publication . Article . Other literature type . Preprint . 2013

Maximally Informative “Stimulus Energies” in the Analysis of Neural Responses to Natural Signals

Kanaka Rajan; William Bialek;
Open Access English
  • Published: 08 Nov 2013 Journal: PLoS ONE, volume 8, issue 11 (eissn: 1932-6203, Copyright policy)
  • Publisher: Public Library of Science
The concept of feature selectivity in sensory signal processing can be formalized as dimensionality reduction: in a stimulus space of very high dimensions, neurons respond only to variations within some smaller, relevant subspace. But if neural responses exhibit invariances, then the relevant subspace typically cannot be reached by a Euclidean projection of the original stimulus. We argue that, in several cases, we can make progress by appealing to the simplest nonlinear construction, identifying the relevant variables as quadratic forms, or "stimulus energies." Natural examples include non-phase-locked cells in the auditory system, complex cells in visual corte...
arXiv: Quantitative Biology::Neurons and Cognition
free text keywords: Research Article, Medicine, R, Science, Q, Quantitative Biology - Neurons and Cognition, Condensed Matter - Disordered Systems and Neural Networks, Physics - Biological Physics, General Biochemistry, Genetics and Molecular Biology, General Agricultural and Biological Sciences, General Medicine, Bioinformatics, Mutual information, Maximally informative dimensions, Sensory system, Physics, Artificial intelligence, business.industry, business, Kernel (linear algebra), Stimulus (physiology), Neuronal tuning, Subspace topology, Dimensionality reduction, Pattern recognition
Related Organizations
Funded by
NSF| Emerging Frontiers of Science of Information
  • Funder: National Science Foundation (NSF)
  • Project Code: 0939370
  • Funding stream: Directorate for Computer & Information Science & Engineering | Division of Computing and Communication Foundations
NSF| The Theoretical Physics of Biological Systems
  • Funder: National Science Foundation (NSF)
  • Project Code: 0957573
  • Funding stream: Directorate for Mathematical & Physical Sciences | Division of Physics
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publication . Article . Other literature type . Preprint . 2013

Maximally Informative “Stimulus Energies” in the Analysis of Neural Responses to Natural Signals

Kanaka Rajan; William Bialek;