Modeling V1 Disparity Tuning to Time-Varying Stimuli

2001 ◽  
Vol 86 (1) ◽  
pp. 143-155 ◽  
Author(s):  
Yuzhi Chen ◽  
Yunjiu Wang ◽  
Ning Qian
Keyword(s):  
Large Body ◽  
Cell Types ◽  
Physiological Data ◽  
Time Varying ◽  
Temporal Response ◽  
Temporal Dimension ◽  
Complex Cells ◽  
Motion In Depth ◽  
Random Dot Stereograms ◽  
Simple And Complex Cells

Most models of disparity selectivity consider only the spatial properties of binocular cells. However, the temporal response is an integral component of real neurons' activities, and time-varying stimuli are often used in the experiments of disparity tuning. To understand the temporal dimension of V1 disparity representation, we incorporate a specific temporal response function into the disparity energy model and demonstrate that the binocular interaction of complex cells is separable into a Gabor disparity function and a positive time function. We then investigate how the model simple and complex cells respond to widely used time-varying stimuli, including motion-in-depth patterns, drifting gratings, moving bars, moving random-dot stereograms, and dynamic random-dot stereograms. It is found that both model simple and complex cells show more reliable disparity tuning to time-varying stimuli than to static stimuli, but similarities in the disparity tuning between simple and complex cells depend on the stimulus. Specifically, the disparity tuning curves of the two cell types are similar to each other for either drifting sinusoidal gratings or moving bars. In contrast, when the stimuli are dynamic random-dot stereograms, the disparity tuning of simple cells is highly variable, whereas the tuning of complex cells remains reliable. Moreover, cells with similar motion preferences in the two eyes cannot be truly tuned to motion in depth regardless of the stimulus types. These simulation results are consistent with a large body of extant physiological data, and provide some specific, testable predictions.

scholarly journals The divisive normalization model of V1 neurons: a comprehensive comparison of physiological data and model predictions

2017 ◽  
Vol 118 (6) ◽  
pp. 3051-3091 ◽  
Author(s):  
Tadamasa Sawada ◽  
Alexander A. Petrov
Keyword(s):  
Physiological Data ◽  
Simulation Experiments ◽  
Complex Cells ◽  
V1 Neurons ◽  
Wide Range ◽  
Divisive Normalization ◽  
Standard Parameter ◽  
Comprehensive Comparison ◽  
Simple And Complex Cells ◽  
Mathematical Analyses

The physiological responses of simple and complex cells in the primary visual cortex (V1) have been studied extensively and modeled at different levels. At the functional level, the divisive normalization model (DNM; Heeger DJ. Vis Neurosci 9: 181–197, 1992) has accounted for a wide range of single-cell recordings in terms of a combination of linear filtering, nonlinear rectification, and divisive normalization. We propose standardizing the formulation of the DNM and implementing it in software that takes static grayscale images as inputs and produces firing rate responses as outputs. We also review a comprehensive suite of 30 empirical phenomena and report a series of simulation experiments that qualitatively replicate dozens of key experiments with a standard parameter set consistent with physiological measurements. This systematic approach identifies novel falsifiable predictions of the DNM. We show how the model simultaneously satisfies the conflicting desiderata of flexibility and falsifiability. Our key idea is that, while adjustable parameters are needed to accommodate the diversity across neurons, they must be fixed for a given individual neuron. This requirement introduces falsifiable constraints when this single neuron is probed with multiple stimuli. We also present mathematical analyses and simulation experiments that explicate some of these constraints.

scholarly journals The Divisive-Normalization Model of V1 Neurons: A Comprehensive Comparison of Physiological Data and Model Predictions

2016 ◽  
Author(s):  
Tadamasa Sawada ◽  
Alexander A. Petrov
Keyword(s):  
Physiological Data ◽  
Simulation Experiments ◽  
Complex Cells ◽  
V1 Neurons ◽  
Wide Range ◽  
Divisive Normalization ◽  
Standard Parameter ◽  
Comprehensive Comparison ◽  
Simple And Complex Cells ◽  
Mathematical Analyses

AbstractThe physiological responses of simple and complex cells in the primary visual cortex (V1) have been studied extensively and modeled at different levels. At the functional level, the divisive normalization model (DNM, Heeger, 1992) has accounted for a wide range of single-cell recordings in terms of a combination of linear filtering, nonlinear rectification, and divisive normalization. We propose standardizing the formulation of the DNM and implementing it in software that takes static grayscale images as inputs and produces firing-rate responses as outputs. We also review a comprehensive suite of 30 empirical phenomena and report a series of simulation experiments that qualitatively replicate dozens of key experiments with a standard parameter set consistent with physiological measurements. This systematic approach identifies novel falsifiable predictions of the DNM. We show how the model simultaneously satisfies the conflicting desiderata of flexibility and falsifiability. Our key idea is that, while adjustable parameters are needed to accommodate the diversity across neurons, they must be fixed for a given individual neuron. This requirement introduces falsifiable constraints when this single neuron is probed with multiple stimuli. We also present mathematical analyses and simulation experiments that explicate some of these constraints.

scholarly journals The MAL Protein, an Integral Component of Specialized Membranes, in Normal Cells and Cancer

Cells ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1065
Author(s):  
Armando Rubio-Ramos ◽  
Leticia Labat-de-Hoz ◽  
Isabel Correas ◽  
Miguel A. Alonso
Keyword(s):  
Epithelial Cells ◽  
Large Body ◽  
Original Description ◽  
Cell Types ◽  
Future Research ◽  
Transmembrane Segments ◽  
Epsilon Toxin ◽  
Proteolipid Proteins ◽  
Polarized Epithelial Cells

The MAL gene encodes a 17-kDa protein containing four putative transmembrane segments whose expression is restricted to human T cells, polarized epithelial cells and myelin-forming cells. The MAL protein has two unusual biochemical features. First, it has lipid-like properties that qualify it as a member of the group of proteolipid proteins. Second, it partitions selectively into detergent-insoluble membranes, which are known to be enriched in condensed cell membranes, consistent with MAL being distributed in highly ordered membranes in the cell. Since its original description more than thirty years ago, a large body of evidence has accumulated supporting a role of MAL in specialized membranes in all the cell types in which it is expressed. Here, we review the structure, expression and biochemical characteristics of MAL, and discuss the association of MAL with raft membranes and the function of MAL in polarized epithelial cells, T lymphocytes, and myelin-forming cells. The evidence that MAL is a putative receptor of the epsilon toxin of Clostridium perfringens, the expression of MAL in lymphomas, the hypermethylation of the MAL gene and subsequent loss of MAL expression in carcinomas are also presented. We propose a model of MAL as the organizer of specialized condensed membranes to make them functional, discuss the role of MAL as a tumor suppressor in carcinomas, consider its potential use as a cancer biomarker, and summarize the directions for future research.

Direction selectivity of complex cells in a comparison with simple cells

1975 ◽  
Vol 38 (6) ◽  
pp. 1524-1540 ◽  
Author(s):  
A. W. Goodwin ◽  
G. H. Henry
Keyword(s):  
Spontaneous Activity ◽  
Visual Information ◽  
Striate Cortex ◽  
Cell Types ◽  
Direction Selectivity ◽  
Complex Cell ◽  
Simple Cells ◽  
Complex Cells ◽  
Sequential Processing

Following our earlier study on direction selectivity in simple cells (5), the present findings on complex cells made it possible to compare the direction selectivity in the two types of striate cell. Common properties were found in the dimension of the smallest stimulus displacement giving a direction-selective response and in the role of inhibition in suppressing the response as the stimulus moved in the nonpreferred direction. However, the effectiveness of this inhibition varied in the two cell types since it suppressed both driven and spontaneous activity in the simple cell, but only driven firing in the complex cell. It is argued that direction selectivity must enter the response before the complex cell if the inhibition responsible for it's generation fails to influence the spontaneous activity of the cell. The consequences of this finding are considered in the terms of parallel or sequential processing of visual information in striate cortex.

scholarly journals Electroretinography in dogs: a review 

2014 ◽  
Vol 59 (No. 11) ◽  
pp. 515-526 ◽  
Author(s):  
M. Drazek ◽  
M. Lew ◽  
S. Lew ◽  
A. Pomianowski
Keyword(s):  
Small Animal ◽  
Cell Types ◽  
Time Varying ◽  
Outer Retina ◽  
Light Stimulation ◽  
Full Field ◽  
Retinal Disorders ◽  
Spatially Distributed ◽  
Different Cell Types ◽  
Stimulation Of

Electroretinography (ERG) in the form of full-field, flash ERG is the most commonly used technique in veterinary ophthalmology for diagnosing the functioning of the outer retina. Under light stimulation spatially distributed different cell types within the retina produce time-varying electric responses. These are recorded in the form of ERG traces consisting of a series of positive and negative wavelets. The possibility of selective stimulation of individual types of retinal cells and the analysis of constituent components of ERGs are the basis for determining the source of abnormalities and diagnosis of various types of dysfunction. In many cases, the ERG allows diagnosis of hereditary retinal disorders in dogs before the appearance of behavioural and ophthalmoscopic symptoms. This review is an introduction to the electrophysiology of vision, intended for small animal practitioners, and aimed at presenting the benefits of ERG for early ophthalmic diagnostics in dogs.

Selective effects of aging on simple and complex cells in primary visual cortex of rhesus monkeys

2012 ◽  
Vol 1470 ◽  
pp. 17-23 ◽  
Author(s):  
Zhen Liang ◽  
Hongxin Li ◽  
Yun Yang ◽  
Guangxing Li ◽  
Yong Tang ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Rhesus Monkeys ◽  
Complex Cells ◽  
Simple And Complex Cells ◽  
Effects Of Aging ◽  
Selective Effects

scholarly journals Spatial and Temporal Features of Synaptic to Discharge Receptive Field Transformation in Cat Area 17

2010 ◽  
Vol 103 (2) ◽  
pp. 677-697 ◽  
Author(s):  
Lionel G. Nowak ◽  
Maria V. Sanchez-Vives ◽  
David A. McCormick
Keyword(s):  
Spatial Frequency ◽  
Response Latency ◽  
Frequency Tuning ◽  
Receptive Fields ◽  
Width Ratio ◽  
Area 17 ◽  
Simple Cells ◽  
Complex Cells ◽  
Temporal Features ◽  
Simple And Complex Cells

The aim of the present study was to characterize the spatial and temporal features of synaptic and discharge receptive fields (RFs), and to quantify their relationships, in cat area 17. For this purpose, neurons were recorded intracellularly while high-frequency flashing bars were used to generate RFs maps for synaptic and spiking responses. Comparison of the maps shows that some features of the discharge RFs depended strongly on those of the synaptic RFs, whereas others were less dependent. Spiking RF duration depended poorly and spiking RF amplitude depended moderately on those of the underlying synaptic RFs. At the other extreme, the optimal spatial frequency and phase of the discharge RFs in simple cells were almost entirely inherited from those of the synaptic RFs. Subfield width, in both simple and complex cells, was less for spiking responses compared with synaptic responses, but synaptic to discharge width ratio was relatively variable from cell to cell. When considering the whole RF of simple cells, additional variability in width ratio resulted from the presence of additional synaptic subfields that remained subthreshold. Due to these additional, subthreshold subfields, spatial frequency tuning predicted from synaptic RFs appears sharper than that predicted from spiking RFs. Excitatory subfield overlap in spiking RFs was well predicted by subfield overlap at the synaptic level. When examined in different regions of the RF, latencies appeared to be quite variable, but this variability showed negligible dependence on distance from the RF center. Nevertheless, spiking response latency faithfully reflected synaptic response latency.

scholarly journals Substructure of Direction-Selective Receptive Fields in Macaque V1

2003 ◽  
Vol 89 (5) ◽  
pp. 2743-2759 ◽  
Author(s):  
Margaret S. Livingstone ◽  
Bevil R. Conway
Keyword(s):  
Receptive Fields ◽  
Direction Selectivity ◽  
Positive Interactions ◽  
Null Direction ◽  
Simple Cells ◽  
Complex Cells ◽  
Preferred Direction ◽  
Orientation Axis ◽  
Interaction Regions ◽  
Simple And Complex Cells

We used two-dimensional (2-D) sparse noise to map simultaneous and sequential two-spot interactions in simple and complex direction-selective cells in macaque V1. Sequential-interaction maps for both simple and complex cells showed preferred-direction facilitation and null-direction suppression for same-contrast stimulus sequences and the reverse for inverting-contrast sequences, although the magnitudes of the interactions were weaker for the simple cells. Contrast-sign selectivity in complex cells indicates that direction-selective interactions in these cells must occur in antecedent simple cells or in simple-cell-like dendritic compartments. Our maps suggest that direction selectivity, and on andoff segregation perpendicular to the orientation axis, can occur prior to receptive-field elongation along the orientation axis. 2-D interaction maps for some complex cells showed elongated alternating facilitatory and suppressive interactions as predicted if their inputs were orientation-selective simple cells. The negative interactions, however, were less elongated than the positive interactions, and there was an inflection at the origin in the positive interactions, so the interactions were chevron-shaped rather than band-like. Other complex cells showed only two round interaction regions, one negative and one positive. Several explanations for the map shapes are considered, including the possibility that directional interactions are generated directly from unoriented inputs.

Temporal Coding of Time-Varying Stimuli

2007 ◽  
Vol 19 (12) ◽  
pp. 3239-3261 ◽  
Author(s):  
Maoz Shamir ◽  
Kamal Sen ◽  
H. Steven Colburn
Keyword(s):  
Information Content ◽  
Temporal Resolution ◽  
Temporal Structure ◽  
Observation Time ◽  
Temporal Coding ◽  
Information Capacity ◽  
Time Varying ◽  
Temporal Response ◽  
Temporal Noise ◽  
The Brain

Temporal structure is an inherent property of various sensory inputs and motor outputs of the brain. For example, auditory stimuli are defined by the sound waveform. Temporal structure is also an important feature of certain visual stimuli, for example, the image on the retina of a fly during flight. In many cases, this temporal structure of the stimulus is being represented by a time-dependent neuronal activity that is locked to certain features of the stimulus. Here, we study the information capacity of the temporal code. In particular we are interested in the following questions. First, how does the information content of the code depend on the observation time of the cell's response, and what is the effect of temporal noise correlations on this information capacity? Second, what is the effect on the information content of reading the code with a finite temporal resolution for the neural response? We address these questions in the framework of a statistical model for the neuronal temporal response to a time-varying stimulus in a two-alternative forced-choice paradigm. We show that information content of the temporal response scales linearly with the overall time of the response, even in the presence of temporal noise correlations. More precisely, we find that positive temporal noise correlations have a scaling effect that decreases the information content. Nevertheless, the information content of the response continues to scale linearly with the observation time. We further show that finite temporal resolution is sufficient for obtaining most of the information from the cell's response. This finite timescale is related to the response properties of the cell.

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