Multivariate autoregressive models with exogenous inputs for intracerebral responses to direct electrical stimulation of the human brain

Jui Yang Chang, Andrea Pigorini, Marcello Massimini, Giulio Tononi, Lino Nobili, Barry D. Van Veen

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

A multivariate autoregressive model with exogenous inputs is developed for describing the cortical interactions excited by direct electrical current stimulation of the cortex. Current stimulation is challenging to model because it excites neurons in multiple locations both near and distant to the stimulation site. The approach presented here models these effects using an exogenous input that is passed through a bank of filters, one for each channel. The filtered input and a random input excite a multivariate autoregressive system describing the interactions between cortical activity at the recording sites. The exogenous input filter coefficients, the autoregressive coefficients, and random input characteristics are estimated from the measured activity due to current stimulation. The effectiveness of the approach is demonstrated using intracranial recordings from three surgical epilepsy patients. We evaluate models for wakefulness and NREM sleep in these patients with two stimulation levels in one patient and two stimulation sites in another resulting in a total of ten datasets. Excellent agreement between measured and model-predicted evoked responses is obtained across all datasets. Furthermore, one-step prediction is used to show that the model also describes dynamics in prestimulus and evoked recordings. We also compare integrated information a measure of intracortical communication thought to reflect the capacity for consciousness associated with the network model in wakefulness and sleep. As predicted, higher information integration is found in wakefulness than in sleep for all five cases.

Original languageEnglish
JournalFrontiers in Human Neuroscience
Issue numberNOVEMBER 2012
DOIs
Publication statusPublished - Nov 7 2012

Fingerprint

Deep Brain Stimulation
Wakefulness
Sleep
Consciousness
Electric Stimulation
Epilepsy
Communication
Neurons
Datasets

Keywords

  • Cross-validation
  • Evoked response
  • Integrated information
  • Intracerebal EEG
  • MVARX model

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Neurology
  • Biological Psychiatry
  • Behavioral Neuroscience
  • Neuropsychology and Physiological Psychology

Cite this

Multivariate autoregressive models with exogenous inputs for intracerebral responses to direct electrical stimulation of the human brain. / Chang, Jui Yang; Pigorini, Andrea; Massimini, Marcello; Tononi, Giulio; Nobili, Lino; Van Veen, Barry D.

In: Frontiers in Human Neuroscience, No. NOVEMBER 2012, 07.11.2012.

Research output: Contribution to journalArticle

@article{41a54bd1c26e40a4b790bfa569301a09,
title = "Multivariate autoregressive models with exogenous inputs for intracerebral responses to direct electrical stimulation of the human brain",
abstract = "A multivariate autoregressive model with exogenous inputs is developed for describing the cortical interactions excited by direct electrical current stimulation of the cortex. Current stimulation is challenging to model because it excites neurons in multiple locations both near and distant to the stimulation site. The approach presented here models these effects using an exogenous input that is passed through a bank of filters, one for each channel. The filtered input and a random input excite a multivariate autoregressive system describing the interactions between cortical activity at the recording sites. The exogenous input filter coefficients, the autoregressive coefficients, and random input characteristics are estimated from the measured activity due to current stimulation. The effectiveness of the approach is demonstrated using intracranial recordings from three surgical epilepsy patients. We evaluate models for wakefulness and NREM sleep in these patients with two stimulation levels in one patient and two stimulation sites in another resulting in a total of ten datasets. Excellent agreement between measured and model-predicted evoked responses is obtained across all datasets. Furthermore, one-step prediction is used to show that the model also describes dynamics in prestimulus and evoked recordings. We also compare integrated information a measure of intracortical communication thought to reflect the capacity for consciousness associated with the network model in wakefulness and sleep. As predicted, higher information integration is found in wakefulness than in sleep for all five cases.",
keywords = "Cross-validation, Evoked response, Integrated information, Intracerebal EEG, MVARX model",
author = "Chang, {Jui Yang} and Andrea Pigorini and Marcello Massimini and Giulio Tononi and Lino Nobili and {Van Veen}, {Barry D.}",
year = "2012",
month = "11",
day = "7",
doi = "10.3389/fnhum.2012.00317",
language = "English",
journal = "Frontiers in Human Neuroscience",
issn = "1662-5161",
publisher = "Frontiers Media S. A.",
number = "NOVEMBER 2012",

}

TY - JOUR

T1 - Multivariate autoregressive models with exogenous inputs for intracerebral responses to direct electrical stimulation of the human brain

AU - Chang, Jui Yang

AU - Pigorini, Andrea

AU - Massimini, Marcello

AU - Tononi, Giulio

AU - Nobili, Lino

AU - Van Veen, Barry D.

PY - 2012/11/7

Y1 - 2012/11/7

N2 - A multivariate autoregressive model with exogenous inputs is developed for describing the cortical interactions excited by direct electrical current stimulation of the cortex. Current stimulation is challenging to model because it excites neurons in multiple locations both near and distant to the stimulation site. The approach presented here models these effects using an exogenous input that is passed through a bank of filters, one for each channel. The filtered input and a random input excite a multivariate autoregressive system describing the interactions between cortical activity at the recording sites. The exogenous input filter coefficients, the autoregressive coefficients, and random input characteristics are estimated from the measured activity due to current stimulation. The effectiveness of the approach is demonstrated using intracranial recordings from three surgical epilepsy patients. We evaluate models for wakefulness and NREM sleep in these patients with two stimulation levels in one patient and two stimulation sites in another resulting in a total of ten datasets. Excellent agreement between measured and model-predicted evoked responses is obtained across all datasets. Furthermore, one-step prediction is used to show that the model also describes dynamics in prestimulus and evoked recordings. We also compare integrated information a measure of intracortical communication thought to reflect the capacity for consciousness associated with the network model in wakefulness and sleep. As predicted, higher information integration is found in wakefulness than in sleep for all five cases.

AB - A multivariate autoregressive model with exogenous inputs is developed for describing the cortical interactions excited by direct electrical current stimulation of the cortex. Current stimulation is challenging to model because it excites neurons in multiple locations both near and distant to the stimulation site. The approach presented here models these effects using an exogenous input that is passed through a bank of filters, one for each channel. The filtered input and a random input excite a multivariate autoregressive system describing the interactions between cortical activity at the recording sites. The exogenous input filter coefficients, the autoregressive coefficients, and random input characteristics are estimated from the measured activity due to current stimulation. The effectiveness of the approach is demonstrated using intracranial recordings from three surgical epilepsy patients. We evaluate models for wakefulness and NREM sleep in these patients with two stimulation levels in one patient and two stimulation sites in another resulting in a total of ten datasets. Excellent agreement between measured and model-predicted evoked responses is obtained across all datasets. Furthermore, one-step prediction is used to show that the model also describes dynamics in prestimulus and evoked recordings. We also compare integrated information a measure of intracortical communication thought to reflect the capacity for consciousness associated with the network model in wakefulness and sleep. As predicted, higher information integration is found in wakefulness than in sleep for all five cases.

KW - Cross-validation

KW - Evoked response

KW - Integrated information

KW - Intracerebal EEG

KW - MVARX model

UR - http://www.scopus.com/inward/record.url?scp=84933677329&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84933677329&partnerID=8YFLogxK

U2 - 10.3389/fnhum.2012.00317

DO - 10.3389/fnhum.2012.00317

M3 - Article

JO - Frontiers in Human Neuroscience

JF - Frontiers in Human Neuroscience

SN - 1662-5161

IS - NOVEMBER 2012

ER -