Complex Cells Increase Their Phase Sensitivity at Low Contrasts and Following Adaptation

2007 ◽  
Vol 98 (3) ◽  
pp. 1155-1166 ◽  
Author(s):  
N. A. Crowder ◽  
J. van Kleef ◽  
B. Dreher ◽  
M. R. Ibbotson
Keyword(s):  
Receptive Fields ◽  
Phase Sensitivity ◽  
Complex Cells ◽  
Spike Threshold ◽  
Cell Responses ◽  
Layer 4 ◽  
A Cell ◽  
Phase Sensitive ◽  
Simple And Complex Cells ◽  
Mean Time

One of the best-known dichotomies in neuroscience is the division of neurons in the mammalian primary visual cortex into simple and complex cells. Simple cells have receptive fields with separate on and off subregions and give phase-sensitive responses to moving gratings, whereas complex cells have uniform receptive fields and are phase invariant. The phase sensitivity of a cell is calculated as the ratio of the first Fourier coefficient ( F1) to the mean time-average ( F0) of the response to moving sinusoidal gratings at 100% contrast. Cells are then classified as simple ( F1/ F0>1) or complex ( F1/ F0<1). We manipulated cell responses by changing the stimulus contrast or through adaptation. The F1/ F0ratios of cells defined as complex at 100% contrast increased at low contrasts and following adaptation. Conversely, the F1/ F0ratios remained constant for cells defined as simple at 100% contrast. The latter cell type was primarily located in thalamorecipient layers 4 and 6. Many cells initially classified as complex exhibit F1/ F0>1 at low contrasts and after adaptation (particularly in layer 4). The results are consistent with the spike-threshold hypothesis, which suggests that the division of cells into two types arises from the nonlinear interaction of spike threshold with membrane potential responses.

Quantum-like signal-tuned approach to V1 modeling

2019 ◽  
Vol 30 (05) ◽  
pp. 1950032
Author(s):  
José R. A. Torreão ◽  
Marcos S. Amaral
Keyword(s):  
Receptive Fields ◽  
Spatial Summation ◽  
Cortical Cells ◽  
Complex Cells ◽  
Cell Responses ◽  
Gabor Functions ◽  
Half Wave ◽  
Plausible Model ◽  
Simple And Complex Cells ◽  
Carry Over

Signal-tuned Gabor functions — Gaussian-modulated sinusoids whose parameters are determined by a spatial or spectral “tuning signal” — have previously been shown to provide a plausible model for the stimulus-dependent receptive fields and responses of the simple and complex cells of the primary visual cortex (V1). The signal-tuned responses obey Schrödinger equations, which has led to the proposal of a quantum-like model for V1 cells: by considering the squared magnitude of a particular signal-tuned wave function as a probability density, one arrives at a Poisson spiking process which appears consistent with the neurophysiological findings. Here, by incorporating Hermite-polynomial factors to the signal-tuned Gabor functions, we obtain a generalized quantum-like signal-tuned model for which further relevant properties are demonstrated, such as receptive-field coding of the stimulus and its derivatives, saturating spatial summation curves and half-wave rectification of the simple cell responses. Although only a one-dimensional approach is considered here, such properties will carry over to a two-dimensional model, in which case, as our preliminary analysis indicates, end-stopping — another important feature of cortical cells — can also be accommodated.

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 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.

scholarly journals Image statistics at the point of gaze during human navigation

2009 ◽  
Vol 26 (1) ◽  
pp. 81-92 ◽  
Author(s):  
CONSTANTIN A. ROTHKOPF ◽  
DANA H. BALLARD
Keyword(s):  
Visual System ◽  
Selection Process ◽  
Human Subjects ◽  
Image Features ◽  
Complex Cells ◽  
Cell Responses ◽  
Active Selection ◽  
Active Nature ◽  
Simple And Complex Cells ◽  
Distinct Features

AbstractTheories of efficient sensory processing have considered the regularities of image properties due to the structure of the environment in order to explain properties of neuronal representations of the visual world. The regularities imposed on the input to the visual system due to the regularities of the active selection process mediated by the voluntary movements of the eyes have been considered to a much lesser degree. This is surprising, given that the active nature of vision is well established. The present article investigates statistics of image features at the center of gaze of human subjects navigating through a virtual environment and avoiding and approaching different objects. The analysis shows that contrast can be significantly higher or lower at fixation location compared to random locations, depending on whether subjects avoid or approach targets. Similarly, significant differences in the distribution of responses of model simple and complex cells between horizontal and vertical orientations are found over timescales of tens of seconds. By clustering the model simple cell responses, it is established that gaze was directed toward three distinct features of intermediate complexity the vast majority of time. Thus, this study demonstrates and quantifies how the visuomotor tasks of approaching and avoiding objects during navigation determine feature statistics of the input to the visual system through the combined influence on body and eye movements.

Cone Inputs to Simple and Complex Cells in V1 of Awake Macaque

2007 ◽  
Vol 97 (4) ◽  
pp. 3070-3081 ◽  
Author(s):  
Gregory D. Horwitz ◽  
E. J. Chichilnisky ◽  
Thomas D. Albright
Keyword(s):  
Linear Models ◽  
Noise Analysis ◽  
Receptive Fields ◽  
Light Responses ◽  
Simple Cells ◽  
Complex Cells ◽  
V1 Neurons ◽  
Spike Triggered Averaging ◽  
Simple And Complex Cells ◽  
Simple And Complex Cell

Rules by which V1 neurons combine signals originating in the cone photoreceptors are poorly understood. We measured cone inputs to V1 neurons in awake, fixating monkeys with white-noise analysis techniques that reveal properties of light responses not revealed by purely linear models used in previous studies. Simple cells were studied by spike-triggered averaging that is robust to static nonlinearities in spike generation. This analysis revealed, among heterogeneously tuned neurons, two relatively discrete categories: one with opponent L- and M-cone weights and another with nonopponent cone weights. Complex cells were studied by spike-triggered covariance, which identifies features in the stimulus sequence that trigger spikes in neurons with receptive fields containing multiple linear subunits that combine nonlinearly. All complex cells responded to nonopponent stimulus modulations. Although some complex cells responded to cone-opponent stimulus modulations too, none exhibited the pure opponent sensitivity observed in many simple cells. These results extend the findings on distinctions between simple and complex cell chromatic tuning observed in previous studies in anesthetized monkeys.

scholarly journals Replicating Receptive Fields of Simple and Complex Cells in Primary Visual Cortex in a Neuronal Network Model with Temporal and Population Sparseness and Reliability

2012 ◽  
Vol 24 (10) ◽  
pp. 2700-2725 ◽  
Author(s):  
Takuma Tanaka ◽  
Toshio Aoyagi ◽  
Takeshi Kaneko
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Learning Rule ◽  
Simple Cell ◽  
Complex Cells ◽  
Receptive Field Properties ◽  
Output Neurons ◽  
Simple And Complex Cells

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

scholarly journals Learning simple and complex cells-like receptive fields from natural images: a plausibility proof

2010 ◽  
Vol 7 (9) ◽  
pp. 81-81 ◽  
Author(s):  
T. Masquelier ◽  
T. Serre ◽  
S. Thorpe ◽  
T. Poggio
Keyword(s):  
Receptive Fields ◽  
Natural Images ◽  
Complex Cells ◽  
Simple And Complex Cells

Signal-Tuned Gabor Functions as Models for Stimulus-Dependent Cortical Receptive Fields

2014 ◽  
Vol 26 (5) ◽  
pp. 920-952 ◽  
Author(s):  
José R. A. Torreão ◽  
Silvia M. C. Victer ◽  
Marcos S. Amaral
Keyword(s):  
Receptive Fields ◽  
Gabor Transform ◽  
Spectral Tuning ◽  
Complex Cells ◽  
Model Based ◽  
Accurate Detection ◽  
Gabor Functions ◽  
Neurophysiological Studies ◽  
Simple And Complex Cells ◽  
Cortical Receptive Fields

We propose and analyze a model, based on signal-tuned Gabor functions, for the receptive fields and responses of V1 cells. Signal-tuned Gabor functions are gaussian-modulated sinusoids whose parameters are obtained from a given, spatial, or spectral “tuning” signal. These functions can be proven to yield exact representations of their tuning signals and have recently been proposed as the kernels of a variant Gabor transform—the signal-tuned Gabor transform (STGT)—which allows the accurate detection of spatial and spectral events. Here we show that by modeling the receptive fields of simple and complex cells as signal-tuned Gabor functions and expressing their responses as STGTs, we are able to replicate the properties of these cells when tested with standard grating and slit inputs, at the same time emulating their stimulus-dependent character as revealed by recent neurophysiological studies.

Contrast-dependent phase sensitivity in V1 but not V2 of macaque visual cortex

2015 ◽  
Vol 113 (2) ◽  
pp. 434-444 ◽  
Author(s):  
Shaun L. Cloherty ◽  
Michael R. Ibbotson
Keyword(s):  
Visual Cortex ◽  
Receptive Fields ◽  
Brain Regions ◽  
Sine Wave ◽  
Phase Sensitivity ◽  
Simple Cells ◽  
Low Contrast ◽  
Cortical Input ◽  
Hierarchical Processing ◽  
Complex Cells

Some neurons in early visual cortex are highly selective for the position of oriented edges in their receptive fields (simple cells), whereas others are largely position insensitive (complex cells). These characteristics are reflected in their sensitivity to the spatial phase of moving sine-wave gratings: simple cell responses oscillate at the fundamental frequency of the stimulus, whereas this is less so for complex cells. In primates, when assessed at high stimulus contrast, simple cells and complex cells are roughly equally represented in the first visual cortical area, V1, whereas in the second visual area, V2, the majority of cells are complex. Recent evidence has shown that phase sensitivity of complex cells is contrast dependent. This has led to speculation that reduced contrast may lead to changes in the spatial structure of receptive fields, perhaps due to changes in how feedforward and recurrent signals interact. Given the substantial interconnections between V1 and V2 and recent evidence for the emergence of unique functional capacity in V2, we assess the relationship between contrast and phase sensitivity in the two brain regions. We show that a substantial proportion of complex cells in macaque V1 exhibit significant increases in phase sensitivity at low contrast, whereas this is rarely observed in V2. Our results support a degree of hierarchical processing from V1 to V2 with the differences possibly relating to the fact that V1 combines both subcortical and cortical input, whereas V2 receives input purely from cortical circuits.

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