This page contains course materials for the CoSMo 2016 summer school.
- 1 Introduction
- 2 Modeling movement and disorders
- 3 The Bayesian Brain
- 4 Computational Neuroimaging
- 5 Motor control & learning
- 6 DREAM database - Shared data and models for CoSMo projects
- 7 Group projects
Lecturers: Gunnar Blohm, Paul Schrater, Konrad Kording
Day 1 - Overview of sensory-motor computations
Afternoon tutorial 1 - plotting neural data
Here is the file [Stevenson Data Set]
As part of the tuning curve exercise we will understand it.
Afternoon tutorial 2: gain modulation for reference frame transformations
The goal of this tutorial is to understand how gain modulation can be used for reference frame transformations and how gain modulation can emerge from training a simple artificial neural network carrying out reference frame transformations.
There are 2 different approaches to solving this:
- exact determination of read-out weights from eye-position gain-modulated neurons as in this seminal paper. Here the solution can be found by computing the least-square optimal set of weights mapping the gain-modulated neurons (population code) to head-centered output neuron(s). For this to work, population code neurons need to be of the exponential function family.
- training a neural network to perform reference frame transformations using this code. For this you can plot each individual neuron's receptive field for different eye positions and analyze how the receptive field changes with eye position in each network layer.
Day 2 - Bayesian approaches
Bayesian perception - an introduction: a tremendous book written by Wei Ji Ma, Konrad Kording, Daniel Goldreich
Morning lectures and tutorial (Konrad)
Afternoon lectures and tutorial (Paul)
Day 3 - Linear systems
Morning lectures and tutorials (Theory and saccades)
Linear systems theory slides
Modelling saccades slides
This Matlab file contains both the time representation and frequency representation (using the control systems toolbox) solutions for modelling saccades. Here is yet another way to approach the solution through explicit convolution (this is not preferred but possible ;-) ).
van Opstal syllabus - linear systems theory: a great syllabus developed by John van Opstal for CoSMo on using linear systems to model gaze control with theory, exercises and answers to exercises
Afternoon lectures and tutorials (Kalman filter)
Understanding the Basis of the Kalman Filter Via a Simple and Intuitive Derivation
Kalman Filter tutorials and slides
Day 4 - Optimality and data analyses
Modeling movement and disorders
Lecturers: Dagmar Sternad & Francisco Valero-Cuevas
Day 5 (Francisco)
Book website for Fundamentals of Neuromechanics (free pdf!)
Day 6 (Dagmar)
The Bayesian Brain
Lecturer: Adam Johnson
Link to lecture video (requires installing webex plugin).
Individual Meeting Sign-up Sheet: Adam Johnson
Lecturer: Jörn Diedrichsen
Link to lecture video.
Individual Meeting Sign-up Sheet:
Representational models paper by Joern and Niko (in preparation)
RSA tooblox on Github
Motor control & learning
Aug 10 & 11
Lecturers: Reza Shadmehr, John Krakauer, & Alaa Ahmed
Link to Wed lecture video.
JHU learning theory YouTube channel: Reza teaching
Jul 31 - Aug 14
Curtesy: Konrad Kording
You can get the DREAM project from Gunnar on a USB drive. DREAM can also be downloaded piece-wise (data sets, models, tools, and documentation) from CRCNS: http://crcns.org/data-sets/movements/dream/downloading-dream. You will need to create an account on CRCNS to be able to download the project files.
If you want "all" of DREAM (models, tools, and documentation), click here: AllDream.zip
- If you're familiar with svn and would like info/credentials for code in the repository, contact Ben Walker
Here's the latest version of LoadDreamPaths.m. (This script should work for all OSes.)
Here is a description of data sets currently in Dream. Dream is growing, but this list is accurate as of the time of the summer school (click on the link to access the related publication).
- Burns -- reaching with head tilt and left/right visual perturbations
- Corbett -- reach trajectory predictions based on EMG and gaze movements
- Fernandes -- reaching with uncertain and rotated midpoint feedback
- Flint -- decoding of reaching movements from local field potentials
- Kording -- reaching with uncertain midpoint feedback
- Mattar 07 -- generalizing from one, two or multi targets to another direction
- Mattar 10 -- reaching to a distance (short/long), generalizing to the other one (long/short)
- Ostry -- move in force field, get an estimation of where the hand is
- Scott -- monkey (no spike), center out: even and not evenly distributed targets, also a forward/back
- Stevenson -- center out, monkey with neural time stamps
- Thoroughman -- reach adaptation to perturbations with different complexity
- Vahdat -- movement in force field with FMRI scans pre/post learning
- Wei 08 -- visual perturbations, cursor shown only at target
- Wei 10 -- movement in differing force fields
- Young -- movement time stayed the same, but distance changed; fast, medium, slow reaches.
Jul 31 - Aug 14
Here are some ideas for 2-week project topics.
How-to-model tutorial (Aug 2, evening)
Instructions: Every group will have a 30min slot (20min presentation, 10min questions). The research question, hypotheses and rationale for the choice of the approach should be clearly presented. Models, simulations, results, discussion etc should be detailed enough for everyone to follow.
Best group gets a free short talk at TCMC 2016!!! (confirmed by John Krakauer)
Here is a link to the SfN satellite events - submission deadline Sept 1 !!! The winner has to apply too and specify you are CoSMo 2016 project winner...
PROJECT PRESENTATIONS (Aug 13)
4:00-4:30pm - The Name’s Irrelephant
"Encoding Sequentially Presented Items with a Recurrent Memory Network"
Group: Charles Holmes, Silvia Maggi, Kevin Willeford
4:30-5:00 - Neuro Miners
"Towards bayesian decoding of ECoG channels"
Group: Shuchen, Ali Marjaninejad, Rajat
5:00-5:30 - Granger Danger
"Modeling feedback-driven perceptual learning"
Group: Daniel Lametti, Josh Moskowitz, Xiang Mou
5:30-6:00 - BASH Group
"Modeling increased learning with intermittent feedback"
Group: Maria Ayala, Dan Blustein, James Heald, Raphael Schween
6:00-6:30 - Cool, Kalm an' collected
"Modeling the relationship between reward and sensory feedback in sensory motor adaptation"
Group: Elizabeth, Giacomo, Giulia, Jerry, Patrick
7:00-7:30 - State EsTeamation
"Velocity Modulation given State Estimation Uncertainty"
Group: Brian Cohn, Clare Palmer, Darius Parvin, Vonne van Polanen, Ivan Trujillo-Priego
7:30-8:00 - Horrible Acrylic Nails
"If we only had more time to prepare for this…"
Group: Nathan Wispinski, Cole Simpson, Claire Chambers, Erik Summerside
8:00-8:30 - BayesX - WINNER !!!
"Environmental consistency increases learning saturation level in a visuomotor rotation task"
Group: Scott Albert, Lonneke Teunissen, Hannah Sheahan, Koenraad Vandevoorde
8:30-9:00 - The Swan Elks
"Dissecting the nature of persistent activity in macaque parietal cortex"
Group: Nakahashi, Sedaghat, Katz, Weingaertner
9:00-9:30 - Utterly Unpredictable
"To Go or Not To Go: Bayesian Integration of Stimulus Statistics and Reward Structure in Action Decision Making"
Group: Quan Lei, Thomas Ringstrom, Huaiyong Zhao