Exploratory study of the effect of binaural beat stimulation on the EEG activity pattern in resting state using artificial neural networks

• Published in: Cognitive systems research Vol. 54; pp. 1 - 20
• Main Authors: da Silva Junior, Maurício, de Freitas, Rafaela Covello, dos Santos, Wellington Pinheiro, da Silva, Washington Wagner Azevedo, Rodrigues, Marcelo Cairrão Araújo, Conde, Erick Francisco Quintas
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.05.2019
• Subjects: Anxiety; Artificial neural networks; Binaural beats; Electroencephalography (EEG); Machine learning; Binaural beats; Anxiety; Electroencephalography (EEG); Artificial neural networks; Machine learning
• DOI: 10.1016/j.cogsys.2018.11.002
• ISSN: 1389-0417

Anxiety disorders afflict almost 7.3 percent of the world’s population. One in 14 people will experience anxiety disorder at the given year. When associated with mood disorders, anxiety can also trigger or increase other diseases’ symptoms and effects, like depression and suicidal behavior. Binaural beats are a low-frequency type of acoustic stimulation perceived when the individual is subjected to two slightly different wave frequencies, from 200 to 900 Hz. Binaural beats can contribute to anxiety reduction and modification of other psychological conditions and states, modifying cognitive processes and mood states. In this work, we applied a 5 Hz binaural beat to 6 different subjects, to detect a relevant change in their brainwaves before and after the stimuli. We applied 20 min stimuli in 10 separated sessions. We assessed the differences using a Multi-Layer Perceptron classifier in comparison with non-parametric tests and Low-Resolution Brain Electromagnetic Tomography (eLORETA). eLORETA showed remarkable changes in High Alpha. Both eLORETA and MLP approaches revealed outstanding modifications in high Beta. MLP evinced significant changes in Theta brainwaves. Our study evidenced high Alpha modulation at the limbic lobe, implicating in a possible reduction of sympathetic system activation in the studied sample. Our main results on eLORETA suggest a strong increase in the current distribution, mostly in Alpha 2, at the Anterior Cingulate, which is related to the monitoring of mistakes regarding social conduct, recognition and expression of emotions. We also found that MLPs are able of evincing the main differences with high separability in Delta and Theta.