The combination of hyperventilation test and graph theory parameters to characterize EEG changes in mild cognitive impairment (MCI) condition

Hyperventilation (HV) is a voluntary activity that causes changes in the neuronal firing characteristics noticeable in the electroencephalogram (EEG) signals. HV-related changes have been scribed to modulation of pO2/pCO2 blood contents. Therefore, an HV test is routinely used for highlighting brain...

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Bibliographic Details
Published in:GeroScience 2023-06, Vol.45 (3), p.1857-1867
Main Authors: Miraglia, Francesca, Pappalettera, Chiara, Guglielmi, Valeria, Cacciotti, Alessia, Manenti, Rosa, Judica, Elda, Vecchio, Fabrizio, Rossini, Paolo Maria
Format: Article
Language:English
Subjects:
Aged
Alzheimer Disease - diagnosis
Alzheimer's disease
Biomedical and Life Sciences
Brain
Cell Biology
Cerebrum
Cognitive ability
Cognitive Dysfunction - diagnosis
EEG
Electroencephalography
Geriatrics/Gerontology
Humans
Hyperventilation
Information processing
Life Sciences
Molecular Medicine
Nervous system diseases
Neural networks
Neurodegenerative diseases
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Original Article
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Summary:Hyperventilation (HV) is a voluntary activity that causes changes in the neuronal firing characteristics noticeable in the electroencephalogram (EEG) signals. HV-related changes have been scribed to modulation of pO2/pCO2 blood contents. Therefore, an HV test is routinely used for highlighting brain abnormalities including those depending to neurobiological mechanisms at the basis of neurodegenerative disorders. The main aim of the present paper is to study the effectiveness of HV test in modifying the functional connectivity from the EEG signals that can be typical of a prodromal state of Alzheimer’s disease (AD), the Mild Cognitive Impairment prodromal to Alzheimer condition. MCI subjects and a group of age-matched healthy elderly (Ctrl) were enrolled and subjected to EEG recording during HV, eyes-closed (EC), and eyes-open (EO) conditions. Since the cognitive decline in MCI seems to be a progressive disconnection syndrome, the approach we used in the present study is the graph theory, which allows to describe brain networks with a series of different parameters. Small world (SW), modularity (M), and global efficiency (GE) indexes were computed among the EC, EO, and HV conditions comparing the MCI group to the Ctrl one. All the three graph parameters, computed in the typical EEG frequency bands, showed significant changes among the three conditions, and more interestingly, a significant difference in the GE values between the MCI group and the Ctrl one was obtained, suggesting that the combination of HV test and graph theory parameters should be a powerful tool for the detection of possible cerebral dysfunction and alteration.
ISSN:2509-2723
2509-2715
2509-2723
DOI:10.1007/s11357-023-00733-5