期刊
NEURAL COMPUTATION
卷 23, 期 9, 页码 2209-2241出版社
MIT PRESS
DOI: 10.1162/NECO_a_00169
关键词
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资金
- National Science Foundation [IIS-0643995]
- Burroughs Wellcome Fund
- Direct For Mathematical & Physical Scien
- Division Of Mathematical Sciences [1042134] Funding Source: National Science Foundation
The coherence between neural spike trains and local-field potential recordings, called spike-field coherence, is of key importance in many neuroscience studies. In this work, aside from questions of estimator performance, we demonstrate that theoretical spike-field coherence for a broad class of spiking models depends on the expected rate of spiking. This rate dependence confounds the phase locking of spike events to field-potential oscillations with overall neuron activity and is demonstrated analytically, for a large class of stochastic models, and in simulation. Finally, the relationship between the spike-field coherence and the intensity field coherence is detailed analytically. This latter quantity is independent of neuron firing rate and, under commonly found conditions, is proportional to the probability that a neuron spikes at a specific phase of field oscillation. Hence, intensity field coherence is a rate-independent measure and a candidate on which to base the appropriate statistical inference of spike field synchrony.
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