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タイトル: | Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software |
著者: | Sato, Wataru https://orcid.org/0000-0002-5335-1272 (unconfirmed) Kochiyama, Takanori Uono, Shota Usui, Naotaka Kondo, Akihiko Matsuda, Kazumi Usui, Keiko Toichi, Motomi Inoue, Yushi |
著者名の別形: | 佐藤, 弥 魚野, 翔太 |
発行日: | 30-Oct-2018 |
出版者: | MyJove Corporation |
誌名: | Journal of Visualized Experiments |
号: | 140 |
論文番号: | e58187 |
抄録: | 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. |
著作権等: | 発行元の許可を得て掲載しています。 |
URI: | http://hdl.handle.net/2433/236372 |
DOI(出版社版): | 10.3791/58187 |
PubMed ID: | 30451234 |
出現コレクション: | 学術雑誌掲載論文等 |
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