Lai, Giuseppe. 2024. Heart-to-Brain Interaction Facilitates Mental Imagery Performance: a novel Methodological Approach for Improving non-invasive Brain-Computer Interfaces. Doctoral thesis, Goldsmiths, University of London [Thesis]

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Abstract or Description

Interoception has demonstrated that individuals are better at processing and responding to sensory cues when perceived during diastole. This facilitatory effect may present opportunities to improve assistive technologies that rely on the systematic processing of experimental cues, such as brain-computer interfaces (BCIs). BCIs offer paralysed patients an effective way to restore communication and interaction. Motor imagery (MI)—rehearsing the kinesthetic sensations of movements—and visual imagery (VI)—imagining visual scenes in absence of external stimulation—are common paradigms in electroencephalogram (EEG)-based BCIs that have faced challenges due to intra- and inter-subject variability. Understanding the relationship between MI/VI performance—indexed by differences in normalised power spectral density (PSD) in alpha (MI: 8–13 Hz; VI: 8–12 Hz) and beta (MI: 14–30 Hz; VI: 13–130 Hz) frequency bands—and the cardiac cycle could help reduce the variability reported in several BCIs studies. In study 1, we recorded the EEG and the electrocardiogram (ECG) of 29 healthy human participants while they performed real and imaginary left- and right-thumb movements. In study 2, we conducted a similar experiment with 22 participants, instructing them to imagine either a static or a moving object in their minds (VI). Using nonparametric permutation tests, we analysed MI and VI neural responses separately for whether they occurred during the systole or diastole phases of the cardiac cycle. The results of both sensors and source-domains demonstrated more sustained alpha and beta suppression during MI/VI tasks when the experimental cues fell during diastole. However, the extent of this suppression was not significantly different between the systole and diastole conditions. Additionally, using circular statistics, study 1 revealed that contralateral and ipsilateral trials clustered during the quietest time of the cardiac cycle: between the T-wave and the P-wave. Finally, study 3 applied machine learning to validate our results for MI- and VI-based BCIs. The analysis demonstrated that decoding MI and VI trials that occurred during both cardiac phases may lead to higher decoding accuracy than training classifiers on all available trials. While further investigation is required to validate these effects, the results of this thesis suggest that the cardiac cycle influences MI and VI performance, with promising implications for MI- and VI-based assistive technologies.

Item Type:	Thesis (Doctoral)
Keywords:	Heart-to-Brain Interaction; Brain-Computer Interface
Departments, Centres and Research Units:	Psychology
Date:	30 November 2024
Item ID:	38042
Date Deposited:	02 Jan 2025 14:11
Last Modified:	02 Jan 2025 14:14
URI:	https://research.gold.ac.uk/id/eprint/38042

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