Title |
Functional two-way analysis of variance and bootstrap methods for neural synchrony analysis
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Published in |
BMC Neuroscience, August 2014
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DOI | 10.1186/1471-2202-15-96 |
Pubmed ID | |
Authors |
Aldana M González Montoro, Ricardo Cao, Nelson Espinosa, Javier Cudeiro, Jorge Mariño |
Abstract |
Pairwise association between neurons is a key feature in understanding neural coding. Statistical neuroscience provides tools to estimate and assess these associations. In the mammalian brain, activating ascending pathways arise from neuronal nuclei located at the brainstem and at the basal forebrain that regulate the transition between sleep and awake neuronal firing modes in extensive regions of the cerebral cortex, including the primary visual cortex, where neurons are known to be selective for the orientation of a given stimulus. In this paper, the estimation of neural synchrony as a function of time is studied in data obtained from anesthetized cats. A functional data analysis of variance model is proposed. Bootstrap statistical tests are introduced in this context; they are useful tools for the study of differences in synchrony strength regarding 1) transition between different states (anesthesia and awake), and 2) affinity given by orientation selectivity. |
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