Prediction of Alpha Power Using Multiple Subjective Measures and Autonomic Responses

Alpha oscillations are associated with various cognitive functions. However, the determinants of alpha power variation remain ambiguous, primarily due to its inconsistent associations with autonomic responses and subjective states under different experimental conditions. To thoroughly examine the correlations between alpha power variation and these factors, we implemented a range of experimental conditions, encompassing attentional and emotional tasks, as well as a resting-state. In addition to the electroencephalogram data, we gathered a suite of autonomic response measurements and subjective ratings. We employed multiple linear regression analysis, utilizing autonomic responses and subjective reports as predictors of alpha power. We also subtracted the aperiodic components for better estimation of the power of periodic alpha oscillations. Our results from two separately conducted experiments robustly demonstrated that the combined use of autonomic response measurements and subjective ratings effectively predicted the parietal-occipital periodic alpha power variation across a range of conditions. These predictions were supported by leave-one-participant-out cross-validation and cross-experiment validation, confirming that multiple linear relationships can be generalized to new participants. This study demonstrates the links of alpha power variations with autonomic responses and subjective states, suggesting that during investigations of the cognitive functions of alpha oscillations, it is important to consider the potential influences of autonomic responses and subjective states on alpha oscillations.

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Publication Details

Journal
Psychophysiology
Published
2025-03-01
DOI
https://doi.org/10.1111/psyp.70028
Citations
3
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
4.29

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article

Prediction of Alpha Power Using Multiple Subjective Measures and Autonomic Responses

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3 citations
Psychophysiology
Neural dynamics and brain function
4.29
article

Prediction of Alpha Power Using Multiple Subjective Measures and Autonomic Responses

Kyuto Uno, Tomoya Kawashima, Yuting Xu, Ayumu Yamashita, Kaoru Amano
article en
3 citations

Abstract

Alpha oscillations are associated with various cognitive functions. However, the determinants of alpha power variation remain ambiguous, primarily due to its inconsistent associations with autonomic responses and subjective states under different experimental conditions. To thoroughly examine the correlations between alpha power variation and these factors, we implemented a range of experimental conditions, encompassing attentional and emotional tasks, as well as a resting-state. In addition to the electroencephalogram data, we gathered a suite of autonomic response measurements and subjective ratings. We employed multiple linear regression analysis, utilizing autonomic responses and subjective reports as predictors of alpha power. We also subtracted the aperiodic components for better estimation of the power of periodic alpha oscillations. Our results from two separately conducted experiments robustly demonstrated that the combined use of autonomic response measurements and subjective ratings effectively predicted the parietal-occipital periodic alpha power variation across a range of conditions. These predictions were supported by leave-one-participant-out cross-validation and cross-experiment validation, confirming that multiple linear relationships can be generalized to new participants. This study demonstrates the links of alpha power variations with autonomic responses and subjective states, suggesting that during investigations of the cognitive functions of alpha oscillations, it is important to consider the potential influences of autonomic responses and subjective states on alpha oscillations.

PsychophysiologyVol. 62(3)
Kanazawa Institute of Technology (JP), The University of Tokyo (JP)
Japan Society for the Promotion of Science
Reduced inequalities
Openalex Percentile: Top 7%
Neural dynamics and brain function
4.29
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