Evidence map›Paper›PMID 28487128›Full record

ArticleMedical image analysis2017

Continuous representations of brain connectivity using spatial point processes.

Daniel Moyer, Boris A Gutman, Joshua Faskowitz, Neda Jahanshad, Paul M Thompson

Abstract read
In one paragraph

Article in Medical image analysis, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Daniel MoyerImaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, United States; Information Sciences Institute, University of Southern California, United States; Department of Computer Science, University of Southern California, United States. Electronic address: dcmoyer@gmail.com.
Boris A GutmanImaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, United States.
Joshua FaskowitzImaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, United States; Department of Psychological and Brain Sciences, Indiana University, United States.
Neda JahanshadImaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, United States.
Paul M ThompsonImaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging & Informatics, University of Southern California, United States. Electronic address: pthomp@usc.edu.

Funding

Training U54EB020403 · NIBIB · UNIVERSITY OF SOUTHERN CALIFORNIA · PI THOMPSON, PAUL M · 2014 to 2018
$10.1M
NIBIB NIH HHS U54 EB020403
6 · The paper itself

Abstract

We present a continuous model for structural brain connectivity based on the Poisson point process. The model treats each streamline curve in a tractography as an observed event in connectome space, here the product space of the gray matter/white matter interfaces. We approximate the model parameter via kernel density estimation. To deal with the heavy computational burden, we develop a fast parameter estimation method by pre-computing associated Legendre products of the data, leveraging properties of the spherical heat kernel. We show how our approach can be used to assess the quality of cortical parcellations with respect to connectivity. We further present empirical results that suggest that "discrete" connectomes derived from our model have substantially higher test-retest reliability compared to standard methods. In this, the expanded form of this paper for journal publication, we also explore parcellation free analysis techniques that avoid the use of explicit partitions of the cortical surface altogether. We provide an analysis of sex effects on our proposed continuous representation, demonstrating the utility of this approach.

Indexed as

ConnectomeAlgorithmsBrainFemaleHumansMaleReproducibility of ResultsSensitivity and SpecificityConnectivity analysisDiffusion MRINon-parametric estimationPoint process

Identifiers

PMID28487128
PMCPMC5559296

What OpenQuestion holds

Textmetadata
LicenceTDM
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.