Difference between revisions of "CoSMo 2017"

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'''Afternoon tutorial 1 - plotting neural data'''
 
'''Afternoon tutorial 1 - plotting neural data'''
  
Here is the file [[http://http://compneurosci.com/wiki/images/M1_Stevenson_Binned.mat Stevenson Data Set]]
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Here is the file [[http://compneurosci.com/wiki/images/M1_Stevenson_Binned.mat Stevenson Data Set]]
 
As part of the tuning curve exercise we will understand it. <br>
 
As part of the tuning curve exercise we will understand it. <br>
  

Revision as of 22:33, 30 January 2018

This page contains course materials for the CoSMo 2017 summer school.

CoSMo logo


Introduction

Jul 31 - Aug 4
Lecturers: Gunnar Blohm, Paul Schrater, Konrad Kording


Day 1 - Overview of sensory-motor computations

Organization slides
Philosophy of modelling slides
Sensorimotor overview slides


Afternoon tutorial 1 - plotting neural data

Here is the file [Stevenson Data Set] As part of the tuning curve exercise we will understand it.

Tutorial is available here


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

AFTERNOON LECTURE TUTORIAL Dropbox link to slides and tutorial: Material for decision making lecture and tutorial


Day 2 (evening) - How to model tutorial

Paul's Illusion exercise slides are in the afternoon tutorial dropbox.

How to model tutorial slides


Day 3 - Linear systems

Morning lectures and tutorials (Theory and saccades)
Linear systems theory slides
Modelling saccades slides

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)

Face attractiveness and decision tutorials, and lecture slides

Here are modeling tutorial instructions. Please also read the papers by Lappe and Seno.


Day 3 (evening) - paper writing 101

Konrad talked about paper writing 101. This is also formalized in the Ten simple rules for structuring papers article.


Day 4 - Optimal Feedback Control

OFC slides

Inverted pendulum problem
LQG code


Day 5 - optimality and model fitting

Konrad discussed if we can understand a micro-processor. This is published here


BADS model fitting (afternoon)

Luigi Acerbi's slides
Tutorial files


Model evaluation discussion

Model evaluation slides also containing the brainstorming outcome


The Bayesian Brain

Aug 5
Lecturer: Jan Drugowitsch

Jan's slides
Jan's tutorial material


Motor control & learning

Aug 7-8
Lecturers: Alaa Ahmed and Reza Shadmehr

Morning Lectures

Afternoon Problems and Lecture slides

SLIDES AND PROBLEMS

From basic insights to clinical applications

"Aug 9-10"
Lecturer: Dagmar Sternad

DAY 1 MATERIALS
DAY 2 MATERIALS


DREAM database - Shared data and models for CoSMo projects

Jul 31 - Aug 13
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.


Group projects

Jul 31 - Aug 12

Here are some ideas for 2-week project topics.

How to model tutorial slides

Group project presentation template


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 Advances in Motor Control and Motor Learning 2017 (SfN satellite workshop)!!! (confirmed by John Krakauer)
Here is a link to the SfN satellite events - submission deadline Sept 15 !!! The winner has to apply too and specify you are CoSMo 2017 project winner...


PROJECT PRESENTATIONS (Sat, Aug 12)


12:30-1pm - Kalman Kong and four Monkeys
"Does uncertainty in visual and proprioceptive hand estimates determine the degree of sensory recalibration?"
Group: Eugene Poh, Gaiqing Kong, Jianfei Guo, Pierre Petitet, Zhaoran Zhang


1-1:30pm - Buzzfeed LAMAS
"You won't BELIEVE how S1 spiking activity encodes sensory feedback for goal directed movements in a grasping task!"
Group: Liza Okorokova, Alex Kaiser, Monica Liu, Spencer Arbuckle, Angelica Herrera


1:30-2pm - The Acronym
"Influence of task difficulty history on the adaptation rate in a motion prediction task"
Group: Chloe, Moji, Ben, Jonny and Corson


2-2:30pm - Too Bayesic
"Copy-mechanism explains transfer in visual perceptual learning"
Group: Suraj Chakravarthi Raja, Pedro Cisneros-Velarde, Wanying Jiang, Katrin Sutter


2:30-3pm - Cucumber Nation
"Modelling savings using a probabilistic estimate of the environment"
Group: Kevin Day, Hyosub Kim, Rory Flemming, Agustin Solano, Jing Huang


3-3:30pm - The encoders
"Bayesian Decision Making in Biological Motion"
Group: Anakani Chattoraj, Deepak Gopinath, Khashayar Misaghian, Albert Buchard, Santiago Alonso-Diaz


3:30-4pm - Where-The-Fovea? (WTF)
"Do natural scenes influence the development of the preferred retinal location with foveal scotoma?"
Group: Yangzi, Rakesh, Ali, Charlotte, & Immo


4-4:30pm - Eurovision
"Can people make optimal decisions when both visual evidence and reward vary over time?"
Group: Ioanna Polyzou, Baptiste Caziot, Jozsef Arató, David Aguilar-Lleyda


4:30-5pm - Team Locomotion
"Predicting optimal gaze direction as a function of running speed when running on targets"
Group: Nidhi Seethapathi, Tzu-Hsiang Lin, Yashar Aucie