[Comp-neuro] Neuroinformatics course at Marine Biological
Laboratory, Woods Hole,
MA: Application Deadline has been extended to April 26th, 2010
neuro.informatics.at.mbl at gmail.com
Fri Apr 23 00:23:26 CEST 2010
Neuroinformatics course at Marine Biological Laboratory, Woods Hole, MA
Application Deadline has been extended to April 26th, 2010
Dates: August 14th to 29th, 2010
The objective of this two week course is to develop an understanding of the
methods of managing and analyzing data sets from neurophysiological and
behavioral measurements, particularly large data volumes that require
systematic statistical and computational approaches. The course includes
lectures on fundamental analytical methods, established and emerging
applications and focused hands-on computer-based sessions. Topics include
point processes (*e.g., *spike trains), continuous processes (*e.g.*,
LFP/ECoG/EEG/MEG recordings, fMRI, and behavioral recordings), and methods
for analyzing neuroanatomical (*e.g., *light and electron microscopy) data.
Various statistical techniques for exploratory and confirmatory analysis of
the data will be treated along with underlying scientific questions and
potential applications. The course also includes tutorials on computer
methods and discussions of major open issues in the field.
The course is targeted broadly, from experimental researchers to researchers
with a theoretical or analytical orientation who work closely with data. A
main aim of the course is to foster close working relations between the
theorists and experimentalists. Researchers at all levels, from advanced
graduate student to working professional, may benefit from the course.
Limited to 26 participants.
Computer Laboratory: A hands-on approach will be taken in a computer
laboratory that forms an integral part of this course. Example data sets
will be supplied, and participants are encouraged to bring their own data.
We will primarily use MATLAB, with additional tools used as needed (*e.g.*,
MySQL). Participants will be guided in applying analytical techniques to the
example data sets and will further participate in a structured "data
analysis challenge", in which teams will analyze published data sets in the
context of specific questions. This should benefit both experimental
researchers that wish to analyze their own data sets and theorists who want
to work with data.
Structure of the Course: The first week will contain lectures dealing with
fundamental statistical and analytical techniques appropriate for neural
data analysis. A concurrent computer laboratory will run in the evenings to
supplement the lectures. The second week contains application-based
lectures, focused on emerging research areas and associated analytical and
experimental techniques, along with the "data analysis challenge".
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