ArticleJournal of neurophysiology2017
Dynamic population codes of multiplexed stimulus features in primate area MT.
Article in Journal of neurophysiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Magnetoencephalography contrast adaptation reflects perceptual adaptation.Journal of vision · 2022Article
- Neural mechanism of priming in visual search.Attention, perception & psychophysics · 2021Review
- Stimulus Feature-Specific Information Flow Along the Columnar Cortical Microcircuit Revealed by Multivariate Laminar Spiking Analysis.Frontiers in systems neuroscience · 2020Article
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Authors and funding
3 authors.
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Abstract
The middle-temporal area (MT) of primate visual cortex is critical in the analysis of visual motion. Single-unit studies suggest that the response dynamics of neurons within area MT depend on stimulus features, but how these dynamics emerge at the population level, and how feature representations interact, is not clear. Here, we used multivariate classification analysis to study how stimulus features are represented in the spiking activity of populations of neurons in area MT of marmoset monkey. Using representational similarity analysis we distinguished the emerging representations of moving grating and dot field stimuli. We show that representations of stimulus orientation, spatial frequency, and speed are evident near the onset of the population response, while the representation of stimulus direction is slower to emerge and sustained throughout the stimulus-evoked response. We further found a spatiotemporal asymmetry in the emergence of direction representations. Representations for high spatial frequencies and low temporal frequencies are initially orientation dependent, while those for high temporal frequencies and low spatial frequencies are more sensitive to motion direction. Our analyses reveal a complex interplay of feature representations in area MT population response that may explain the stimulus-dependent dynamics of motion vision.
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