Decoupling of Early V5 Motion Processing from Visual Awareness: a Matter of Velocity As Revealed by Transcranial Magnetic Stimulation
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The Hodgkin-Huxley Neuron Model for Motion Detection in Image Sequences Hayat Yedjour, Boudjelal Meftah, Dounia Yedjour, Olivier Lézoray
The Hodgkin-Huxley neuron model for motion detection in image sequences Hayat Yedjour, Boudjelal Meftah, Dounia Yedjour, Olivier Lézoray To cite this version: Hayat Yedjour, Boudjelal Meftah, Dounia Yedjour, Olivier Lézoray. The Hodgkin-Huxley neuron model for motion detection in image sequences. Neural Computing and Applications, Springer Verlag, In press, 10.1007/s00521-021-06446-0. hal-03331961 HAL Id: hal-03331961 https://hal.archives-ouvertes.fr/hal-03331961 Submitted on 2 Sep 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Noname manuscript No. (will be inserted by the editor) The Hodgkin{Huxley neuron model for motion detection in image sequences Hayat Yedjour · Boudjelal Meftah · Dounia Yedjour · Olivier L´ezoray Received: date / Accepted: date Abstract In this paper, we consider a biologically-inspired spiking neural network model for motion detection. The proposed model simulates the neu- rons' behavior in the cortical area MT to detect different kinds of motion in image sequences. We choose the conductance-based neuron model of the Hodgkin-Huxley to define MT cell responses. Based on the center-surround antagonism of MT receptive fields, we model the area MT by its great pro- portion of cells with directional selective responses. -
Capture of Stereopsis and Apparent Motion by Illusory Contours
Perception & Psychophysics 1986, 39 (5), 361-373 Capture of stereopsis and apparent motion by illusory contours V. S. RAMACHANDRAN University of California, San Diego, La Jolla, California The removal of right-angle sectors from four circular black disks created the impression of a white "subjective" square with its four corners occluding the disks ("illusory contours"). The dis play in one eye was identical to that in the other except that for one eye a horizontal disparity was introduced between the edges of the cut sectors so that an illusory white square floated out in front of the paper. When a "template" ofthis stereogram was superimposed on a vertical square wave grating (6 cycles/deg) the illusory square pulled the corresponding lines of grating forward even though the grating was at zero disparity. (Capture was not observed if the template was superimposed on horizontal gratings; the grating remained flush with the background). Analo gous effects were observed in apparent motion ("motion capture"). Removal of sectors from disks in an appropriately timed sequence generated apparent motion of an illusory square. When a template of this display was superimposed on a grating, the lines appeared to move vividly with the square even though they were physically stationary. It was concluded that segmentation of the visual scene into surfaces and objects can profoundly influence the early visual processing of stereopsis and apparent motion. However, there are interesting differences between stereo cap ture and motion capture, which probably reflect differences in natural constraints. The implica tions of these findings for computational models of vision are discussed. -
Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: from Events to Global Motion Perception
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2019 1 Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: From Events to Global Motion Perception Federico Paredes-Valles´ , Kirk Y. W. Scheper , and Guido C. H. E. de Croon , Member, IEEE Abstract—The combination of spiking neural networks and event-based vision sensors holds the potential of highly efficient and high-bandwidth optical flow estimation. This paper presents the first hierarchical spiking architecture in which motion (direction and speed) selectivity emerges in an unsupervised fashion from the raw stimuli generated with an event-based camera. A novel adaptive neuron model and stable spike-timing-dependent plasticity formulation are at the core of this neural network governing its spike-based processing and learning, respectively. After convergence, the neural architecture exhibits the main properties of biological visual motion systems, namely feature extraction and local and global motion perception. Convolutional layers with input synapses characterized by single and multiple transmission delays are employed for feature and local motion perception, respectively; while global motion selectivity emerges in a final fully-connected layer. The proposed solution is validated using synthetic and real event sequences. Along with this paper, we provide the cuSNN library, a framework that enables GPU-accelerated simulations of large-scale spiking neural networks. Source code and samples are available at https://github.com/tudelft/cuSNN. Index Terms—Event-based vision, feature extraction, motion detection, neural nets, neuromorphic computing, unsupervised learning F 1 INTRODUCTION HENEVER an animal endowed with a visual system interconnected cells for motion estimation, among other W navigates through an environment, turns its gaze, or tasks. -
Human Visual Motion Perception Shows Hallmarks of Bayesian Structural Inference Sichao Yang1,2,6*, Johannes Bill3,4,6*, Jan Drugowitsch3,5,7 & Samuel J
www.nature.com/scientificreports OPEN Human visual motion perception shows hallmarks of Bayesian structural inference Sichao Yang1,2,6*, Johannes Bill3,4,6*, Jan Drugowitsch3,5,7 & Samuel J. Gershman4,5,7 Motion relations in visual scenes carry an abundance of behaviorally relevant information, but little is known about how humans identify the structure underlying a scene’s motion in the frst place. We studied the computations governing human motion structure identifcation in two psychophysics experiments and found that perception of motion relations showed hallmarks of Bayesian structural inference. At the heart of our research lies a tractable task design that enabled us to reveal the signatures of probabilistic reasoning about latent structure. We found that a choice model based on the task’s Bayesian ideal observer accurately matched many facets of human structural inference, including task performance, perceptual error patterns, single-trial responses, participant-specifc diferences, and subjective decision confdence—especially, when motion scenes were ambiguous and when object motion was hierarchically nested within other moving reference frames. Our work can guide future neuroscience experiments to reveal the neural mechanisms underlying higher-level visual motion perception. Motion relations in visual scenes are a rich source of information for our brains to make sense of our environ- ment. We group coherently fying birds together to form a fock, predict the future trajectory of cars from the trafc fow, and infer our own velocity from a high-dimensional stream of retinal input by decomposing self- motion and object motion in the scene. We refer to these relations between velocities as motion structure. -
Motion-In-Depth Perception and Prey Capture in the Praying Mantis Sphodromantis Lineola
© 2019. Published by The Company of Biologists Ltd | Journal of Experimental Biology (2019) 222, jeb198614. doi:10.1242/jeb.198614 RESEARCH ARTICLE Motion-in-depth perception and prey capture in the praying mantis Sphodromantis lineola Vivek Nityananda1,*, Coline Joubier1,2, Jerry Tan1, Ghaith Tarawneh1 and Jenny C. A. Read1 ABSTRACT prey as they come near. Just as with depth perception, several cues Perceiving motion-in-depth is essential to detecting approaching could contribute to the perception of motion-in-depth. or receding objects, predators and prey. This can be achieved Two of the motion-in-depth cues that have received the most using several cues, including binocular stereoscopic cues such attention in humans are binocular: changing disparity and as changing disparity and interocular velocity differences, and interocular velocity differences (IOVDs) (Cormack et al., 2017). monocular cues such as looming. Although these have been Stereoscopic disparity refers to the difference in the position of an studied in detail in humans, only looming responses have been well object as seen by the two eyes. This disparity reflects the distance to characterized in insects and we know nothing about the role of an object. Thus as an object approaches, the disparity between the stereoscopic cues and how they might interact with looming cues. We two views changes. This changing disparity cue suffices to create a used our 3D insect cinema in a series of experiments to investigate perception of motion-in-depth for human observers, even in the the role of the stereoscopic cues mentioned above, as well as absence of other cues (Cumming and Parker, 1994). -
Visual Problems After Brain Injury
Visual problems after brain injury As a charity, we rely on donations from people like you to continue providing free information to people affected by brain injury. Donate today: www.headway.org.uk/donate Introduction Vision is the skill that allows us to see the world around us. When we look at the world, a complex series of processes takes place between the eyes and the brain. The eyes take in the information, while the brain (which is connected to the eyes by a nerve called the optic nerve) is responsible for processing and interpreting it. Through this system we are able to see things such as colours, shapes, movement, objects and people. When the brain is injured, the ability to interpret visual information can be affected in different ways. This factsheet has been written to explain how brain injury can affect vision and how to seek professional support with these issues. Tips for coping with visual problems are also offered. Words in bold are defined in a glossary at the end of the factsheet. What is vision? There are lots of different aspects of vision. Some of the things the brain needs to do to decode information that it receives from the eyes are: • process the shape and colour of objects • process and merge information received from both eyes • recall information from memory to recognise objects or places • process the movement of objects • process the location and position of an object in space • process information across the visual field (including peripheral vision) Generally, different parts of the brain are responsible for processing these different aspects of vision. -
Motion Processing in Human Visual Cortex
1 Motion Processing in Human Visual Cortex Randolph Blake*, Robert Sekuler# and Emily Grossman* *Vanderbilt Vision Research Center, Nashville TN 37203 #Volen Center for Complex Systems, Brandeis University, Waltham MA 02454 Acknowledgments. The authors thank David Heeger, Alex Huk, Nestor Matthews and Mark Nawrot for comments on sections of this chapter. David Bloom helped greatly with manuscript formatting and references. During preparation of this chapter RB and EG were supported by research grants from the National Institutes of Health (EY07760) and the National Science Foundation (BCS0121962) and by a Core Grant from the National Institutes of Health (EY01826) awarded to the Vanderbilt Vision Research Center. [email protected] 2 During the past few decades our understanding of the neural bases of visual perception and visually guided actions has advanced greatly; the chapters in this volume amply document these advances. It is fair to say, however, that no area of visual neuroscience has enjoyed greater progress than the physiology of visual motion perception. Publications dealing with visual motion perception and its neural bases would fill volumes, and the topic remains central within the visual neuroscience literature even today. This chapter aims to provide an overview of brain mechanisms underlying human motion perception. The chapter comprises four sections. We begin with a short review of the motion pathways in the primate visual system, emphasizing work from single-cell recordings in Old World monkeys; more extensive reviews of this literature appear elsewhere.1,2 With this backdrop in place, the next three sections concentrate on striate and extra-striate areas in the human brain that are implicated in the perception of motion. -
Abnormal Cortical Processing of Pattern Motion in Amblyopia: Evidence from Fmri
NeuroImage 60 (2012) 1307–1315 Contents lists available at SciVerse ScienceDirect NeuroImage journal homepage: www.elsevier.com/locate/ynimg Abnormal cortical processing of pattern motion in amblyopia: Evidence from fMRI B. Thompson a,b,⁎, M.Y. Villeneuve c,d, C. Casanova e, R.F. Hess b a Department of Optometry and Vision Science, University of Auckland, Private Bag 92019, Auckland, New Zealand b McGill Vision Research, Department of Ophthalmology, McGill University, Royal Victoria Hospital, 687 Pine Avenue West, Montreal, Canada c NMR Martinos Center, Massachusetts General Hospital, Harvard Medical School, Harvard University, Boston, USA d Montreal Neurological Institute, Departments of Neurology and Neurosurgery, McGill University, Montreal, Canada e Laboratoire des Neurosciences de la Vision, École d'optométrie, Université de Montréal, CP 6128, succ. Centre-Ville, Montreal, Canada article info abstract Article history: Converging evidence from human psychophysics and animal neurophysiology indicates that amblyopia is as- Received 12 November 2011 sociated with abnormal function of area MT, a motion sensitive region of the extrastriate visual cortex. In this Revised 29 December 2011 context, the recent finding that amblyopic eyes mediate normal perception of dynamic plaid stimuli was sur- Accepted 14 January 2012 prising, as neural processing and perception of plaids has been closely linked to MT function. One intriguing Available online 24 January 2012 potential explanation for this discrepancy is that the amblyopic eye recruits alternative visual brain areas to support plaid perception. This is the hypothesis that we tested. We used functional magnetic resonance im- Keywords: Amblyopia aging (fMRI) to measure the response of the amblyopic visual cortex and thalamus to incoherent and coher- Motion ent motion of plaid stimuli that were perceived normally by the amblyopic eye. -
Binocular Eye Movement Control and Motion Perception: What Is Being Tracked?
Eye Movements, Strabismus, Amblyopia, and Neuro-Ophthalmology Binocular Eye Movement Control and Motion Perception: What Is Being Tracked? Johannes van der Steen and Joyce Dits PURPOSE. We investigated under what conditions humans can representation of the visual world is constructed based on make independent slow phase eye movements. The ability to binocular retinal correspondence.4 To achieve this, the brain make independent movements of the two eyes generally is must use the visual information from each eye to stabilize the attributed to few specialized lateral eyed animal species, for two retinal images relative to each other. Imagine one is example chameleons. In our study, we showed that humans holding two laser pointers, one in each hand, and one must also can move the eyes in different directions. To maintain project the two beams precisely on top of each other on a wall. binocular retinal correspondence independent slow phase Eye movements contribute to binocular vision using visual movements of each eye are produced. feedback from image motion of each eye and from binocular correspondence. It generally is believed that the problem of METHODS. We used the scleral search coil method to measure binocular eye movements in response to dichoptically viewed binocular correspondence is solved in the primary visual 5,6 visual stimuli oscillating in orthogonal direction. cortex (V1). Neurons in V1 process monocular and binocular visual information.7 At subsequent levels of process- RESULTS. Correlated stimuli led to orthogonal slow eye ing eye-of-origin information is lost, and the perception of the movements, while the binocularly perceived motion was the binocular world is invariant for eye movements and self- vector sum of the motion presented to each eye. -
Motion Perception and Prediction: a Subsymbolic Approach
Motion Perception and Prediction: A Subsymbolic Approach Volker Baier Institut für Informatik, Lehrstuhl für Theoretische Informatik und Grundlagen der Künstliche Intelligenz Motion Perception and Prediction: A Subsymbolic Approach Volker Baier Vollständiger Abdruck der von der Fakultät für Informatik der Technischen Universität München zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr. A. Knoll Prüfer der Dissertation: 1. Univ.-Prof. Dr. Dr. h.c. mult. W. Brauer 2. Univ.-Prof. Dr. K. Schill Universität Bremen 3. Univ.-Prof. M. Beetz, PhD Die Dissertation wurde am 28.06.2006 bei der Technischen Universität München eingereicht und durch die Fakultät für Informatik am 13.11.2006 angenommen. Contents 1 Introduction 3 2 Overview of the Model 9 3 Paradigms of Perception 13 3.1 Philosophy . 13 3.2 Behaviorism . 14 3.3 Cognitivism . 15 3.4 Cybernetics and Constructivism . 17 3.5 Connectionism . 18 3.6 Computational Neuroscience . 19 3.7 Guiding Concepts . 20 4 Neuro-Anatomy 21 4.1 Visual Streams . 21 4.1.1 The Dorsal Pathway . 22 4.1.2 The Ventral Pathway . 23 4.2 Visual Cortical Areas . 23 4.2.1 Retina and Lateral Geniculate Nucleus . 24 4.2.2 Primary Visual Cortex V1 . 24 4.3 Motion Processing Related Areas . 28 4.4 What we Derive from Neuro-Anatomy . 30 5 Cognitive Psychology 33 5.1 Visual Spatio-Temporal Memory . 34 5.2 Dynamic Spatio-Temporal Memory . 36 5.3 Psychophysic Experimental Results . 39 5.4 What we Derive for our Model . 44 6 Neural Networks for Static Patterns 47 6.1 Multilayer Perceptron . -
Neuropsychiatry Review Series: Disorders of Visual Perception. Dominic Ffytche, Jan Dirk Blom, Marco Catani
Neuropsychiatry Review series: Disorders of Visual perception. Dominic Ffytche, Jan Dirk Blom, Marco Catani To cite this version: Dominic Ffytche, Jan Dirk Blom, Marco Catani. Neuropsychiatry Review series: Disorders of Visual perception.. Journal of Neurology, Neurosurgery and Psychiatry, BMJ Publishing Group, 2010, 81 (11), pp.1280. 10.1136/jnnp.2008.171348. hal-00587980 HAL Id: hal-00587980 https://hal.archives-ouvertes.fr/hal-00587980 Submitted on 22 Apr 2011 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Disorders of visual perception Dr Dominic H ffytche1,4* Dr JD Blom2,3 4 Dr M Catani 1 Department of Old Age Psychiatry, Institute of Psychiatry, King’s College London, UK 2 Parnassia Bavo Group, The Hague, the Netherlands 3 Department of Psychiatry, University of Groningen, Groningen, the Netherlands 4 Natbrainlab, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, King’s College London, UK *Address for Correspondence Dr D H ffytche Department of Old Age Psychiatry, Institute of Psychiatry PO70, King’s College -
A Dictionary of Neurological Signs.Pdf
A DICTIONARY OF NEUROLOGICAL SIGNS THIRD EDITION A DICTIONARY OF NEUROLOGICAL SIGNS THIRD EDITION A.J. LARNER MA, MD, MRCP (UK), DHMSA Consultant Neurologist Walton Centre for Neurology and Neurosurgery, Liverpool Honorary Lecturer in Neuroscience, University of Liverpool Society of Apothecaries’ Honorary Lecturer in the History of Medicine, University of Liverpool Liverpool, U.K. 123 Andrew J. Larner MA MD MRCP (UK) DHMSA Walton Centre for Neurology & Neurosurgery Lower Lane L9 7LJ Liverpool, UK ISBN 978-1-4419-7094-7 e-ISBN 978-1-4419-7095-4 DOI 10.1007/978-1-4419-7095-4 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2010937226 © Springer Science+Business Media, LLC 2001, 2006, 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of going to press, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made.