A model of variability in brain stimulation evoked responses.

dc.contributor.author

Goetz, SM

dc.contributor.author

Peterchev, AV

dc.date.accessioned

2021-12-13T11:33:50Z

dc.date.available

2021-12-13T11:33:50Z

dc.date.issued

2012

dc.date.updated

2021-12-13T11:33:49Z

dc.description.abstract

The input-output (IO) curve of cortical neuron populations is a key measure of neural excitability and is related to other response measures including the motor threshold which is widely used for individualization of neurostimulation techniques, such as transcranial magnetic stimulation (TMS). The IO curve parameters provide biomarkers for changes in the state of the target neural population that could result from neurostimulation, pharmacological interventions, or neurological and psychiatric conditions. Conventional analyses of IO data assume a sigmoidal shape with additive Gaussian scattering that allows simple regression modeling. However, careful study of the IO curve characteristics reveals that simple additive noise does not account for the observed IO variability. We propose a consistent model that adds a second source of intrinsic variability on the input side of the IO response. We develop an appropriate mathematical method for calibrating this new nonlinear model. Finally, the modeling framework is applied to a representative IO data set. With this modeling approach, previously inexplicable stochastic behavior becomes obvious. This work could lead to improved algorithms for estimation of various excitability parameters including established measures such as the motor threshold and the IO slope, as well as novel measures relating to the variability characteristics of the IO response that could provide additional insight into the state of the targeted neural population.

dc.identifier.issn

1557-170X

dc.identifier.uri

https://hdl.handle.net/10161/24068

dc.relation.ispartof

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference

dc.relation.isversionof

10.1109/EMBC.2012.6347467

dc.title

A model of variability in brain stimulation evoked responses.

dc.type

Journal article

duke.contributor.orcid

Peterchev, AV|0000-0002-4385-065X

pubs.begin-page

6434

pubs.end-page

6437

pubs.organisational-group

School of Medicine

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Biomedical Engineering

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Electrical and Computer Engineering

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Duke Institute for Brain Sciences

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Nicholas Institute-Energy Initiative

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Neurosurgery

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Duke

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Pratt School of Engineering

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University Institutes and Centers

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Institutes and Provost's Academic Units

pubs.organisational-group

Clinical Science Departments

pubs.volume

2012

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