Causal entropies—A measure for determining changes in the temporal organization of neural systems
Autor: | Brett T. Riley, Rhonda Dzakpasu, Jonathan D. Reasor, Victoria Booth, Jack Waddell, Michal Zochowski, Gina R. Poe |
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Rok vydání: | 2007 |
Předmět: |
Male
Neurons Cross-correlation business.industry Acclimatization Pyramidal Cells General Neuroscience Maze learning Pattern recognition Hippocampal formation Hippocampus Rats Inbred F344 Article Rats Simulated data Animals Neural system Artificial intelligence Temporal organization Maze Learning business Neuroscience Probability Mathematics |
Zdroj: | Journal of Neuroscience Methods. 162:320-332 |
ISSN: | 0165-0270 |
Popis: | 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. |
Databáze: | OpenAIRE |
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