scholarly journals Shorter latencies for motion trajectories than for flashes in population responses of cat primary visual cortex

2004 ◽  
Vol 556 (3) ◽  
pp. 971-982 ◽  
Author(s):  
Dirk Jancke ◽  
Wolfram Erlhagen ◽  
Gregor Schöner ◽  
Hubert R. Dinse
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Population Responses ◽  
Motion Trajectories

Mapping of Stimulus Energy in Primary Visual Cortex

2005 ◽  
Vol 94 (1) ◽  
pp. 788-798 ◽  
Author(s):  
Valerio Mante ◽  
Matteo Carandini
Keyword(s):  
Visual Cortex ◽  
Optical Imaging ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Imaging Study ◽  
Energy Model ◽  
Related Phenomenon ◽  
Population Responses ◽  
Stimulus Energy ◽  
Length Direction

A recent optical imaging study of primary visual cortex (V1) by Basole, White, and Fitzpatrick demonstrated that maps of preferred orientation depend on the choice of stimuli used to measure them. These authors measured population responses expressed as a function of the optimal orientation of long drifting bars. They then varied bar length, direction, and speed and found that stimuli of a same orientation can elicit different population responses and stimuli with different orientation can elicit similar population responses. We asked whether these results can be explained from known properties of V1 receptive fields. We implemented an “energy model” where a receptive field integrates stimulus energy over a region of three-dimensional frequency space. The population of receptive fields defines a volume of visibility, which covers all orientations and a plausible range of spatial and temporal frequencies. This energy model correctly predicts the population response to bars of different length, direction, and speed and explains the observations made with optical imaging. The model also readily explains a related phenomenon, the appearance of motion streaks for fast-moving dots. We conclude that the energy model can be applied to activation maps of V1 and predicts phenomena that may otherwise appear to be surprising. These results indicate that maps obtained with optical imaging reflect the layout of neurons selective for stimulus energy, not for isolated stimulus features such as orientation, direction, and speed.

scholarly journals Attending Multiple Items Decreases the Selectivity of Population Responses in Human Primary Visual Cortex

2013 ◽  
Vol 33 (22) ◽  
pp. 9273-9282 ◽  
Author(s):  
D. E. Anderson ◽  
E. F. Ester ◽  
J. T. Serences ◽  
E. Awh
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Population Responses

scholarly journals On the Subspace Invariance of Population Responses

2018 ◽  
Author(s):  
Elaine Tring ◽  
Dario L. Ringach
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Power Distribution ◽  
Gain Control ◽  
Population Coding ◽  
Neural Population ◽  
Angular Deviation ◽  
Strong Negative Correlation ◽  
Population Responses ◽  
The Individual

The response of a neural population in cat primary visual cortex to the linear combination of two sinusoidal gratings (a plaid) can be well approximated by a weighted sum of the population responses to the individual gratings – a property we refer to as subspace invariance. We tested subspace invariance in mouse primary visual cortex by measuring the angle between the population response to a plaid and the plane spanned by the population responses to its individual components. We found robust violations of subspace invariance, represented by a median angular deviation of ~55 deg. The cause of this departure is a strong, negative correlation between the mean responses a neuron to the individual gratings and its response to the plaid. We suggest that an early nonlinearity may distort the power distribution of grating and plaid stimuli such that plaids have a prominent power component at ±45 deg off the fundamental orientations. We conclude that subspace invariance does not hold in mouse V1. This finding rules out a large class of possible models of population coding, including vector averaging and gain control.

scholarly journals Effect of Cross-Orientation Normalization on Different Neural Measures in Macaque Primary Visual Cortex

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Aritra Das ◽  
Supratim Ray
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Evoked Potential ◽  
Population Level ◽  
Field Potentials ◽  
Similar Stimulus ◽  
Brain Areas ◽  
Population Responses ◽  
Divisive Normalization ◽  
High Gamma

Abstract Divisive normalization is a canonical mechanism that can explain a variety of sensory phenomena. While normalization models have been used to explain spiking activity in response to different stimulus/behavioral conditions in multiple brain areas, it is unclear whether similar models can also explain modulation in population-level neural measures such as power at various frequencies in local field potentials (LFPs) or steady-state visually evoked potential (SSVEP) that is produced by flickering stimuli and popular in electroencephalogram studies. To address this, we manipulated normalization strength by presenting static as well as flickering orthogonal superimposed gratings (plaids) at varying contrasts to 2 female monkeys while recording multiunit activity (MUA) and LFP from the primary visual cortex and quantified the modulation in MUA, gamma (32–80 Hz), high-gamma (104–248 Hz) power, as well as SSVEP. Even under similar stimulus conditions, normalization strength was different for the 4 measures and increased as: spikes, high-gamma, SSVEP, and gamma. However, these results could be explained using a normalization model that was modified for population responses, by varying the tuned normalization parameter and semisaturation constant. Our results show that different neural measures can reflect the effect of stimulus normalization in different ways, which can be modeled by a simple normalization model.

scholarly journals Similar masking effects of natural backgrounds on detection performances in humans, macaques, and macaque-V1 population responses

2020 ◽  
Author(s):  
Yoon Bai ◽  
Spencer Chen ◽  
Yuzhi Chen ◽  
Wilson S. Geisler ◽  
Eyal Seidemann
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Macaque Monkey ◽  
Quantitative Agreement ◽  
Neural Responses ◽  
Population Responses ◽  
Single Scale ◽  
Neural Computations ◽  
Optimal Decoding ◽  
Population Decoding

AbstractVisual systems evolve to process the stimuli that arise in the organism’s natural environment and hence to fully understand the neural computations in the visual system it is important to measure behavioral and neural responses to natural visual stimuli. Here we measured psychometric and neurometric functions and thresholds in the macaque monkey for detection of a windowed sine-wave target in uniform backgrounds and in natural backgrounds of various contrasts. The neurometric functions and neurometric thresholds were obtained by near-optimal decoding of voltage-sensitive-dye-imaging (VSDI) responses at the retinotopic scale in primary visual cortex (V1). The results were compared with previous human psychophysical measurements made under the same conditions. We found that human and macaque behavioral thresholds followed the generalized Weber’s law as function of contrast, and that both the slopes and the intercepts of the threshold functions match each other up to a single scale factor. We also found that the neurometric thresholds followed the generalized Weber’s law and that the neurometric slopes and intercepts matched the behavioral slopes and intercepts up to a single scale factor. We conclude that human and macaque ability to detect targets in natural backgrounds are affected in the same way by background contrast, that these effects are consistent with population decoding at the retinotopic scale by down-stream circuits, and that the macaque monkey is an appropriate animal model for gaining an understanding of the neural mechanisms in humans for detecting targets in natural backgrounds. Finally, we discuss limitations of the current study and potential next steps.New & NoteworthyWe measured macaque detection performance in natural images and compared their performance to the detection sensitivity of neurophysiological responses recorded in the primary visual cortex (V1), and to the performance of human subjects. We found that (i) human and macaque behavioral performances are in quantitative agreement, (ii) are consistent with near-optimal decoding of V1 population responses.SignificanceNatural selection guarantees that neural computations will be matched to the task-relevant natural stimuli in the organism’s environment, and thus it is crucial to measure behavioral and neural responses to natural stimuli. We measured the ability of macaque monkeys to detect targets in natural images and compared their performance to neurophysiological responses recorded in the macaque’s primary visual cortex (V1), and to the performance of humans under the same conditions. We found that (i) human and macaque behavioral performance are in quantitative agreement, (ii) are consistent with near-optimal population decoding of V1 neural responses, and (iii) that the macaque monkey is an appropriate animal model for gaining understanding of the neural mechanisms in humans for detecting targets in natural backgrounds.

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