This proposal is for a five-year T90/R90 training program in Computational Neuroscience at Brandeis University containing the Research Education Program component (R90), the Undergraduate Research Training Component (R90), and the Predoctoral Research Training Program (T90). The proposed program requests funding to support 6 undergraduates (R90), 4 NRSA eligible graduate students (T90), and 2 non-NRSA eligible graduate students (R90) each year. Our goal is to identify early career students and provide them the formal and informal education and training they will need to develop into the next generation of computational/quantitative neuroscientists. The long-term goals and objectives are to increase the number of scientists with strong quantitative and modeling skills in neuroscience, as this cohort will be needed to understand brain function in health and disease. The 13 training faculty has research expertise from human cognition to cellular and molecular neuroscience, so a wide range of research problems, at numerous levels of analysis are available to trainees. The training faculty were chosen because they have demonstrated commitment to the use of theoretical and computational methods to understand the nervous system in health and disease. Students will take courses in computational neuroscience, obtain skills in building models of neurons, synapses, and networks, and employ these in a variety of independent research projects. Two cohorts of prospective trainees will be targeted: 1) Individuals in degree programs in Physics, Math, and Computer Science who wish to work in neuroscience. This cohort already has significant quantitative skills, but needs training in neuroscience. 2) Individuals in degree programs in Biology, Biochemistry, Neuroscience, or Psychology who wish to learn to employ quantitative and computational methods as part of their ability to tackle important problems in neuroscience. In addition to course work and laboratory research, students and trainees will be engaged in a large number of other activities designed to enhance their speaking skills, writing skills, and ability to collaborate with other scientists. All students and trainees will receive training in the responsible conduct of science, and students and trainees from underrepresented populations will be included.
Alleviating the burden of neurological and psychiatric disorders will require a cohort of investigators who can use computational and theoretical tools to understand brain function in health and disease. This program will train undergraduates and graduate students to use quantitative modeling methods and statistics to reveal features of brain function and disease not possible without these quantitative approaches.
|Hengen, Keith B; Torrado Pacheco, Alejandro; McGregor, James N et al. (2016) Neuronal Firing Rate Homeostasis Is Inhibited by Sleep and Promoted by Wake. Cell 165:180-91|
|Roy, Arani; Osik, Jason J; Ritter, Neil J et al. (2016) Optogenetic spatial and temporal control of cortical circuits on a columnar scale. J Neurophysiol 115:1043-62|
|Keller, Arielle S; Sekuler, Robert (2015) Memory and learning with rapid audiovisual sequences. J Vis 15:7|
|Cousins, Katheryn A Q; Dar, Hayim; Wingfield, Arthur et al. (2014) Acoustic masking disrupts time-dependent mechanisms of memory encoding in word-list recall. Mem Cognit 42:622-38|
|Gorla, Suresh Kumar; Kavitha, Mandapati; Zhang, Minjia et al. (2013) Optimization of benzoxazole-based inhibitors of Cryptosporidium parvum inosine 5'-monophosphate dehydrogenase. J Med Chem 56:4028-43|
|Colton, Gabriel; Leshikar, Eric D; Gutchess, Angela H (2013) Age differences in neural response to stereotype threat and resiliency for self-referenced information. Front Hum Neurosci 7:537|
|Goeritz, Marie L; Bowers, Matthew R; Slepian, Brian et al. (2013) Neuropilar projections of the anterior gastric receptor neuron in the stomatogastric ganglion of the Jonah crab, Cancer borealis. PLoS One 8:e79306|