Synergistic Network of Depressive Traits

[ErnWg]

Title

Synergistic Network of Depressive Traits

Leaders

Ern Wong (@ern_wng)
Emanuele Agrimi

Collaborators

Alessandra Algieri
+2

Brainhack Global 2023 Event

Brainhack Lucca

Project Description

Higher-order interactions provide sophisticated descriptions of complex and dynamical networks
beyond what contemporary pairwise analysis can capture. Particularly, to support
cognitive functions, brain regions are thought to collaborate synergistically, i.e. by means of
complex and rich patterns that only arise from the combination of the activity of multiple regions.
Since these synergies are thought to subserve higher cognitive functions, they could contribute
to our understanding of psychiatric impairments. This project thus aims to build synergistic
networks of brain function from resting-state fMRI and to identify network characteristics that
may be indicative of depressive traits, and that may help in patient classification.

Link to project repository/sources

No response

Goals for Brainhack Global

• Create a pipeline for building and analysing synergistic networks.
• Leverage rs-fMRI data from HCP Young Adult to identify network characteristics that
  correlate with depressive traits measured from a composite scale.
• Preprocess functional and anatomical data from an independent dataset (Bezmaternykh
  et al., 2021).

Good first issues

1. Create a composite scale of depressive traits from HCP behavioural and questionnaire
   data
2. Correlation between composite scale and synergistic interactions from HCP
3. Preprocessing functional and anatomical data from an independent dataset
4. Build a synergistic network of the independent dataset
5. Build a classifier to test the independent dataset

Communication channels

• Slack/Discord

Skills

• Familiarity with fMRI
• General proficiency with Python/MATLAB/Bash
• Network analysis
• Data Visualisation and Communication

Onboarding documentation

No response

What will participants learn?

• Preprocessing of anatomical and functional MRI data
• Higher-order interactions measures
• Network analysis
• Machine learning techniques

Data to use

HCP Young Adult Dataset
https://openneuro.org/datasets/ds002748/versions/1.0.5

Number of collaborators

1-3

Credit to collaborators

No response

Image

Type

coding_methods, method_development, pipeline_development, visualization

Development status

1_basic structure

Topic

connectome, data_visualisation, information_theory, machine_learning, statistical_modelling

Tools

AFNI, ANTs, FSL, Jupyter, Nipype

Programming language

Matlab, Python, shell_scripting

Modalities

fMRI

Git skills

0_no_git_skills

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 @brainhacklucca my project is ready!
• Twitter-sized summary of your project pitch.

[ErnWg]

Hi @brainhacklucca my project is ready!

[StanSStanman]

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