scholarly journals Do Simple Cells in Primary Visual Cortex Form a Tight Frame?

2000 ◽  
Vol 12 (2) ◽  
pp. 313-335 ◽  
Author(s):  
Emilio Salinas ◽  
L. F. Abbott
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Function Approximation ◽  
Receptive Fields ◽  
Tight Frame ◽  
Orthogonal Functions ◽  
Simple Cells ◽  
Tuning Curves ◽  
Neuronal Tuning ◽  
The Relationship

Sets of neuronal tuning curves, which describe the responses of neurons as functions of a stimulus, can serve as a basis for approximating other functions of stimulus parameters. In a function-approximating network, synaptic weights determined by a correlation-based Hebbian rule are closely related to the coefficients that result when a function is expanded in an orthogonal basis. Although neuronal tuning curves typically are not orthogonal functions, the relationship between function approximation and correlation-based synaptic weights can be retained if the tuning curves satisfy the conditions of a tight frame. We examine whether the spatial receptive fields of simple cells in cat and monkey primary visual cortex (V1) form a tight frame, allowing them to serve as a basis for constructing more complicated extrastriate receptive fields using correlation-based synaptic weights. Our calculations show that the set of V1 simple cell receptive fields is not tight enough to account for the acuity observed psychophysically.

scholarly journals Sub-Optimality of the Early Visual System Explained Through Biologically Plausible Plasticity

2021 ◽  
Vol 15 ◽  
Author(s):  
Tushar Chauhan ◽  
Timothée Masquelier ◽  
Benoit R. Cottereau
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Spike Timing ◽  
Orientation Tuning ◽  
Biologically Relevant ◽  
Tuning Curves ◽  
Stdp Rule ◽  
Early Visual Cortex ◽  
Minimisation Problem

The early visual cortex is the site of crucial pre-processing for more complex, biologically relevant computations that drive perception and, ultimately, behaviour. This pre-processing is often studied under the assumption that neural populations are optimised for the most efficient (in terms of energy, information, spikes, etc.) representation of natural statistics. Normative models such as Independent Component Analysis (ICA) and Sparse Coding (SC) consider the phenomenon as a generative, minimisation problem which they assume the early cortical populations have evolved to solve. However, measurements in monkey and cat suggest that receptive fields (RFs) in the primary visual cortex are often noisy, blobby, and symmetrical, making them sub-optimal for operations such as edge-detection. We propose that this suboptimality occurs because the RFs do not emerge through a global minimisation of generative error, but through locally operating biological mechanisms such as spike-timing dependent plasticity (STDP). Using a network endowed with an abstract, rank-based STDP rule, we show that the shape and orientation tuning of the converged units are remarkably close to single-cell measurements in the macaque primary visual cortex. We quantify this similarity using physiological parameters (frequency-normalised spread vectors), information theoretic measures [Kullback–Leibler (KL) divergence and Gini index], as well as simulations of a typical electrophysiology experiment designed to estimate orientation tuning curves. Taken together, our results suggest that compared to purely generative schemes, process-based biophysical models may offer a better description of the suboptimality observed in the early visual cortex.

scholarly journals Sensory coding and contrast invariance emerge from the control of plastic inhibition over excitatory connectivity

2020 ◽  
Author(s):  
René Larisch ◽  
Lorenz Gönner ◽  
Michael Teichmann ◽  
Fred H. Hamker
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Gain Control ◽  
Metabolic Efficiency ◽  
Tuning Curves ◽  
Coding Efficiency ◽  
Inhibitory Feedback ◽  
Efficient Code ◽  
Inhibitory Plasticity

Visual stimuli are represented by a highly efficient code in the primary visual cortex, but the development of this code is still unclear. Two distinct factors control coding efficiency: Representational efficiency, which is determined by neuronal tuning diversity, and metabolic efficiency, which is influenced by neuronal gain. How these determinants of coding efficiency are shaped during development, supported by excitatory and inhibitory plasticity, is only partially understood. We investigate a fully plastic spiking network of the primary visual cortex, building on phenomenological plasticity rules. Our results show that inhibitory plasticity is key to the emergence of tuning diversity and accurate input encoding. Additionally, inhibitory feedback increases the metabolic efficiency by implementing a gain control mechanism. Interestingly, this led to the spontaneous emergence of contrast-invariant tuning curves. Our findings highlight the role of interneuron plasticity during the development of receptive fields and in shaping sensory representations.

scholarly journals Spatial phase sensitivity of complex cells in primary visual cortex depends on stimulus contrast

2015 ◽  
Vol 114 (6) ◽  
pp. 3326-3338 ◽  
Author(s):  
H. Meffin ◽  
M. A. Hietanen ◽  
S. L. Cloherty ◽  
M. R. Ibbotson
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Spatial Summation ◽  
Phase Sensitivity ◽  
Simple Cells ◽  
Low Contrast ◽  
Complex Cells ◽  
Spatial Phase ◽  
Phase Sensitive

Neurons in primary visual cortex are classified as simple, which are phase sensitive, or complex, which are significantly less phase sensitive. Previously, we have used drifting gratings to show that the phase sensitivity of complex cells increases at low contrast and after contrast adaptation while that of simple cells remains the same at all contrasts (Cloherty SL, Ibbotson MR. J Neurophysiol 113: 434–444, 2015; Crowder NA, van Kleef J, Dreher B, Ibbotson MR. J Neurophysiol 98: 1155–1166, 2007; van Kleef JP, Cloherty SL, Ibbotson MR. J Physiol 588: 3457–3470, 2010). However, drifting gratings confound the influence of spatial and temporal summation, so here we have stimulated complex cells with gratings that are spatially stationary but continuously reverse the polarity of the contrast over time (contrast-reversing gratings). By varying the spatial phase and contrast of the gratings we aimed to establish whether the contrast-dependent phase sensitivity of complex cells results from changes in spatial or temporal processing or both. We found that most of the increase in phase sensitivity at low contrasts could be attributed to changes in the spatial phase sensitivities of complex cells. However, at low contrasts the complex cells did not develop the spatiotemporal response characteristics of simple cells, in which paired response peaks occur 180° out of phase in time and space. Complex cells that increased their spatial phase sensitivity at low contrasts were significantly overrepresented in the supragranular layers of cortex. We conclude that complex cells in supragranular layers of cat cortex have dynamic spatial summation properties and that the mechanisms underlying complex cell receptive fields differ between cortical layers.

scholarly journals Development of orientation tuning in simple cells of primary visual cortex

2012 ◽  
Vol 107 (9) ◽  
pp. 2506-2516 ◽  
Author(s):  
Bartlett D. Moore ◽  
Ralph D. Freeman
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Receptive Fields ◽  
Orientation Selectivity ◽  
Orientation Tuning ◽  
Simple Cells ◽  
Hierarchical Processing ◽  
Tuning Curves ◽  
Linear Connections ◽  
Basic Features

Orientation selectivity and its development are basic features of visual cortex. The original model of orientation selectivity proposes that elongated simple cell receptive fields are constructed from convergent input of an array of lateral geniculate nucleus neurons. However, orientation selectivity of simple cells in the visual cortex is generally greater than the linear contributions based on projections from spatial receptive field profiles. This implies that additional selectivity may arise from intracortical mechanisms. The hierarchical processing idea implies mainly linear connections, whereas cortical contributions are generally considered to be nonlinear. We have explored development of orientation selectivity in visual cortex with a focus on linear and nonlinear factors in a population of anesthetized 4-wk postnatal kittens and adult cats. Linear contributions are estimated from receptive field maps by which orientation tuning curves are generated and bandwidth is quantified. Nonlinear components are estimated as the magnitude of the power function relationship between responses measured from drifting sinusoidal gratings and those predicted from the spatial receptive field. Measured bandwidths for kittens are slightly larger than those in adults, whereas predicted bandwidths are substantially broader. These results suggest that relatively strong nonlinearities in early postnatal stages are substantially involved in the development of orientation tuning in visual cortex.

scholarly journals Layer 4 in Primary Visual Cortex of the Awake Rabbit: Contrasting Properties of Simple Cells and Putative Feedforward Inhibitory Interneurons

2013 ◽  
Vol 33 (28) ◽  
pp. 11372-11389 ◽  
Author(s):  
J. Zhuang ◽  
C. R. Stoelzel ◽  
Y. Bereshpolova ◽  
J. M. Huff ◽  
X. Hei ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Inhibitory Interneurons ◽  
Simple Cells ◽  
Layer 4

A model for the estimate of local image velocity by cells in the visual cortex

1990 ◽  
Vol 239 (1295) ◽  
pp. 129-161 ◽  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Frequency Tuning ◽  
Temporal Frequency ◽  
Spatial Integration ◽  
Temporal Area ◽  
Image Velocity ◽  
Tuning Curves ◽  
Spatio Temporal ◽  
Local Image

Some computational theories of motion perception assume that the first stage en route to this perception is the local estimate of image velocity. However, this assumption is not supported by data from the primary visual cortex. Its motion sensitive cells are not selective to velocity, but rather are directionally selective and tuned to spatio-temporal frequen­cies. Accordingly, physiologically based theories start with filters selec­tive to oriented spatio-temporal frequencies. This paper shows that computational and physiological theories do not necessarily conflict, because such filters may, as a population, compute velocity locally. To prove this point, we show how to combine the outputs of a class of frequency tuned filters to detect local image velocity. Furthermore, we show that the combination of filters may simulate ‘Pattern’ cells in the middle temporal area (MT), whereas each filter simulates primary visual cortex cells. These simulations include three properties of the primary cortex. First, the spatio-temporal frequency tuning curves of the in­dividual filters display approximate space-time separability. Secondly, their direction-of-motion tuning curves depend on the distribution of orientations of the components of the Fourier decomposition and speed of the stimulus. Thirdly, the filters show facilitation and suppression for responses to apparent motions in the preferred and null directions, respect­ively. It is suggested that the MT’s role is not to solve the aperture problem, but to estimate velocities from primary cortex information. The spatial integration that accounts for motion coherence may be postponed to a later cortical stage.

scholarly journals Subdomains within orientation columns of primary visual cortex

2019 ◽  
Vol 5 (6) ◽  
pp. eaaw0807 ◽  
Author(s):  
Ming Li ◽  
Xue Mei Song ◽  
Tao Xu ◽  
Dewen Hu ◽  
Anna Wang Roe ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Accurate Method ◽  
Electrode Position ◽  
Tree Shrews ◽  
Form Processing ◽  
Orientation Columns ◽  
Relationship Of ◽  
First Time ◽  
The Relationship

In the mammalian visual system, early stages of visual form processing begin with orientation-selective neurons in primary visual cortex (V1). In many species (including humans, monkeys, tree shrews, cats, and ferrets), these neurons are organized in a beautifully arrayed pinwheel-like orientation columns, which shift in orientation preference across V1. However, to date, the relationship of orientation architecture to the encoding of multiple elemental aspects of visual contours is still unknown. Here, using a novel, highly accurate method of targeting electrode position, we report for the first time the presence of three subdomains within single orientation domains. We suggest that these zones subserve computation of distinct aspects of visual contours and propose a novel tripartite pinwheel-centered view of an orientation hypercolumn.

scholarly journals Spatial Distribution of Contextual Interactions in Primary Visual Cortex and in Visual Perception

2000 ◽  
Vol 84 (4) ◽  
pp. 2048-2062 ◽  
Author(s):  
Mitesh K. Kapadia ◽  
Gerald Westheimer ◽  
Charles D. Gilbert
Keyword(s):  
Spatial Distribution ◽  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Cortical Neurons ◽  
Receptive Fields ◽  
Human Perception ◽  
Spatial Arrangement ◽  
Orthogonal Axis ◽  
V1 Neurons ◽  
Contextual Interactions

To examine the role of primary visual cortex in visuospatial integration, we studied the spatial arrangement of contextual interactions in the response properties of neurons in primary visual cortex of alert monkeys and in human perception. We found a spatial segregation of opposing contextual interactions. At the level of cortical neurons, excitatory interactions were located along the ends of receptive fields, while inhibitory interactions were strongest along the orthogonal axis. Parallel psychophysical studies in human observers showed opposing contextual interactions surrounding a target line with a similar spatial distribution. The results suggest that V1 neurons can participate in multiple perceptual processes via spatially segregated and functionally distinct components of their receptive fields.

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