Nonlinear modeling of neural population dynamics for hippocampal prostheses |
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| Authors: | Dong Song Rosa HM Chan Vasilis Z Marmarelis Robert E Hampson Sam A Deadwyler Theodore W Berger |
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| Institution: | 1. Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA;2. Center for Neural Engineering, University of Southern California, Los Angeles, CA 90089, USA;3. Program in Neuroscience, University of Southern California, Los Angeles, CA 90089, USA;4. Department of Physiology & Pharmacology, Wake Forest University, School of Medicine, Winston-Salem, NC 27157, USA;1. Communications and Computer Research Center, Ferdowsi University of Mashhad, Iran;2. Department of Electrical Engineering, Ferdowsi University of Mashhad, Iran;1. Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States;2. EpilepsyAI, LLC, San Francisco, CA, United States;3. Department of Neurology, Montefiore Medical Center/Albert Einstein College of Medicine, New York, NY, United States;4. Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland;5. Clinical Epilepsy Section, National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health (NIH), Bethesda, MD, United States;6. Seizure Tracker, LLC, Springfield, VA, United States;7. Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA, United States;1. Beijing Neurosurgical Institute, Capital Medical University, Beijing, China;2. Tsinghua University, Beijing, China;3. Beijing Tantan Hospital, Capital Medical University, Beijing, China;1. State Key Laboratory Breeding Base of Eco-Environment and Bio-Resource of the Three Gorges Area, Key Laboratory of Eco-Environments in Three Gorges Reservoir Region, Ministry of Education, School of Life Sciences, Institute of Modern Biopharmaceuticals, Southwest University, Chongqing, PR China;2. Department of Biotechnology, Faculty of Science and Technology, Omdurman Islamic University, Omdurman, Khartoum, Sudan;3. Department of Botany and Microbiology, Faculty of Science, Al-Azhar University Assuit branch, Egypt |
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| Abstract: | Developing a neural prosthesis for the damaged hippocampus requires restoring the transformation of population neural activities performed by the hippocampal circuitry. To bypass a damaged region, output spike trains need to be predicted from the input spike trains and then reinstated through stimulation. We formulate a multiple-input, multiple-output (MIMO) nonlinear dynamic model for the input–output transformation of spike trains. In this approach, a MIMO model comprises a series of physiologically-plausible multiple-input, single-output (MISO) neuron models that consist of five components each: (1) feedforward Volterra kernels transforming the input spike trains into the synaptic potential, (2) a feedback kernel transforming the output spikes into the spike-triggered after-potential, (3) a noise term capturing the system uncertainty, (4) an adder generating the pre-threshold potential, and (5) a threshold function generating output spikes. It is shown that this model is equivalent to a generalized linear model with a probit link function. To reduce model complexity and avoid overfitting, statistical model selection and cross-validation methods are employed to choose the significant inputs and interactions between inputs. The model is applied successfully to the hippocampal CA3–CA1 population dynamics. Such a model can serve as a computational basis for the development of hippocampal prostheses. |
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