Course Description
Our brain is highly complex with billions of neurons; how do neurons work together to produce adaptive & flexible behaviors? Systems neuroscience studies this question at the systems level. Using various animal models, it aims to provide quantitative and causal links between neural circuits/networks and perception, behavior, and cognition. Through this course, you will learn about the popular animal models with simpler brains and interpret the neural mechanisms from multiple perspectives, to acquire a quantitative understanding. Particularly, this course will emphasize interdisciplinary technology, such as large-scale optical neural recording and computational tools. Knowledge gained will provide insights into understanding mental disorders and artificial intelligence.
Prerequisite
Minimum 75% in MAT136H1, and minimum 75% in BIO271H1/ CJH332H1/ PSL300H1
Lecturer(s)
Prof Q. Lin
neuroqian.lin@utoronto.ca
Contact Hours
24L/S, 12P
Required Text(s)/Readings
Required readings will be posted on Quercus.
Evaluation (Subject to change)
Attendance (5%)
Participation (10%)
Presentation of journal papers (25%)
Coding tasks for brain (15%)
Coding tasks behavioral recordings (15%)
Final proposal (30%)
Last updated on March 27th, 2024