Data analysis, Modelling & Causality in Neuroscience

From:: Monday, 22 February 2021
To:: Friday, 05 March 2021
Location:: Online

The first ZENITH bespoke workshops “Data analysis, Modelling & Causality in Neuroscience” provided advanced, hands-on training in data analysis and computational modelling, experimental design and statistics.

The two-week workshops was taught by the ZENITH faculty together with invited international experts and included both theoretical background and practical training supported by several teaching assistants from the different labs.

Modules

The course will be split into 2 modules:

Introduction to Statistics, Signal Processing and Machine Learning
Introduction to Computational Systems Neuroscience:
Introduction to Image processing and modelling behavioral data; Single neuron coding; Population coding; Introduction to neural networks; Building neural network models from data; Abstract modelling approaches

Organisers

Moritz Grosse-Wentrup

University of Vienna

Project at ZENITH:

Modelling Behavior

Ruben Portugues

Technical University of Munich (TUM)

Project at ZENITH:

Eyes 'n Tail

James Fitzgerald

Janelia Research Campus

Academic Collaborator

Schedule

Module 1: Introduction to Statistics, Signal Processing and Machine Learning

Monday, 22 February 2021

09:00 — 09:15: Day 1: statistics
09:15 — 10:00: Lecture 1: Probability theory; Moritz Grosse-Wentrup
10:00 — 10:15: Coffee break
10:15 — 11:45: Coding 1: Samples estimates
11:45 — 12:00: Coding wrap-up
12:00 — 13:15: Lunch break
13:15 — 14:00: Lecture 2: Statistical testing; Moritz Grosse-Wentrup
14:00 — 14:15: Coffee break
14:15 — 15:45: Coding 2: Permutation tests
15:45 — 16:00: Coding wrap-up
16:00 — 16:30: Break
16:30 — 17:15: Lecture 3: Causality; Moritz Grosse-Wentrup
17:15 — 17:30: Coffee break
17:30 — 19:00: Coding 3: Causal inference
19:00 — 19:15: Coding wrap-up
19:15 — 19:30: Wrap-up

Tuesday, 23 February 2021

09:00 — 09:15: Day 2 : Signal Processing
09:15 — 10:00: Lecture 1: Linear time-invariant (LTI) systems; Moritz Grosse-Wentrup
10:00 — 10:15: Coffee break
10:15 — 11:45: Coding 1: Convolution and filtering
11:45 — 12:00: Coding wrap-up
12:00 — 13:15: Lunch break
13:15 — 14:00: Lecture 2: Discrete Fourier Transform; Moritz Grosse-Wentrup
14:00 — 14:15: Coffee break
14:15 — 15:45: Coding 2: Spectral estimation
15:45 — 16:00: Coding wrap-up
16:00 — 16:30: Break
16:30 — 17:15: Lecture 3: Information theory; Moritz Grosse-Wentrup
17:15 — 17:30: Coffee break
17:30 — 19:00: Coding 3: Spectral power density estimation
19:00 — 19:15: Coding wrap-up
19:15 — 19:30: Wrap-up

Wednesday, 24 February 2021

09:00 — 09:15: Day 3 : Machine Learning
09:15 — 10:00: Lecture 1: Supervised learning; Moritz Grosse-Wentrup
10:00 — 10:15: Coffee break
10:15 — 11:45: Coding 1: Linear discriminant analysis
11:45 — 12:00: Coding wrap-up
12:00 — 13:15: Lunch break
13:15 — 14:00: Lecture 2: Statistical learning theory; Moritz Grosse-Wentrup
14:00 — 14:15: Coffee break
14:15 — 15:45: Coding 2: Model validation
15:45 — 16:00: Coding wrap-up
16:00 — 16:30: Break
16:30 — 17:15: Lecture 3: Interpretable machine learning; Gunnar König
17:15 — 17:30: Coffee break
17:30 — 19:00: Coding 3: Feature importance scores
19:00 — 19:15: Coding wrap-up
19:15 — 19:30: Wrap-up

Module 2: Introduction to Computational Systems Neuroscience

Thursday, 25 February 2021

09:00 — 10:30: Lecture 1: Methods for brain-wide imaging in larval zebrafish; Ruben Portugues
10:30 — 12:30: Getting up-and-running with data; Ruben Portugues, James Fitzgerald
12:30 — 13:30: Lunch break
13:30 — 14:15: Lecture 2: Statistical signal processing for calcium imaging data; Ruben Portugues
14:15 — 15:00: Lecture 3: The importance of theory for understanding data; James Fitzgerald
15:00 — 17:00: Pre-processing of calcium imaging data; Ruben Portugues, James Fitzgerald
17:00 — 18:30: The importance of theory for understanding biology; James Fitzgerald

Friday, 26 February 2021

09:00 — 10:30: Lecture 1: Brain activity mapping; Ruben Portugues
10:30 — 12:30: Regressor analysis; Ruben Portugues, James Fitzgerald
12:30 — 13:30: Lunch break
13:30 — 15:00: Lecture 2: The problem of neural coding; James Fitzgerald
15:00 — 17:00: Theoretical exercises on signal processing, information theory, and neural coding; Ruben Portugues, James Fitzgerald
17:00 — 18:30: Lecture 3: Building statistical models of neural coding from data; James Fitzgerald

Thursday, 04 March 2021

09:00 — 10:30: Lecture 1: Training artificial neural networks; Ruben Portugues
10:30 — 12:30: Learning to accumulate evidence; Ruben Portugues, James Fitzgerald
12:30 — 13:30: Lunch break
14:00 — 15:00: Lecture 2: "Zebrafish Neural Circuits & Behavior” online seminar
15:00 — 17:00: Fitting neural network models; Ruben Portugues, James Fitzgerald
17:00 — 18:30: Lecture 3: Natural scene statistics and algorithms for behavior; James Fitzgerald

Friday, 05 March 2021

10:00 — 11:30: Lecture 1: Lecture and discussion; Moritz Grosse-Wentrup
11:30 — 13:00: Lunch break
13:00 — 14:30: Lecture 2: Lecture and discussion; Ruben Portugues
14:30 — 14:45: Break
14:45 — 16:15: Lecture 3: Lecture and discussion; James Fitzgerald
16:15 — 17:00: Break
17:00 — 18:30: ZENITH Seminar; Thomas Gregor