Evidence map›Paper›PMID 38014005›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Edge Time Series Components of Functional Connectivity and Cognitive Function in Alzheimer's Disease.

Evgeny J Chumin, Sarah A Cutts, Shannon L Risacher, Liana G Apostolova, Martin R Farlow, Brenna C McDonald, Yu-Chien Wu, Richard Betzel, Andrew J Saykin, Olaf Sporns

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Evgeny J ChuminDepartment of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States.ORCID 0000-0001-6696-6105
Sarah A CuttsDepartment of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States.ORCID 0000-0002-7393-8484
Shannon L RisacherIndiana University Network Sciences Institute, IU, Bloomington, IN, United States.ORCID 0000-0002-3304-7943
Liana G ApostolovaIndiana University Network Sciences Institute, IU, Bloomington, IN, United States.ORCID 0000-0003-1823-2451
Martin R FarlowStark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States.ORCID 0000-0001-7897-5471
Brenna C McDonaldIndiana University Network Sciences Institute, IU, Bloomington, IN, United States.ORCID 0000-0001-6895-4490
Yu-Chien WuStark Neurosciences Research Institute, Indiana University School of Medicine (IUSM), Indianapolis, IN, United States.ORCID 0000-0003-1084-2634
Richard BetzelDepartment of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States.ORCID 0000-0001-9200-1681
Andrew J SaykinIndiana University Network Sciences Institute, IU, Bloomington, IN, United States.ORCID 0000-0002-1376-8532
Olaf SpornsDepartment of Psychological and Brain Sciences, Indiana University (IU), Bloomington, IN, United States.ORCID 0000-0001-7265-4036
Indiana University Bloomington · USIndiana University School of Medicine

Funding

Research Education ComponentP30AG010133 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI GHETTI, BERNARDINO FRANCESCO · 1991 to 2020
$37.3M
Research Education ComponentP30AG072976 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI ANDREW J SAYKIN · 2021 to 2026
$24.1M
Memory Circuitry in MCI and Early Alzheimer’s Disease Prodrome: Molecular DriversR01AG019771 · NIA · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI SAYKIN, ANDREW J · 2001 to 2021
$6.9M
Multi-Domain Sensory Measures as Biomarkers of Alzheimer's Disease in Preclinical and Prodromal StagesR01AG061788 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI RISACHER, SHANNON L · 2019 to 2023
$3.0M
Sensory and Perceptual Measures as Biomarkers of Alzheimer's Disease PathologyK01AG049050 · NIA · INDIANA UNIVERSITY INDIANAPOLIS · PI RISACHER, SHANNON L · 2015 to 2019
$612k
CRCNS: Linking connectomic and large-Scale Dynamics of the Human BrainR01AT009036 · NCCIH · TRUSTEES OF INDIANA UNIVERSITY · PI SPORNS, OLAF · 2015 to 2017
$443k
NCCIH NIH HHS R01 AT009036NIA NIH HHS K01 AG049050NIA NIH HHS P30 AG010133NIA NIH HHS P30 AG072976NIA NIH HHS R01 AG019771NIA NIH HHS R01 AG061788
6 · The paper itself

Abstract

Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer's disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer's Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer's disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.

Indexed as

Alzheimer’s diseasebrain-behavior relationshipsbrain networksFunctional connectivity

Identifiers

PMID38014005
PMCPMC10680898
OpenAlexW4376609869

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.