Spontaneous and Perturbational Complexity in Cortical Cultures.

complexity cortical networks electrical stimulation in vitro local field potentials (LFP) micro-electrode array (MEA) perturbational complexity index (PCI) spikes

Journal

Brain sciences
ISSN: 2076-3425
Titre abrégé: Brain Sci
Pays: Switzerland
ID NLM: 101598646

Informations de publication

Date de publication:
01 Nov 2021
Historique:
received: 29 09 2021
revised: 27 10 2021
accepted: 27 10 2021
entrez: 27 11 2021
pubmed: 28 11 2021
medline: 28 11 2021
Statut: epublish

Résumé

Dissociated cortical neurons in vitro display spontaneously synchronized, low-frequency firing patterns, which can resemble the slow wave oscillations characterizing sleep in vivo. Experiments in humans, rodents, and cortical slices have shown that awakening or the administration of activating neuromodulators decrease slow waves, while increasing the spatio-temporal complexity of responses to perturbations. In this study, we attempted to replicate those findings using in vitro cortical cultures coupled with micro-electrode arrays and chemically treated with carbachol (CCh), to modulate sleep-like activity and suppress slow oscillations. We adapted metrics such as neural complexity (NC) and the perturbational complexity index (PCI), typically employed in animal and human brain studies, to quantify complexity in simplified, unstructured networks, both during resting state and in response to electrical stimulation. After CCh administration, we found a decrease in the amplitude of the initial response and a marked enhancement of the complexity during spontaneous activity. Crucially, unlike in cortical slices and intact brains, PCI in cortical cultures displayed only a moderate increase. This dissociation suggests that PCI, a measure of the complexity of causal interactions, requires more than activating neuromodulation and that additional factors, such as an appropriate circuit architecture, may be necessary. Exploring more structured in vitro networks, characterized by the presence of strong lateral connections, recurrent excitation, and feedback loops, may thus help to identify the features that are more relevant to support causal complexity.

Identifiants

pubmed: 34827452
pii: brainsci11111453
doi: 10.3390/brainsci11111453
pmc: PMC8615728
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Ilaria Colombi (I)

Brain Development and Disease Laboratory, Istituto Italiano di Tecnologia, 16163 Genova, Italy.

Thierry Nieus (T)

Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, 20157 Milan, Italy.

Marcello Massimini (M)

Department of Biomedical and Clinical Sciences "L. Sacco", University of Milan, 20157 Milan, Italy.
IRCCS, Fondazione Don Carlo Gnocchi, 20148 Milan, Italy.

Michela Chiappalone (M)

Department of Informatics, Bioengineering, Robotics and System Engineering, 16145 Genova, Italy.
Rehab Technologies Lab., Istituto Italiano di Tecnologia, 16163 Genova, Italy.

Classifications MeSH