Design of optimal stimulation patterns for neuronal ensembles based on Volterra-type hierarchical modeling
Identifieur interne : 000413 ( Main/Exploration ); précédent : 000412; suivant : 000414Design of optimal stimulation patterns for neuronal ensembles based on Volterra-type hierarchical modeling
Auteurs : V Z Marmarelis [États-Unis] ; D C Shin [États-Unis] ; R E Hampson [États-Unis] ; S A Deadwyler [États-Unis] ; D. Song [États-Unis] ; T W Berger [États-Unis]Source :
- Journal of Neural Engineering [ 1741-2560 ] ; 2012-12.
English descriptors
- Entity :
- org : DARPA, Department of Biomedical Engineering, Department of Physiology and Pharmacology, IOP Publishing Ltd, Neuroscience, Center for Neural Engineering, Triangle Biosystems, Inc., University of Southern California, University of Southern California, Los Angeles, Wake Forest University, Wake-Forest University.
- pers : Deadwyler, Hampson, Resource.
- place : Durham, NC, Salem, UK, Volterra.
- Teeft :
- Alternate hypothesis, Baseline, Behavioral outcome, Blue line, Chan, Computational evaluation, Control experiment, Conventional histogram, Correct response, Datum, Deadwyler, Delay phase, Different neuron, Dnms, Dnms task, Experimental datum, Gure, Hampson, Hippocampal, Hippocampus, Histogram, Ieee, Incorrect response, Marmarelis, Methodology, Modeling, Monte carlo simulation, Negative value, Neural, Neural syst, Neuron, Neuronal, Neuronal activity, Neuronal ensemble, Nonlinear, Nonlinear modeling, Nonmatch, Nonmatch response, Null hypothesis, Omusp, Omusp spike, Optimal stimulation pattern, Prosthesis, Random spontaneous activity, Random stimulation, Reference event, Right column, Ring rate, Rodent, Sample phase, Sample presentation, Search segment, Southern california, Spike, Spontaneous activity, Stimulation pattern, Stimulation pulse, Stimulation spike, Tlf1, Tlf1s, Tlf2 value, Tlf2s, Tlfs, Utility function.
Abstract
This paper presents a general methodology for the optimal design of stimulation patterns applied to neuronal ensembles in order to elicit a desired effect. The methodology follows a variant of the hierarchical Volterra modeling approach that utilizes inputoutput data to construct predictive models that describe the effects of interactions among multiple input events in an ascending order of interaction complexity. The illustrative example presented in this paper concerns the multi-unit activity of CA1 neurons in the hippocampus of a rodent performing a learned delayed-nonmatch-to-sample (DNMS) task. The multi-unit activity of the hippocampal CA1 neurons is recorded via chronically implanted multi-electrode arrays during this task. The obtained model quantifies the likelihood of having correct performance of the specific task for a given multi-unit (spatiotemporal) activity pattern of a CA1 neuronal ensemble during the sample presentation phase of the DNMS task. The model can be used to determine computationally (off-line) the optimal multi-unit stimulation pattern that maximizes the likelihood of inducing the correct performance of the DNMS task. Our working hypothesis is that application of this optimal stimulation pattern will enhance performance of the DNMS task due to enhancement of memory formation and storage during the sample presentation phase of the task.
Url:
DOI: 10.1088/1741-2560/9/6/066003
Affiliations:
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Song</name></author><author><name sortKey="Berger, T W" sort="Berger, T W" uniqKey="Berger T" first="T W" last="Berger">T W Berger</name></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:DA0F8E4B3F5CE422C6DEA1E8FD339A4C9826A69E</idno><date when="2012" year="2012">2012</date><idno type="doi">10.1088/1741-2560/9/6/066003</idno><idno type="url">https://api.istex.fr/ark:/67375/0T8-720PLQ61-G/fulltext.pdf</idno><idno type="wicri:Area/Istex/Corpus">001485</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">001485</idno><idno type="wicri:Area/Istex/Curation">001397</idno><idno type="wicri:Area/Istex/Checkpoint">000382</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Checkpoint">000382</idno><idno type="wicri:doubleKey">1741-2560:2012:Marmarelis V:design:of:optimal</idno><idno type="wicri:Area/Main/Merge">000415</idno><idno type="wicri:Area/Main/Curation">000413</idno><idno type="wicri:Area/Main/Exploration">000413</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a">Design of optimal stimulation patterns for neuronal ensembles based on Volterra-type hierarchical modeling</title><author><name sortKey="Marmarelis, V Z" sort="Marmarelis, V Z" uniqKey="Marmarelis V" first="V Z" last="Marmarelis">V Z Marmarelis</name><affiliation wicri:level="4"><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering and the Biomedical Simulations Resource (BMSR), University of Southern California, Los Angeles, CA 90089</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Los Angeles</settlement></placeName><orgName type="university">Université de Californie du Sud</orgName></affiliation><affiliation wicri:level="1"><country wicri:rule="url">États-Unis</country></affiliation></author><author><name sortKey="Shin, D C" sort="Shin, D C" uniqKey="Shin D" first="D C" last="Shin">D C Shin</name><affiliation wicri:level="4"><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering and the Biomedical Simulations Resource (BMSR), University of Southern California, Los Angeles, CA 90089</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Los Angeles</settlement></placeName><orgName type="university">Université de Californie du Sud</orgName></affiliation></author><author><name sortKey="Hampson, R E" sort="Hampson, R E" uniqKey="Hampson R" first="R E" last="Hampson">R E Hampson</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Physiology and Pharmacology, Wake Forest University, School of Medicine, Winston-Salem, NC 27157</wicri:regionArea><placeName><region type="state">Caroline du Nord</region></placeName></affiliation></author><author><name sortKey="Deadwyler, S A" sort="Deadwyler, S A" uniqKey="Deadwyler S" first="S A" last="Deadwyler">S A Deadwyler</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Physiology and Pharmacology, Wake Forest University, School of Medicine, Winston-Salem, NC 27157</wicri:regionArea><placeName><region type="state">Caroline du Nord</region></placeName></affiliation></author><author><name sortKey="Song, D" sort="Song, D" uniqKey="Song D" first="D" last="Song">D. Song</name><affiliation wicri:level="4"><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering and the Program in Neuroscience, Center for Neural Engineering, University of Southern California, Los Angeles, CA 90089</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Los Angeles</settlement></placeName><orgName type="university">Université de Californie du Sud</orgName></affiliation></author><author><name sortKey="Berger, T W" sort="Berger, T W" uniqKey="Berger T" first="T W" last="Berger">T W Berger</name><affiliation wicri:level="4"><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biomedical Engineering and the Program in Neuroscience, Center for Neural Engineering, University of Southern California, Los Angeles, CA 90089</wicri:regionArea><placeName><region type="state">Californie</region><settlement type="city">Los Angeles</settlement></placeName><orgName type="university">Université de Californie du Sud</orgName></affiliation></author></analytic><monogr></monogr><series><title level="j">Journal of Neural Engineering</title><idno type="ISSN">1741-2560</idno><idno type="eISSN">1741-2552</idno><imprint><publisher>IOP Publishing</publisher><date type="published" when="2012-12">2012-12</date><biblScope unit="volume">9</biblScope><biblScope unit="issue">6</biblScope></imprint><idno type="ISSN">1741-2560</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">1741-2560</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="Entity" type="org" xml:lang="en"><term>DARPA</term><term>Department of Biomedical Engineering</term><term>Department of Physiology and Pharmacology</term><term>IOP Publishing Ltd</term><term>Neuroscience, Center for Neural Engineering</term><term>Triangle Biosystems, Inc.</term><term>University of Southern California</term><term>University of Southern California, Los Angeles</term><term>Wake Forest University</term><term>Wake-Forest University</term></keywords><keywords scheme="Entity" type="pers" xml:lang="en"><term>Deadwyler</term><term>Hampson</term><term>Resource</term></keywords><keywords scheme="Entity" type="place" xml:lang="en"><term>Durham</term><term>NC</term><term>Salem</term><term>UK</term><term>Volterra</term></keywords><keywords scheme="Teeft" xml:lang="en"><term>Alternate hypothesis</term><term>Baseline</term><term>Behavioral outcome</term><term>Blue line</term><term>Chan</term><term>Computational evaluation</term><term>Control experiment</term><term>Conventional histogram</term><term>Correct response</term><term>Datum</term><term>Deadwyler</term><term>Delay phase</term><term>Different neuron</term><term>Dnms</term><term>Dnms task</term><term>Experimental datum</term><term>Gure</term><term>Hampson</term><term>Hippocampal</term><term>Hippocampus</term><term>Histogram</term><term>Ieee</term><term>Incorrect response</term><term>Marmarelis</term><term>Methodology</term><term>Modeling</term><term>Monte carlo simulation</term><term>Negative value</term><term>Neural</term><term>Neural syst</term><term>Neuron</term><term>Neuronal</term><term>Neuronal activity</term><term>Neuronal ensemble</term><term>Nonlinear</term><term>Nonlinear modeling</term><term>Nonmatch</term><term>Nonmatch response</term><term>Null hypothesis</term><term>Omusp</term><term>Omusp spike</term><term>Optimal stimulation pattern</term><term>Prosthesis</term><term>Random spontaneous activity</term><term>Random stimulation</term><term>Reference event</term><term>Right column</term><term>Ring rate</term><term>Rodent</term><term>Sample phase</term><term>Sample presentation</term><term>Search segment</term><term>Southern california</term><term>Spike</term><term>Spontaneous activity</term><term>Stimulation pattern</term><term>Stimulation pulse</term><term>Stimulation spike</term><term>Tlf1</term><term>Tlf1s</term><term>Tlf2 value</term><term>Tlf2s</term><term>Tlfs</term><term>Utility function</term></keywords></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract">This paper presents a general methodology for the optimal design of stimulation patterns applied to neuronal ensembles in order to elicit a desired effect. The methodology follows a variant of the hierarchical Volterra modeling approach that utilizes inputoutput data to construct predictive models that describe the effects of interactions among multiple input events in an ascending order of interaction complexity. The illustrative example presented in this paper concerns the multi-unit activity of CA1 neurons in the hippocampus of a rodent performing a learned delayed-nonmatch-to-sample (DNMS) task. The multi-unit activity of the hippocampal CA1 neurons is recorded via chronically implanted multi-electrode arrays during this task. The obtained model quantifies the likelihood of having correct performance of the specific task for a given multi-unit (spatiotemporal) activity pattern of a CA1 neuronal ensemble during the sample presentation phase of the DNMS task. The model can be used to determine computationally (off-line) the optimal multi-unit stimulation pattern that maximizes the likelihood of inducing the correct performance of the DNMS task. Our working hypothesis is that application of this optimal stimulation pattern will enhance performance of the DNMS task due to enhancement of memory formation and storage during the sample presentation phase of the task.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Californie</li><li>Caroline du Nord</li></region><settlement><li>Los Angeles</li></settlement><orgName><li>Université de Californie du Sud</li></orgName></list><tree><country name="États-Unis"><region name="Californie"><name sortKey="Marmarelis, V Z" sort="Marmarelis, V Z" uniqKey="Marmarelis V" first="V Z" last="Marmarelis">V Z Marmarelis</name></region><name sortKey="Berger, T W" sort="Berger, T W" uniqKey="Berger T" first="T W" last="Berger">T W Berger</name><name sortKey="Deadwyler, S A" sort="Deadwyler, S A" uniqKey="Deadwyler S" first="S A" last="Deadwyler">S A Deadwyler</name><name sortKey="Hampson, R E" sort="Hampson, R E" uniqKey="Hampson R" first="R E" last="Hampson">R E Hampson</name><name sortKey="Marmarelis, V Z" sort="Marmarelis, V Z" uniqKey="Marmarelis V" first="V Z" last="Marmarelis">V Z Marmarelis</name><name sortKey="Shin, D C" sort="Shin, D C" uniqKey="Shin D" first="D C" last="Shin">D C Shin</name><name sortKey="Song, D" sort="Song, D" uniqKey="Song D" first="D" last="Song">D. 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