Supplementary file 1_CCPD under sparsity and low-rank constraints: multi-frequency dynamic

A supplementary file describing a computational analysis of brain network dynamics in schizophrenia. The study uses data from 145 subjects (71 schizophrenia patients and 74 healthy controls) from the COBRE dataset. The proposed SLRCCPD model decomposes multi-frequency dynamic functional connectivity tensors to reveal group differences in connectivity patterns and temporal state transitions.

Use Cases

• Method development for decomposing multi-frequency dynamic functional connectivity tensors based on the described SLRCCPD model.
• Comparative analysis of brain network states between schizophrenia patients and healthy controls based on fractional and dwell time metrics.
• Investigating connectivity differences within auditory, somatomotor, cognitive control, visual, and cerebellar networks across dynamic modules.
• Studying the relationship between state transition frequency and schizophrenia across different frequency bands.

Strengths

• Data is derived from a specific, named cohort (COBRE dataset) with 145 subjects.
• The analysis framework incorporates explicit constraints (L1-norm and nuclear norm) for sparsity and low-rank approximation.
• Results are presented across five shared dynamic modules and multiple frequency bands.

Limitations

• The primary file is a PDF (1.8 MB), which likely contains results and methodology rather than the raw underlying data tables.
• Column-level documentation is absent; field semantics must be inferred from the paper.
• Row count for any underlying data is unknown, which may limit suitability assessment.

Provenance

Source

COBRE dataset, analyzed by Li-Dan Kuang.

Collection Method

Group independent component analysis and a filter-banked connectivity framework were used to construct multi-frequency dFNC tensors.

Time Range

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Freshness

Last updated 2026-05-08 05:51:57

Geography

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