Alpha wave asymmetry is associated with only one component of melancholia, and in different directions across brain regions

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Sharpley, CF
Bitsika, V
Shadli, SM
Jesulola, E
Agnew, LL
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2023
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Abstract

Alpha wave asymmetry inconsistently correlates with Major Depressive Disorder (MDD). One possible reason for this inconsistency is the heterogeneity of MDD, leading to study of depressive ‘subtypes’, one of which is Melancholia. To investigate the correlation between Melancholia and alpha-wave asymmetry, 100 community participants (44 males, 56 females; aged at least 18 yr) completed the Zung self-rated Depression Scale, and underwent 3 min of eyes closed EEG recording from 24 scalp sites. There was no significant correlation between EEG data and Melancholia total score for the entire sample, but there was for those participants who had clinically significant depression (n = 33). When examined at the level of individual Melancholia scale items, significant EEG data correlations were found for some of the items but not for others. Factor analysis revealed a two-factor structure for the Melancholia scale, only one of which exhibited significant correlations with EEG AA data. Further exploration of those data identified two subcomponents of that Melancholia factor, one which was inversely correlated with frontal alpha asymmetry, and another which was directly correlated with parietal-occipital alpha wave asymmetry. These findings suggest that Melancholia may itself be heterogeneous, similarly to MDD, and rely upon different aspects of cognitive function.

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Psychiatry Research: Neuroimaging

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334

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© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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Biomedical imaging

Clinical sciences

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Biological psychology

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Sharpley, CF; Bitsika, V; Shadli, SM; Jesulola, E; Agnew, LL, Alpha wave asymmetry is associated with only one component of melancholia, and in different directions across brain regions, Psychiatry Research: Neuroimaging, 2023, 334, pp. 111687

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