Connectionists: Announcement: Neuroinformatics course at Marine Biological Laboratory, Woods Hole, MA, August 14-29, 2010

[Neuro Informatics]

Neuroinformatics course at Marine Biological Laboratory, Woods Hole, MA



Dates: August 14th to 29th, 2010

Web: http://www.mbl.edu/education/courses/special_topics/neufo.html



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.



Application deadline is April 16, 2010. 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".