Mapping multiple features in the population response of visual cortex

Voluntary and stimulus-driven shifts of attention can modulate the representation of behaviorally relevant stimuli in early areas of visual cortex. In turn, attended items are processed faster and more accurately, facilitating the selection of appropriate behavioral responses. Information processing is also strongly influenced by past experience and recent studies indicate that the learned value of a stimulus can influence relatively late stages of decision making such as the process of selecting a motor response. However, the learned value of a stimulus can also influence the magnitude of cortical responses in early sensory areas such as V1 and S1. These early effects of stimulus value are presumed to improve the quality of sensory representations; however, the nature of these modulations is not clear. They could reflect nonspecific changes in response amplitude associated with changes in general arousal or they could reflect a bias in population responses so that high-value features are represented more robustly. To examine this issue, subjects performed a two-alternative forced choice paradigm with a variable-interval payoff schedule to dynamically manipulate the relative value of two stimuli defined by their orientation (one was rotated clockwise from vertical, the other counterclockwise). Activation levels in visual cortex were monitored using functional MRI and feature-selective voxel tuning functions while subjects performed the behavioral task. The results suggest that value not only modulates the relative amplitude of responses in early areas of human visual cortex, but also sharpens the response profile across the populations of feature-selective neurons that encode the critical stimulus feature (orientation). Moreover, changes in space- or feature-based attention cannot easily explain the results because representations of both the selected and the unselected stimuli underwent a similar feature-selective modulation. This sharpening in the population response profile could theoretically improve the probability of correctly discriminating high-value stimuli from low-value alternatives.

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Orientation Coding by Population of Neurons in Rats' Primary Visual Cortex

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.427-429.2089 ◽

2013 ◽

Vol 427-429 ◽

pp. 2089-2093

Author(s):

Li Shi ◽

Qi Ming Ye ◽

Xiao Ke Niu

Keyword(s):

Visual Cortex ◽

Single Channel ◽

Lasso Regression ◽

Electrode Arrays ◽

Population Response ◽

Effective Response ◽

Specific Stimulus ◽

Channel Response ◽

Stimulus Response ◽

Single Feature

Research on Primate visual cortex (V1 area) neurons orientation coding mechanism is the base of revealing the whole visual cortex information processing mechanism. Firstly, this paper adopted different orientation grating to stimulate visually on rats. Meanwhile, gather response signals of population neurons from V1 area using multi-electrode arrays. Then, screen effective response channels according to the orientation selection of different neurons in different channels. Besides, extract Spike average fire rate and LFPγ band power feature in every effective channel signals within specific stimulus response time to construct population response joint features. Finally, taking Lasso regression model as coding model, use joint features to differentiate grating orientation, in order to research on V1 areas population neurons orientation coding. The consequences indicate that the results of population response joint features coding for six different orientation are superior to the results of any single feature of population response coding, and remarkably better than the results of single channel response feature coding.

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Distortions in perceived direction of motion predicted by population response dynamics in primary visual cortex

Journal of Vision ◽

10.1167/8.17.33 ◽

2010 ◽

Vol 8 (17) ◽

pp. 33-33

Author(s):

W. Wu ◽

P. H. Tiesinga ◽

T. R. Tucker ◽

S. R. Mitroff ◽

D. Fitzpatrick

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Response Dynamics ◽

Population Response

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Divided attention for feature-based selection in visual cortex

10.1101/2020.01.27.922047 ◽

2020 ◽

Author(s):

James C. Moreland ◽

Geoffrey M. Boynton

Keyword(s):

Visual Cortex ◽

Brain Activity ◽

Receptive Fields ◽

Behavioral Study ◽

Multiple Features ◽

Bold Responses ◽

Feature Based ◽

Left And Right ◽

Divide Attention ◽

Model Approach

AbstractFeature-based attention can select relevant features such as colors or directions of motion from the visual field irrespective of the spatial position. In visual cortex not only do we see feature-specific attention affecting responses in neurons with receptive fields at an attended location, but that effect also spreads to neurons with receptive fields beyond the spatially relevant location. When only one feature is task relevant, the spread of activity across space can act to facilitate perception of behaviorally relevant stimuli. However, when multiple features are relevant, what is the effect on behavior and brain activity? We tested this question by having observers divide attention between two patches (left and right of fixation) of moving dot stimuli, each containing overlapping upward and downward motion fields. In one condition, subjects performed a task on motion fields moving in the same direction in both patches. In another condition attention was divided between opposite directions of motion. Replicating a previous behavioral study, we found that observers showed better performance when dividing attention to the same directions of motion than opposing directions of motion. We analyzed the BOLD responses while observers performed this task using an inverted encoding model approach that provides estimates of responses to each of the four component dot fields. We found larger responses to the attended components, replicating previous studies of spatial and feature-based attention. However, these effects were much larger when attention was divided to between the same directions of motion than to opposing directions. Our fMRI results in area hMT+ predict our behavioral results by extending the normalization model of attention to include a global feature-based attention component in that leads to suppressed responses to attended stimulus components when attention is directed to opposing directions of motion.

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