Natural stimuli evoke dynamic sequences of states in sensory cortical ensembles

doi:10.1073/pnas.0705546104

Natural stimuli evoke dynamic sequences of states in sensory cortical ensembles

^‡Psychology Department,
*Biology Department,
^†Volen National Center for Complex Systems, Volen 208/MS 013, Brandeis University, 415 South Street, Waltham, MA 02454

Edited by Charles F. Stevens, The Salk Institute for Biological Studies, La Jolla, CA, and approved September 26, 2007 (received for review June 13, 2007)

Abstract

Although temporal coding is a frequent topic of neurophysiology research, trial-to-trial variability in temporal codes is typically dismissed as noise and thought to play no role in sensory function. Here, we show that much of this supposed “noise” faithfully reflects stimulus-related processes carried out in coherent neural networks. Cortical neurons responded to sensory stimuli by progressing through sequences of states, identifiable only in examinations of simultaneously recorded ensembles. The specific times at which ensembles transitioned from state to state varied from trial to trial, but the state sequences were reliable and stimulus-specific. Thus, the characterization of ensemble responses in terms of state sequences captured facets of sensory processing that are missing from, and obscured in, other analyses. This work provides evidence that sensory neurons act as parts of a systems-level dynamic process, the nature of which can best be appreciated through observation of distributed ensembles.

Footnotes

^§To whom correspondence should be addressed. E-mail: dbkatz{at}brandeis.edu
Author contributions: L.M.J. and A.F. contributed equally to this work; L.M.J., A.F., and D.B.K. designed research; L.M.J. and A.F. performed research; L.M.J., A.F., B.F.S., and P.M. analyzed data; and L.M.J., A.F., B.F.S., P.M., and D.B.K. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/cgi/content/full/0705546104/DC1.
Abbreviations:

GC,

gustatory cortex;

HMM,

hidden Markov model;

PCA,

principal components analysis;

PSTH,

peristimulus time histogram.
Freely available online through the PNAS open access option.