The goal of the Neuroinformatics course at the Marine Biological Laboratory is to train 25 researchers a year, ranging from advanced students to senior investigators, in statistical and computational techniques for the analysis of a broad spectrum of neuroscientific data. This is a natural outgrowth of the MBL Workshop on Analysis of Neural Data, which helped crystallize the community and intellectual agenda reflected in this course.The course spans two weeks, and by emphasizing data analysis and informatics is complementary to the Methods in Computational Neuroscience course at the MBL, which focuses on modeling and theory. The first week consists of pedagogical lectures in statistics, ranging from an elementary introduction to advanced topics. Evenings will have tutorials to help attendees gain experience and concrete understanding. There will also be lectures on data acquisition techniques, stimulus design and the underlying neurobiology. The second week will include focused workshops on various topics, such as neural prostheses, temporal coding, functional MRI. Participants will present their research throughout the course, and analyze their own data in the open laboratory time. All faculty members are expected to interact closely with the attendees and with each other, to analyze specific data sets and to advance the field in general.The course is unique in the spectrum of subjects covered in a unified manner, ranging from multiple spike trains to functional imaging data, and ranging from neuroscience to biomedical engineering. To assist the development of standards in this nascent field, the course presents a unified pedagogical approach grounded in the relevant disciplinary areas of statistics, mathematics and physics, while maintaining intimate ties to neurobiological and biomedical problems. The interdisciplinary scope of the course cannot currently be replicated in a university setting, although the syllabus and experience gathered in this course will prove invaluable for future university courses. Apart from the academic implications, the course has clear consequences for advanced medical technology, and helps involve physical and computer scientists in neurobiology.
| Kass, Robert E; Ventura, Valerie; Brown, Emery N (2005) Statistical issues in the analysis of neuronal data. J Neurophysiol 94:8-25 |
| Brown, Emery N; Kass, Robert E; Mitra, Partha P (2004) Multiple neural spike train data analysis: state-of-the-art and future challenges. Nat Neurosci 7:456-61 |
