Removing pink noise (1/f) in LFP across different electrophysiological recording systems
Title
Removing pink noise (1/f) in LFP across different electrophysiological recording systems
Leaders
Laura LÓPEZ GALDO, Shrabasti JANA, Camila LOSADA, Hasnae AGOURAM, Cléo SCHOEFFEL, Nilanjana NANDI
Collaborators
No response
Brainhack Global 2022 Event
Brainhack Marseille
Project Description
- What are you doing, for whom, and why?
- What makes your project special and exciting?
- How to get started?
- Where to find key resources?
We will try to remove the aperiodic noise found in the spectrum of the LFP data using the fooof module (https://github.com/fooof-tools/fooof). We will parametrize our signals, the aperiodic and periodic components and make some comparison across the different frequency bands.
We have data from EEG human recordings, LFP monkey utah array recordings and monkey laminar intracranial recordings across different areas. We want to see the effect of pink noise in each of the different setups and try to clean the signal.
Some related literature can be found in the following links:
- Parametrizing aperiodic component: https://doi.org/10.1038/s41593-020-00744-x
- Gamma-Beta frequency interactions: www.pnas.org/cgi/doi/10.1073/pnas.1710323115 and 10.1162/jocn_a_01600
Link to project repository/sources
https://github.com/lauralopezgaldo/Brainhack-Marseille-2022
Goals for Brainhack Global
- Working together with different datasets
- Compare the different results
- Share the analysis code
Good first issues
Get the spectrum from the raw data
Parametrize the 1/f
Frequency band comparison
Communication channels
https://mattermost.brainhack.org/brainhack/channels/bhg22-marseille-pinknoise
Skills
- python coding: 70%
- sharing ideas: 60%
- electrophysiological data: 100%
- literature review: 30%
Onboarding documentation
No response
What will participants learn?
Participants will learn to parametrize the spectrum of electrophysiological data and undertand the meaning of pink noise.
Data to use
No response
Number of collaborators
more
Credit to collaborators
Everyone will be able to use the data we have and we’ll make the code open for everyone.
Image
Type
coding_methods, pipeline_development
Development status
0_concept_no_content
Topic
neural_encoding
Tools
Jupyter, MNE
Programming language
Python
Modalities
EEG, other
Git skills
1_commit_push
Anything else?
No response
Things to do after the project is submitted and ready to review.
- Add a comment below the main post of your issue saying:
Hi @brainhackorg/project-monitors my project is ready! - Twitter-sized summary of your project pitch.