scholarly journals Unifying Temporal Phenomena in Human Visual Cortex

2017 ◽  
Author(s):  
Jingyang Zhou ◽  
Noah C. Benson ◽  
Kendrick Kay ◽  
Jonathan Winawer
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Temporal Dynamics ◽  
Gain Control ◽  
Spatial Vision ◽  
Research Area ◽  
Neuronal Responses ◽  
Stimulus Contrast ◽  
Temporal Properties ◽  
Cortical Responses

AbstractNeuronal responses in visual cortex show a diversity of complex temporal properties. These properties include sub-additive temporal summation, response reduction with repeated or sustained stimuli (adaptation), and slower dynamics at low stimulus contrast. Here, we hypothesize that these seemingly disparate effects can be explained by a single, shared computational mechanism. We propose a model consisting of a linear stage, followed by history-dependent gain control. The model accounts for these various temporal phenomena, tested against an unusually diverse set of measurements - intracranial electrodes in patients, fMRI, and macaque single unit spiking. The model further enables us to uncover a systematic and rich variety of temporal encoding strategies across visual cortex: First, temporal receptive field shape differs both across and within visual field maps. Second, later visual areas show more rapid and pronounced adaptation. Our study provides a new framework to understand the transformation between visual input and dynamical cortical responses.Author SummaryThe nervous system extracts meaning from the distribution of light over space and time. Spatial vision has been a highly successful research area, and the spatial receptive field has served as a fundamental and unifying concept that spans perception, computation, and physiology. While there has also been a large interest in temporal vision, the temporal domain has lagged the spatial domain in terms of quantitative models of how signals are transformed across the visual hierarchy. Here we present a model of temporal dynamics of neuronal responses in human cerebral cortex. We show that the model can accurately predict responses at the millisecond scale using intracortical electrodes in patient volunteers, and that the same model generalizes to multiple types of other measurements, including functional MRI and action potentials from monkey cortex. Further, we show that a single model can account for a variety of temporal phenomena, including short-term adaptation and slower dynamics at low stimulus contrast. By developing a computational model and showing that it successfully generalizes across measurement types, cortical areas, and stimuli, we provide new insights into how time-varying images are encoded and transformed into dynamic cortical responses.

Temporal properties of surround suppression in cat primary visual cortex

2007 ◽  
Vol 24 (5) ◽  
pp. 679-690 ◽  
Author(s):  
SÉVERINE DURAND ◽  
TOBE C.B. FREEMAN ◽  
MATTEO CARANDINI
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Cortical Neurons ◽  
Prolonged Exposure ◽  
Intracortical Inhibition ◽  
Surround Suppression ◽  
Temporal Properties ◽  
Contrast Adaptation ◽  
Cortical Responses

The responses of neurons in primary visual cortex (V1) are suppressed by stimuli presented in the region surrounding the receptive field. There is debate as to whether this surround suppression is due to intracortical inhibition, is inherited from lateral geniculate nucleus (LGN), or is due to a combination of these factors. The mechanisms involved in surround suppression may differ from those involved in suppression within the receptive field, which is called cross-orientation suppression. To compare surround suppression to cross-orientation suppression, and to help elucidate its underlying mechanisms, we studied its temporal properties in anesthetized and paralyzed cats. We first measured the temporal resolution of suppression. While cat LGN neurons respond vigorously to drift rates up to 30 Hz, most cat V1 neurons stop responding above 10–15 Hz. If suppression originated in cortical responses, therefore, it should disappear above such drift rates. In a majority of cells, surround suppression decreased substantially when surround drift rate was above ∼15 Hz, but some neurons demonstrated suppression with surround drift rates as high as 21 Hz. We then measured the susceptibility of suppression to contrast adaptation. Contrast adaptation reduces responses of cortical neurons much more than those of LGN neurons. If suppression originated in cortical responses, therefore, it should be reduced by adaptation. Consistent with this hypothesis, we found that prolonged exposure to the surround stimulus decreased the strength of surround suppression. The results of both experiments differ markedly from those previously obtained in a study of cross-orientation suppression, whose temporal properties were found to resemble those of LGN neurons. Our results provide further evidence that these two forms of suppression are due to different mechanisms. Surround suppression can be explained by a mixture of thalamic and cortical influences. It could also arise entirely from intracortical inhibition, but only if inhibitory neurons respond to somewhat higher drift rates than most cortical cells.

scholarly journals Orientation Tuning of Input Conductance, Excitation, and Inhibition in Cat Primary Visual Cortex

2000 ◽  
Vol 84 (2) ◽  
pp. 909-926 ◽  
Author(s):  
Jeffrey S. Anderson ◽  
Matteo Carandini ◽  
David Ferster
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Stimulation ◽  
Gain Control ◽  
Orientation Tuning ◽  
Visual Responses ◽  
Stimulus Contrast ◽  
Simple Cells ◽  
Conductance Changes ◽  
Input Conductance

The input conductance of cells in the cat primary visual cortex (V1) has been shown recently to grow substantially during visual stimulation. Because increasing conductance can have a divisive effect on the synaptic input, theoretical proposals have ascribed to it specific functions. According to the veto model, conductance increases would serve to sharpen orientation tuning by increasing most at off-optimal orientations. According to the normalization model, conductance increases would control the cell's gain, by being independent of stimulus orientation and by growing with stimulus contrast. We set out to test these proposals and to determine the visual properties and possible synaptic origin of the conductance increases. We recorded the membrane potential of cat V1 cells while injecting steady currents and presenting drifting grating patterns of varying contrast and orientation. Input conductance grew with stimulus contrast by 20–300%, generally more in simple cells (40–300%) than in complex cells (20–120%), and in simple cells was strongly modulated in time. Conductance was invariably maximal for stimuli of the preferred orientation. Thus conductance changes contribute to a gain control mechanism, but the strength of this gain control does not depend uniquely on contrast. By assuming that the conductance changes are entirely synaptic, we further derived the excitatory and inhibitory synaptic conductances underlying the visual responses. In simple cells, these conductances were often arranged in push-pull: excitation increased when inhibition decreased and vice versa. Excitation and inhibition had similar preferred orientations and did not appear to differ in tuning width, suggesting that the intracortical synaptic inputs to simple cells of cat V1 originate from cells with similar orientation tuning. This finding is at odds with models where orientation tuning in simple cells is achieved by inhibition at off-optimal orientations or sharpened by inhibition that is more broadly tuned than excitation.

Contrast Dependence of Response Normalization in Area MT of the Rhesus Macaque

2002 ◽  
Vol 88 (6) ◽  
pp. 3398-3408 ◽  
Author(s):  
Hilary W. Heuer ◽  
Kenneth H. Britten
Keyword(s):  
Receptive Field ◽  
Rhesus Macaque ◽  
Extrastriate Cortex ◽  
Neuronal Responses ◽  
Stimulus Contrast ◽  
Linear Summation ◽  
Middle Temporal ◽  
Good Account ◽  
Rapid Transition ◽  
Contrast Normalization

Contrast normalization is a process whereby responses of neurons are scaled according to the total amount of contrast in a region of the image nearby the receptive field of a neuron. This process allows neurons to code for informative scene or object attributes in a manner unaffected by changes in illumination. Evidence for normalization is seen in striate and extrastriate cortex from experiments where multiple stimuli are presented with a single receptive field (RF). Neuronal responses in such experiments are smaller than that predicted by linear summation, revealing the presence of normalization. While the presence of normalization is often clear, its mechanism is less so. To study the mechanism of normalization, we measured the interaction between pairs of brief local stimuli (spatial Gabor functions) within the RFs of cells in the middle temporal (MT or V5) area of monkeys and varied both the location and contrast of the stimuli. We found response summed approximately linearly when contrast was low but rapidly became normalized as stimulus contrast increased. The rapid transition to effective normalization at low contrasts suggested cooperativity in the normalization, and a model embodying such a cooperative step provided a good account of our data.

scholarly journals Gain control from beyond the classical receptive field in primate primary visual cortex

2003 ◽  
Vol 20 (3) ◽  
pp. 221-230 ◽  
Author(s):  
BEN S. WEBB ◽  
CHRIS J. TINSLEY ◽  
NICK E. BARRACLOUGH ◽  
AMANDA PARKER ◽  
ANDREW M. DERRINGTON
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Gain Control ◽  
Salient Feature ◽  
Retinal Eccentricity ◽  
V1 Neurons ◽  
Contrast Gain ◽  
Classical Receptive Field ◽  
Extrastriate Areas

Gain control is a salient feature of information processing throughout the visual system. Heeger (1991, 1992) described a mechanism that could underpin gain control in primary visual cortex (V1). According to this model, a neuron's response is normalized by dividing its output by the sum of a population of neurons, which are selective for orientations covering a broad range. Gain control in this scheme is manifested as a change in the semisaturation constant (contrast gain) of a V1 neuron. Here we examine how flanking and annular gratings of the same or orthogonal orientation to that preferred by a neuron presented beyond the receptive field modulate gain in V1 neurons in anesthetized marmosets (Callithrix jacchus). To characterize how gain was modulated by surround stimuli, the Michaelis–Menten equation was fitted to response versus contrast functions obtained under each stimulus condition. The modulation of gain by surround stimuli was modelled best as a divisive reduction in response gain. Response gain varied with the orientation of surround stimuli, but was reduced most when the orientation of a large annular grating beyond the classical receptive field matched the preferred orientation of neurons. The strength of surround suppression did not vary significantly with retinal eccentricity or laminar distribution. In the marmoset, as in macaques (Angelucci et al., 2002a, b), gain control over the sort of distances reported here (up to 10 deg) may be mediated by feedback from extrastriate areas.

Visual Cortex Neurons of Monkeys and Cats: Temporal Dynamics of the Contrast Response Function

2002 ◽  
Vol 88 (2) ◽  
pp. 888-913 ◽  
Author(s):  
Duane G. Albrecht ◽  
Wilson S. Geisler ◽  
Robert A. Frazor ◽  
Alison M. Crane
Keyword(s):  
Visual Cortex ◽  
Response Function ◽  
Temporal Dynamics ◽  
Gain Control ◽  
Temporal Response ◽  
Contrast Response Function ◽  
Visual Cortex Neurons ◽  
Contrast Normalization ◽  
Single Fixation ◽  
Contrast Response

Cortical neurons display two fundamental nonlinear response characteristics: contrast-set gain control (also termed contrast normalization) and response expansion (also termed half-squaring). These nonlinearities could play an important role in forming and maintaining stimulus selectivity during natural viewing, but only if they operate well within the time frame of a single fixation. To analyze the temporal dynamics of these nonlinearities, we measured the responses of individual neurons, recorded from the primary visual cortex of monkeys and cats, as a function of the contrast of transient stationary gratings that were presented for a brief interval (200 ms). We then examined 1) the temporal response profile (i.e., the post stimulus time histogram) as a function of contrast and 2) the contrast response function throughout the course of the temporal response. We found that the shape and complexity of the temporal response profile varies considerably from cell to cell. However, within a given cell, the shape remains relatively invariant as a function of contrast and appears to be simply scaled and shifted. Stated quantitatively, approximately 95% of the variation in the temporal responses as a function of contrast could be accounted for by scaling and shifting the average poststimulus time histogram. Equivalently, we found that the overall shape of the contrast response function (measured every 2 ms) remains relatively invariant from the onset through the entire temporal response. Further, the contrast-set gain control and the response expansion are fully expressed within the first 10 ms after the onset of the response. Stated quantitatively, the same, scaled Naka-Rushton equation (with the same half-saturation contrast and expansive response exponent) provides a good fit to the contrast response function from the first 10 ms through the last 10 ms of the temporal response. Based upon these measurements, it appears as though the two nonlinear properties, contrast-set gain control and response expansion, are present in full strength, virtually instantaneously, at the onset of the response. This observation suggests that response expansion and contrast-set gain control can influence the performance of visual cortex neurons very early in a single fixation, based on the contrast within that fixation. In the discussion, we consider the implications of the results within the context of 1) slower types of contrast gain control, 2) discrimination performance, 3) drifting steady-state measurements, 4) functional models that incorporate response expansion and contrast normalization, and 5) structural models of the biochemical and biophysical neural mechanisms.

scholarly journals V1 receptive field structure contributes to neuronal response latency

2022 ◽  
Author(s):  
Amin Vafaei ◽  
Milad Mohammadi ◽  
Alireza Khadir ◽  
Erfan Zabeh ◽  
Faraz YazdaniBanafsheDaragh ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Response Latency ◽  
Neuronal Response ◽  
Underlying Mechanism ◽  
Geometrical Model ◽  
Fine Tuning ◽  
Neuronal Responses ◽  
Periodic Patterns ◽  
Response Latencies

The timing of neuronal responses is considered to be important for information transferring and communication across individual neurons. However, the sources of variabilities in the timing of neuronal responses are not well understood and sometimes over-interpreted. A systematic variability in the response latencies of the primary visual cortex has been reported in presence of drifting grating stimulus. Whereas the response latencies are systematically dependent on stimulus orientation. To understand the underlying mechanism of these systematic latencies, we recorded the neuronal response of the cat visual cortex, area 17, and simulated the response latency of V1 neurons, with two geometric models. We showed that outputs of these two models significantly predict the response latencies of the electrophysiology recording during orientation tasks. The periodic patterns created in the raster plots were dependent on the relative position of the stimulus rotation center and the receptive-field sub-regions. We argue the position of stimulus is contributing to systematic response latencies, dependent on drifting orientation. Therefore, we provide a toolbox based on our geometrical model for determining the exact location of RF sub-regions. Our result indicates that a major source of neuronal variability is the lack of fine-tuning in the task parameters. Considering the simplicity of the orientation selectivity task, we argue fine-tuning of stimulus properties is crucial for deduction of neural variability in higher-order cortical areas and understanding their neural dynamics.

scholarly journals Dynamics of absolute and relative disparity processing in human visual cortex

2021 ◽  
Author(s):  
Milena Kaestner ◽  
Marissa L Evans ◽  
Yulan D Chen ◽  
Anthony M Norcia
Keyword(s):  
Visual Cortex ◽  
Temporal Dynamics ◽  
Second Harmonic ◽  
Response Component ◽  
Human Visual Cortex ◽  
Temporal Properties ◽  
Random Dot Stereograms ◽  
Occipital Pole ◽  
Higher Visual Areas ◽  
The Relationship

Cortical processing of binocular disparity is believed to begin in V1 where cells are sensitive to absolute disparity, followed by the extraction of relative disparity in higher visual areas. While much is known about the cortical distribution and spatial tuning of disparity-selective neurons, the relationship between their spatial and temporal properties is less well understood. Here, we use steady-state Visual Evoked Potentials and dynamic random dot stereograms to characterize the temporal dynamics of spatial mechanisms in human visual cortex that are primarily sensitive to either absolute or relative disparity. Stereograms alternated between disparate and non-disparate states at 2 Hz. By varying the spatial frequency content of the disparate fields from a planar surface to corrugated ones, we biased responses towards absolute vs. relative disparities. Reliable Components Analysis was used to derive two dominant sources from the 128 channel EEG records. The first component (RC1) was maximal over the occipital pole while the second component (RC2) was maximal over right lateral occipital electrodes. In RC1, first harmonic responses were sustained, tuned for corrugation frequency, and sensitive to the presence of disparity references, consistent with prior psychophysical sensitivity measurements. By contrast, the second harmonic, associated with transient processing, was not spatially tuned and was indifferent to references, consistent with it being generated by an absolute disparity mechanism. In RC2, the sustained response component showed similar tuning and sensitivity to references. However, sensitivity for absolute disparity dropped off, and transient signals were mainly driven by the lowest corrugation frequencies.

Spatiotemporal characteristics of surround suppression in primary visual cortex and lateral geniculate nucleus of the cat

2014 ◽  
Vol 112 (3) ◽  
pp. 603-619 ◽  
Author(s):  
Satoshi Shimegi ◽  
Ayako Ishikawa ◽  
Hiroyuki Kida ◽  
Hiroshi Sakamoto ◽  
Sin-ichiro Hara ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Lateral Geniculate Nucleus ◽  
Primary Visual Cortex ◽  
Neuronal Response ◽  
High Specificity ◽  
Fast Component ◽  
Sinusoidal Grating ◽  
Temporal Properties ◽  
Lateral Geniculate

In the primary visual cortex (V1), a neuronal response to stimulation of the classical receptive field (CRF) is predominantly suppressed by a stimulus presented outside the CRF (extraclassical receptive field, ECRF), a phenomenon referred to as ECRF suppression. To elucidate the neuronal mechanisms and origin of ECRF suppression in V1 of anesthetized cats, we examined the temporal properties of the spatial extent and orientation specificity of ECRF suppression in V1 and the lateral geniculate nucleus (LGN), using stationary-flashed sinusoidal grating. In V1, we found three components of ECRF suppression: 1) local and fast, 2) global and fast, and 3) global and late. The local and fast component, which resulted from within 2° of the boundary of the CRF, started no more than 10 ms after the onset of the CRF response and exhibited low specificity for the orientation of the ECRF stimulus. These spatiotemporal properties corresponded to those of geniculate ECRF suppression, suggesting that the local and fast component of V1 is inherited from the LGN. In contrast, the two global components showed rather large spatial extents ∼5° from the CRF boundary and high specificity for orientation, suggesting that their possible origin is the cortex, not the LGN. Correspondingly, the local component was observed in all neurons of the thalamocortical recipient layer, while the global component was biased toward other layers. Therefore, we conclude that both subcortical and cortical mechanisms with different spatiotemporal properties are involved in ECRF suppression.

Motion selectivity and the contrast-response function of simple cells in the visual cortex

1991 ◽  
Vol 7 (6) ◽  
pp. 531-546 ◽  
Author(s):  
Duane G. Albrecht ◽  
Wilson S. Geisler
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Response Function ◽  
Gain Control ◽  
Direction Selectivity ◽  
Metabolic Energy ◽  
Simple Cells ◽  
Contrast Response Function ◽  
Spatiotemporal Receptive Field ◽  
Contrast Response

AbstractThe responses of simple cells were recorded from the visual cortex of cats, as a function of the position and contrast of counterphase and drifting grating patterns, to assess whether direction selectivity can be accounted for on the basis of linear summation. The expected responses to a counterphase grating, given a strictly linear model, would be the sum of the responses to the two drifting components. The measured responses were not consistent with the linear prediction. For example, nearly all cells showed two positions where the responses approached zero (i.e. two “null phase positions”); this was true, even for the most direction selective cells. However, the measured responses were consistent with the hypothesis that direction selectivity is a consequence of the linear spatiotemporal receptive-field structure, coupled with the nonlinearities revealed by the contrast-response function: contrast gain control, halfwave rectification, and expansive exponent. When arranged in a particular sequence, each of these linear and nonlinear mechanisms performs a useful function in a general model of simple cells. The linear spatiotemporal receptive field initiates stimulus selectivity (for direction, orientation, spatial frequency, etc.). The expansive response exponent enhances selectivity. The contrast-set gain control maintains selectivity (over a wide range of contrasts, in spite of the limited dynamic response range and steep slope of the contrast-response function). Rectification conserves metabolic energy.

Contrast sensitivity of MT receptive field centers and surrounds

2011 ◽  
Vol 106 (4) ◽  
pp. 1888-1900 ◽  
Author(s):  
James M. G. Tsui ◽  
Christopher C. Pack
Keyword(s):  
Visual Cortex ◽  
Contrast Sensitivity ◽  
Receptive Fields ◽  
Extrastriate Cortex ◽  
Model Parameters ◽  
Surround Suppression ◽  
Neuronal Responses ◽  
Stimulus Contrast ◽  
Area Mt ◽  
Complex Center

Neurons throughout the visual system have receptive fields with both excitatory and suppressive components. The latter are responsible for a phenomenon known as surround suppression, in which responses decrease as a stimulus is extended beyond a certain size. Previous work has shown that surround suppression in the primary visual cortex depends strongly on stimulus contrast. Such complex center-surround interactions are thought to relate to a variety of functions, although little is known about how they affect responses in the extrastriate visual cortex. We have therefore examined the interaction of center and surround in the middle temporal (MT) area of the macaque ( Macaca mulatta) extrastriate cortex by recording neuronal responses to stimuli of different sizes and contrasts. Our findings indicate that surround suppression in MT is highly contrast dependent, with the strongest suppression emerging unexpectedly at intermediate stimulus contrasts. These results can be explained by a simple model that takes into account the nonlinear contrast sensitivity of the neurons that provide input to MT. The model also provides a qualitative link to previous reports of a topographic organization of area MT based on clusters of neurons with differing surround suppression strength. We show that this organization can be detected in the gamma-band local field potentials (LFPs) and that the model parameters can predict the contrast sensitivity of these LFP responses. Overall our results show that surround suppression in area MT is far more common than previously suspected, highlighting the potential functional importance of the accumulation of nonlinearities along the dorsal visual pathway.

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