Stochastic Optimal Control of Spike Times in Single Neurons
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Stochastic Optimal Control of Spike Times in Single Neurons. / Iolov, A.; Ditlevsen, S.; Longtin, A.
Closed Loop Neuroscience. Elsevier, 2016. s. 101-111.Publikation: Bidrag til bog/antologi/rapport › Bidrag til bog/antologi › Forskning › fagfællebedømt
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TY - CHAP
T1 - Stochastic Optimal Control of Spike Times in Single Neurons
AU - Iolov, A.
AU - Ditlevsen, S.
AU - Longtin, A.
PY - 2016/9/29
Y1 - 2016/9/29
N2 - We consider the application of optimal control techniques to stochastic models of neural firing. There can be many goals for such control. Here we focus on the targeting of the spiking times of the cell, using a time-varying current applied additively to the current balance equation.We review the theory behind the maximum principle for stochastic optimal control, as well as the challenges posed by its numerical implementation. We then discuss dynamic programming methods for such control, and illustrate its implementation for spike time targeting in the leaky integrate-and-fire model with additive Gaussian white noise. The technique is described in the context where the controller has access to the ongoing voltage. The case where only spike times are available is briefly discussed, along with an outlook into future challenges in designing controls for threshold crossing in drift-diffusion processes.
AB - We consider the application of optimal control techniques to stochastic models of neural firing. There can be many goals for such control. Here we focus on the targeting of the spiking times of the cell, using a time-varying current applied additively to the current balance equation.We review the theory behind the maximum principle for stochastic optimal control, as well as the challenges posed by its numerical implementation. We then discuss dynamic programming methods for such control, and illustrate its implementation for spike time targeting in the leaky integrate-and-fire model with additive Gaussian white noise. The technique is described in the context where the controller has access to the ongoing voltage. The case where only spike times are available is briefly discussed, along with an outlook into future challenges in designing controls for threshold crossing in drift-diffusion processes.
KW - Morris-Lecar model
KW - Noise
KW - Ornstein-Uhlenbeck process
KW - Single neuron
KW - Spike times
KW - Stochastic optimal control
UR - http://www.scopus.com/inward/record.url?scp=85021963937&partnerID=8YFLogxK
U2 - 10.1016/B978-0-12-802452-2.00008-1
DO - 10.1016/B978-0-12-802452-2.00008-1
M3 - Book chapter
AN - SCOPUS:85021963937
SN - 9780128024522
SP - 101
EP - 111
BT - Closed Loop Neuroscience
PB - Elsevier
ER -
ID: 231900399