Journal
TRENDS IN COGNITIVE SCIENCES
Volume 13, Issue 2, Pages 55-64Publisher
ELSEVIER SCIENCE LONDON
DOI: 10.1016/j.tics.2008.11.005
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Funding
- NICHD NIH HHS [T32 HD007151] Funding Source: Medline
- NIMH NIH HHS [R01 MH080318-01A2, MH080318, R56 MH080318, R01 MH080318-02, R01 MH080318] Funding Source: Medline
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Neural activity in the mammalian CNS is determined by both observable processes, such as sensory stimuli or motor output, and covert, internal cognitive processes that cannot be directly observed. We propose methods to identify these cognitive processes by examining the covert structure within the apparent 'noise' in spike trains. Contemporary analyses of neural codes include encoding (tuning curves derived from spike trains and behavioral, sensory or motor variables), decoding (reconstructing behavioral, sensory or motor variables from spike trains and hypothesized tuning curves) and generative models (predicting the spike trains from hypothesized encoding models and decoded variables). We review examples of each of these processes in hippocampal activity, and propose a general methodology to examine cognitive processes via the identification of dynamic changes in covert variables.
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