Enhancing Cognitive Performance by Rhythmic Auditory Stimulation at Individual EEG Theta Frequency

Poster No:

68 

Submission Type:

Abstract Submission 

Authors:

Andre Gómez-Lombardi1,2,3,4, Begoña Góngora3,4, Pavel Prado-Gutiérrez5, Pablo Muñoz6, Wael El-Deredy1,7,8

Institutions:

1Brain Dynamics Laboratory, Universidad de Valparaíso, Valparaíso, Chile, 2Doctorado en Ciencias e Ingeniería para la Salud, Universidad de Valparaíso, Valparaíso, Chile, 3Escuela de Fonoaudiología, Universidad de Valparaíso, Valparaíso, Chile, 4Centro de Investigación en Cognición y Lenguaje, Universidad de Valparaíso, Valparaíso, Chile, 5Escuela de Fonoaudiología, Universidad San Sebastián, Santiago, Chile, 6Departamento de Patología y Fisiología, Universidad de Valparaíso, Valparaíso, Chile, 7Department of Electronic Engineeing, School of Enginnering, University of Valencia, Valencia, Spain, 8ValgrAI, Valencian Graduate School & Research Network of Artificial Intelligence, Valencia, Spain

First Author:

Andre Gómez-Lombardi  
Brain Dynamics Laboratory, Universidad de Valparaíso|Doctorado en Ciencias e Ingeniería para la Salud, Universidad de Valparaíso|Escuela de Fonoaudiología, Universidad de Valparaíso|Centro de Investigación en Cognición y Lenguaje, Universidad de Valparaíso
Valparaíso, Chile|Valparaíso, Chile|Valparaíso, Chile|Valparaíso, Chile

Co-Author(s):

Begoña Góngora  
Escuela de Fonoaudiología, Universidad de Valparaíso|Centro de Investigación en Cognición y Lenguaje, Universidad de Valparaíso
Valparaíso, Chile|Valparaíso, Chile
Pavel Prado-Gutiérrez  
Escuela de Fonoaudiología, Universidad San Sebastián
Santiago, Chile
Pablo Muñoz  
Departamento de Patología y Fisiología, Universidad de Valparaíso
Valparaíso, Chile
WAEL EL-DEREDY  
Brain Dynamics Laboratory, Universidad de Valparaíso|Department of Electronic Engineeing, School of Enginnering, University of Valencia|ValgrAI, Valencian Graduate School & Research Network of Artificial Intelligence
Valparaíso, Chile|Valencia, Spain|Valencia, Spain

Introduction:

Rhythmic sensory stimulation is a safe and effective method of non-invasive brain stimulation that has been shown to improve different cognitive functions in a variety of health conditions, including normal aging and Alzheimer's disease (Manippa et al., 2022; Sahu & Tseng, 2023; Traikapi & Konstantinou, 2021). Significant results have been obtained in the auditory, somatosensory, and visual rhythmic stimulation modalities (Henry & Obleser, 2012; Lea-Carnall et al., 2017; Ronconi et al., 2018) inducing resonant brain responses at the presentation frequencies. However, there is no consensus about the best method for setting the frequency parameter. We propose that the individual EEG-induced frequency observed during the execution of an inhibitory control task is related to performance, and using this parameter in rhythmic auditory stimulation could potentially enhance cognitive performance.

Methods:

Older adults between 60 and 75 years old (n =38, 19 female) were recruited for this study. All participants were right-handed, had more than 12 years of schooling, and did not have neurological impairment or hearing disorders that impacted their communication. Participants realized the auditory version of the Simon task (Simon & Rudell, 1967) before and after receiving rhythmic auditory stimulation. Their brain activity was registered through EEG using Biosemi 64 channels. Following the preprocessing of the EEG data from the pre-stimulation phase and the implementation of a time-frequency analysis of induced response, we identify the frequency of each participant (individual frequency) as the one with the highest amplitude within the theta band. To contrast the results of using different stimulation conditions through clicks, we included individual frequency, lower frequency (2Hz), higher frequency (33% upper than individual frequency), and irregular stimulation (non-periodical). Finally, the reaction time (RT) change of the Simon task before and after stimulation was compared between the different conditions.

Results:

The individual frequency of older adults was in the range of theta band (M = 3.64 Hz, SD = 0.82), revealing a significant negative correlation with RTs in both conditions of the Simon task (congruent, r = -.59, p < .001; incongruent: r = -.54, p < .001). We conducted a repeated measures ANOVA to investigate the effect of stimulation and congruency on the change in the reaction times pre-post stimulation in the Simon task. The results showed a main effect of stimulation type (p < .001, ηp2 = 0.48) and congruency [p = .023, ηp2 = 0.13]. Furthermore, an interaction effect between stimulation and congruency was observed [p = .015, ηp2 = 0.09] (Figure 1). Based on post hoc analyses, it was found that the two stimulation conditions that yielded the best results were the individual frequency (M = 28.28 ms, SD = 35.72) and the higher frequency (M = 30.26 ms, SD = 37.08), with no significant difference between them. The irregular stimulation obtained the worst result (M = 2.88 ms, SD = 34.37). The lower frequency produced a moderate result (M = 17.57 ms, SD = 36.93), which was significantly better than the irregular stimulation (mean difference = 14.68 ms, t = 4.85, p < .001), but worse than the results obtained with the individual frequency (mean difference = 10.71 ms, t = 3.54, p = 0.001) and the higher frequency (mean difference = 12.68 ms, t = 4.19, p < .001).
Supporting Image: Fig1.png
   ·Figure 1. Change in Reaction time of the Simon task pre - post rythmic auditory stimulation.
 

Conclusions:

Our findings suggest that rhythmic auditory stimulation can enhance performance on the Simon task compared to non-periodical stimulation. Notably, the greatest improvements were observed when the stimulation was customized to the individual EEG-induced frequency, even if it was higher. Considering individual oscillatory activity related to specific cognitive tasks could improve the outcomes of neurorehabilitation programs using rhythmic auditory stimulation.

Brain Stimulation:

Non-Invasive Stimulation Methods Other 1

Higher Cognitive Functions:

Executive Function, Cognitive Control and Decision Making

Lifespan Development:

Aging 2

Modeling and Analysis Methods:

EEG/MEG Modeling and Analysis

Keywords:

Aging
Cognition
Electroencephaolography (EEG)
Other - Rhythmic auditory stimulation

1|2Indicates the priority used for review

Provide references using author date format

Henry, M. J. (2012). 'Frequency modulation entrains slow neural oscillations and optimizes human listening behavior', Proceedings of the National Academy of Sciences, 109(49), 20095-20100.

Lea-Carnall, C. A. (2017). 'Evidence for frequency-dependent cortical plasticity in the human brain', Proceedings of the National Academy of Sciences, 114(33), 8871-8876.

Manippa, V. (2022). 'An update on the use of gamma (multi)sensory stimulation for Alzheimer’s disease treatment', Frontiers in Aging Neuroscience, 14.

Ronconi, L. (2018). 'Alpha-band sensory entrainment alters the duration of temporal windows in visual perception', Scientific Reports, 8(1), Article 1.

Sahu, P. (2023). 'Gamma sensory entrainment for cognitive improvement in neurodegenerative diseases: Opportunities and challenges ahead', Frontiers in Integrative Neuroscience, 17, 1146687.

Simon, J. R. (1967). 'Auditory S-R compatibility: The effect of an irrelevant cue on information processing', Journal of Applied Psychology, 51(3), 300-304.

Traikapi, A. (2021). 'Gamma Oscillations in Alzheimer’s Disease and Their Potential Therapeutic Role', Frontiers in Systems Neuroscience, 15, 782399.