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

Autor(es):Mostrar menos -

Comolatti, Renzo ^[1] ; Pigorini, Andrea ^[2] ; Casarotto, Silvia ^[2] ; Fecchio, Matteo ^[2] ; Faria, Guilherme ^[1] ; Sarasso, Simone ^[2] ; Rosanova, Mario ^[2] ; Gosseries, Olivia ^{[3, 4]} ; Boly, Melanie ^[5] ; Bodart, Olivier ^{[3, 4]} ; Ledoux, Didier ^[3] ; Brichant, Jean-Francois ^[6] ; Nobili, Lino ^{[7, 8]} ; Laureys, Steven ^{[3, 4]} ; Tononi, Giulio ^[5] ; Massimini, Marcello ^{[2, 9]} ; Casali, Adenauer G. ^[1]

Afiliação do(s) autor(es)

^[1] Univ Fed Sao Paulo, Inst Sci & Technol, BR-12231280 Sao Jose Dos Campos - Brazil

^[2] Univ Milan, Dept Biomed & Clin Sci Luigi Sacco, I-20157 Milan - Italy

^[3] Univ Liege, GIGA Consciousness, GIGA Res, B-4000 Liege - Belgium

^[4] Univ Hosp Liege, Coma Sci Grp, B-4000 Liege - Belgium

^[5] Univ Wisconsin, Dept Psychiat, Madison, WI 53719 - USA

^[6] Univ Hosp Liege, Dept Anesthesia & Intens Care Med, B-4000 Liege - Belgium

^[7] Osped Niguarda Ca Granda, Ctr Epilepsy Surg C Munari, Dept Neurosci, I-20162 Milan - Italy

^[8] Univ Genoa, Child Neuropsychiat, IRCCS G Gaslini, DINOGMI, I-16147 Genoa - Italy

^[9] Fdn Don Carlo Gnocchi, Ist Ricovero & Cura Carattere Sci, I-20148 Milan - Italy

• Tipo de documento: Artigo Científico
• Fonte: BRAIN STIMULATION; v. 12, n. 5, p. 1280-1289, SEP-OCT 2019.
• Citações Web of Science: 1

Resumo

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. (C) 2019 Elsevier Inc. All rights reserved. (AU)

• Processo FAPESP: 16/08263-9 - Padronização, validação e caracterização de uma nova medida de complexidade cerebral
• Beneficiário: Adenauer Girardi Casali
• Modalidade de apoio: Auxílio à Pesquisa - Jovens Pesquisadores
• Processo FAPESP: 17/03678-9 - Padronização do índice de complexidade perturbacional para o estudo da conectividade efetiva talamocortical
• Beneficiário: Renzo Comolatti
• Modalidade de apoio: Bolsas no Brasil - Mestrado