The school will target interdisciplinary students (including medicine, biology and psychology with demonstrated quantitative abilities) from undergraduate to PhD level. For the undergrads, potentiality for graduate studies in neuroscience will be assessed. A one page statement of purpose "Why I want to participate in the school," will be required of all applicants. Since some of the software for hands on demo (SPM, EEGLAB etc) are based on MATLAB, knowledge in MATLAB should have priority. There will be no fee and everything will be provided free of cost, but selection will be based on back ground. Students with work experience in neuroscience and related areas will be given preference, as will students with a clear academic career track in mind.

The following resource persons will participate in teaching and tutorials.

1) Dr. Ramesh Venkatesan (GE, Health Care) - From MRI physics to fMRI acquisition and basics of the processing.

2) Dr. Pravat Mandal (NBRC) -  Biomarkers for brain neurochemicals using non-invasive imaging.

3) Dr. Jitender Saini (NIMHANS) - Clinical applications of fMRI.

4) Dr. Sumitra Purakayastha (ISI Kolkata) - Statistical aspects of fMRI.

5) Dr. Phaneendra Yalavarthy(IISc) - Medical imaging.

6) Dr. Supratim Ray (IISc) - Local field potential.

7) Dr. Christoph Herrmann (University of Oldenburg, Germany) - Trancranial electrical and magnetic stimulation under EEG.

8) Dr. Kaushik Majumdar (ISI Bangalore) - Scalp and depth EEG processing.

In addition, there will be hands on demo on real neural data sets. Students will also be provided with computer peripherals for online lessons. The course lab space and institutional accommodation can accommodate up to 30 students.

The school will be from 4th to 12th June 2012 in the ISI Bangalore Center. Each tutorial lecture will be three hour long interspersed by a coffee break in the middle. There will be an introductory lecture on Neuroinformatics on the morning of the first day (4th June).

The course will have a strong component of neuroimaging and data analysis.