We propose an interdisciplinary program at the University of Pennsylvania to train outstanding undergraduate and predoctoral students in computational neuroscience. Penn offers unique strengths in basic and clinical neuroscience, both integrated with computational approaches. All participating departments at Penn are national leaders in their field, have a long history of research and educational collaborations, and are located in close proximity on a single campus. The undergraduate and graduate student populations are highly qualified. Twenty-four faculty at Penn, plus faculty at six nearby regional institutions are involved, including experimentalists, modelers, and many faculty with expertise in both domains. The preceptors have extensive experience in education and research training in computational neuroscience. The program consists of three components: an undergraduate research training program, a summer research program for undergraduates, and a predoctoral training program. The focus is on directly integrating Neuroscience and quantitative studies through course work and extensive research training. Students will carry out integrated experimental/modeling research projects directed at computational problems. The structure and strategy of our program is designed to have each student individually achieve a significant research contribution through the integrated development of model, experiment, and data analysis. We propose to develop an integrated undergraduate curriculum in computational neuroscience including a new, keystone course, and to significantly update and expand our current graduate courses in computational neuroscience-all including substantial laboratory components. We will also introduce a dedicated seminar series, separate undergraduate and graduate journal clubs, an annual retreat, and other programmatic activities. A distinguishing focus of our program is on application of computational neuroscience to neurological and psychiatric disorders. Students will undertake clinical rotations, analyze clinically obtained data, and have the option of rotations on computational projects in Penn's clinically-directed research centers. A summer research program will be developed, which will attract undergraduates primarily from the Philadelphia region. Six nearby universities are participating in this summer program, including Swarthmore, Drexel, Temple, Haverford, Bryn Mawr, and Lincoln Universities. The summer program will be designed to engage and excite students to pursue graduate work in computational neuroscience. The student population will include a significant proportion of women and underrepresented minorities. ? ? ?
Vanleer, Ann C; Blanco, Justin A; Wagenaar, Joost B et al. (2016) Millimeter-scale epileptiform spike propagation patterns and their relationship to seizures. J Neural Eng 13:026015 |
Arcaro, Michael J; Pinsk, Mark A; Kastner, Sabine (2015) The Anatomical and Functional Organization of the Human Visual Pulvinar. J Neurosci 35:9848-71 |
Simmons, Kristina D; Prentice, Jason S; Tka?ik, Gašper et al. (2013) Transformation of stimulus correlations by the retina. PLoS Comput Biol 9:e1003344 |
Nassar, Matthew R; Rumsey, Katherine M; Wilson, Robert C et al. (2012) Rational regulation of learning dynamics by pupil-linked arousal systems. Nat Neurosci 15:1040-6 |
Prentice, Jason S; Homann, Jan; Simmons, Kristina D et al. (2011) Fast, scalable, Bayesian spike identification for multi-electrode arrays. PLoS One 6:e19884 |
Wulsin, D F; Gupta, J R; Mani, R et al. (2011) Modeling electroencephalography waveforms with semi-supervised deep belief nets: fast classification and anomaly measurement. J Neural Eng 8:036015 |
Chamberlain, Ann C; Viventi, Jonathan; Blanco, Justin A et al. (2011) Millimeter-scale epileptiform spike patterns and their relationship to seizures. Conf Proc IEEE Eng Med Biol Soc 2011:761-4 |
Arcaro, Michael J; Pinsk, Mark A; Li, Xin et al. (2011) Visuotopic organization of macaque posterior parietal cortex: a functional magnetic resonance imaging study. J Neurosci 31:2064-78 |
Lee, Thomas Y; Brainard, David H (2011) Detection of changes in luminance distributions. J Vis 11: |
Nassar, Matthew R; Wilson, Robert C; Heasly, Benjamin et al. (2010) An approximately Bayesian delta-rule model explains the dynamics of belief updating in a changing environment. J Neurosci 30:12366-78 |
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