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Title: Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software
Authors: Sato, Wataru  KAKEN_id  orcid (unconfirmed)
Kochiyama, Takanori
Uono, Shota
Usui, Naotaka
Kondo, Akihiko
Matsuda, Kazumi
Usui, Keiko
Toichi, Motomi  kyouindb  KAKEN_id
Inoue, Yushi
Author's alias: 佐藤, 弥
魚野, 翔太
Issue Date: 30-Oct-2018
Publisher: MyJove Corporation
Journal title: Journal of Visualized Experiments
Issue: 140
Thesis number: e58187
Abstract: Measuring neural activity and connectivity associated with cognitive functions at high spatial and temporal resolutions is an important goal in cognitive neuroscience. Intracranial electroencephalography (EEG) can directly record electrical neural activity and has the unique potential to accomplish this goal. Traditionally, averaging analysis has been applied to analyze intracranial EEG data; however, several new techniques are available for depicting neural activity and intra- and inter-regional connectivity. Here, we introduce two analytical protocols we recently applied to analyze intracranial EEG data using the Statistical Parametric Mapping (SPM) software: time-frequency SPM analysis for neural activity and dynamic causal modeling of induced responses for intra- and inter-regional connectivity. We report our analysis of intracranial EEG data during the observation of faces as representative results. The results revealed that the inferior occipital gyrus (IOG) showed gamma-band activity at very early stages (110 ms) in response to faces, and both the IOG and amygdala showed rapid intra- and inter-regional connectivity using various types of oscillations. These analytical protocols have the potential to identify the neural mechanisms underlying cognitive functions with high spatial and temporal profiles.
Rights: 発行元の許可を得て掲載しています。
DOI(Published Version): 10.3791/58187
PubMed ID: 30451234
Appears in Collections:Journal Articles

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