NeuMapper
NeuMapper leverages the Mapper algorithm from topological data analysis (TDA) to produce individualized, whole-brain representations of fMRI dynamics without requiring initial spatiotemporal averaging.
Key Features:
- Mapper / TDA-based representation: Applies the Mapper approach from topological data analysis to explore whole-brain configurations at the single-participant level.
- Dimensionality reduction elimination: Removes the need for dimensionality reduction commonly required in traditional Mapper implementations.
- Efficient parameter exploration: Implements a biologically grounded heuristic to facilitate efficient exploration of the Mapper parameter space.
- Integration with neuroanatomy and behavior: Uses novel meta-analytic approaches to anchor Mapper-derived representations to neuroanatomical structures and behavioral outcomes.
- Scalability and validation: Validated on multiple fMRI datasets including continuous multitask experiments and designed to scale to consortium-size datasets.
Scientific Applications:
- Single-participant fMRI analysis: Generate individualized insights into brain dynamical organization from fMRI data.
- Psychiatric neuroimaging and personalized medicine: Support research aimed at characterizing individual variability for personalized/precision approaches in psychiatry and neuroscience.
- Translational neuroimaging: Link neuroimaging-derived representations to behavioral outcomes to bridge imaging findings and clinical applications.
- Large-scale dataset analysis: Enable analysis of consortium-size fMRI datasets for population-level studies while preserving single-participant detail.
Methodology:
Uses the Mapper algorithm from topological data analysis; operates without initial spatiotemporal averaging or imposed dimensionality reduction; employs a biologically grounded heuristic for Mapper parameter exploration; applies meta-analytic anchoring of representations to neuroanatomy and behavior; validated on multiple fMRI datasets including continuous multitask experiments.
Topics
Details
- License:
- BSD-3-Clause-Clear
- Cost:
- Free of charge
- Tool Type:
- library
- Operating Systems:
- Mac, Linux, Windows
- Programming Languages:
- MATLAB
- Added:
- 9/5/2022
- Last Updated:
- 9/5/2022
Operations
Publications
Geniesse C, Chowdhury S, Saggar M. NeuMapper: A scalable computational framework for multiscale exploration of the brain’s dynamical organization. Network Neuroscience. 2022. doi:10.1162/netn_a_00229. PMID:35733428. PMCID:PMC9207992.