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Phase-amplitude coupling between slow and high frequency EEG oscillations after peripheral nerve stimulation in humans

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Detalhes bibliográficos
Resumo:Amyotrophic Lateral Sclerosis (ALS) is a complex neurodegenerative syndrome affect- ing upper and lower motor neurons (UMN and LMN, respectively). Current diagnosis relies on evidence of simultaneous brain and spinal motor neuron degeneration, which is often imprecise due to the clinical challenge of recognising cortical dysfunctions. Muscle atrophy from LMN degeneration, frequently masks UMN symptoms, complicating the diagnosis and delaying treatment initiation. Transcranial Magnetic Stimulation (TMS) studies have identified an imbalanced exci- tation/inhibition (E/I) ratio in the early stages of ALS, indicating motor cortex hyperex- citability even before symptoms appear. However, this method is unreliable with disease progression, emphasizing the need for biomarkers that can consistently track cortical dysfunctions in order to enhance ALS diagnosis. It has been shown that theta-gamma phase-amplitude coupling (PAC) extracted from resting state electroencephalography (EEG) can serve as a neuromarker of early cortical dysfunctions in ALS. This suggests that EEG analysis, especially through PAC, can break new ground. The present study further explores beta-gamma PAC after peripheral nerve stimulation as a potential early biomarker for cortical dysfunctions in ALS. By exploring the effects of applied stimuli, the aim is to uncover valuable insights into disease evaluation, presenting a departure from previous approaches and methodologies. Coupling mean modulation index (MI) was assessed to estimate PAC between slow signals within the beta band (12-30 Hz), and higher frequency oscillations within the gamma band (30-100 Hz), at the level of 12 channels covering the sensorimotor cortex of both hemispheres. Results from linear mixed models show no significant differences between healthy and ALS patients, indicating that, through this method, a biomarker for early stage ALS disease cannot be detected in stimulated data.
Autores principais:Cardoso, Matilde de Vasconcelos
Assunto:ALS cortical dysfunctions biomarker EEG PAC
Ano:2024
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso aberto
Instituição associada:Universidade Nova de Lisboa
Idioma:inglês
Origem:Repositório Institucional da UNL
Descrição
Resumo:Amyotrophic Lateral Sclerosis (ALS) is a complex neurodegenerative syndrome affect- ing upper and lower motor neurons (UMN and LMN, respectively). Current diagnosis relies on evidence of simultaneous brain and spinal motor neuron degeneration, which is often imprecise due to the clinical challenge of recognising cortical dysfunctions. Muscle atrophy from LMN degeneration, frequently masks UMN symptoms, complicating the diagnosis and delaying treatment initiation. Transcranial Magnetic Stimulation (TMS) studies have identified an imbalanced exci- tation/inhibition (E/I) ratio in the early stages of ALS, indicating motor cortex hyperex- citability even before symptoms appear. However, this method is unreliable with disease progression, emphasizing the need for biomarkers that can consistently track cortical dysfunctions in order to enhance ALS diagnosis. It has been shown that theta-gamma phase-amplitude coupling (PAC) extracted from resting state electroencephalography (EEG) can serve as a neuromarker of early cortical dysfunctions in ALS. This suggests that EEG analysis, especially through PAC, can break new ground. The present study further explores beta-gamma PAC after peripheral nerve stimulation as a potential early biomarker for cortical dysfunctions in ALS. By exploring the effects of applied stimuli, the aim is to uncover valuable insights into disease evaluation, presenting a departure from previous approaches and methodologies. Coupling mean modulation index (MI) was assessed to estimate PAC between slow signals within the beta band (12-30 Hz), and higher frequency oscillations within the gamma band (30-100 Hz), at the level of 12 channels covering the sensorimotor cortex of both hemispheres. Results from linear mixed models show no significant differences between healthy and ALS patients, indicating that, through this method, a biomarker for early stage ALS disease cannot be detected in stimulated data.