Dataset Information

Adaptive surround modulation in cortical area MT.

ABSTRACT: Visual motion perception relies on two opposing operations: integration and segmentation. Integration overcomes motion ambiguity in the visual image by spatial pooling of motion signals, whereas segmentation identifies differences between adjacent moving objects. For visual motion area MT, previous investigations have reported that stimuli in the receptive field surround, which do not elicit a response when presented alone, can nevertheless modulate responses to stimuli in the receptive field center. The directional tuning of this "surround modulation" has been found to be mainly antagonistic and hence consistent with segmentation. Here, we report that surround modulation in area MT can be either antagonistic or integrative depending upon the visual stimulus. Both types of modulation were delayed relative to response onset. Our results suggest that the dominance of antagonistic modulation in previous MT studies was due to stimulus choice and that segmentation and integration are achieved, in part, via adaptive surround modulation.

SUBMITTER: Huang X

PROVIDER: S-EPMC1866303 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Adaptive surround modulation in cortical area MT.

Huang Xin X Albright Thomas D TD Stoner Gene R GR

Neuron 20070301 5

Visual motion perception relies on two opposing operations: integration and segmentation. Integration overcomes motion ambiguity in the visual image by spatial pooling of motion signals, whereas segmentation identifies differences between adjacent moving objects. For visual motion area MT, previous investigations have reported that stimuli in the receptive field surround, which do not elicit a response when presented alone, can nevertheless modulate responses to stimuli in the receptive field ce ...[more]

PMID: 17329214

Similar Datasets

Project description:Segmenting objects from each other and their background is critical for vision. The speed at which objects move provides a salient cue for segmentation. However, how the visual system represents and differentiates multiple speeds is largely unknown. Here we investigated the neural encoding of multiple speeds of overlapping stimuli in the primate visual cortex. We first characterized the perceptual capacity of human and monkey subjects to segment spatially overlapping stimuli moving at different speeds. We then determined how neurons in the motion-sensitive, middle-temporal (MT) cortex of macaque monkeys encode multiple speeds. We made a novel finding that the responses of MT neurons to two speeds of overlapping stimuli showed a robust bias toward the faster speed component when both speeds were slow (≤ 20°/s). The faster-speed bias occurred even when a neuron had a slow preferred speed and responded more strongly to the slower component than the faster component when presented alone. The faster-speed bias emerged very early in neuronal response and was robust over time and to manipulations of motion direction and attention. As the stimulus speed increased, the faster-speed bias changed to response averaging. Our finding can be explained by a modified divisive normalization model, in which the weights for the speed components are proportional to the responses of a population of neurons elicited by the individual speeds. Our results suggest that the neuron population, referred to as the weighting pool, includes neurons that have a broad range of speed preferences. As a result, the response weights for the speed components are determined by the stimulus speeds and invariant to the speed preferences of individual neurons. Our findings help to define the neural encoding rule of multiple stimuli and provide new insight into the underlying neural mechanisms. The faster-speed bias would benefit behavioral tasks such as figure-ground segregation if figural objects tend to move faster than the background in the natural environment.

Dataset Information

Adaptive surround modulation in cortical area MT.

Publications

Adaptive surround modulation in cortical area MT.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets