Woods Hole, MA – 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.
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”.
For more info, see http://www.mbl.edu/education/courses/special_topics/neufo.html

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