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.

PMID: 35733428
PMCID: PMC9207992
Funding: - National Institute of Mental Health: MH-104605, MH-119735