Social Experience Affects Decision Making And Learning: Empirical And Computational Analysis,
2018
East Carolina University
Social Experience Affects Decision Making And Learning: Empirical And Computational Analysis, Sungwoo Ahn
Biology and Medicine Through Mathematics Conference
No abstract provided.
Geometric Analysis Of Synchronization In Neuronal Networks With Global Inhibition And Coupling Delays,
2018
University of Hartford
Geometric Analysis Of Synchronization In Neuronal Networks With Global Inhibition And Coupling Delays, Hwayeon Ryu, Sue Ann Campbell
Biology and Medicine Through Mathematics Conference
No abstract provided.
‘Preferred’ Stimulus Of A Whole Model Visual System,
2018
University of St Andrews
‘Preferred’ Stimulus Of A Whole Model Visual System, Olivier Penacchio, Julie M. Harris
MODVIS Workshop
No abstract provided.
Finding Any Waldo: Zero-Shot Invariant And Efficient Visual Search,
2018
HMS
Finding Any Waldo: Zero-Shot Invariant And Efficient Visual Search, Gabriel Kreiman, Mengmi Zhang
MODVIS Workshop
Visual search constitutes a ubiquitous challenge in natural vision, including daily tasks such as finding a friend in a crowd or searching for a car in a parking lot. Visual search must fulfill four key properties: selectivity (to distinguish the target from distractors in a cluttered scene), invariance (to localize the target despite changes in its rotation, scale, illumination, and even searching for generic object categories), speed (to efficiently localize the target without exhaustive sampling), and generalization (to search for any object, even ones that we have had minimal or no experience with). Here we propose a computational model that …
Linking Signal Detection Theory And Encoding Models To Reveal Independent Neural Representations From Neuroimaging Data,
2018
Florida International University
Linking Signal Detection Theory And Encoding Models To Reveal Independent Neural Representations From Neuroimaging Data, Fabian A. Soto
MODVIS Workshop
No abstract provided.
Texture Statistics Are Sufficient For Ensemble Perception,
2018
Department of Psychology, University of California San Diego
Texture Statistics Are Sufficient For Ensemble Perception, Sasen S. Cain, Matthew S. Cain
MODVIS Workshop
No abstract provided.
Modeling Neural Computations In Lgn And Visual Cortex That Underlie Contextual Modulation Of Lightness And Darkness Magnitudes In Simple And Complex Images,
2018
mrudd@u.washington.edu
Modeling Neural Computations In Lgn And Visual Cortex That Underlie Contextual Modulation Of Lightness And Darkness Magnitudes In Simple And Complex Images, Michael E. Rudd
MODVIS Workshop
No abstract provided.
Brightness Perception Involves Local Adaptation Opposed By Lateral Interaction,
2018
Graduate Center for Vision Research, State University of New York
Brightness Perception Involves Local Adaptation Opposed By Lateral Interaction, Qasim Zaidi, Romain Bachy, Jose-Manuel Alonso
MODVIS Workshop
No abstract provided.
The Road Towards Image-Computable Models Of Human Visual Grasp Planning,
2018
University of Gießen
The Road Towards Image-Computable Models Of Human Visual Grasp Planning, Guido Maiello, Lina K. Klein, Vivian C. Paulun, Katherine R. Storrs, Roland W. Fleming
MODVIS Workshop
No abstract provided.
A Feature-Based Model Of Visually Perceiving Deformable Objects,
2018
Justus Liebig University, Giessen
A Feature-Based Model Of Visually Perceiving Deformable Objects, Vivian C. Paulun, Filipp Schmidt, Roland W. Fleming
MODVIS Workshop
No abstract provided.
Effect Of Noise On Mutually Inhibiting Pyramidal Cells In Visual Cortex: Foundation Of Stochasticity In Bi-Stable Perception,
2018
Biophysics, Donders Institute for Brain, Cognition and Behaviour, Radboud University
Effect Of Noise On Mutually Inhibiting Pyramidal Cells In Visual Cortex: Foundation Of Stochasticity In Bi-Stable Perception, Naoki Kogo, Felix Kern, Thomas Nowotny, Raymond Van Ee, Richard Van Wezel, Takeshi Aihara
MODVIS Workshop
Bi-stable perception has been an important tool to investigate how visual input is interpreted and how it reaches consciousness. To explain the mechanisms of this phenomenon, it has been assumed that a mutual inhibition circuit plays a key role. It is possible that this circuit functions to resolve ambiguity of input image by quickly shifting the balance of competing signals in response to conflicting features. Recently we established an in vitro neural recording system combined with computerized connections mediated by model neurons and synapses (“dynamic clamp” system). With this system, mutual inhibition circuit between two pyramidal cells from primary visual …
Visual Category Learning By Means Of Basal Ganglia,
2018
Chemnitz University of Technology
Visual Category Learning By Means Of Basal Ganglia, Fred H. Hamker, Francesc Villagrasa, Javier Baladron, Henning Schroll, Julien Vitay
MODVIS Workshop
No abstract provided.
Why Latent Representations In Convolutional Neural Networks Fall Outside Visual Space,
2018
Pavlov Institute of Physiology of the Russian Academy of Sciences
Why Latent Representations In Convolutional Neural Networks Fall Outside Visual Space, Katerina Malakhova
MODVIS Workshop
It is common to compare properties of visual information processing by artificial neural networks and the primate visual system.
Some remarkable similarities were observed in the responses of neurons in IT cortex and units in higher layers of CNNs. Here I show that latent representations formed by weights in convolutional layers do not necessarily reflect visual domain. Instead they are strongly dependent on a choice of training set and cost function.
The most striking example is when an individual unit, which is highly selective to some members of a category is, nevertheless, inhibited by visually similar objects of the same …
Appropriate Kernels For Divisive Normalization Explained By Wilson-Cowan Equations,
2018
Image Processing Lab. Universitat de Valencia
Appropriate Kernels For Divisive Normalization Explained By Wilson-Cowan Equations, Jesus Malo, Marcelo Bertalmio
MODVIS Workshop
Cascades of standard Linear+NonLinear-Divisive Normalization transforms [Carandini&Heeger12] can be easily fitted using the appropriate formulation introduced in [Martinez17a] to reproduce the perception of image distortion in naturalistic environments. However, consistently with [Rust&Movshon05], training the model in naturalistic environments does not guarantee the prediction of well known phenomena illustrated by artificial stimuli. For example, the cascade of Divisive Normalizations fitted with image quality databases has to be modified to include a variety aspects of masking of simple patterns. Specifically, the standard Gaussian kernels of [Watson&Solomon97] have to be augmented with extra weights [Martinez17b]. These can be introduced ad-hoc using the intuition …
Model Investigation On Contribution Of Feedback In Distortion Induced Motion Adaptation,
2018
University Tuebingen
Model Investigation On Contribution Of Feedback In Distortion Induced Motion Adaptation, Siegfried Wahl, Selam Habtegiorgis, Christian Jarvers, Katharina Rifai, Heiko Neumann
MODVIS Workshop
Motion information is processed in a neural circuit formed by synaptic organization of feedforward (FF) and feedback (FB) connections between different cortical areas. However, the contribution of a recurrent FB information to adaptation process is not well explored. Here, a biologically plausible neural model that predicts motion adaptation aftereffect (MAE) induced by exposure to geometrically skewed natural image sequences is suggested. The model constitutes two stage recurrent motion processing within cortical areas V1 and MT [1]. It comprises FF excitatory, FB modulatory and lateral inhibitory connections, and a fast and a slow adaptive synapse in the FF and FB streams, …
A Model Of 1d And 2d Motion Processing In The Primate Brain,
2018
University of Nottingham
A Model Of 1d And 2d Motion Processing In The Primate Brain, Alan Johnston
MODVIS Workshop
Velocity encoding in the primate brain can be modelled by a spatiotemporal gradient approach, with neurons characterized as spatio-temporal derivative operators (Johnston et al. 1999). This strategy works well for moving 1D spatial patterns, but it can produce systematic errors, as it can be overly influenced by the direction of the local spatial gradient of the image brightness. For 2D pattern it is possible to develop a similar spatio-temporal approach, in which the system solves a set of over-determined linear equations directly, to provide an estimate for the 2D image motion. However, in this case the matrix one needs to …
An Active Efficient Coding Model Of The Development Of Amblyopia,
2018
Frankfurt Institute for Advanced Studies
An Active Efficient Coding Model Of The Development Of Amblyopia, Samuel Eckmann, Lukas Klimmasch, Bertram Shi, Jochen Triesch
MODVIS Workshop
No abstract provided.
Molecular Mechanism Of Early Amyloid Self-Assembly Revealed By Computational Modeling,
2018
University of Nebraska Medical Center
Molecular Mechanism Of Early Amyloid Self-Assembly Revealed By Computational Modeling, Mohtadin Hashemi
Theses & Dissertations
Protein misfolding followed by the formation of aggregates, is an early step in the cascade of conformational changes in a protein that underlie the development of several neurodegenerative diseases, including Alzheimer’s and Parkinson’s diseases. Efforts aimed at understanding this process have produced little clarity and the mechanism remains elusive.
Here, we demonstrate that the hairpin fold, a structure found in the early folding intermediates of amyloid b, induces morphological and stability changes in the aggregates of Aβ(14-23) peptide. We structurally characterized the interactions of monomer and hairpin using extended molecular dynamics (MD) simulations, which revealed a novel intercalated type complex. …
Efficient Reduced Bias Genetic Algorithm For Generic Community Detection Objectives,
2018
University of Missouri, St. Louis
Efficient Reduced Bias Genetic Algorithm For Generic Community Detection Objectives, Aditya Karnam Gururaj Rao
Theses
The problem of community structure identification has been an extensively investigated area for biology, physics, social sciences, and computer science in recent years for studying the properties of networks representing complex relationships. Most traditional methods, such as K-means and hierarchical clustering, are based on the assumption that communities have spherical configurations. Lately, Genetic Algorithms (GA) are being utilized for efficient community detection without imposing sphericity. GAs are machine learning methods which mimic natural selection and scale with the complexity of the network. However, traditional GA approaches employ a representation method that dramatically increases the solution space to be searched by …
Tinnitus And Dysfunctional Interactions Between Distributed Resting State Networks,
2018
University of Western Ontario
Tinnitus And Dysfunctional Interactions Between Distributed Resting State Networks, Sivayini Kandeepan
Western Research Forum
It is known that peripheral lesions in the cochlea or the auditory nerve produce dysfunctional input to central auditory structures and induce changes in the auditory system causing tinnitus. Recently, it has been proposed that the unified percept of tinnitus could be considered as an emergent property of multiple overlapping dynamic brain networks, each encoding a specific tinnitus characteristic.
The aim of our study was to investigate the neuronal activation patterns associated with specific clinical tinnitus characteristics using fMRI. We hypothesize that tinnitus clinical characteristics could be associated with specific resting-state activity and connectivity patterns and that this could be …
