Journal
JOURNAL OF NEUROSCIENCE METHODS
Volume 162, Issue 1-2, Pages 320-332Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2006.12.008
Keywords
temporal pattern formation; multiunit recording; hippocampal CA1; long term potentiation; asymmetric correlation
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Funding
- NIBIB NIH HHS [1R21 EB 003583, R21 EB003583, R21 EB008163-01A1, R21 EB008163, R21 EB003583-02] Funding Source: Medline
- NIGMS NIH HHS [T32 GM008270, 2T32 GM 08270-17] Funding Source: Medline
- NIMH NIH HHS [R01 MH060670, R01 MH076280, MH 076280, MH 060670, R01 MH060670-06A1] Funding Source: Medline
- NINDS NIH HHS [T32 NS 07222, T32 NS007222] Funding Source: Medline
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We propose a novel measure to detect temporal ordering in the activity of individual neurons in a local network, which is thought to be a hallmark of activity-dependent synaptic modifications during learning. The measure, called causal entropy, is based on the time-adaptive detection of asymmetries in the relative temporal patterning between neuronal pairs. We characterize properties of the measure on both simulated data and experimental multiunit recordings of hippocampal neurons from the awake, behaving rat, and show that the metric can more readily detect those asymmetries than standard cross correlation-based techniques, especially since the temporal sensitivity of causal entropy can detect such changes rapidly and dynamically. (C) 2007 Elsevier B.V. All rights reserved.
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