Evidence map›Paper›PMID 38659856›Full record

ArticlebioRxiv : the preprint server for biology2024

Release the Krakencoder: A unified brain connectome translation and fusion tool.

Keith W Jamison, Zijin Gu, Qinxin Wang, Ceren Tozlu, Mert R Sabuncu, Amy Kuceyeski

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Keith W JamisonDepartment of Computational Biology, Cornell University, Ithaca, NY, USA.ORCID 0000-0001-7139-6661
Zijin GuSchool of Electrical and Computer Engineering, Cornell University and Cornell Tech, New York, NY, USA.ORCID 0000-0002-0385-2677
Qinxin WangDepartment of Biomedical Engineering, Tsinghua University, Beijing, 100084, China.
Ceren TozluDepartment of Radiology, Weill Cornell Medicine, New York, New York, USA.ORCID 0000-0002-6828-886X
Mert R SabuncuDepartment of Radiology, Weill Cornell Medicine, New York, New York, USA.ORCID 0000-0002-7068-719X
Amy KuceyeskiDepartment of Computational Biology, Cornell University, Ithaca, NY, USA.ORCID 0000-0002-5050-8342

Funding

Mapping the Human Connectome: Structure, Function, and HeritabilityU54MH091657 · NIMH · WASHINGTON UNIVERSITY · PI UGURBIL, KAMIL, VAN ESSEN, DAVID C · 2010 to 2014
$34.7M
MAPPING THE HUMAN CONNECTOME DURING TYPICAL AGINGU01AG052564 · NIA · WASHINGTON UNIVERSITY · PI SALAT, DAVID H, TERPSTRA, MELISSA J · 2016 to 2020
$18.9M
Mapping the Human Connectome During Typical DevelopmentU01MH109589 · NIMH · WASHINGTON UNIVERSITY · PI BARCH, DEANNA, BOOKHEIMER, SUSAN Y · 2016 to 2019
$17.1M
Advanced machine learning algorithms that integrate genomewide, longitudinal MRI and demographic data to predict future cognitive decline toward dementiaR01AG053949 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI SABUNCU, MERT RORY · 2017 to 2021
$2.4M
Heritability and cognitive implications of structural-functional connectome couplingRF1MH123232 · NIMH · WEILL MEDICAL COLL OF CORNELL UNIV · PI KUCEYESKI, AMY FRANCES · 2021 to 2021
$1.3M
NIA NIH HHS R01 AG053949NIA NIH HHS U01 AG052564NIMH NIH HHS RF1 MH123232NIMH NIH HHS U01 MH109589NIMH NIH HHS U54 MH091657
6 · The paper itself

Abstract

Brain connectivity can be estimated in many ways, depending on modality and processing strategy. Here we present the Krakencoder, a joint connectome mapping tool that simultaneously, bidirectionally translates between structural (SC) and functional connectivity (FC), and across different atlases and processing choices via a common latent representation. These mappings demonstrate unprecedented accuracy and individual-level identifiability; the mapping between SC and FC has identifiability 42-54% higher than existing models. The Krakencoder combines all connectome flavors via a shared low-dimensional latent space. This "fusion" representation i) better reflects familial relatedness, ii) preserves age- and sex-relevant information and iii) enhances cognition-relevant information. The Krakencoder can be applied without retraining to new, out-of-age-distribution data while still preserving inter-individual differences in the connectome predictions and familial relationships in the latent representations. The Krakencoder is a significant leap forward in capturing the relationship between multi-modal brain connectomes in an individualized, behaviorally- and demographically-relevant way.

Identifiers

PMID38659856
PMCPMC11042193

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.