A fast and general method to empirically estimate the complexity of brain responses to transcranial and intracranial stimulations

Renzo Comolatti, Andrea Pigorini, Silvia Casarotto, Matteo Fecchio, Guilherme Faria, Simone Sarasso, Mario Rosanova, Olivia Gosseries, Mélanie Boly, Olivier Bodart, Didier Ledoux, Jean François Brichant, Lino Nobili, Steven Laureys, Giulio Tononi, Marcello Massimini, Adenauer G. Casali

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: The Perturbational Complexity Index (PCI)was recently introduced to assess the capacity of thalamocortical circuits to engage in complex patterns of causal interactions. While showing high accuracy in detecting consciousness in brain-injured patients, PCI depends on elaborate experimental setups and offline processing, and has restricted applicability to other types of brain signals beyond transcranial magnetic stimulation and high-density EEG (TMS/hd-EEG)recordings. Objective: We aim to address these limitations by introducing PCIST, a fast method for estimating perturbational complexity of any given brain response signal. Methods: PCIST is based on dimensionality reduction and state transitions (ST)quantification of evoked potentials. The index was validated on a large dataset of TMS/hd-EEG recordings obtained from 108 healthy subjects and 108 brain-injured patients, and tested on sparse intracranial recordings (SEEG)of 9 patients undergoing intracranial single-pulse electrical stimulation (SPES)during wakefulness and sleep. Results: When calculated on TMS/hd-EEG potentials, PCIST performed with the same accuracy as the original PCI, while improving on the previous method by being computed in less than a second and requiring a simpler set-up. In SPES/SEEG signals, the index was able to quantify a systematic reduction of intracranial complexity during sleep, confirming the occurrence of state-dependent changes in the effective connectivity of thalamocortical circuits, as originally assessed through TMS/hd-EEG. Conclusions: PCIST represents a fundamental advancement towards the implementation of a reliable and fast clinical tool for the bedside assessment of consciousness as well as a general measure to explore the neuronal mechanisms of loss/recovery of brain complexity across scales and models.

Original languageEnglish
JournalBrain Stimulation
DOIs
Publication statusPublished - Jan 1 2019

Fingerprint

Transcranial Magnetic Stimulation
Electroencephalography
Brain
Consciousness
Electric Stimulation
Sleep
Wakefulness
Evoked Potentials
Healthy Volunteers

Keywords

  • Brain complexity
  • Consciousness
  • EEG
  • Intracranial
  • Single pulse electrical stimulation
  • Transcranial magnetic stimulation

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biophysics
  • Clinical Neurology

Cite this

A fast and general method to empirically estimate the complexity of brain responses to transcranial and intracranial stimulations. / Comolatti, Renzo; Pigorini, Andrea; Casarotto, Silvia; Fecchio, Matteo; Faria, Guilherme; Sarasso, Simone; Rosanova, Mario; Gosseries, Olivia; Boly, Mélanie; Bodart, Olivier; Ledoux, Didier; Brichant, Jean François; Nobili, Lino; Laureys, Steven; Tononi, Giulio; Massimini, Marcello; Casali, Adenauer G.

In: Brain Stimulation, 01.01.2019.

Research output: Contribution to journalArticle

Comolatti, R, Pigorini, A, Casarotto, S, Fecchio, M, Faria, G, Sarasso, S, Rosanova, M, Gosseries, O, Boly, M, Bodart, O, Ledoux, D, Brichant, JF, Nobili, L, Laureys, S, Tononi, G, Massimini, M & Casali, AG 2019, 'A fast and general method to empirically estimate the complexity of brain responses to transcranial and intracranial stimulations', Brain Stimulation. https://doi.org/10.1016/j.brs.2019.05.013
Comolatti, Renzo ; Pigorini, Andrea ; Casarotto, Silvia ; Fecchio, Matteo ; Faria, Guilherme ; Sarasso, Simone ; Rosanova, Mario ; Gosseries, Olivia ; Boly, Mélanie ; Bodart, Olivier ; Ledoux, Didier ; Brichant, Jean François ; Nobili, Lino ; Laureys, Steven ; Tononi, Giulio ; Massimini, Marcello ; Casali, Adenauer G. / A fast and general method to empirically estimate the complexity of brain responses to transcranial and intracranial stimulations. In: Brain Stimulation. 2019.
@article{6ad64e481f6e4e05b3edb88b0f6cd54d,
title = "A fast and general method to empirically estimate the complexity of brain responses to transcranial and intracranial stimulations",
abstract = "Background: The Perturbational Complexity Index (PCI)was recently introduced to assess the capacity of thalamocortical circuits to engage in complex patterns of causal interactions. While showing high accuracy in detecting consciousness in brain-injured patients, PCI depends on elaborate experimental setups and offline processing, and has restricted applicability to other types of brain signals beyond transcranial magnetic stimulation and high-density EEG (TMS/hd-EEG)recordings. Objective: We aim to address these limitations by introducing PCIST, a fast method for estimating perturbational complexity of any given brain response signal. Methods: PCIST is based on dimensionality reduction and state transitions (ST)quantification of evoked potentials. The index was validated on a large dataset of TMS/hd-EEG recordings obtained from 108 healthy subjects and 108 brain-injured patients, and tested on sparse intracranial recordings (SEEG)of 9 patients undergoing intracranial single-pulse electrical stimulation (SPES)during wakefulness and sleep. Results: When calculated on TMS/hd-EEG potentials, PCIST performed with the same accuracy as the original PCI, while improving on the previous method by being computed in less than a second and requiring a simpler set-up. In SPES/SEEG signals, the index was able to quantify a systematic reduction of intracranial complexity during sleep, confirming the occurrence of state-dependent changes in the effective connectivity of thalamocortical circuits, as originally assessed through TMS/hd-EEG. Conclusions: PCIST represents a fundamental advancement towards the implementation of a reliable and fast clinical tool for the bedside assessment of consciousness as well as a general measure to explore the neuronal mechanisms of loss/recovery of brain complexity across scales and models.",
keywords = "Brain complexity, Consciousness, EEG, Intracranial, Single pulse electrical stimulation, Transcranial magnetic stimulation",
author = "Renzo Comolatti and Andrea Pigorini and Silvia Casarotto and Matteo Fecchio and Guilherme Faria and Simone Sarasso and Mario Rosanova and Olivia Gosseries and M{\'e}lanie Boly and Olivier Bodart and Didier Ledoux and Brichant, {Jean Fran{\cc}ois} and Lino Nobili and Steven Laureys and Giulio Tononi and Marcello Massimini and Casali, {Adenauer G.}",
year = "2019",
month = "1",
day = "1",
doi = "10.1016/j.brs.2019.05.013",
language = "English",
journal = "Brain Stimulation",
issn = "1935-861X",
publisher = "Elsevier Inc.",

}

TY - JOUR

T1 - A fast and general method to empirically estimate the complexity of brain responses to transcranial and intracranial stimulations

AU - Comolatti, Renzo

AU - Pigorini, Andrea

AU - Casarotto, Silvia

AU - Fecchio, Matteo

AU - Faria, Guilherme

AU - Sarasso, Simone

AU - Rosanova, Mario

AU - Gosseries, Olivia

AU - Boly, Mélanie

AU - Bodart, Olivier

AU - Ledoux, Didier

AU - Brichant, Jean François

AU - Nobili, Lino

AU - Laureys, Steven

AU - Tononi, Giulio

AU - Massimini, Marcello

AU - Casali, Adenauer G.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Background: The Perturbational Complexity Index (PCI)was recently introduced to assess the capacity of thalamocortical circuits to engage in complex patterns of causal interactions. While showing high accuracy in detecting consciousness in brain-injured patients, PCI depends on elaborate experimental setups and offline processing, and has restricted applicability to other types of brain signals beyond transcranial magnetic stimulation and high-density EEG (TMS/hd-EEG)recordings. Objective: We aim to address these limitations by introducing PCIST, a fast method for estimating perturbational complexity of any given brain response signal. Methods: PCIST is based on dimensionality reduction and state transitions (ST)quantification of evoked potentials. The index was validated on a large dataset of TMS/hd-EEG recordings obtained from 108 healthy subjects and 108 brain-injured patients, and tested on sparse intracranial recordings (SEEG)of 9 patients undergoing intracranial single-pulse electrical stimulation (SPES)during wakefulness and sleep. Results: When calculated on TMS/hd-EEG potentials, PCIST performed with the same accuracy as the original PCI, while improving on the previous method by being computed in less than a second and requiring a simpler set-up. In SPES/SEEG signals, the index was able to quantify a systematic reduction of intracranial complexity during sleep, confirming the occurrence of state-dependent changes in the effective connectivity of thalamocortical circuits, as originally assessed through TMS/hd-EEG. Conclusions: PCIST represents a fundamental advancement towards the implementation of a reliable and fast clinical tool for the bedside assessment of consciousness as well as a general measure to explore the neuronal mechanisms of loss/recovery of brain complexity across scales and models.

AB - Background: The Perturbational Complexity Index (PCI)was recently introduced to assess the capacity of thalamocortical circuits to engage in complex patterns of causal interactions. While showing high accuracy in detecting consciousness in brain-injured patients, PCI depends on elaborate experimental setups and offline processing, and has restricted applicability to other types of brain signals beyond transcranial magnetic stimulation and high-density EEG (TMS/hd-EEG)recordings. Objective: We aim to address these limitations by introducing PCIST, a fast method for estimating perturbational complexity of any given brain response signal. Methods: PCIST is based on dimensionality reduction and state transitions (ST)quantification of evoked potentials. The index was validated on a large dataset of TMS/hd-EEG recordings obtained from 108 healthy subjects and 108 brain-injured patients, and tested on sparse intracranial recordings (SEEG)of 9 patients undergoing intracranial single-pulse electrical stimulation (SPES)during wakefulness and sleep. Results: When calculated on TMS/hd-EEG potentials, PCIST performed with the same accuracy as the original PCI, while improving on the previous method by being computed in less than a second and requiring a simpler set-up. In SPES/SEEG signals, the index was able to quantify a systematic reduction of intracranial complexity during sleep, confirming the occurrence of state-dependent changes in the effective connectivity of thalamocortical circuits, as originally assessed through TMS/hd-EEG. Conclusions: PCIST represents a fundamental advancement towards the implementation of a reliable and fast clinical tool for the bedside assessment of consciousness as well as a general measure to explore the neuronal mechanisms of loss/recovery of brain complexity across scales and models.

KW - Brain complexity

KW - Consciousness

KW - EEG

KW - Intracranial

KW - Single pulse electrical stimulation

KW - Transcranial magnetic stimulation

UR - http://www.scopus.com/inward/record.url?scp=85066103789&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85066103789&partnerID=8YFLogxK

U2 - 10.1016/j.brs.2019.05.013

DO - 10.1016/j.brs.2019.05.013

M3 - Article

AN - SCOPUS:85066103789

JO - Brain Stimulation

JF - Brain Stimulation

SN - 1935-861X

ER -