Teaching

Summer School in Computational Sensory-Motor Neuroscience (CoSMo)

This summer school will integrate modern ML approaches with traditional modeling techniques. Teaching materials will be hands-on Python tutorial-based and will be complemented by step-by-step how to model guidance taught during 2-week group projects. (course credit: NSCI 855)

Organizers: Drs. Gunnar Blohm, Paul Schrater, Megan Peters & Konrad Körding
Dates: n/a
Location: n/a

Note: CoSMo has been replaced with Neuromatch Academy!


NSCI 401: Introduction to Modelling in Neuroscience

This course provides an introduction to the main modelling approaches and theoretical concepts in Neuroscience. We discuss the computational anatomy of the brain and how it implements perception, learning, memory, decision making and motor control, among other topics.

Lectures and seminar. Offered in Fall Term.

Prerequisite: STAT 263* or equivalent and standing in the fourth year BSCH LISC degree; or permission of course director. ANAT 312*, or NSCI 323* or NSCI 324*, or PSYC 271*, or equivalent highly recommended


NSCI 801: Quantitative Neuroscience


This is a tutorial-based introduction to quantitative methods for neuroscience research. The goal is to provide Matlab/Python-based hands-on skills in signal processing, basic and advanced statistics, data neuroscience (machine learning) and model fitting methods. This includes an introduction to scientific programming as well as causality-supporting methods and open science framework approaches.

Lectures and hands-on tutorials. Offered in Winter Term.

Prerequisite: none. No previous experience required


NSCI 850: Computational Approaches to Neuroscience

This course provides an overview and hands on experience of the most important computational approaches in Neuroscience. The main topics covered include single cell and neural network modelling, Bayesian approaches, State Space modelling and Optimal Control Theory. More specific modelling approaches are also discussed as well as some widely used computational data analysis methods.

Lectures and hands-on tutorials. Offered in Winter Term.

Prerequisite: permission of course coordinator.

Note: this course is not offered anymore. Please choose NSCI 855 / 860 instead.


NSCI 855: Modeling in Neuroscience

This course is based on the annual Summer School in Computational Sensory-Motor Neuroscience (CoSMo), and alternatively the online equivalent Neuromatch Academy Computational Neuroscience (NMA-CN) course. Through lectures, tutorials and a problem-based project, students will gain advanced knowledge and experience in the application of computational methodologies to modelling in neuroscience.

Offered in Summer (see NMA website)


NSCI 860: Advancing (Neuro-)Science with Deep Learning

This course is based on the annual Neuromatch Academy Deep Learning Summer School, which is a online 3-week (15 days) intensive course. Through lectures, hands-on tutorials and a problem-based project, students will gain advanced knowledge and experience in how modern deep learning methods can help advance (neuro-)science.

Offered in Summer (see NMA website)