https://www.kyoto-u.ac.jp/ja/access/campus/yoshida/map6r_i.html

日時: 2020 年 1 月 7 日 (火) 12:15-13:30 場所: 京都大学吉田キャンパス医学部構内先端科学研究棟 5 階 501 号室 https://www.kyoto-u.ac.jp/ja/access/campus/yoshida/map6r_i.html 参加費や事前登録は不要です． セミナー中に軽食 (サンドイッチ) を提供します．飲み物はお持ちください．

Date: 2020-01-07 Tue 12:15-13:30 Place: Rm. 501, Science Frontier Laboratory, Kyoto University Faculty of Medicine Campus https://www.kyoto-u.ac.jp/en/access/medicine-campus-map.html The talk is in English. Free, no registration required. We will provide sandwiches for lunch.

The transfer and transformation of cognitive information in functional brain networks

Takuya Ito (Rutgers University)

Abstract: 

The brain processes information in a distributed manner to perform cognitive functions. Previous work investigating cognitive processing in the brain has typically focused on mapping localized cognitive functions to specific brain regions. In this talk, I will provide empirical evidence for the transfer and transformation of cognitive information between functional brain areas and networks using task fMRI data collected in humans. First, I will show how cognitive representations (identified by decoding neural activation patterns) are transferred to other brain regions using empirically estimated inter-region mappings. Second, I will demonstrate how distinct cognitive representations in distinct spatial locations integrate to generate qualitatively new information (information transformation), such as stimulus to motor response transformations from sensory to motor cortices. This would provide an empirically validated computational mapping to describe how information is manipulated and transformed across brain areas using task fMRI. These two previous approaches required the estimation of ‘functional connectivity’ weights between pairs of regions. In the last part of this talk, I will explore the mechanistic basis of these functional connectivity weights. I will provide converging results of correlation-based approaches to fMRI-based functional connectivity and electrophysiology-based noise correlation estimation (from multi-unit recordings from non-human primates), and then provide a dynamical systems framework to ground these results. Together, these results offer an integrative perspective of the transfer and transformation of cognitive information across large-scale functional brain networks.

References: Ito, Takuya, Luke Hearne, Ravi Mill, Carrisa Cocuzza, and Michael W. Cole. “Discovering the Computational Relevance of Brain Network Organization.” Trends in Cognitive Sciences, November 11, 2019. https://doi.org/10.1016/j.tics.2019.10.005.Ito, Takuya, Kaustubh R. Kulkarni, Douglas H. Schultz, Ravi D. Mill, Richard H. Chen, Levi I. Solomyak, and Michael W. Cole. “Cognitive Task Information Is Transferred between Brain Regions via Resting-State Network Topology.” Nature Communications, January 2017. https://doi.org/10.1038/s41467-017-01000-w.Ito, Takuya, Scott L. Brincat, Markus Siegel, Ravi D. Mill, Biyu J. He, Earl K. Miller, Horacio G. Rotstein, and Michael W. Cole. “Task-Evoked Activity Quenches Neural Correlations and Variability across Cortical Areas.” BioRxiv, October 24, 2019, 560730. https://doi.org/10.1101/560730.