2006
NeurIPS
NeurIPS 2006
Temporal dynamics of information content carried by neurons in the primary visual cortex
Abstract
We use multi-electrode recordings from cat primary visual cortex and investigate whether a simple linear classifier can extract information about the presented stim(cid:173) uli. We find that information is extractable and that it even lasts for several hun(cid:173) dred milliseconds after the stimulus has been removed. In a fast sequence of stim(cid:173) ulus presentation, information about both new and old stimuli is present simul(cid:173) taneously and nonlinear relations between these stimuli can be extracted. These results suggest nonlinear properties of cortical representations. The important im(cid:173) plications of these properties for the nonlinear brain theory are discussed.
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Conference Pioneer
- NeurIPS 2006
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Interdisciplinary Bridge
- Artificial Intelligence and Computer Vision and Interdisciplinary
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Trend Setter
- Deep Learning
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Keyword Pioneer
- visual cortex
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Hot Topic Early Bird
- information extraction
Authors
Topics
Machine Learning > Core Methods > Classification
Machine Learning > Optimization & Theory > Stochastic Processes
Computer Vision > Analysis > Scene Understanding
Interdisciplinary > Cognitive Science > Cognitive Modeling
Interdisciplinary > Cognitive Science > Perception
Machine Learning > Learning Types > Deep Learning
Computer Vision > Analysis > Motion Analysis
Interdisciplinary > Science > Neuroscience
Keywords
information theory
neural decoding
neural coding
visual cortex
temporal dynamics
information extraction
primary visual cortex
nonlinear properties
cortical representations
stimulus processing
linear classifier
neural information extraction
multi-electrode recording
nonlinear cortical representation
neural information