7Department of Neurology, Section for Clinical Neurophysiology, Oslo University Hospital, Ullevål, Oslo, Norway; 8Regional Centre for Child and Youth Mental Health and Child Welfare, Faculty of Medicine, Norwegian University of Science and Technology (NTNU, Trondheim, Norway; 9Department of Child and Adolescent Psychiatry, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway; 10Department of Neurology and Clinical Neurophysiology, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway Objective: To conduct a blind study of quantitative electroencephalogram-band amplitudes in patients with anorexia nervosa (AN and healthy controls.Methods: Twenty-one patients with AN and 24 controls were examined with eyes-closed 16-channel electroencephalogram. Main variables were absolute alpha, theta, and delta amplitudes in frontal, temporal, and posterior regions.Results: There were no significant differences between the AN patients and controls regarding absolute regional band amplitudes in µV. Borderline significance was found for anterior theta (P=0.051. Significantly increased left and right frontal electrode theta amplitude was found in AN patients (F3, P=0.014; F4, P

  18. Frontal dynamic aphasia in progressive supranuclear palsy: Distinguishing between generation and fluent sequencing of novel thoughts.

    Science.gov (United States)

    Robinson, Gail A; Spooner, Donna; Harrison, William J

    2015-10-01

    Frontal dynamic aphasia is characterised by a profound reduction in spontaneous speech despite well-preserved naming, repetition and comprehension. Since Luria (1966, 1970) designated this term, two main forms of dynamic aphasia have been identified: one, a language-specific selection deficit at the level of word/sentence generation, associated with left inferior frontal lesions; and two, a domain-general impairment in generating multiple responses or connected speech, associated with more extensive bilateral frontal and/or frontostriatal damage. Both forms of dynamic aphasia have been interpreted as arising due to disturbances in early prelinguistic conceptual preparation mechanisms that are critical for language production. We investigate language-specific and domain-general accounts of dynamic aphasia and address two issues: one, whether deficits in multiple conceptual preparation mechanisms can co-occur; and two, the contribution of broader cognitive processes such as energization, the ability to initiate and sustain response generation over time, to language generation failure. Thus, we report patient WAL who presented with frontal dynamic aphasia in the context of progressive supranuclear palsy (PSP). WAL was given a series of experimental tests that showed that his dynamic aphasia was not underpinned by a language-specific deficit in selection or in microplanning. By contrast, WAL presented with a domain-general deficit in fluent sequencing of novel thoughts. The latter replicated the pattern documented in a previous PSP patient (Robinson, et al., 2006); however, unique to WAL, generating novel thoughts was impaired but there was no evidence of a sequencing deficit because perseveration was absent. Thus, WAL is the first unequivocal case to show a distinction between novel thought generation and subsequent fluent sequencing. Moreover, WAL's generation deficit encompassed verbal and non-verbal responses, showing a similar (but more profoundly reduced) pattern

  19. Pediatric frontal lobe epilepsy : white matter abnormalities and cognitive impairment

    NARCIS (Netherlands)

    Braakman, H.M.H.; Vaessen, M.J.; Jansen, J.F.A.; Debeij-van Hall, M.H.J.A.; Louw, de A.; Hofman, P.A.M.; Vles, J.S.H.; Aldenkamp, A.P.; Backes, W.H.

    2014-01-01

    Objectives: Cognitive impairment is frequent in children with frontal lobe epilepsy (FLE). Its etiology remains unknown. With diffusion tensor imaging, we have studied cerebral white matter properties and associations with cognitive functioning in children with FLE and healthy controls.

  20. Genetics Home Reference: autosomal dominant nocturnal frontal lobe epilepsy

    Science.gov (United States)

    ... with ADNFLE have experienced psychiatric disorders (such as schizophrenia), behavioral problems, or intellectual disability. It is unclear ... Epilepsy Society Citizens United for Research in Epilepsy (CURE) GeneReviews (1 link) Autosomal Dominant Nocturnal Frontal Lobe ...

  1. Challenge-driven attention: interacting frontal and brainstem systems

    Directory of Open Access Journals (Sweden)

    Rajeev D S Raizada

    2008-03-01

    Full Text Available The world is an unpredictable place, presenting challenges that fl uctuate from moment to moment. However, the neural systems for responding to such challenges are far from fully understood. Using fMRI, we studied an audiovisual task in which the trials' diffi culty and onset times varied unpredictably. Two regions were found to increase their activation for challenging trials, with their activities strongly correlated: right frontal cortex and the brainstem. The frontal area matched regions found in previous human studies of cognitive control, and activated in a graded manner with increasing task diffi culty. The brainstem responded only to the most diffi cult trials, showing a phasic activity pattern paralleling locus coeruleus recordings in monkeys. These results reveal a bridge between animal and human studies, and suggest interacting roles for the brainstem and right frontal cortex: the brainstem may signal that an attentional challenge is occurring, while right frontal cortex allocates cognitive resources in response.

  2. Right-frontal cortical asymmetry predicts increased proneness to nostalgia.

    Science.gov (United States)

    Tullett, Alexa M; Wildschut, Tim; Sedikides, Constantine; Inzlicht, Michael

    2015-08-01

    Nostalgia is often triggered by feelings-such as sadness, loneliness, or meaninglessness-that are typically associated with withdrawal motivation. Here, we examined whether a trait tendency to experience withdrawal motivation is associated with nostalgia proneness. Past work indicates that baseline right-frontal cortical asymmetry is a neural correlate of withdrawal-related motivation. We therefore hypothesized that higher baseline levels of right-frontal asymmetry would predict increased proneness to nostalgia. We assessed participants' baseline levels of frontal cortical activity using EEG. Results supported the hypothesis and demonstrated that the association between relative right-frontal asymmetry and increased nostalgia remained significant when controlling for the Big Five personality traits. Overall, these findings indicate that individuals with a stronger dispositional tendency to experience withdrawal-related motivation are more prone to nostalgia. © 2015 Society for Psychophysiological Research.

  3. Frontal lobe epilepsy may present as myoclonic seizures.

    Science.gov (United States)

    Cho, Yong Won; Yi, Sang Doe; Motamedi, Gholam K

    2010-04-01

    We describe a patient with seizures arising from right anterior-inferior frontal lobe presenting as myoclonic epilepsy. A 19-year-old man had experienced frequent paroxysmal bilateral myoclonic jerks involving his upper arms, shoulders, neck, and upper trunk since the age of 10. His baseline EEG showed intermittent right frontal spikes, and his ictal EEG showed rhythmic sharp theta discharges in the same area. MRI revealed cortical dysplasia in the right inferior frontal gyrus, and ictal-interictal SPECT analysis by SPM showed increased signal abnormality in this region. Diffusion tensor imaging (DTI) showed defects in fasciculi in the same area. These findings suggest that frontal lobe epilepsy should be considered in some patients with myoclonic seizures. Copyright (c) 2010 Elsevier Inc. All rights reserved.

  4. Acute Infantile Encephalopathy Predominantly Affecting The Frontal Lobes (AIEF).

    Science.gov (United States)

    Raha, Sarbani; Udani, Vrajesh

    2012-12-01

    Acute Infantile Encephalopathy Predominantly Affecting the Frontal Lobes (AIEF) is a relatively recent described entity. This article includes case reports of two patients who had bifrontal involvement during acute febrile encephalopathy. Case 1 describes a 1-y-old boy who presented with hyperpyrexia and dialeptic seizures. Imaging revealed significant bilateral frontal lobe involvement while serology proved presence of Influenza B infection. Over a period of one wk, he recovered with significant cognitive decline and perseveratory behavior. Another 6-y-old boy presented with language and behavioral problems suggestive of frontal dysfunction after recovering from prolonged impairment of consciousness following a convulsive status epilepticus. Bilateral superior frontal lesions with gyral swelling was evident on neuroimaging. These cases are among the very few cases of AIEF described in recent literature and the article also reviews this unique subtype of acute encephalopathy.

  5. Training strategy for convolutional neural networks in pedestrian gender classification

    Science.gov (United States)

    Ng, Choon-Boon; Tay, Yong-Haur; Goi, Bok-Min

    2017-06-01

    In this work, we studied a strategy for training a convolutional neural network in pedestrian gender classification with limited amount of labeled training data. Unsupervised learning by k-means clustering on pedestrian images was used to learn the filters to initialize the first layer of the network. As a form of pre-training, supervised learning for the related task of pedestrian classification was performed. Finally, the network was fine-tuned for gender classification. We found that this strategy improved the network's generalization ability in gender classification, achieving better test results when compared to random weights initialization and slightly more beneficial than merely initializing the first layer filters by unsupervised learning. This shows that unsupervised learning followed by pre-training with pedestrian images is an effective strategy to learn useful features for pedestrian gender classification.

  6. Accurate lithography simulation model based on convolutional neural networks

    Science.gov (United States)

    Watanabe, Yuki; Kimura, Taiki; Matsunawa, Tetsuaki; Nojima, Shigeki

    2017-07-01

    Lithography simulation is an essential technique for today's semiconductor manufacturing process. In order to calculate an entire chip in realistic time, compact resist model is commonly used. The model is established for faster calculation. To have accurate compact resist model, it is necessary to fix a complicated non-linear model function. However, it is difficult to decide an appropriate function manually because there are many options. This paper proposes a new compact resist model using CNN (Convolutional Neural Networks) which is one of deep learning techniques. CNN model makes it possible to determine an appropriate model function and achieve accurate simulation. Experimental results show CNN model can reduce CD prediction errors by 70% compared with the conventional model.

  7. An effective convolutional neural network model for Chinese sentiment analysis

    Science.gov (United States)

    Zhang, Yu; Chen, Mengdong; Liu, Lianzhong; Wang, Yadong

    2017-06-01

    Nowadays microblog is getting more and more popular. People are increasingly accustomed to expressing their opinions on Twitter, Facebook and Sina Weibo. Sentiment analysis of microblog has received significant attention, both in academia and in industry. So far, Chinese microblog exploration still needs lots of further work. In recent years CNN has also been used to deal with NLP tasks, and already achieved good results. However, these methods ignore the effective use of a large number of existing sentimental resources. For this purpose, we propose a Lexicon-based Sentiment Convolutional Neural Networks (LSCNN) model focus on Weibo's sentiment analysis, which combines two CNNs, trained individually base on sentiment features and word embedding, at the fully connected hidden layer. The experimental results show that our model outperforms the CNN model only with word embedding features on microblog sentiment analysis task.

  8. High Order Tensor Formulation for Convolutional Sparse Coding

    KAUST Repository

    Bibi, Adel Aamer

    2017-12-25

    Convolutional sparse coding (CSC) has gained attention for its successful role as a reconstruction and a classification tool in the computer vision and machine learning community. Current CSC methods can only reconstruct singlefeature 2D images independently. However, learning multidimensional dictionaries and sparse codes for the reconstruction of multi-dimensional data is very important, as it examines correlations among all the data jointly. This provides more capacity for the learned dictionaries to better reconstruct data. In this paper, we propose a generic and novel formulation for the CSC problem that can handle an arbitrary order tensor of data. Backed with experimental results, our proposed formulation can not only tackle applications that are not possible with standard CSC solvers, including colored video reconstruction (5D- tensors), but it also performs favorably in reconstruction with much fewer parameters as compared to naive extensions of standard CSC to multiple features/channels.

  9. Classification of decays involving variable decay chains with convolutional architectures

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Vidyo contribution We present a technique to perform classification of decays that exhibit decay chains involving a variable number of particles, which include a broad class of $B$ meson decays sensitive to new physics. The utility of such decays as a probe of the Standard Model is dependent upon accurate determination of the decay rate, which is challenged by the combinatorial background arising in high-multiplicity decay modes. In our model, each particle in the decay event is represented as a fixed-dimensional vector of feature attributes, forming an $n \\times k$ representation of the event, where $n$ is the number of particles in the event and $k$ is the dimensionality of the feature vector. A convolutional architecture is used to capture dependencies between the embedded particle representations and perform the final classification. The proposed model performs outperforms standard machine learning approaches based on Monte Carlo studies across a range of variable final-state decays with the Belle II det...

  10. CONEDEP: COnvolutional Neural network based Earthquake DEtection and Phase Picking

    Science.gov (United States)

    Zhou, Y.; Huang, Y.; Yue, H.; Zhou, S.; An, S.; Yun, N.

    2017-12-01

    We developed an automatic local earthquake detection and phase picking algorithm based on Fully Convolutional Neural network (FCN). The FCN algorithm detects and segments certain features (phases) in 3 component seismograms to realize efficient picking. We use STA/LTA algorithm and template matching algorithm to construct the training set from seismograms recorded 1 month before and after the Wenchuan earthquake. Precise P and S phases are identified and labeled to construct the training set. Noise data are produced by combining back-ground noise and artificial synthetic noise to form the equivalent scale of noise set as the signal set. Training is performed on GPUs to achieve efficient convergence. Our algorithm has significantly improved performance in terms of the detection rate and precision in comparison with STA/LTA and template matching algorithms.

  11. Computational optical tomography using 3-D deep convolutional neural networks

    Science.gov (United States)

    Nguyen, Thanh; Bui, Vy; Nehmetallah, George

    2018-04-01

    Deep convolutional neural networks (DCNNs) offer a promising performance for many image processing areas, such as super-resolution, deconvolution, image classification, denoising, and segmentation, with outstanding results. Here, we develop for the first time, to our knowledge, a method to perform 3-D computational optical tomography using 3-D DCNN. A simulated 3-D phantom dataset was first constructed and converted to a dataset of phase objects imaged on a spatial light modulator. For each phase image in the dataset, the corresponding diffracted intensity image was experimentally recorded on a CCD. We then experimentally demonstrate the ability of the developed 3-D DCNN algorithm to solve the inverse problem by reconstructing the 3-D index of refraction distributions of test phantoms from the dataset from their corresponding diffraction patterns.

  12. Drug-Drug Interaction Extraction via Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Shengyu Liu

    2016-01-01

    Full Text Available Drug-drug interaction (DDI extraction as a typical relation extraction task in natural language processing (NLP has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM with a large number of manually defined features. Recently, convolutional neural networks (CNN, a robust machine learning method which almost does not need manually defined features, has exhibited great potential for many NLP tasks. It is worth employing CNN for DDI extraction, which has never been investigated. We proposed a CNN-based method for DDI extraction. Experiments conducted on the 2013 DDIExtraction challenge corpus demonstrate that CNN is a good choice for DDI extraction. The CNN-based DDI extraction method achieves an F-score of 69.75%, which outperforms the existing best performing method by 2.75%.

  13. Truncation Depth Rule-of-Thumb for Convolutional Codes

    Science.gov (United States)

    Moision, Bruce

    2009-01-01

    In this innovation, it is shown that a commonly used rule of thumb (that the truncation depth of a convolutional code should be five times the memory length, m, of the code) is accurate only for rate 1/2 codes. In fact, the truncation depth should be 2.5 m/(1 - r), where r is the code rate. The accuracy of this new rule is demonstrated by tabulating the distance properties of a large set of known codes. This new rule was derived by bounding the losses due to truncation as a function of the code rate. With regard to particular codes, a good indicator of the required truncation depth is the path length at which all paths that diverge from a particular path have accumulated the minimum distance of the code. It is shown that the new rule of thumb provides an accurate prediction of this depth for codes of varying rates.

  14. Finding Neutrinos in LArTPCs using Convolutional Neural Networks

    Science.gov (United States)

    Wongjirad, Taritree

    2017-09-01

    Deep learning algorithms, which have emerged over the last decade, are opening up new ways to analyze data for many particle physics experiments. MicroBooNE, which is a neutrino experiment at Fermilab, has been exploring the use of such algorithms, in particular, convolutional neural networks (CNNS). CNNs are the state-of-the-art method for a large class of problems involving the analysis of images. This makes CNNs an attractive approach for MicroBooNE, whose detector, a liquid argon time projection chamber (LArTPC), produces high-resolution images of particle interactions. In this talk, I will discuss the ways CNNs can be applied to tasks like neutrino interaction detection and particle identification in MicroBooNE and LArTPCs.

  15. Radio frequency interference mitigation using deep convolutional neural networks

    Science.gov (United States)

    Akeret, J.; Chang, C.; Lucchi, A.; Refregier, A.

    2017-01-01

    We propose a novel approach for mitigating radio frequency interference (RFI) signals in radio data using the latest advances in deep learning. We employ a special type of Convolutional Neural Network, the U-Net, that enables the classification of clean signal and RFI signatures in 2D time-ordered data acquired from a radio telescope. We train and assess the performance of this network using the HIDE &SEEK radio data simulation and processing packages, as well as early Science Verification data acquired with the 7m single-dish telescope at the Bleien Observatory. We find that our U-Net implementation is showing competitive accuracy to classical RFI mitigation algorithms such as SEEK's SUMTHRESHOLD implementation. We publish our U-Net software package on GitHub under GPLv3 license.

  16. Forecasting Flare Activity Using Deep Convolutional Neural Networks

    Science.gov (United States)

    Hernandez, T.

    2017-12-01

    Current operational flare forecasting relies on human morphological analysis of active regions and the persistence of solar flare activity through time (i.e. that the Sun will continue to do what it is doing right now: flaring or remaining calm). In this talk we present the results of applying deep Convolutional Neural Networks (CNNs) to the problem of solar flare forecasting. CNNs operate by training a set of tunable spatial filters that, in combination with neural layer interconnectivity, allow CNNs to automatically identify significant spatial structures predictive for classification and regression problems. We will start by discussing the applicability and success rate of the approach, the advantages it has over non-automated forecasts, and how mining our trained neural network provides a fresh look into the mechanisms behind magnetic energy storage and release.

  17. Convolutional neural networks with balanced batches for facial expressions recognition

    Science.gov (United States)

    Battini Sönmez, Elena; Cangelosi, Angelo

    2017-03-01

    This paper considers the issue of fully automatic emotion classification on 2D faces. In spite of the great effort done in recent years, traditional machine learning approaches based on hand-crafted feature extraction followed by the classification stage failed to develop a real-time automatic facial expression recognition system. The proposed architecture uses Convolutional Neural Networks (CNN), which are built as a collection of interconnected processing elements to simulate the brain of human beings. The basic idea of CNNs is to learn a hierarchical representation of the input data, which results in a better classification performance. In this work we present a block-based CNN algorithm, which uses noise, as data augmentation technique, and builds batches with a balanced number of samples per class. The proposed architecture is a very simple yet powerful CNN, which can yield state-of-the-art accuracy on the very competitive benchmark algorithm of the Extended Cohn Kanade database.

  18. Network Intrusion Detection through Stacking Dilated Convolutional Autoencoders

    Directory of Open Access Journals (Sweden)

    Yang Yu

    2017-01-01

    Full Text Available Network intrusion detection is one of the most important parts for cyber security to protect computer systems against malicious attacks. With the emergence of numerous sophisticated and new attacks, however, network intrusion detection techniques are facing several significant challenges. The overall objective of this study is to learn useful feature representations automatically and efficiently from large amounts of unlabeled raw network traffic data by using deep learning approaches. We propose a novel network intrusion model by stacking dilated convolutional autoencoders and evaluate our method on two new intrusion detection datasets. Several experiments were carried out to check the effectiveness of our approach. The comparative experimental results demonstrate that the proposed model can achieve considerably high performance which meets the demand of high accuracy and adaptability of network intrusion detection systems (NIDSs. It is quite potential and promising to apply our model in the large-scale and real-world network environments.

  19. Fully Convolutional Network Based Shadow Extraction from GF-2 Imagery

    Science.gov (United States)

    Li, Z.; Cai, G.; Ren, H.

    2018-04-01

    There are many shadows on the high spatial resolution satellite images, especially in the urban areas. Although shadows on imagery severely affect the information extraction of land cover or land use, they provide auxiliary information for building extraction which is hard to achieve a satisfactory accuracy through image classification itself. This paper focused on the method of building shadow extraction by designing a fully convolutional network and training samples collected from GF-2 satellite imagery in the urban region of Changchun city. By means of spatial filtering and calculation of adjacent relationship along the sunlight direction, the small patches from vegetation or bridges have been eliminated from the preliminary extracted shadows. Finally, the building shadows were separated. The extracted building shadow information from the proposed method in this paper was compared with the results from the traditional object-oriented supervised classification algorihtms. It showed that the deep learning network approach can improve the accuracy to a large extent.

  20. Finger vein recognition based on convolutional neural network

    Directory of Open Access Journals (Sweden)

    Meng Gesi

    2017-01-01

    Full Text Available Biometric Authentication Technology has been widely used in this information age. As one of the most important technology of authentication, finger vein recognition attracts our attention because of its high security, reliable accuracy and excellent performance. However, the current finger vein recognition system is difficult to be applied widely because its complicated image pre-processing and not representative feature vectors. To solve this problem, a finger vein recognition method based on the convolution neural network (CNN is proposed in the paper. The image samples are directly input into the CNN model to extract its feature vector so that we can make authentication by comparing the Euclidean distance between these vectors. Finally, the Deep Learning Framework Caffe is adopted to verify this method. The result shows that there are great improvements in both speed and accuracy rate compared to the previous research. And the model has nice robustness in illumination and rotation.