Truly integrative and interdisciplinary training in neuroscience is necessary to understand brain function in both normal and pathological states. And such training is not available presently at the pre- and post-doctoral and junior faculty level due to a multitude of reasons. We propose an integrated approach to train the next generation of `neuro' research scientists from several disciplines including biology, psychology, medicine, engineering, physics and mathematics. Specifically, we will build on past successes with training in interdisciplinary neuroscience, to enhance the research expertise of graduate students, post-doctoral scholars and junior faculty in the growing area of computational neuroscience. This enhancement will be achieved via a 2-week short course, with 24 participants/year, held on the University of Missouri campus in Columbia. The course will begin with an in-depth emphasis on neurophysiological concepts via free software (virtual lab) experiments and some wet-lab experiments using a from biology to model and back again approach. It will then provide training in hands-on software development both at the individual (exercises) and two-person group (projects) levels using the software package NEURON to model single neurons and circuits of neurons. We will place importance on the development of individual computational research projects by participants, to enhance their confidence and ability to integrate such tools into their research careers. Since neuroscience concepts and software development tend to be complex, we will provide follow up to participants for one year on all aspects of the course, and in the process also identify barriers to research training in thi new interdisciplinary area. For interested faculty participants, we are willing to visit their institutions to foster interaction across disciplines, research programs, and institutions, in computational approaches. Our experience and findings will be published in science and engineering education journals and presented at appropriate conferences. Our team includes four interdisciplinary faculty, three with expertise in content (1 computational + 2 neuroscientists) and one in pedagogy and evaluation. Two of the faculty (Nair and Schulz) have been collaborating in research in and teaching interdisciplinary neuroscience for the past 8 years. Over that period they have also been hosting annual summer workshops for 2 and 4-year college faculty with focus on teaching undergraduate neuroscience. Our experience and findings will be published in science and engineering education journals and presented at appropriate conferences.
Integrative and interdisciplinary training in neuroscience is necessary to understand brain function in both normal and pathological states, but is lacking presently. We propose an integrated approach to train the next generation of `neuro' research scientists from several disciplines including biology, psychology, medicine, engineering, physics and mathematics, via a 2-week immersive short course focusing on the development of biophysical computational models. The course will have 7 parallel tracks including mathematics, fundamentals of neurons and circuits, systems analysis, and intensive development of computational models of neurons and networks, using the package NEURON.
