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NeuroMatch Academy (NMA) Computational Neuroscience syllabus

The content should primarily be accessed from our new ebook: https://compneuro.neuromatch.io/

Objectives: Introduce traditional and emerging computational neuroscience tools, their complementarity, and what they can tell us about the brain. A main focus is on modeling choices, model creation, model evaluation and understanding how they relate to biological questions.

Prerequisites: See here

Course materials

Group projects are offered for the interactive track only and will be running during all 3 weeks of NMA!

Course outline

  • Week 0 (Optional)

    • Asynchronous: Python Workshop Part 1 for students + Mandatory TA training for ALL TAS
    • Asynchronous: Python Workshop Part 2 for students + Mandatory TA training for ALL TAS
    • Wed, June 30th: Linear Algebra (Mandatory for all Tutorial TAs). Project TAs have separate training.
    • Thus, July 1st:Calculus (Mandatory for all Tutorial TAs). Project TAs have separate training.
    • Fri, July 2nd: Probability & Statistics (Mandatory for all Tutorial TAs). Project TAs have separate training.
  • Week 1

    • Mon, July 5: Model Types
    • Tue, July 6: Modeling Practice
    • Wed, July 7: Model Fitting
    • Thu, July 8: Generalized Linear Models
    • Fri, July 9: Dimensionality Reduction
  • Week 2

    • Mon, July 12: Deep Learning
    • Tue, July 13: Linear Systems
    • Wed, July 14: Biological Neuron Models
    • Thu, July 15: Dynamic Networks
    • Fri, July 16: Project day!
  • Week 3

    • Mon, July 19: Bayesian Decisions
    • Tue, July 20: Hidden Dynamics
    • Wed, July 21: Optimal Control
    • Thu, July 22: Reinforcement Learning
    • Fri, July 23: Network Causality

Daily schedule

All days (except W1D2, W2D5, and W3D5) will follow this schedule for course time:

Time (Hour) Lecture
0:00-0:30* Intro video & text
0:30-0:45** Pod discussion I
0:45-2:15 Tutorials + nano-lectures I
2:15-3:15 Big break
3:15-4:45 Tutorials + nano-lectures II
4:45-4:55 Pod dicussion II
4:55-5:00 Reflections & content checks
5:05-5:35* Outro

* The intro and outro will be watched asynchronously, which means that you can watch this lecture before and after the start of the synchronous session

** Note that the synchronous session starts at 0:30 with the first pod discussion!

On W2D1, W2D4, and W3D4:

Time (Hour) Lecture
5:40-6:40 Live Q&A

On W1D2 (project launch day):

Time (Hour) Lecture
0:00-0:30* Intro video & text
0:30-2:30** Tutorials + nano-lectures I
2:30-2:45 Outro
2:45-3:45 Big break
3:45-5:30 Literature review
5:30-5:45 Break
5:45-8:30*** Project proposal

* The intro and outro will be watched asynchronously, which means that you can watch this lecture before and after the start of the synchronous session

** Note that the synchronous session starts at 0:30 with the first pod discussion!

*** Note that this includes the next available project time, which may be on the next day.

On W2D5 (abstract writing day):

Time (Hour) Lecture
0:00-2:20* Abstract workshop
2:20-2:50 Break
2:50-4:20 Individual abstract editing
4:20-5:05 Mentor meeting
5:05-5:25 Break
5:25-6:25 Pod abstract swap
6:25-8:00 Finalize abstract
  • This day is completely asynchronous, so you should combine tutorial and project time for a total of 8 hours.

On W3D5 (final day!), we will have an extra celebration and pod wrap-ups after the material:

Time (Hour) Lecture
0:00-0:30* Intro video & text
0:30-0:45** Pod discussion I
0:45-2:15 Tutorials + nano-lectures I
2:15-3:15 Big break
3:15-4:45 Tutorials + nano-lectures II
4:45-4:55 Pod dicussion II
4:55-5:00 Reflections & content checks
5:05-5:35* Outro
5:35-5:45 Break
5:45-6:10 Evaluation report
6:10-7:10 Project presentations
7:10-7:25 Pod farewell
7:25-8:15 Closing ceremony

* The intro and outro will be watched asynchronously, which means that you can watch this lecture before and after the start of the synchronous session

** Note that the synchronous session starts at 0:30 with the first pod discussion!

Licensing

CC BY 4.0

CC BY 4.0 BSD-3

The contents of this repository are shared under under a Creative Commons Attribution 4.0 International License.

Software elements are additionally licensed under the BSD (3-Clause) License.

Derivative works may use the license that is more appropriate to the relevant context.

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NMA Computational Neuroscience course

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