This proposal continues and evolves an undergraduate and graduate (NRSA and non-NRSA) Training Program in Neural Computation and Engineering. The University of Washington has a rich history and a large and growing breadth of active teaching and research in this area, with faculty mentors distributed through many departments and schools, including Physiology and Biophysics, Biological Structure, Computer Science and Engineering, Applied Math, Biology, Psychology and Bioengineering. This program evolves the extremely successful previous five-year program which saw the development of an active and highly visible training program, including new undergraduate and graduate program, website, community activities, to take advantage of new opportunities and momentum in Seattle. Support for undergraduate and graduate education and research will enhance interaction between theorists and experimentalists; expand and integrate coursework in emerging approaches in neuroscience, particularly novel offerings in neuroengineering and big data; enhance interactions between undergraduate and graduate students; provide opportunities for undergraduate research and draw together the community across campus to strengthen our already excellent interdisciplinary exchange and collaboration. The undergraduate training program is a 2-year sequence in computational neuroscience, with support for 6 trainees yearly from neurobiology or from a computational/engineering major (Physics, Computer Science and Engineering, Bioengineering, Applied and Computational Mathematics). Trainees take a core curriculum including a research seminar, a choice of laboratory neurobiology sequence and common quantitative courses. Choice of additional electives in an individualized curriculum and career development is guided by a mentoring committee. All students will complete at least 1 and preferably 4 quarters of mentored laboratory research. The graduate training program will support up to 6 students from multiple graduate programs. Students will apply for training grant support at the end of the first year and carry out a core curriculum consisting of neurobiology, quantitative and journal club courses. Individually tailored curricula including electives selected from offerings in computational neuroscience, mathematics, computer science and physics will be devised in consultation with a mentoring committee. Trainees will have access to the UW/Allen Institute Summer Workshop for the Dynamic Brain on San Juan Island. All trainees will attend a regular seminar and and present their research at an annual retreat. The program will be co-directed by Profs. Adrienne Fairhall, Physiology and Biophysics and Eric Shea-Brown, Applied Mathematics, assisted by Leadership Team Prof. Bill Moody, Director, Undergraduate Neurobiology Program and Prof. David Perkel, Director, Neuroscience Graduate Program.
This training grant aims to train young neuroscientists to use mathematical and computational tools to understand the highly dynamical processing capabilities of the brain and neural circuitry. It will also give students in physics, mathematics, engineering and computer science deeper insight into the biology of the brain in order to devise more appropriate theoretical models and methods to interface with brain signals. This program will allow students to use and devise methods to deal with the large and complex data collected from new recording technologies and to engage in the development of assistive technologies that integrate with nervous system function.
| Casimo, Kaitlyn; Grassia, Fabio; Poliachik, Sandra L et al. (2018) Preservation of electrophysiological functional connectivity after partial corpus callosotomy: case report. J Neurosurg Pediatr 22:214-219 |
| Oleskiw, Timothy D; Nowack, Amy; Pasupathy, Anitha (2018) Joint coding of shape and blur in area V4. Nat Commun 9:466 |
| Abraham, Antony D; Fontaine, Harrison M; Song, Allisa J et al. (2018) ?-Opioid Receptor Activation in Dopamine Neurons Disrupts Behavioral Inhibition. Neuropsychopharmacology 43:362-372 |
| Grassia, Fabio; Poliakov, Andrew V; Poliachik, Sandra L et al. (2018) Changes in resting-state connectivity in pediatric temporal lobe epilepsy. J Neurosurg Pediatr 22:270-275 |
| Grimes, William N; Songco-Aguas, Adree; Rieke, Fred (2018) Parallel Processing of Rod and Cone Signals: Retinal Function and Human Perception. Annu Rev Vis Sci 4:123-141 |
| Casimo, Kaitlyn; Levinson, Lila H; Zanos, Stavros et al. (2017) An interspecies comparative study of invasive electrophysiological functional connectivity. Brain Behav 7:e00863 |
| Casimo, Kaitlyn; Weaver, Kurt E; Wander, Jeremiah et al. (2017) BCI Use and Its Relation to Adaptation in Cortical Networks. IEEE Trans Neural Syst Rehabil Eng 25:1697-1704 |
| Vincent, Joris; Kale, Alex M; Buck, Steven L (2016) Luminance-dependent long-term chromatic adaptation. J Opt Soc Am A Opt Image Sci Vis 33:A164-9 |
| Schmidt, Brian P; Touch, Phanith; Neitz, Maureen et al. (2016) Circuitry to explain how the relative number of L and M cones shapes color experience. J Vis 16:18 |
| Weaver, Kurt E; Wander, Jeremiah D; Ko, Andrew L et al. (2016) Directional patterns of cross frequency phase and amplitude coupling within the resting state mimic patterns of fMRI functional connectivity. Neuroimage 128:238-251 |
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