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날짜 2024-10-02 12:00 
일시 Oct 2nd(Wed), 4PM 
장소 E6-2, #3441 
연사 YoungJu Jo (Stanford Univ.) 

10월 2일(수) 오후 4시에 Stanford 대학 조영주 박사 (KAIST 물리학과 학부, Stanford 대학 생물학 석사, 응용물리 박사, 현 Stanford 대학 박사후 연구원)를 모시고 세미나를 진행하고자 합니다.

관심있는 분들의 많은 참여 바랍니다. 

 

[Seminar]

2024/10/2, Wed, 4PM-5PM

Physics Department, 3441

 

Data-driven discovery of neural computations

through brain-wide and cell-type-specific dynamical systems

 

 

YoungJu Jo, Ph.D.

 

Postdoctoral Scholar in Bioengineering, Deisseroth Laboratory, Stanford University

 

The brain is a nonlinear dynamical system performing diverse computations essential for behavior and cognition. A mechanistic understanding of neural population dynamics implementing specific computations may require measuring, modeling, and controlling neural activity in behaving animals in a principled manner. Here we propose and experimentally demonstrate a data-driven discovery framework through the closed-loop integration of large-scale neurophysiology and interpretable dynamical systems modeling. This approach enabled the unexpected discovery of cell-type-specific habenular line attractor dynamics implementing reward history integration. Building on this finding, a brain-wide spiking activity map in memory-guided decision-making was constructed, elucidating dynamical structures implementing bidirectional value update. To achieve precise optogenetic control over these identified neural computations, a multifunctional family of new channelrhodopsins was engineered, guided by atomic-resolution protein structures, and their cellular-resolution control was demonstrated in vivo using multiphoton holographic illumination. These converging advances enabled the targeted modulation of neural integration in silico by shaping optogenetic control in both space and time through data-constrained dynamical systems. Together, this work paves the way for data-driven systems neuroscience for reading and writing complex information in the brain.

 

 

 

 

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