Spatiotemporal frequency tuning of BOLD and gamma band MEG responses compared in primary visual cortex

NeuroImage ◽  
2008 ◽  
Vol 40 (4) ◽  
pp. 1552-1560 ◽  
Author(s):  
Suresh D. Muthukumaraswamy ◽  
Krish D. Singh
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Frequency Tuning ◽  
Gamma Band

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 Thalamic inputs determine functionally distinct gamma bands in mouse primary visual cortex

2020 ◽  
Author(s):  
Nicolò Meneghetti ◽  
Chiara Cerri ◽  
Elena Tantillo ◽  
Eleonora Vannini ◽  
Matteo Caleo ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Visual Information ◽  
Narrow Band ◽  
Broad Band ◽  
Gamma Band ◽  
Neuron Network ◽  
Sensory Stimuli ◽  
Thalamic Input ◽  
Visual Contrast

AbstractGamma band is known to be involved in the encoding of visual features in the primary visual cortex (V1). Recent results in rodents V1 highlighted the presence, within a broad gamma band (BB) increasing with contrast, of a narrow gamma band (NB) peaking at ∼60 Hz suppressed by contrast and enhanced by luminance. However, the processing of visual information by the two channels still lacks a proper characterization. Here, by combining experimental analysis and modeling, we prove that the two bands are sensitive to specific thalamic inputs associated with complementary contrast ranges. We recorded local field potentials from V1 of awake mice during the presentation of gratings and observed that NB power progressively decreased from low to intermediate levels of contrast. Conversely, BB power was insensitive to low levels of contrast but it progressively increased going from intermediate to high levels of contrast. Moreover, BB response was stronger immediately after contrast reversal, while the opposite held for NB. All the aforementioned dynamics were accurately reproduced by a recurrent excitatory-inhibitory leaky integrate-and-fire network, mimicking layer IV of mouse V1, provided that the sustained and periodic component of the thalamic input were modulated over complementary contrast ranges. These results shed new light on the origin and function of the two V1 gamma bands. In addition, here we propose a simple and effective model of response to visual contrast that might help in reconstructing network dysfunction underlying pathological alterations of visual information processing.Significance StatementGamma band is a ubiquitous hallmark of cortical processing of sensory stimuli. Experimental evidence shows that in the mouse visual cortex two types of gamma activity are differentially modulated by contrast: a narrow band (NB), that seems to be rodent specific, and a standard broad band (BB), observed also in other animal models.We found that narrow band correlates and broad band anticorrelates with visual contrast in two complementary contrast ranges (low and high respectively). Moreover, BB displayed an earlier response than NB. A thalamocortical spiking neuron network model reproduced the aforementioned results, suggesting they might be due to the presence of two complementary but distinct components of the thalamic input into visual cortical circuitry.

scholarly journals Functional decoupling of BOLD and gamma-band amplitudes in human primary visual cortex

2009 ◽  
Vol 30 (7) ◽  
pp. 2000-2007 ◽  
Author(s):  
Suresh D. Muthukumaraswamy ◽  
Krish D. Singh
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Gamma Band

scholarly journals Stochastic Generation of Gamma-Band Activity in Primary Visual Cortex of Awake and Anesthetized Monkeys

2012 ◽  
Vol 32 (40) ◽  
pp. 13873-13880a ◽  
Author(s):  
D. Xing ◽  
Y. Shen ◽  
S. Burns ◽  
C.-I. Yeh ◽  
R. Shapley ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Gamma Band ◽  
Stochastic Generation ◽  
Gamma Band Activity ◽  
Band Activity

Cross-Orientation Suppression: Monoptic and Dichoptic Mechanisms Are Different

2005 ◽  
Vol 94 (2) ◽  
pp. 1645-1650 ◽  
Author(s):  
Baowang Li ◽  
Matthew R. Peterson ◽  
Jeffrey K. Thompson ◽  
Thang Duong ◽  
Ralph D. Freeman
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Frequency Tuning ◽  
Temporal Frequency ◽  
Intracortical Inhibition ◽  
A Cell

The response of a cell in the primary visual cortex to an optimally oriented grating is suppressed by a superimposed orthogonal grating. This cross-orientation suppression (COS) is exhibited when the orthogonal and optimal stimuli are presented to the same eye (monoptically) or to different eyes (dichoptically). A recent study suggested that monoptic COS arises from subcortical processes; however, the mechanisms underlying dichoptic COS were not addressed. We have compared the temporal frequency tuning and stimulus adaptation properties of monoptic and dichoptic COS. We found that dichoptic COS is best elicited with lower temporal frequencies and is substantially reduced after prolonged adaptation to a mask grating. In contrast, monoptic COS is more pronounced with mask gratings at much higher temporal frequencies and is less prone to stimulus adaptation. These results suggest that monoptic COS is mediated by subcortical mechanisms, whereas intracortical inhibition is the mechanism for dichoptic COS.

scholarly journals Influence of Contrast on Orientation and Temporal Frequency Tuning in Ferret Primary Visual Cortex

2004 ◽  
Vol 91 (6) ◽  
pp. 2797-2808 ◽  
Author(s):  
Henry J. Alitto ◽  
W. Martin Usrey
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Cortical Neurons ◽  
Frequency Tuning ◽  
Temporal Frequency ◽  
Orientation Tuning ◽  
Visual Response ◽  
Stimulus Contrast ◽  
Tuning Curves ◽  
Simple And Complex Cells

Neurons in primary visual cortex are highly sensitive to the contrast, orientation, and temporal frequency of a visual stimulus. These three stimulus properties can be varied independently of one another, raising the question of how they interact to influence neuronal responses. We recorded from individual neurons in ferret primary visual cortex to determine the influence of stimulus contrast on orientation tuning, temporal-frequency tuning, and latency to visual response. Results show that orientation-tuning bandwidth is not affected by contrast level. Thus neurons in ferret visual cortex display contrast-invariant orientation tuning. Stimulus contrast does, however, influence the structure of orientation-tuning curves as measures of circular variance vary inversely with contrast for both simple and complex cells. This change in circular variance depends, in part, on a contrast-dependent change in the ratio of null to preferred orientation responses. Stimulus contrast also has an influence on the temporal-frequency tuning of cortical neurons. Both simple and complex cells display a contrast-dependent rightward shift in their temporal frequency-tuning curves that results in an increase in the highest temporal frequency needed to produce a half-maximum response (TF50). Results show that the degree of the contrast-dependent increase in TF50 is similar for cortical neurons and neurons in the lateral geniculate nucleus (LGN) and indicate that subcortical mechanisms likely play a major role in establishing the degree of effect displayed by downstream neurons. Finally, results show that LGN and cortical neurons experience a contrast-dependent phase advance in their visual response. This phase advance is most pronounced for cortical neurons indicating a role for both subcortical and cortical mechanisms.

scholarly journals Image discontinuity changes LFP gamma-band activity in primary visual cortex V1

2010 ◽  
Vol 9 (8) ◽  
pp. 753-753
Author(s):  
D. Xing ◽  
C.-I. Yeh ◽  
P. Williams ◽  
A. Henrie ◽  
R. Shapley
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Gamma Band ◽  
Gamma Band Activity ◽  
Band Activity

scholarly journals Gamma-Band Correlations in Primary Visual Cortex

2018 ◽  
Author(s):  
Xiaochen Morning Liu ◽  
Paula Sanz-Leon ◽  
P. A. Robinson
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Time Lag ◽  
Spatial Separation ◽  
Gamma Band ◽  
Two Dimensional ◽  
Neural Field Theory ◽  
Cross Correlations ◽  
Correlation Properties ◽  
Zero Time

Neural field theory is used to quantitatively analyze the two-dimensional spatiotemporal correlation properties of gamma-band (30 - 70 Hz) oscillations evoked by stimuli arriving at the primary visual cortex (V1), and modulated by patchy connectivities that depend on orientation preference (OP). Correlation functions are derived analytically under different stimulus and measurement conditions. The predictions reproduce a range of published experimental results, including the existence of two-point oscillatory temporal cross-correlations with zero time-lag between neurons with similar OP, the influence of spatial separation of neurons on the strength of the correlations, and the effects of differing stimulus orientations.

scholarly journals Model-based characterization of the selectivity of neurons in primary visual cortex

2021 ◽  
Author(s):  
Felix Bartsch ◽  
Bruce G Cumming ◽  
Daniel A Butts
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Primary Visual Cortex ◽  
Visual Processing ◽  
Frequency Tuning ◽  
Nonlinear Models ◽  
Field Size ◽  
V1 Neurons ◽  
Model Based ◽  
Spatial Frequencies

To understand the complexity of stimulus selectivity in primary visual cortex (V1), models constructed to match observed responses to complex time-varying stimuli, instead of to explain responses to simple parametric stimuli, are increasingly used. While such models often can more accurately reflect the computations performed by V1 neurons in more natural visual environments, they do not by themselves provide insight into established measures of V1 neural selectivity such as receptive field size, spatial frequency tuning and phase invariance. Here, we suggest a series of analyses that can be directly applied to encoding models to link complex encoding models to more interpretable aspects of stimulus selectivity, applied to nonlinear models of V1 neurons recorded in awake macaque in response to random bar stimuli. In linking model properties to more classical measurements, we demonstrate several novel aspects of V1 selectivity not available to simpler experimental measurements. For example, we find that individual spatiotemporal elements of the V1 models often have a smaller spatial scale than the overall neuron sensitivity, and that this results in non-trivial tuning to spatial frequencies. Additionally, our proposed measures of nonlinear integration suggest that more classical classifications of V1 neurons into simple versus complex cells are spatial-frequency dependent. In total, rather than obfuscate classical characterizations of V1 neurons, model-based characterizations offer a means to more fully understand their selectivity, and provide a means to link their classical tuning properties to their roles in more complex, natural, visual processing.

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