Advanced Matlab
Scott Gorlin
Mon-Wed, Fri, Jan 20-21, 23, 26, 28, 30, 12-01:00pm, 46-3310
No limit but advance sign up required (see contact below)
Participants requested to attend all sessions (non-series)
Beneath the extensive data and matrix tools in Matlab lies a comprehensive programming environment largely untapped by the casual user. For those who want to do more than analyze simple data sets, this class will explore how universal programming concepts apply to Matlab and how to exploit them to build powerful tools - whether you simply want a deeper understanding of how Matlab works or you want to build a sophisticated application for experimental control. Special topics to include object-oriented programming, application development, multi-threading, parallel and distributed applications, optimization, and Java integration. This course presupposes basic working knowledge of Matlab or sufficient experience in another programming language to ease the transition.
Contact: Scott Gorlin, 46-6227, x3-8785, gorlins@mit.edu
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Assessment: How We May Sometimes Be Deceiving or Confusing Ourselves Based Upon The Statistical Assessment Methods and Empirical Methods We Use In Res
David Singer
Wed Jan 21, 12-02:00pm, 46-3015
No limit but advance sign up required (see contact below)
Essentially this two hour workshop will relate some of the common fallacies that sometimes exist in doing research in educational technology. This will be a highly participatory workshop, and we especially invite participants to bring their research designs for review and discussion. Pre-registration is required singerd@mit.edu
Contact: David Singer, singerd@mit.edu
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Assessment: How We May Sometimes Be Deceiving or Confusing Oursleves Based Upon The Statistical Assessment Methods and Empirical Methods We Use In Res
David Singer visiting scholar
Wed Jan 28, 12-02:00pm, 46-3015
No limit but advance sign up required (see contact below)
Essentially this two hour workshop will relate some of the common fallacies that sometimes exist in doing research in behavioral neuroscience. This will be a highly participatory workshop, and we especially invite participants to bring their research designs for review and discussion. Pre-registration is required singerd@mit.edu
Contact: David Singer, singerd@mit.edu
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From understanding cortex to building a mathematical theory
Tommy Poggio, Thomas Serre, Lorenzo Rosasco
Mon Jan 12, Tue Jan 13, 11am-03:30pm, 46-3310, lunch break 12:30-2:00 pm
No enrollment limit, no advance sign up
Participants requested to attend all sessions (non-series)
Understanding the processing of information in our cortex is a significant part of understanding how the brain works and of understanding intelligence itself, arguably one of the greatest problems in science today.
Beginning by reviewing research at CBCL on the problem of intelligence. Continuing with a brief review of modern learning theory; a more specialized session on current approaches & open questions in learning theory.Focusing on current topics of research on the computational architecture of visual cortex and discuss their implications for advancing computer vision technology.
Web: http://cbcl.mit.edu/publications/index-pubs.html
Contact: Tommy Poggio, 46-5177B, x3-5230, tp@ai.mit.edu
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Neuropharmacology Class
Daniela Tropea
Tue Jan 6, 13, 20, 27, 12-01:00pm, 46-3015
The Neuropharmacology course will discuss the drug-induced changes in functioning of the nervous system. The specific focus of this course will be to provide a description of the cellular and molecular actions of drugs on synaptic
transmission. This course will also refer to specific diseases of the nervous system and their treatment in addition to giving an overview of the techniques
used for the study of neuropharmacology.
This course is open to both graduate and undergraduate students with a basic knowledge of neuroscience principles.
Contact: Daniela Tropea
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Philosophy of cognitive science choose your own adventure!!
Steven Piantadosi, Tim Brady
Mon Jan 26 thru Fri Jan 30, 06-07:30pm, 46-3015
We'll argue our way through the logical landscape of philosophy in cognitive science in a choose-your-own adventure format, using thought experiments, philosophical arguments, and scientific results. This course explores the relationship between science, philosophy, and our
theories of the mind. No required readings or pre-requisites.
Contact: Steven Piantadosi, x3-9794, piantado@MIT.EDU
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Statistics and Visualization for Data Analysis and Inference
Michael Frank, Edward Vul
Mon Jan 26 thru Thu Jan 29, 01-04:00pm, 46-3189
Fri Jan 30, 01-04:00pm, 46-3310
Participants requested to attend all sessions (non-series)
A whirl-wind tour of the statistics used in modern behavioral science research, covering topics including: data visualization, building your own null-hypothesis distribution through permutation, useful parametric distributions, the generalized linear model, and model-based analysis more generally. Familiarity with Matlab, Octave, or R will be exceptionally useful, prior experience with statistics will be helpful but is not essential. This course is intended to be a ground-up sketch of a coherent, alternative perspective to the "null-hypothesis significance testing" method for behavioral research (but don't worry if you don't know what this means).
Contact: Michael Frank, mcfrank@mit.edu
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