Center for Multimodal Neuroimaging
CMN brings together NIMH neuroimaging, processing, and neuromodulation expertise so communication is stronger between cores, sections, units, staff scientists, and users.
This integration fosters collaborative bridges, gives users a centralized view of available resources, and helps generate questions suited to cross-modal investigation. The Center connects NIMH-based core facilities in neuroimaging, image data processing, and neuromodulation with the Machine Learning and Data Science and Sharing Teams.
Operationally, each core and team remains independent. CMN convenes regular meetings around practical needs such as harmonized data structures, shared processing methods, multimodal integration, and data sharing. This site is a clearinghouse for what is available across the network.
Collaborative Cores and Teams
Recent Talks
NIMH Workshop on Combined PET-MRI
NIMH Workshop on Naturalistic Stimuli and Individual Differences
Using EEG to Decode Semantics During an Artificial Language Learning Task
Explainable AI in Neuro-Imaging: Challenges and Future Directions
Machine Learning in Neuroimaging: Applications to Clinical Neuroscience and Neurooncology
Tools / Software
MLC
VICE
Toolbox for creating interpretable item embeddings from odd-one-out triplet task judgments.
MLC
Functional Linear Mixed Effects Models for Fiber Photometry
R and Python packages for fitting functional linear mixed effects models to fiber photometry data.
MLC
Interpretability-Constrained Questionnaire Factorization
Tools for generating interpretable factors and loadings from questionnaire data.
MLC
Fast Functional GEE
One-step functional GEE algorithm for longitudinal functional regression.
CMN
NiFTIViewQL
QuickLook Plugin for macOS to inspect NiFTI medical images
CMN
Sumaru
A surface viewer written in Rust with AFNI/SUMA compatibility
CMN
egi-pynetstation
Python package for communicating with EGI EEG Amplifiers