Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Physical Sciences and Mathematics (43)
- Psychology (28)
- Social and Behavioral Sciences (28)
- Applied Mathematics (26)
- Cognition and Perception (24)
-
- Systems Neuroscience (24)
- Cognitive Neuroscience (22)
- Engineering (15)
- Mathematics (12)
- Non-linear Dynamics (12)
- Dynamical Systems (11)
- Biomedical Engineering and Bioengineering (9)
- Medicine and Health Sciences (9)
- Statistics and Probability (8)
- Vision Science (8)
- Dynamic Systems (7)
- Biochemistry, Biophysics, and Structural Biology (6)
- Cognitive Psychology (6)
- Computer Sciences (6)
- Ordinary Differential Equations and Applied Dynamics (6)
- Physics (6)
- Biophysics (5)
- Artificial Intelligence and Robotics (4)
- Behavioral Neurobiology (4)
- Biological and Chemical Physics (4)
- Electrical and Computer Engineering (4)
- Numerical Analysis and Computation (4)
- Institution
- Keyword
-
- Neuroscience (18)
- V1 (7)
- Lightness (6)
- Model (5)
- Attention (4)
-
- Natural scenes (4)
- Object recognition (4)
- Saliency (4)
- Visual cortex (4)
- Deep learning (3)
- Fixational eye movements (3)
- Peripheral vision (3)
- V2 (3)
- Vision (3)
- Active vision (2)
- Biased competition (2)
- Central vision (2)
- Computational model (2)
- Curvature (2)
- Efficient coding (2)
- FMRI (2)
- Feedback (2)
- Gain control (2)
- Hebbian learning (2)
- Image statistics (2)
- Induction (2)
- Invariance (2)
- LGN (2)
- MT (2)
- Machine Learning (2)
- Publication Year
- Publication
- File Type
Articles 121 - 133 of 133
Full-Text Articles in Computational Neuroscience
A Binocular Model For Motion Integration In Mt Neurons, Pamela M. Baker, Wyeth Bair
A Binocular Model For Motion Integration In Mt Neurons, Pamela M. Baker, Wyeth Bair
MODVIS Workshop
Processing of visual motion by neurons in MT has long been an active area of study, however circuit models detailing the computations underlying binocular integration of motion signals remains elusive. Such models are important for studying the visual perception of motion in depth (MID), which involves both frontoparallel (FP) visual motion and binocular signal integration. Recent studies (Czuba et al. 2014, Sanada and DeAngelis 2014) have shown that many MT neurons are MID sensitive, contrary to the prevailing view (Maunsell and van Essen, 1983). These novel data are ideal for constraining models of binocular motion integration in MT. We have …
A Critical Evaluation Of Computational Mechanisms Of Binocular Disparity Processing, Junkyung Kim, David A. Mély, Thomas Serre
A Critical Evaluation Of Computational Mechanisms Of Binocular Disparity Processing, Junkyung Kim, David A. Mély, Thomas Serre
MODVIS Workshop
The past decades of research in visual neuroscience have generated a large and disparate body of literature on the computation of binocular disparity in the primary visual cortex. Models have been proposed to describe specific phenomena, yet we lack a theoretical framework which is grounded in neurophysiology and also explains the effectiveness of disparity computation. Here, we examine neural circuits that are thought to play an important role in the computation of binocular disparity. Starting with the binocular energy model (Ohzawa et al. 1990), we consider plausible extensions which include suppressive mechanisms from units tuned to different phase disparities (Tanabe …
Modeling Shape Representation In Area V4, Wyeth Bair, Dina Popovkina, Abhishek De, Anitha Pasupathy
Modeling Shape Representation In Area V4, Wyeth Bair, Dina Popovkina, Abhishek De, Anitha Pasupathy
MODVIS Workshop
Our model builds on a convolutional-style neural network with hierarchical stages representing processing steps in the ventral visual pathway. It was designed to capture the translation-invariance and shape-selectivity of neurons in area V4. The model uses biologically plausible linear filters at the front end, normalization and sigmoidal nonlinear activation functions. The max() function is used to generate translation invariance.
A Recurrent Multilayer Model With Hebbian Learning And Intrinsic Plasticity Leads To Invariant Object Recognition And Biologically Plausible Receptive Fields, Michael Teichmann, Fred H. Hamker
A Recurrent Multilayer Model With Hebbian Learning And Intrinsic Plasticity Leads To Invariant Object Recognition And Biologically Plausible Receptive Fields, Michael Teichmann, Fred H. Hamker
MODVIS Workshop
Much effort has been spent to develop biologically plausible models for different aspects of the processing in the visual cortex. However, most of these models are not investigated with respect to the functionality of the neural code for the purpose of object recognition comparable to the framework of deep learning in the machine learning community.
We developed a model of V1 and V2 based on anatomical evidence of the layered architecture, using excitatory and inhibitory neurons where the connectivity to each neuron is learned in parallel. We address learning by three different mechanisms of plasticity: intrinsic plasticity, Hebbian learning with …
A Computational Model To Account For Dynamics Of Spatial Updating Of Remembered Visual Targets Across Slow And Rapid Eye Movements, Yalda Mohsenzadeh, J. Douglas Crawford
A Computational Model To Account For Dynamics Of Spatial Updating Of Remembered Visual Targets Across Slow And Rapid Eye Movements, Yalda Mohsenzadeh, J. Douglas Crawford
MODVIS Workshop
Despite the ever-changing visual scene on the retina between eye movements, our perception of the visual world is constant and unified. It is generally believed that this space constancy is due to the brain’s ability of spatial updating. Although many efforts have been made to discover the mechanism underlying spatial updating across eye movements, still there are many unanswered questions about the neuronal mechanism of this phenomenon.
We developed a state space model for updating gaze-centered spatial information. To explore spatial updating, we considered two kinds of eye movements, saccade and smooth pursuit. The inputs to our proposed model are: …
A Model Of Repetitive Microsaccades, Coupled With Pre-Microsaccadic Changes In Vision, Is Sufficient To Account For Both Attentional Capture And Inhibition Of Return In Posner Cueing, Ziad M. Hafed, Xiaoguang Tian
A Model Of Repetitive Microsaccades, Coupled With Pre-Microsaccadic Changes In Vision, Is Sufficient To Account For Both Attentional Capture And Inhibition Of Return In Posner Cueing, Ziad M. Hafed, Xiaoguang Tian
MODVIS Workshop
When a cue is presented at a location, orienting efficacy towards that location is improved relative to other locations (“attentional capture”), but only briefly; a mere few hundred milliseconds later, orienting incurs large costs. These costs have been classically termed “inhibition of return” (IOR), alluding to voluntary, cognitive strategies avoiding perseverance at one location. However, despite this popular hypothesis, the origins of both attentional capture and IOR remain elusive. Here we show that both of these phenomena can be accounted for by a single concept of oculomotor rhythmicity, and one that involves the entire gamut of saccadic activity including microsaccades. …
Object Recognition And Visual Search With A Physiologically Grounded Model Of Visual Attention, Frederik Beuth, Fred H. Hamker
Object Recognition And Visual Search With A Physiologically Grounded Model Of Visual Attention, Frederik Beuth, Fred H. Hamker
MODVIS Workshop
Visual attention models can explain a rich set of physiological data (Reynolds & Heeger, 2009, Neuron), but can rarely link these findings to real-world tasks. Here, we would like to narrow this gap with a novel, physiologically grounded model of visual attention by demonstrating its objects recognition abilities in noisy scenes.
To base the model on physiological data, we used a recently developed microcircuit model of visual attention (Beuth & Hamker, in revision, Vision Res) which explains a large set of attention experiments, e.g. biased competition, modulation of contrast response functions, tuning curves, and surround suppression. Objects are represented by …
Modeling Visual Features To Recognize Biological Motion: A Developmental Approach, Giulio Sandini, Nicoletta Noceti, Alessia Vignolo, Alessandra Sciutti, Francesco Rea, Alessandro Verri, Francesca Odone
Modeling Visual Features To Recognize Biological Motion: A Developmental Approach, Giulio Sandini, Nicoletta Noceti, Alessia Vignolo, Alessandra Sciutti, Francesco Rea, Alessandro Verri, Francesca Odone
MODVIS Workshop
In this work we deal with the problem of designing and developing computational vision models – comparable to the early stages of the human development – using coarse low-level information.
More specifically, we consider a binary classification setting to characterize biological movements with respect to non-biological dynamic events. To this purpose, our model builds on top of the optical flow estimation, and abstract the representation to simulate the limited amount of visual information available at birth. We take inspiration from known biological motion regularities explained by the Two-Thirds Power Law, and design a motion representation that includes different low-level features, …
Complementary Effect Of Electrical And Inhibitory Coupling In Bursting Synchronization, Kevin Daley
Complementary Effect Of Electrical And Inhibitory Coupling In Bursting Synchronization, Kevin Daley
Georgia State Undergraduate Research Conference
gsurc 2015
Quantitative And Qualitative Stability Analysis Of Polyrhythmic Circuits, Drake Knapper
Quantitative And Qualitative Stability Analysis Of Polyrhythmic Circuits, Drake Knapper
Georgia State Undergraduate Research Conference
No abstract provided.
The Effect Of The R1648h Sodium Channel Mutation On Neuronal Excitability: A Model Study, Christopher Locandro, Robert Clewley
The Effect Of The R1648h Sodium Channel Mutation On Neuronal Excitability: A Model Study, Christopher Locandro, Robert Clewley
Georgia State Undergraduate Research Conference
No abstract provided.
Switching Bistable Leech Heart Interneurons With A Pulse Of Current From Bursting To Silence, Aaron Gomez-Lugo
Switching Bistable Leech Heart Interneurons With A Pulse Of Current From Bursting To Silence, Aaron Gomez-Lugo
Georgia State Undergraduate Research Conference
No abstract provided.
Resiliency To Bistability In The Neurons From The Pre-Bötzinger Complex, Treadwell D. Singfield Ii
Resiliency To Bistability In The Neurons From The Pre-Bötzinger Complex, Treadwell D. Singfield Ii
Georgia State Undergraduate Research Conference
No abstract provided.