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EEG-Based Sensory Classification using Machine Learning #6

Open LindaFiorini opened 7 months ago

LindaFiorini commented 7 months ago

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

20231202_174637

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.

StanSStanman commented 7 months ago

Hi @LindaFiorini, your project has been successfully added to the BHL 2023 website! 🎉 See you soon! Ruggero