Ambiguity and nonidentifiability in the statistical analysis of neural codes
Abstract
Among the most important open questions in neurophysiology are those regarding the nature of the code that neurons use to transmit information. Experimental approaches to such questions are challenging because the spike outputs of a neuronal subpopulation are influenced by a vast array of factors, ranging from microscopic to macroscopic scales, but only a small fraction of these is measured. Inevitably, there is variability from trial to trial in the recorded data. We show that a prominent conceptual approach to modeling spike-train variability can be ill-posed, confusing the interpretation of results bearing on neural codes. We argue for more careful definitions and more explicit statements of physiological assumptions.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- May 01, 2015
- Source ID
- 10.1073/pnas.1506400112
Entities
People
- Asohan Amarasingham
- Matthew T. Harrison
- Stuart Geman
Organizations
- Brown University
- CUNY Graduate School and University Center
- City College of New York
- National Institute of Mental Health
- National Institutes of Health
- National Science Foundation
- Office of Naval Research