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Pronin S, Wellacott L, Pimentel J, Moioli RC, Vargas PA. Neurorobotic Models of Neurological Disorders: A Mini Review. Front Neurorobot 2021; 15:634045. [PMID: 33828474 PMCID: PMC8020031 DOI: 10.3389/fnbot.2021.634045] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 02/23/2021] [Indexed: 01/07/2023] Open
Abstract
Modeling is widely used in biomedical research to gain insights into pathophysiology and treatment of neurological disorders but existing models, such as animal models and computational models, are limited in generalizability to humans and are restricted in the scope of possible experiments. Robotics offers a potential complementary modeling platform, with advantages such as embodiment and physical environmental interaction yet with easily monitored and adjustable parameters. In this review, we discuss the different types of models used in biomedical research and summarize the existing neurorobotics models of neurological disorders. We detail the pertinent findings of these robot models which would not have been possible through other modeling platforms. We also highlight the existing limitations in a wider uptake of robot models for neurological disorders and suggest future directions for the field.
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Affiliation(s)
- Savva Pronin
- Robotics Laboratory, Edinburgh Centre for Robotics, Heriot-Watt University, Edinburgh, United Kingdom.,College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Liam Wellacott
- Robotics Laboratory, Edinburgh Centre for Robotics, Heriot-Watt University, Edinburgh, United Kingdom
| | - Jhielson Pimentel
- Robotics Laboratory, Edinburgh Centre for Robotics, Heriot-Watt University, Edinburgh, United Kingdom
| | - Renan C Moioli
- Bioinformatics Multidisciplinary Environment, Digital Metropolis Institute, Federal University of Rio Grande do Norte, Natal, Brazil
| | - Patricia A Vargas
- Robotics Laboratory, Edinburgh Centre for Robotics, Heriot-Watt University, Edinburgh, United Kingdom
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2
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Zhang M, Feng J, Ma KT, Lim JH, Zhao Q, Kreiman G. Finding any Waldo with zero-shot invariant and efficient visual search. Nat Commun 2018; 9:3730. [PMID: 30213937 PMCID: PMC6137219 DOI: 10.1038/s41467-018-06217-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 08/10/2018] [Indexed: 11/11/2022] Open
Abstract
Searching for a target object in a cluttered scene constitutes a fundamental challenge in daily vision. Visual search must be selective enough to discriminate the target from distractors, invariant to changes in the appearance of the target, efficient to avoid exhaustive exploration of the image, and must generalize to locate novel target objects with zero-shot training. Previous work on visual search has focused on searching for perfect matches of a target after extensive category-specific training. Here, we show for the first time that humans can efficiently and invariantly search for natural objects in complex scenes. To gain insight into the mechanisms that guide visual search, we propose a biologically inspired computational model that can locate targets without exhaustive sampling and which can generalize to novel objects. The model provides an approximation to the mechanisms integrating bottom-up and top-down signals during search in natural scenes.
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Affiliation(s)
- Mengmi Zhang
- Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, 138632, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 138632, Singapore
- Visual Intelligence Unit, Image/Video Analytics Dept, A*STAR, Singapore, 138632, Singapore
| | - Jiashi Feng
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 138632, Singapore
| | - Keng Teck Ma
- Artificial Intelligence Program, Agency for Science, Technology and Research, Singapore, 138632, Singapore
| | - Joo Hwee Lim
- Visual Intelligence Unit, Image/Video Analytics Dept, A*STAR, Singapore, 138632, Singapore
| | - Qi Zhao
- Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, 55455, USA
| | - Gabriel Kreiman
- Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
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Gigliotta O, Seidel Malkinson T, Miglino O, Bartolomeo P. Pseudoneglect in Visual Search: Behavioral Evidence and Connectional Constraints in Simulated Neural Circuitry. eNeuro 2017; 4:ENEURO.0154-17.2017. [PMID: 29291241 PMCID: PMC5745611 DOI: 10.1523/eneuro.0154-17.2017] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 11/30/2017] [Accepted: 12/04/2017] [Indexed: 11/29/2022] Open
Abstract
Most people tend to bisect horizontal lines slightly to the left of their true center (pseudoneglect) and start visual search from left-sided items. This physiological leftward spatial bias may depend on hemispheric asymmetries in the organization of attentional networks, but the precise mechanisms are unknown. Here, we modeled relevant aspects of the ventral and dorsal attentional networks (VAN and DAN) of the human brain. First, we demonstrated pseudoneglect in visual search in 101 right-handed psychology students. Participants consistently tended to start the task from a left-sided item, thus showing pseudoneglect. Second, we trained populations of simulated neurorobots to perform a similar task, by using a genetic algorithm. The neurorobots' behavior was controlled by artificial neural networks, which simulated the human VAN and DAN in the two brain hemispheres. Neurorobots differed in the connectional constraints that were applied to the anatomy and function of the attention networks. Results indicated that (1) neurorobots provided with a biologically plausible hemispheric asymmetry of the VAN-DAN connections, as well as with interhemispheric inhibition, displayed the best match with human data; however; (2) anatomical asymmetry per se was not sufficient to generate pseudoneglect; in addition, the VAN must have an excitatory influence on the ipsilateral DAN; and (3) neurorobots provided with bilateral competence in the VAN but without interhemispheric inhibition failed to display pseudoneglect. These findings provide a proof of concept of the causal link between connectional asymmetries and pseudoneglect and specify important biological constraints that result in physiological asymmetries of human behavior.
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Affiliation(s)
- Onofrio Gigliotta
- Department of Humanistic Studies, University of Naples Federico II, 80133 Naples, Italy
| | - Tal Seidel Malkinson
- Institut National de la Santé et de la Recherche Médicale Unité 1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche (UMR) 7225, Sorbonne Universités, Université Pierre-et-Marie-Curie Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle Épinière ICM, 75013 Paris, France
| | - Orazio Miglino
- Department of Humanistic Studies, University of Naples Federico II, 80133 Naples, Italy
- Institute of Cognitive Sciences and Technologies, National Research Council, 00185 Rome, Italy
| | - Paolo Bartolomeo
- Institut National de la Santé et de la Recherche Médicale Unité 1127, Centre National de la Recherche Scientifique Unité Mixte de Recherche (UMR) 7225, Sorbonne Universités, Université Pierre-et-Marie-Curie Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle Épinière ICM, 75013 Paris, France
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Beran MJ, Menzel CR, Parrish AE, Perdue BM, Sayers K, Smith JD, Washburn DA. Primate cognition: attention, episodic memory, prospective memory, self-control, and metacognition as examples of cognitive control in nonhuman primates. WILEY INTERDISCIPLINARY REVIEWS. COGNITIVE SCIENCE 2016; 7:294-316. [PMID: 27284790 PMCID: PMC5173379 DOI: 10.1002/wcs.1397] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Revised: 04/21/2016] [Accepted: 04/28/2016] [Indexed: 11/09/2022]
Abstract
Primate Cognition is the study of cognitive processes, which represent internal mental processes involved in discriminations, decisions, and behaviors of humans and other primate species. Cognitive control involves executive and regulatory processes that allocate attention, manipulate and evaluate available information (and, when necessary, seek additional information), remember past experiences to plan future behaviors, and deal with distraction and impulsivity when they are threats to goal achievement. Areas of research that relate to cognitive control as it is assessed across species include executive attention, episodic memory, prospective memory, metacognition, and self-control. Executive attention refers to the ability to control what sensory stimuli one attends to and how one regulates responses to those stimuli, especially in cases of conflict. Episodic memory refers to memory for personally experienced, autobiographical events. Prospective memory refers to the formation and implementation of future-intended actions, such as remembering what needs to be done later. Metacognition consists of control and monitoring processes that allow individuals to assess what information they have and what information they still need, and then if necessary to seek information. Self-control is a regulatory process whereby individuals forego more immediate or easier to obtain rewards for more delayed or harder to obtain rewards that are objectively more valuable. The behavioral complexity shown by nonhuman primates when given tests to assess these capacities indicates psychological continuities with human cognitive control capacities. However, more research is needed to clarify the proper interpretation of these behaviors with regard to possible cognitive constructs that may underlie such behaviors. WIREs Cogn Sci 2016, 7:294-316. doi: 10.1002/wcs.1397 For further resources related to this article, please visit the WIREs website.
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Affiliation(s)
- Michael J Beran
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Charles R Menzel
- Language Research Center, Georgia State University, Atlanta, GA, USA
| | - Audrey E Parrish
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Bonnie M Perdue
- Department of Psychology, Agnes Scott College, Decatur, GA, USA
| | - Ken Sayers
- Language Research Center, Georgia State University, Atlanta, GA, USA
| | - J David Smith
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - David A Washburn
- Department of Psychology, Georgia State University, Atlanta, GA, USA
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Conti D, Di Nuovo S, Cangelosi A, Di Nuovo A. Lateral specialization in unilateral spatial neglect: a cognitive robotics model. Cogn Process 2016; 17:321-8. [PMID: 27018020 PMCID: PMC4933727 DOI: 10.1007/s10339-016-0761-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Accepted: 03/10/2016] [Indexed: 11/25/2022]
Abstract
In this paper, we present the experimental results of an embodied cognitive robotic approach for modelling the human cognitive deficit known as unilateral spatial neglect (USN). To this end, we introduce an artificial neural network architecture designed and trained to control the spatial attentional focus of the iCub robotic platform. Like the human brain, the architecture is divided into two hemispheres and it incorporates bio-inspired plasticity mechanisms, which allow the development of the phenomenon of the specialization of the right hemisphere for spatial attention. In this study, we validate the model by replicating a previous experiment with human patients affected by the USN and numerical results show that the robot mimics the behaviours previously exhibited by humans. We also simulated recovery after the damage to compare the performance of each of the two hemispheres as additional validation of the model. Finally, we highlight some possible advantages of modelling cognitive dysfunctions of the human brain by means of robotic platforms, which can supplement traditional approaches for studying spatial impairments in humans.
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Affiliation(s)
- Daniela Conti
- Department of Education Sciences, University of Catania, Via Biblioteca 4, 95124, Catania, Italy
| | - Santo Di Nuovo
- Psychology Operative Unit, IRCCS "Maria SS" Oasi di Troina, 73, Conte Ruggero, 94018, Troina, Italy
| | - Angelo Cangelosi
- Centre for Robotics and Neural Systems, Plymouth University, Drake Circus, Plymouth, PL48AA, UK
| | - Alessandro Di Nuovo
- Sheffield Robotics, Sheffield Hallam University, Howard Street, Sheffield, S11WB, UK. .,Department of Engineering and Architecture, University of Enna "Kore", Viale delle Olimpiadi, 94100, Enna, Italy.
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Miconi T, Groomes L, Kreiman G. There's Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task. Cereb Cortex 2015; 26:3064-82. [PMID: 26092221 DOI: 10.1093/cercor/bhv129] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
When searching for an object in a scene, how does the brain decide where to look next? Visual search theories suggest the existence of a global "priority map" that integrates bottom-up visual information with top-down, target-specific signals. We propose a mechanistic model of visual search that is consistent with recent neurophysiological evidence, can localize targets in cluttered images, and predicts single-trial behavior in a search task. This model posits that a high-level retinotopic area selective for shape features receives global, target-specific modulation and implements local normalization through divisive inhibition. The normalization step is critical to prevent highly salient bottom-up features from monopolizing attention. The resulting activity pattern constitues a priority map that tracks the correlation between local input and target features. The maximum of this priority map is selected as the locus of attention. The visual input is then spatially enhanced around the selected location, allowing object-selective visual areas to determine whether the target is present at this location. This model can localize objects both in array images and when objects are pasted in natural scenes. The model can also predict single-trial human fixations, including those in error and target-absent trials, in a search task involving complex objects.
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Affiliation(s)
- Thomas Miconi
- Children's Hospital, Harvard Medical School, Boston, MA, USA The Neurosciences Institute, La Jolla, CA 92037, USA
| | - Laura Groomes
- Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Gabriel Kreiman
- Children's Hospital, Harvard Medical School, Boston, MA, USA Center for Brain Science Swartz Center for Theoretical Neuroscience, Harvard University, Cambridge, MA, USA
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Abstract
While moving through their environment, medicinal leeches stop periodically and wave their head or body back and forth. This activity has been previously described as two separate behaviors: one called ‘head movement’ and another called ‘body waving’. Here, we report that these behaviors exist on a continuum, and provide a detailed description of what we now call ‘scanning’. Scanning-related behavior has been thought to be involved in orientation; its function has never before been assessed. While previous studies suggested an involvement of scanning in social behavior, or sucker placement, our behavioral studies indicate that scanning is involved in orienting the leech towards prey stimuli. When such stimuli are present, scanning behavior is used to re-orient the leech in the direction of a prey-like stimulus. Scanning, however, occurs whether or not prey is present, but in the presence of prey-like stimuli scanning becomes localized to the stimulus origin. Most likely, this behavior helps the leech to gain a more detailed picture of its prey target. The display of scanning, regardless of the presence or absence of prey stimuli, is suggestive of a behavior that is part of an internally driven motor program, which is not released by the presence of sensory stimuli. The data herein include first steps to understanding the neural mechanisms underlying this important behavior.
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Visual search and line bisection in hemianopia: computational modelling of cortical compensatory mechanisms and comparison with hemineglect. PLoS One 2013; 8:e54919. [PMID: 23390506 PMCID: PMC3563648 DOI: 10.1371/journal.pone.0054919] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2011] [Accepted: 12/20/2012] [Indexed: 11/23/2022] Open
Abstract
Hemianopia patients have lost vision from the contralateral hemifield, but make behavioural adjustments to compensate for this field loss. As a result, their visual performance and behaviour contrast with those of hemineglect patients who fail to attend to objects contralateral to their lesion. These conditions differ in their ocular fixations and perceptual judgments. During visual search, hemianopic patients make more fixations in contralesional space while hemineglect patients make fewer. During line bisection, hemianopic patients fixate the contralesional line segment more and make a small contralesional bisection error, while hemineglect patients make few contralesional fixations and a larger ipsilesional bisection error. Hence, there is an attentional failure for contralesional space in hemineglect but a compensatory adaptation to attend more to the blind side in hemianopia. A challenge for models of visual attentional processes is to show how compensation is achieved in hemianopia, and why such processes are hindered or inaccessible in hemineglect. We used a neurophysiology-derived computational model to examine possible cortical compensatory processes in simulated hemianopia from a V1 lesion and compared results with those obtained with the same processes under conditions of simulated hemineglect from a parietal lesion. A spatial compensatory bias to increase attention contralesionally replicated hemianopic scanning patterns during visual search but not during line bisection. To reproduce the latter required a second process, an extrastriate lateral connectivity facilitating form completion into the blind field: this allowed accurate placement of fixations on contralesional stimuli and reproduced fixation patterns and the contralesional bisection error of hemianopia. Neither of these two cortical compensatory processes was effective in ameliorating the ipsilesional bias in the hemineglect model. Our results replicate normal and pathological patterns of visual scanning, line bisection, and differences between hemianopia and hemineglect, and may explain why compensatory processes that counter the effects of hemianopia are ineffective in hemineglect.
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Kamimura R. Self-enhancement learning: target-creating learning and its application to self-organizing maps. BIOLOGICAL CYBERNETICS 2011; 104:305-338. [PMID: 21594651 DOI: 10.1007/s00422-011-0434-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2010] [Accepted: 04/23/2011] [Indexed: 05/30/2023]
Abstract
In this article, we propose a new learning method called "self-enhancement learning." In this method, targets for learning are not given from the outside, but they can be spontaneously created within a neural network. To realize the method, we consider a neural network with two different states, namely, an enhanced and a relaxed state. The enhanced state is one in which the network responds very selectively to input patterns, while in the relaxed state, the network responds almost equally to input patterns. The gap between the two states can be reduced by minimizing the Kullback-Leibler divergence between the two states with free energy. To demonstrate the effectiveness of this method, we applied self-enhancement learning to the self-organizing maps, or SOM, in which lateral interactions were added to an enhanced state. We applied the method to the well-known Iris, wine, housing and cancer machine learning database problems. In addition, we applied the method to real-life data, a student survey. Experimental results showed that the U-matrices obtained were similar to those produced by the conventional SOM. Class boundaries were made clearer in the housing and cancer data. For all the data, except for the cancer data, better performance could be obtained in terms of quantitative and topological errors. In addition, we could see that the trustworthiness and continuity, referring to the quality of neighborhood preservation, could be improved by the self-enhancement learning. Finally, we used modern dimensionality reduction methods and compared their results with those obtained by the self-enhancement learning. The results obtained by the self-enhancement were not superior to but comparable with those obtained by the modern dimensionality reduction methods.
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Affiliation(s)
- Ryotaro Kamimura
- IT Education Center, Tokai University, 1117 Kitakaname, Hiratsuka, Kanagawa 259-1292, Japan.
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11
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Selective information enhancement learning for creating interpretable representations in competitive learning. Neural Netw 2011; 24:387-405. [DOI: 10.1016/j.neunet.2010.12.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2009] [Revised: 10/19/2010] [Accepted: 12/29/2010] [Indexed: 11/22/2022]
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Modelling visual neglect: computational insights into conscious perception. PLoS One 2010; 5:e11128. [PMID: 20559559 PMCID: PMC2886104 DOI: 10.1371/journal.pone.0011128] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2009] [Accepted: 04/12/2010] [Indexed: 11/19/2022] Open
Abstract
Background Visual neglect is an attentional deficit typically resulting from parietal cortex lesion and sometimes frontal lesion. Patients fail to attend to objects and events in the visual hemifield contralateral to their lesion during visual search. Methodology/Principal Finding The aim of this work was to examine the effects of parietal and frontal lesion in an existing computational model of visual attention and search and simulate visual search behaviour under lesion conditions. We find that unilateral parietal lesion in this model leads to symptoms of visual neglect in simulated search scan paths, including an inhibition of return (IOR) deficit, while frontal lesion leads to milder neglect and to more severe deficits in IOR and perseveration in the scan path. During simulations of search under unilateral parietal lesion, the model's extrastriate ventral stream area exhibits lower activity for stimuli in the neglected hemifield compared to that for stimuli in the normally perceived hemifield. This could represent a computational correlate of differences observed in neuroimaging for unconscious versus conscious perception following parietal lesion. Conclusions/Significance Our results lead to the prediction, supported by effective connectivity evidence, that connections between the dorsal and ventral visual streams may be an important factor in the explanation of perceptual deficits in parietal lesion patients and of conscious perception in general.
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Hampson RE, Opris I, Deadwyler SA. Neural correlates of fast pupil dilation in nonhuman primates: relation to behavioral performance and cognitive workload. Behav Brain Res 2010; 212:1-11. [PMID: 20226215 DOI: 10.1016/j.bbr.2010.03.011] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2009] [Revised: 02/28/2010] [Accepted: 03/04/2010] [Indexed: 10/19/2022]
Abstract
Pupil dilation in humans has been previously shown to correlate with cognitive workload, whereby increased frequency of dilation is associated with increased degree of difficulty of a task. It has been suggested that frontal oculomotor brain areas control cognitively related pupil dilations, but this has not been confirmed due to lack of animal models of cognitive workload and task-related pupil dilation. This is the first report of a wavelet analysis applied to continuous measures of pupil size used to detect the onset of abrupt pupil dilations and the frequency of those dilations in nonhuman primates (NHPs) performing a trial-unique delayed-match-to-sample (DMS) task. A unique finding shows that electrophysiological recordings in the same animals revealed firing of neurons in frontal cortex correlated to different components of pupil dilation during task performance. It is further demonstrated that the frequency of fast pupil dilations (but not rate of eye movements) correlated with cognitive workload during task performance. Such correlations suggest that frontal neuron encoding of pupil dilation provides critical feedback to other brain areas involved in the processing of complex visual information.
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Affiliation(s)
- R E Hampson
- Department of Physiology & Pharmacology, Wake Forest University School of Medicine, Winston-Salem, NC 27157, United States
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Begum M, Karray F, Mann GKI, Gosine RG. A probabilistic model of overt visual attention for cognitive robots. IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS. PART B, CYBERNETICS : A PUBLICATION OF THE IEEE SYSTEMS, MAN, AND CYBERNETICS SOCIETY 2010; 40:1305-18. [PMID: 20089477 DOI: 10.1109/tsmcb.2009.2037511] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Visual attention is one of the major requirements for a robot to serve as a cognitive companion for human. The robotic visual attention is mostly concerned with overt attention which accompanies head and eye movements of a robot. In this case, each movement of the camera head triggers a number of events, namely transformation of the camera and the image coordinate systems, change of content of the visual field, and partial appearance of the stimuli. All of these events contribute to the reduction in probability of meaningful identification of the next focus of attention. These events are specific to overt attention with head movement and, therefore, their effects are not addressed in the classical models of covert visual attention. This paper proposes a Bayesian model as a robot-centric solution for the overt visual attention problem. The proposed model, while taking inspiration from the primates visual attention mechanism, guides a robot to direct its camera toward behaviorally relevant and/or visually demanding stimuli. A particle filter implementation of this model addresses the challenges involved in overt attention with head movement. Experimental results demonstrate the performance of the proposed model.
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Affiliation(s)
- Momotaz Begum
- Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
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Attentional Focus Modulated by Mesothalamic Dopamine: Consequences in Parkinson’s Disease and Attention Deficit Hyperactivity Disorder. Cognit Comput 2009. [DOI: 10.1007/s12559-009-9029-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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Lanyon LJ, Denham SL. Modelling attention in individual cells leads to a system with realistic saccade behaviours. Cogn Neurodyn 2009; 3:223-42. [PMID: 19125356 DOI: 10.1007/s11571-008-9073-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2008] [Revised: 12/05/2008] [Accepted: 12/05/2008] [Indexed: 12/01/2022] Open
Abstract
Single cell recordings in monkey inferior temporal cortex (IT) and area V4 during visual search tasks indicate that modulation of responses by the search target object occurs in the late portion of the cell's sensory response (Chelazzi et al. in J Neurophysiol 80:2918-2940, 1998; Cereb Cortex 11:761-772, 2001) whereas attention to a spatial location influences earlier responses (Luck et al. in J Neurophysiol 77:24-42, 1997). Previous computational models have not captured differences in the latency of these attentional effects and yet the more protracted development of the object-based effect could have implications for behaviour. We present a neurodynamic biased competition model of visual attention in which we aimed to model the timecourse of spatial and object-based attention in order to simulate cellular responses and saccade onset times observed in monkey recordings. In common with other models, a top-down prefrontal signal, related to the search target, biases activity in the ventral visual stream. However, we conclude that this bias signal is more complex than modelled elsewhere: the latency of object-based effects in V4 and IT, and saccade onset, can be accurately simulated when the target object feedback bias consists of a sensory response component in addition to a mnemonic response. These attentional effects in V4 and IT cellular responses lead to a system that is able to produce search scan paths similar to those observed in monkeys and humans, with attention being guided to locations containing behaviourally relevant stimuli. This work demonstrates that accurate modelling of the timecourse of single cell responses can lead to biologically realistic behaviours being demonstrated by the system as a whole.
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Affiliation(s)
- Linda J Lanyon
- Human Vision & Eye Movement Laboratory, Department of Ophthalmology & Visual Sciences, Medicine (Neurology), Psychology, University of British Columbia, Room 365, 3rd Floor Research Labs, VGH Eye Care Centre, 2550 Willow Street, Vancouver, BC, V5Z 3N9, Canada,
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de Kamps M, Baier V, Drever J, Dietz M, Mösenlechner L, van der Velde F. The state of MIIND. Neural Netw 2008; 21:1164-81. [PMID: 18783918 DOI: 10.1016/j.neunet.2008.07.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2007] [Revised: 06/09/2008] [Accepted: 07/28/2008] [Indexed: 10/21/2022]
Abstract
MIIND (Multiple Interacting Instantiations of Neural Dynamics) is a highly modular multi-level C++ framework, that aims to shorten the development time for models in Cognitive Neuroscience (CNS). It offers reusable code modules (libraries of classes and functions) aimed at solving problems that occur repeatedly in modelling, but tries not to impose a specific modelling philosophy or methodology. At the lowest level, it offers support for the implementation of sparse networks. For example, the library SparseImplementationLib supports sparse random networks and the library LayerMappingLib can be used for sparse regular networks of filter-like operators. The library DynamicLib, which builds on top of the library SparseImplementationLib, offers a generic framework for simulating network processes. Presently, several specific network process implementations are provided in MIIND: the Wilson-Cowan and Ornstein-Uhlenbeck type, and population density techniques for leaky-integrate-and-fire neurons driven by Poisson input. A design principle of MIIND is to support detailing: the refinement of an originally simple model into a form where more biological detail is included. Another design principle is extensibility: the reuse of an existing model in a larger, more extended one. One of the main uses of MIIND so far has been the instantiation of neural models of visual attention. Recently, we have added a library for implementing biologically-inspired models of artificial vision, such as HMAX and recent successors. In the long run we hope to be able to apply suitably adapted neuronal mechanisms of attention to these artificial models.
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Affiliation(s)
- Marc de Kamps
- Biosystems Group, School of Computing, University of Leeds, LS2 9JT Leeds, United Kingdom.
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Lanyon LJ, Denham SL. A biased competition computational model of spatial and object-based attention mediating active visual search. Neurocomputing 2004. [DOI: 10.1016/j.neucom.2004.01.110] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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