Decoding Individual and Shared Experiences of Media Perception Using CNN Architectures

The brain is an incredibly complex organ capable of perceiving and interpreting a wide range of stimuli. Depending on individual brain chemistry and wiring, different people decipher the same stimuli differently, conditioned by their life experiences and environment. This study’s objective is to decode how the CNN models capture and learn...

Brain Activity Recognition using Deep Electroencephalography Representation

Advances in neurotechnology have enhanced and simplified our ability to research brain activity with low-cost and effective equipment. One such scalable and noninvasive technique is Electroencephalography (EEG), which detects and records electrical brain activity. Brain activity recognition is one of the emerging problems as EEG wearables...

Stronger correlation of music features with brain signals predicts increased levels of enjoyment

Music recommendation systems struggle with predicting the aesthetic responses of listeners based solely on acoustic characteristics, which are dependent on the listener's perception. This research correlates acoustic music features with brain responses to report the neural aesthetic hypothesis that the intensity of an aesthetic experience can...

Detecting moments of distraction during meditation practice based on changes in the EEG signal

Electroencephalography (EEG) enables online monitoring brain activity, which can be used for neurofeedback. One of the growing applications of EEG neurofeedback is to facilitate meditation practice. Specifically, EEG neurofeedback can be used to alert participants whenever they get distracted during meditation practice based on changes in their...

Music identification using brain responses to initial snippets

Naturalistic music typically contains repetitive musical patterns that are present throughout the song. These patterns form a signature, enabling effortless song recognition. We investigate whether neural responses corresponding to these repetitive patterns also serve as a signature, enabling recognition of later song segments on learning...

Classifying EEG Signals of Mind-Wandering Across Different Styles of Meditation

In the modern world, it is easy to get lost in thought, partly because of the vast knowledge available at our fingertips via smartphones that divide our cognitive resources and partly because of our intrinsic thoughts. In this work, we aim to find the differences in the neural signatures of mind-wandering and meditation that are common across...

EEG Spectral Correlates of Rapid and Deep Slow Breathing States and classification using ML

One interpretation of breathing exercise is to enforce mind-body harmony, when someone feels well and healthy, different organs of our body function harmoniously. One dysfunctional organ may disturb the resonating mechanism across multiple organs. There are different breathing techniques, and recent scientific evidence encourages...

Real-time Sensing and NeuroFeedback for Practicing Meditation Using simultaneous EEG and Eye Tracking

Next-generation intelligent health-monitoring systems have been ushered in by mobile phones with robust computation power, affordable high-resolution cameras, and embedded wearable sensors. Wearable Electroencephalography (EEG) headset to record brain signals with simultaneous eye tracking using a mobile front camera can become a powerful tool...

Electroencephalography (EEG) dataset during naturalistic music listening comprising different genres with familiarity and enjoyment ratings

The article provides an open-source Music Listening- Genre (MUSIN-G) EEG dataset which contains 20 participants’ continuous Electroencephalography responses to 12 songs of different genres (from Indian folk music to Goth Rock to western electronic), along with their familiarity and enjoyment ratings. The participants include 16 males and 4...