Brain Functional Connectivity Data for Anesthesia and Psychiatric Conditions

Five fMRI datasets from independent research sites include participants under propofol deep sedation, propofol general anesthesia, ketamine anesthesia, and patients with unresponsive wakefulness syndrome, schizophrenia, bipolar disorder, and ADHD. The data comprises functional connectivity matrices derived from 400 cortical brain regions per participant. The dataset was authored by Zirui Huang of the University of Michigan and sourced from paperswithcode.

Use Cases

• Classifying brain states under anesthesia based on functional connectivity matrices.
• Comparing neural network patterns between psychiatric diagnoses like schizophrenia and bipolar disorder.
• Training graph neural networks on 400x400 brain region connectivity graphs.
• Investigating the neural correlates of disorders of consciousness like unresponsive wakefulness syndrome.

Strengths

• Data is derived from five independent research sites, suggesting multi-site validation.
• Connectivity matrices are standardized using a well-established brain parcellation scheme with 400 regions of interest.
• Includes data from multiple conditions: two levels of propofol anesthesia, ketamine anesthesia, and several neuropsychiatric diagnoses.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

paperswithcode

Collection Method

Collected fMRI data from independent research sites and processed into functional connectivity matrices.