Selective spiking in neuronal populations

Anirban Nandi, Heinz Schattler, Shinung Ching

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

The use of extrinsic stimulation to control activity in neuronal networks i.e., neurocontrol, is a key problem in control engineering and neuroscience. Here, we study the general problem of selective spiking in a population of neurons. The goal is to use an input stimulus in order to induce a spike in a specific neuron of a population while keeping all others suppressed. We formulate a strict version of this problem for the class of Integrate-and-Fire neuron models, which amounts to an optimal control problem with state constraints. While possible to solve in low dimensions, the strict problem is harder to handle for larger networks. Thus, we relax the problem via regularization and derive the ensuing optimal controls for selective spiking. The properties of the solution are highlighted through several examples. The results provide a tractable, scalable solution for a baseline neurocontrol problem.

Original languageEnglish
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2811-2816
Number of pages6
ISBN (Electronic)9781509059928
DOIs
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Conference

Conference2017 American Control Conference, ACC 2017
Country/TerritoryUnited States
CitySeattle
Period05/24/1705/26/17

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