EEG-Based Sensory Classification using Machine Learning
Leaders
Linda Fiorini e Francesco Pietrogiacomi
Collaborators
No response
Brainhack Global 2023 Event
Brainhack Lucca
Project Description
Understanding how the brain perceives the world has always been one of the most intriguing topics in neuroscience. We want to apply machine learning (ML) techniques to classify the electrophysiological signal of the brain recorded during sensory stimulation in healthy subjects. This project endeavors to decode the unique neural signatures associated with auditory and visual stimulation by integrating ML and neuroscience, in particular electroencephalography (EEG) data. ML has been applied to EEG in various fields, such as motor imagery (e.g. Amin et al., 2019) and emotions recognition (Wang et al., 2021), as well as for clinical purposes (e.g. Ozdemir et Al., 2021) but only few researches on sensory processing using ML have been published. We will analyze EEG data collected for a study on anticipatory multisensory integration (Fiorini et al., 2023).
Potential applications of this project could be extended to better understand brain activity in states of altered consciousness - i.e., sleep, vegetative state, and coma - as well as in the field of brain-computer interfaces (BCI).
We aim to demonstrate the novel use of AI in enhancing our knowledge of neural dynamics, specifically in sensory processing. The interdisciplinary nature of this project - bridging neuroscience, artificial intelligence, and sensory psychology - offers a unique perspective and contributes significantly to the field of cognitive science and neurotechnology.
Link to project repository/sources
No response
Goals for Brainhack Global
Deepen the literature about application of deep learning on EEG
Define EEG data preprocessing pipeline
Implement different models to classify EEG signal
Train and test the models
Good first issues
No response
Communication channels
Slack/Discord/WhatsApp/Mail
Skills
EEG signal processing
Machine Learning/Deep Learning
Python programming
Onboarding documentation
No response
What will participants learn?
Participants can learn or improve EEG signal processing knowledge and the implementation of Machine Learning models in Python
Data to use
Participants will be provided with preprocessed EEG data collected during passive tasks (volunteers saw or heard stimuli without performing any specific task).
Number of collaborators
None
Credit to collaborators
Future collaboration in later stages in case a collaborator is interested in continuing to work on the project.
Title
EEG-Based Sensory Classification using Machine Learning
Leaders
Linda Fiorini e Francesco Pietrogiacomi
Collaborators
No response
Brainhack Global 2023 Event
Brainhack Lucca
Project Description
Understanding how the brain perceives the world has always been one of the most intriguing topics in neuroscience. We want to apply machine learning (ML) techniques to classify the electrophysiological signal of the brain recorded during sensory stimulation in healthy subjects. This project endeavors to decode the unique neural signatures associated with auditory and visual stimulation by integrating ML and neuroscience, in particular electroencephalography (EEG) data. ML has been applied to EEG in various fields, such as motor imagery (e.g. Amin et al., 2019) and emotions recognition (Wang et al., 2021), as well as for clinical purposes (e.g. Ozdemir et Al., 2021) but only few researches on sensory processing using ML have been published. We will analyze EEG data collected for a study on anticipatory multisensory integration (Fiorini et al., 2023). Potential applications of this project could be extended to better understand brain activity in states of altered consciousness - i.e., sleep, vegetative state, and coma - as well as in the field of brain-computer interfaces (BCI). We aim to demonstrate the novel use of AI in enhancing our knowledge of neural dynamics, specifically in sensory processing. The interdisciplinary nature of this project - bridging neuroscience, artificial intelligence, and sensory psychology - offers a unique perspective and contributes significantly to the field of cognitive science and neurotechnology.
Link to project repository/sources
No response
Goals for Brainhack Global
Good first issues
No response
Communication channels
Slack/Discord/WhatsApp/Mail
Skills
Onboarding documentation
No response
What will participants learn?
Participants can learn or improve EEG signal processing knowledge and the implementation of Machine Learning models in Python
Data to use
Participants will be provided with preprocessed EEG data collected during passive tasks (volunteers saw or heard stimuli without performing any specific task).
Number of collaborators
None
Credit to collaborators
Future collaboration in later stages in case a collaborator is interested in continuing to work on the project.
Image
Type
data_management, method_development
Development status
0_concept_no_content
Topic
deep_learning, machine_learning, neural_decoding, physiology
Tools
MNE, other
Programming language
Python
Modalities
EEG
Git skills
0_no_git_skills, 1_commit_push
Anything else?
No response
Things to do after the project is submitted and ready to review.
Hi @brainhacklucca my project is ready!