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Micapipe: A pipeline for multimodal neuroimaging and connectome analysis

2022· article· en· 123 citations· W4294968711 on OpenAlex· 10.1016/j.neuroimage.2022.119612

Why is this work in the frame?

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

Canadian affiliationAn author listed a Canadian institution. This is the only route the usual frame has.
Canadian funderA Canadian agency funded it. The work may carry no Canadian affiliation at all.

Full frame distilled prediction

Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

Candidate categories
none
Consensus categories
none
Domain
Candidate signal: noneConsensus signal: none
Study design
Candidate signal: Bench or experimentalConsensus signal: none
Genre
Candidate signal: EmpiricalConsensus signal: Empirical
Teacher disagreement score
0.921
Threshold uncertainty score
0.906
Validation status
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Opus teacher head0.036
GPT teacher head0.283
Teacher spread
0.247 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Abstract

Multimodal magnetic resonance imaging (MRI) has accelerated human neuroscience by fostering the analysis of brain microstructure, geometry, function, and connectivity across multiple scales and in living brains. The richness and complexity of multimodal neuroimaging, however, demands processing methods to integrate information across modalities and to consolidate findings across different spatial scales. Here, we present micapipe, an open processing pipeline for multimodal MRI datasets. Based on BIDS-conform input data, micapipe can generate i) structural connectomes derived from diffusion tractography, ii) functional connectomes derived from resting-state signal correlations, iii) geodesic distance matrices that quantify cortico-cortical proximity, and iv) microstructural profile covariance matrices that assess inter-regional similarity in cortical myelin proxies. The above matrices can be automatically generated across established 18 cortical parcellations (100-1000 parcels), in addition to subcortical and cerebellar parcellations, allowing researchers to replicate findings easily across different spatial scales. Results are represented on three different surface spaces (native, conte69, fsaverage5), and outputs are BIDS-conform. Processed outputs can be quality controlled at the individual and group level. micapipe was tested on several datasets and is available at https://github.com/MICA-MNI/micapipe, documented at https://micapipe.readthedocs.io/, and containerized as a BIDS App http://bids-apps.neuroimaging.io/apps/. We hope that micapipe will foster robust and integrative studies of human brain microstructure, morphology, function, cand connectivity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

The record

Venue
NeuroImage
Topic
Functional Brain Connectivity Studies
Field
Neuroscience
Canadian institutions
Université du Québec à MontréalMcGill UniversityMontreal Neurological Institute and Hospital
Funders
Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de MontréalNational Institute of Mental HealthMinistry of Science, ICT and Future PlanningFonds de Recherche du Québec - SantéNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchCanadian Open Neuroscience PlatformHealth CanadaNatural Sciences and Engineering Research Council of CanadaInstitute for Information and Communications Technology PromotionHospital for Sick ChildrenNational Research Foundation of KoreaInha UniversityUniversidad Nacional Autónoma de MéxicoSavoy FoundationUniversiteit MaastrichtNational Research FoundationInstitute for Basic ScienceConsejo Nacional de Ciencia y TecnologíaNational Institutes of HealthCanada First Research Excellence FundCanada Research ChairsMcGill UniversityDirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de MéxicoMinistry of Science and ICT, South KoreaFondation Brain Canada
Keywords
Human Connectome ProjectConnectomeNeuroimagingComputer scienceTractographyConnectomicsDiffusion MRIArtificial intelligenceFunctional magnetic resonance imagingNeurosciencePattern recognition (psychology)Functional connectivityPsychologyMagnetic resonance imagingMedicine
Has abstract in OpenAlex
yes