Neuroscience and Neurobiology Commons^™

‘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, 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, Fabian A. Soto

MODVIS Workshop

No abstract provided.

Texture Statistics Are Sufficient For Ensemble Perception, Sasen S. Cain, Matthew S. Cain

MODVIS Workshop

No abstract provided.

Michelson Contrast For Transparency Perception In Scenes With Multiple Luminances, Minjung Kim, Guillermo Aguilar, Marianne Maertens

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, Michael E. Rudd

MODVIS Workshop

No abstract provided.

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, 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, Vivian C. Paulun, Filipp Schmidt, Roland W. Fleming

MODVIS Workshop

No abstract provided.

Global Estimation Of Signed 3d Surface Tilt From Natural Images, Seha Kim, Johannes Burge

MODVIS Workshop

The ability of human visual systems to estimate 3D surface orientation from 2D retinal images is critical. But the computation to calculate 3D orientation in real-world scenes is not fully understood. A Bayes optimal model grounded in natural statistics has explained 3D surface tilt estimation of human observers in natural scenes (Kim and Burge, 2018). However, the model is limited because it estimates only unsigned tilt (tilt modulo 180deg). We extend the model to predict signed tilt estimates and compared with human signed estimates. The model takes image pixels as input and produces optimal estimates of tilt as output, using …

Inferring The Neural Representation Of Faces From Adaptation Aftereffects, Kara J. Emery, Michael A. Webster Ph.D.

MODVIS Workshop

The aftereffects of adaptation to faces have been studied widely, in part to characterize the coding schemes for representing different facial attributes. Often these aftereffects have been interpreted in terms of two alternative models of face processing: 1) a norm-based or opponent code, in which the facial dimension is represented by relative activity in a pair of broadly-tuned mechanisms with opposing sensitivities; or 2) an exemplar code, in which the dimension is sampled by multiple channels narrowly-tuned to different levels of the stimulus. Evidence for or against these alternatives is based on the different patterns of aftereffects they predict (e.g. …

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, 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, 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, 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 …

Divisive Inhibition As A Solution To The Correspondence Problem In Perceptual Grouping, Chien-Chung Chen, Yi-Shiuan Lin, Li Lin

MODVIS Workshop

No abstract provided.

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, 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 …

Modeling Emmetropization In An Incessantly Moving Eye, Michele Rucci, Jonathan D. Victor

MODVIS Workshop

Many questions remain unanswered regarding the specific cues and mechanisms for emmetropization, the process by which, during development, the eye adjusts itself so that distant objects are in focus. Research has so far primarily focused on the spatial cues present in the image on the retina, such as the degree of blur. However, eye movements incessantly transform a mostly static scene into temporal modulations, so that the input to the retina is not an image, but a spatiotemporal flow of luminance. Models of retinal input signals indicate that this space-time reformatting caused by eye movements yields additional cues to the …

An Active Efficient Coding Model Of The Development Of Amblyopia, Samuel Eckmann, Lukas Klimmasch, Bertram Shi, Jochen Triesch

MODVIS Workshop

No abstract provided.

Discovery Of Activities Via Statistical Clustering Of Fixation Patterns, Jeffrey B. Mulligan

MODVIS Workshop

No abstract provided.