<span style="font-size: 14pt;">Neuroinformatics course at
Marine Biological Laboratory, Woods Hole, MA</span><div class="gmail_quote">
<p class="MsoNormal" style="text-align: justify;"><span style="font-size: 14pt;"> </span></p>
<p class="MsoNormal" style="text-align: justify;">Application Deadline has been
extended to April 26<sup>th</sup>, 2010</p>
<p class="MsoNormal" style="text-align: justify;"><span style="font-size: 14pt;"> </span></p>
<p class="MsoNormal" style="text-align: justify;">Dates: August 14<sup>th</sup> to
29<sup>th</sup>, 2010</p>
<p class="MsoNormal" style="text-align: justify;">Web: <a href="http://www.mbl.edu/education/courses/special_topics/neufo.html" target="_blank">http://www.mbl.edu/education/courses/special_topics/neufo.html</a></p>
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<p class="MsoNormal" style="text-align: justify;">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 (<i>e.g.,
</i>spike trains), continuous processes (<i>e.g.</i>,
LFP/ECoG/EEG/MEG recordings, fMRI, and behavioral recordings), and methods for
analyzing neuroanatomical (<i>e.g., </i>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.</p>
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<p class="MsoNormal" style="text-align: justify;">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.</p>
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<p class="MsoNormal" style="text-align: justify;">Limited to 26 participants.</p>
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<p class="MsoNormal" style="text-align: justify;">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 (<i>e.g.</i>, 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.</p>
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<p class="MsoNormal" style="text-align: justify;">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".</p>
</div><br>