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Full-Text Articles in Neuroscience and Neurobiology

Linking Signal Detection Theory And Encoding Models To Reveal Independent Neural Representations From Neuroimaging Data, Fabian A. Soto May 2018

Linking Signal Detection Theory And Encoding Models To Reveal Independent Neural Representations From Neuroimaging Data, Fabian A. Soto

MODVIS Workshop

No abstract provided.


A Feature-Based Model Of Visually Perceiving Deformable Objects, Vivian C. Paulun, Filipp Schmidt, Roland W. Fleming May 2018

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 May 2018

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. May 2018

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 May 2018

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 …


Why Latent Representations In Convolutional Neural Networks Fall Outside Visual Space, Katerina Malakhova May 2018

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 …


Divisive Inhibition As A Solution To The Correspondence Problem In Perceptual Grouping, Chien-Chung Chen, Yi-Shiuan Lin, Li Lin May 2018

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.


Discovery Of Activities Via Statistical Clustering Of Fixation Patterns, Jeffrey B. Mulligan May 2018

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

MODVIS Workshop

No abstract provided.