Neuroscience and Neurobiology Commons^™

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.

Central And Peripheral Difference In Perceptual Bias In Ambiguous Perception Using Dichoptic Stimuli --- Implications For The Analysis-By-Synthesis Process In Visual Recognition, Li Zhaoping Prof

MODVIS Workshop

No abstract provided.

Predicting Fixations From Deep And Low-Level Features, Matthias Kümmerer, Thomas S.A. Wallis, Leon A. Gatys, Matthias Bethge

MODVIS Workshop

Learning what properties of an image are associated with human gaze placement is important both for understanding how biological systems explore the environment and for computer vision applications. Recent advances in deep learning for the first time enable us to explain a significant portion of the information expressed in the spatial fixation structure. Our saliency model DeepGaze II uses the VGG network (trained on object recognition in the ImageNet challenge) to convert an image into a high-dimensional feature space which is then readout by a second very simple network to yield a density prediction. DeepGaze II is right now the …

Mapping The Spatio-Temporal Dynamics Of Vision In The Human Brain, Aude Oliva

MODVIS Workshop

Recognition of objects and scenes is a fundamental function of the human brain, necessitating a complex neural machinery that transforms low level visual information into semantic content. Despite significant advances in characterizing the locus and function of key visual areas, integrating the temporal and spatial dynamics of this processing stream has posed a decades-long challenge to human neuroscience. In this talk I will describe a brain mapping approach to combine magnetoencephalography (MEG), functional MRI (fMRI) measurements, and convolutional neural networks (CNN) by representational similarity analysis to yield a spatially and temporally integrated characterization of neuronal representations when observers perceive visual …

Neural Computation Of Statistical Image Properties In Peripheral Vision, Christoph Zetzsche, Ruth Rosenholtz, Noshaba Cheema, Konrad Gadzicki, Lex Fridman

MODVIS Workshop

No abstract provided.

Similarity-Based Fusion Of Meg And Fmri Discerns Early Feedforward And Feedback Processing In The Ventral Stream, Yalda Mohsenzadeh Dr., Radoslaw Martin Cichy Dr., Aude Oliva Dr., Dimitrios Pantazis Dr.

MODVIS Workshop

Successful models of vision, such as DNNs and HMAX, are inspired by the human visual system, relying on a hierarchical cascade of feedforward transformations akin to the ventral stream. Despite these advances, the human visual cortex remains unique in complexity, with feedforward and feedback pathways characterized by rapid spatiotemporal dynamics as visual information is transformed into semantic content. Thus, a systematic characterization of the spatiotemporal and representational space of the ventral visual pathway can offer novel insights in the duration and sequencing of cognitive processes, suggesting computational constraints and new architectures for computer vision models.

To discern the feedforward and …

Using Classification Images To Understand Models Of Lightness Perception, Minjung Kim, Jason M. Gold, Richard F. Murray

MODVIS Workshop

No abstract provided.

Edge Integration And Image Segmentation In Lightness And Color: Computational And Neural Theory, Michael E. Rudd

MODVIS Workshop

No abstract provided.

Modeling Accommodation Control Of The Human Eye: Chromatic Aberration And Color Opponency, Agostino Gibaldi, Steven A. Cholewiak, Marty S. Banks

MODVIS Workshop

Accommodation is the process by which the eye lens changes optical power to maintain a clear retinal image as the distance to the fixated object varies. Although luminance blur has long been considered the driving feature for accommodation, it is by definition unsigned (i.e., there is no difference between the defocus of an object closer or farther than the focus distance). Nonetheless, the visual system initially accommodates in the correct direction, implying that it exploits a cue with sign information. Here, we present a model of accommodation control based on such a cue: Longitudinal Chromatic Aberration (LCA). The model relies …

Can Cone Signals In The Wild Be Predicted From The Past?, David H. Foster, Iván Marín-Franch

MODVIS Workshop

In the natural world, the past is usually a good guide to the future. If light from the sun and sky is blue earlier in the day and yellow now, then it is likely to be more yellow later, as the sun's elevation decreases. But is the light reflected from a scene into the eye as predictable as the light incident upon the scene, especially when lighting changes are not just spectral but include changes in local shadows and mutual reflections? The aim of this work was to test the predictability of cone photoreceptor signals in the wild over the …

Role Of The Cost Of Plasticity In Determining The Features Of Fast Vision In Humans., Maria M. Del Viva Phd, Renato Budinich M. Sc, Laura Palmieri M. Sc, Vladimir S Georgiev Phd, Giovanni Punzi Phd

MODVIS Workshop

No abstract provided.

Modeling The Mechanisms Of Reward Learning That Bias Visual Attention, Jason Hays, Fabian Soto Phd

MODVIS Workshop

No abstract provided.

Heuristics From Statistics—Modeling The Behavior And Perception Of Non-Rigid Materials, Vivian C. Paulun, Roland W. Fleming

MODVIS Workshop

No abstract provided.