NDDM
importedsoftware/nddm
Neural drift-diffusion model (NDDM) is a repository to integrate simultaneously both single-trial EEG measures and behavioral performance (response time and accuracy) to understand cognition.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/AGhaderi/NDDM
- Documentation
- unknown
- Tags
- cognitive-neuroscience · ddm · deep-learning · eeg · joint-modeling · model-based-cognitive-neuroscience · neurocognitive-model · parameter-recovery · single-trial-analysis
- Regulatory
- unknown
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- intro-to-eegcognitive-neuroscience · eeg
Introduction to EEG analysis course using MNE-Python
- methodes-cogneuro.github.iocognitive-neuroscience
Notes de cours pour PSY3018 - Méthodes en neurosciences cognitives
- processFNIRS2cognitive-neuroscience
Modular MATLAB toolbox for fNIRS analysis: import, preprocessing, hemoglobin conversion, QC, block/GLM modeling, group statistics (LME), connectivity & hyperscanning, and 3D visualization / diffuse…
- PyNoetic-officialcognitive-neuroscience
PyNoetic: A Modular Python Framework for No-Code Development of EEG Brain-Computer Interfaces
- ScienceAgentBenchcognitive-neuroscience
[ICLR'25] ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
- pyDecNefcognitive-neuroscience
A complete Python framework to perform real-time fMRI decoded neurofeedback experiments
- api.github.com/repos/AGhaderi/NDDMretrieved 2026-08-25 · via github-api
Machine-imported from GitHub search. Last push 2024-07-04, 19 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/20.json→ .entries["nddm"]
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