Neural Correlates of Phrase Rhythm: An EEG Study of Bipartite vs. Rondo Sonata Form

Martínez-Rodrigo, Arturo; Fernández-Sotos, Alicia; Postigo, José Miguel Latorre; Moncho-Bogani, José; Fernández-Caballero, Antonio

doi:10.3389/fninf.2017.00029

Cited by 13 publications

(13 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…EEG connectivity features were reported to play an essential role in the recognition tasks [37]. Another study, using the same device, observed a correlation of EEG with classical music rhythm [38], [39]. Music therapy is one of the applications emanating from music-elicited emotion [40].…”

Section: Consumer Grade Eeg For Emotion Recognitionmentioning

confidence: 98%

Consumer Grade Brain Sensing for Emotion Recognition

et al. 2019

View full text Add to dashboard Cite

For several decades, electroencephalography (EEG) has featured as one of the most commonly used tools in emotional state recognition via monitoring of distinctive brain activities. An array of datasets have been generated with the use of diverse emotion-eliciting stimuli and the resulting brainwave responses conventionally captured with high-end EEG devices. However, the applicability of these devices is to some extent limited by practical constraints and may prove difficult to be deployed in highly mobile context omnipresent in everyday happenings. In this study, we evaluate the potential of OpenBCI to bridge this gap by first comparing its performance to research grade EEG system, employing the same algorithms that were applied on benchmark datasets. Moreover, for the purpose of emotion classification, we propose a novel method to facilitate the selection of audio-visual stimuli of high/low valence and arousal. Our setup entailed recruiting 200 healthy volunteers of varying years of age to identify the top 60 affective video clips from a total of 120 candidates through standardized self assessment, genre tags, and unsupervised machine learning. Additional 43 participants were enrolled to watch the pre-selected clips during which emotional EEG brainwaves and peripheral physiological signals were collected. These recordings were analyzed and extracted features fed into a classification model to predict whether the elicited signals were associated with a high or low level of valence and arousal. As it turned out, our prediction accuracies were decidedly comparable to those of previous studies that utilized more costly EEG amplifiers for data acquisition.

show abstract

Section: Consumer Grade Eeg For Emotion Recognitionmentioning

confidence: 98%

Consumer Grade Brain Sensing for Emotion Recognition

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Information that identifies a user' affective states is used to adapt the behavior of an application to keep the user satisfied or engaged. For example, some studies found neurophysiological responses in theta and alpha frequency bands to differentiate between episodes of frustrating and normal game play (Shergill et al, 2013 ) or even musical emotion regulation (Fernández-Sotos et al, 2016 ; Martínez-Rodrigo et al, 2017 ).…”

Section: Most Important Challenges In Human-avatar Symbiosis For Amentioning

confidence: 99%

Human-Avatar Symbiosis for the Treatment of Auditory Verbal Hallucinations in Schizophrenia through Virtual/Augmented Reality and Brain-Computer Interfaces

Fernández-Caballero

Navarro

Fernández-Sotos

et al. 2017

Front. Neuroinform.

Self Cite

View full text Add to dashboard Cite

This perspective paper faces the future of alternative treatments that take advantage of a social and cognitive approach with regards to pharmacological therapy of auditory verbal hallucinations (AVH) in patients with schizophrenia. AVH are the perception of voices in the absence of auditory stimulation and represents a severe mental health symptom. Virtual/augmented reality (VR/AR) and brain computer interfaces (BCI) are technologies that are growing more and more in different medical and psychological applications. Our position is that their combined use in computer-based therapies offers still unforeseen possibilities for the treatment of physical and mental disabilities. This is why, the paper expects that researchers and clinicians undergo a pathway toward human-avatar symbiosis for AVH by taking full advantage of new technologies. This outlook supposes to address challenging issues in the understanding of non-pharmacological treatment of schizophrenia-related disorders and the exploitation of VR/AR and BCI to achieve a real human-avatar symbiosis.

show abstract

“…Electroencephalographic techniques find applications in adult psychiatry (Sand et al, 2013 ). Electrophysiological methods have developed in recent decades (Kamarajan and Porjesz, 2015 ; Martínez-Rodrigo et al, 2017 ). Recently there has been a rapid advance in therapeutic use of Brain-Computer Interfaces (BCI) in which the acquisition of electrical activity of selected areas of brain cortex plays the main role (Mikołajewska and Mikołajewski, 2012 , 2013 , 2014 ; Teruel et al, 2017 ) and Event-Related Potentials (ERP) and other evoked potentials can lead not only to explanation of psychological behaviors in particular situations (Kotyra and Wojcik, 2017a , b ) but also to finding some biomarkers characteristic of psychiatric disorders (Chapman and Bragdon, 1964 ; Sutton et al, 1965 ; Campanella, 2013 ; Golonka et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Mapping the Human Brain in Frequency Band Analysis of Brain Cortex Electroencephalographic Activity for Selected Psychiatric Disorders

Wójcik

Masiak

Kawiak

et al. 2018

Front. Neuroinform.

View full text Add to dashboard Cite

There are still no good quantitative methods to be applied in psychiatric diagnosis. The interview is still the main and most important tool in the psychiatrist work. This paper presents the results of electroencephalographic research with the subjects of a group of 30 patients with psychiatric disorders compared to the control group of healthy volunteers. All subjects were solving working memory task. The digit-span working memory task test was chosen as one of the most popular tasks given to subjects with cognitive dysfunctions, especially for the patients with panic disorders, depression (including the depressive phase of bipolar disorder), phobias, and schizophrenia. Having such cohort of patients some results for the subjects with insomnia and Asperger syndrome are also presented. The cortical activity of their brains was registered by the dense array EEG amplifier. Source localization using the photogrammetry station and the sLORETA algorithm was then performed in five EEG frequency bands. The most active Brodmann Areas are indicated. Methodology for mapping the brain and research protocol are presented. The first results indicate that the presented technique can be useful in finding psychiatric disorder neurophysiological biomarkers. The first attempts were made to associate hyperactivity of selected Brodmann Areas with particular disorders.

show abstract

Neural Correlates of Phrase Rhythm: An EEG Study of Bipartite vs. Rondo Sonata Form

Cited by 13 publications

References 24 publications

Consumer Grade Brain Sensing for Emotion Recognition

Consumer Grade Brain Sensing for Emotion Recognition

Human-Avatar Symbiosis for the Treatment of Auditory Verbal Hallucinations in Schizophrenia through Virtual/Augmented Reality and Brain-Computer Interfaces

Mapping the Human Brain in Frequency Band Analysis of Brain Cortex Electroencephalographic Activity for Selected Psychiatric Disorders

Contact Info

Product

Resources

About