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Modularity and neuronal heterogeneity: Two properties that influence in vitro neuropharmacological experiments

INTRODUCTION: The goal of this work is to prove the relevance of the experimental model (in vitro neuronal networks in this study) when drug-delivery testing is performed. METHODS: We used dissociated cortical and hippocampal neurons coupled to Micro-Electrode Arrays (MEAs) arranged in different con...

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Detalles Bibliográficos
Autores principales: Brofiga, Martina, Poggio, Fabio, Callegari, Francesca, Tedesco, Mariateresa, Massobrio, Paolo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10067731/
https://www.ncbi.nlm.nih.gov/pubmed/37020847
http://dx.doi.org/10.3389/fncel.2023.1147381
Descripción
Sumario:INTRODUCTION: The goal of this work is to prove the relevance of the experimental model (in vitro neuronal networks in this study) when drug-delivery testing is performed. METHODS: We used dissociated cortical and hippocampal neurons coupled to Micro-Electrode Arrays (MEAs) arranged in different configurations characterized by modularity (i.e., the presence of interconnected sub-networks) and heterogeneity (i.e., the co-existence of neurons coming from brain districts). We delivered increasing concentrations of bicuculline (BIC), a neuromodulator acting on the GABAergic system, and we extracted the IC(50) values (i.e., the effective concentration yielding a reduction in the response by 50%) of the mean firing rate for each configuration. RESULTS: We found significant lower values of the IC(50) computed for modular cortical-hippocampal ensembles than isolated cortical or hippocampal ones. DISCUSSION: Although tested with a specific neuromodulator, this work aims at proving the relevance of ad hoc experimental models to perform neuropharmacological experiments to avoid errors of overestimation/underestimation leading to biased information in the characterization of the effects of a drug on neuronal networks.