Evidence map›Paper›PMID 33065515›Full record

ArticleCortex; a journal devoted to the study of the nervous system and behavior2020

Age differences in predicting working memory performance from network-based functional connectivity.

Rachel N Pläschke, Kaustubh R Patil, Edna C Cieslik, Alessandra D Nostro, Deepthi P Varikuti, Anna Plachti, Patrick Lösche, Felix Hoffstaedter, Tobias Kalenscher, Robert Langner and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Cortex; a journal devoted to the study of the nervous system and behavior, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.3field-weighted citation impact, top 11% of its field
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

20 citing papers in PubMed, 28 citations in OpenAlex.

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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

11 authors at 2 institutions in 1 country.

Rachel N PläschkeInstitute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany. Electronic address: Rachel.Plaeschke@uni-duesseldorf.de.
Kaustubh R PatilInstitute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
Edna C CieslikInstitute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
Alessandra D NostroInstitute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
Deepthi P VarikutiInstitute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
Anna PlachtiInstitute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
Patrick LöscheLeibniz Institute for International Educational Research (DIPF), Centre for Research on Human Development and Education, Frankfurt am Main, Germany.
Felix HoffstaedterInstitute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
Tobias KalenscherComparative Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
Robert LangnerInstitute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.
Simon B EickhoffInstitute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany. Electronic address: S.Eickhoff@fz-juelich.de.
Heinrich Heine University Düsseldorf · DEDIPF | Leibniz Institute for Research and Information in Education · DE

Funding

Meta-anaylsis in human brain mappingR01MH074457 · NIMH · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI FOX, PETER THORNTON · 2006 to 2024
$10.5M
Meta-analysis in human brain mappingR56MH074457 · NIMH · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI FOX, PETER THORNTON · 2020 to 2020
$543k
NIMH NIH HHS R01 MH074457NIMH NIH HHS R56 MH074457
6 · The paper itself

Abstract

Deterioration in working memory capacity (WMC) has been associated with normal aging, but it remains unknown how age affects the relationship between WMC and connectivity within functional brain networks. We therefore examined the predictability of WMC from fMRI-based resting-state functional connectivity (RSFC) within eight meta-analytically defined functional brain networks and the connectome in young and old adults using relevance vector machine in a robust cross-validation scheme. Particular brain networks have been associated with mental functions linked to WMC to a varying degree and are associated with age-related differences in performance. Comparing prediction performance between the young and old sample revealed age-specific effects: In young adults, we found a general unpredictability of WMC from RSFC in networks subserving WM, cognitive action control, vigilant attention, theory-of-mind cognition, and semantic memory, whereas in older adults each network significantly predicted WMC. Moreover, both WM-related and WM-unrelated networks were differently predictive in older adults with low versus high WMC. These results indicate that the within-network functional coupling during task-free states is specifically related to individual task performance in advanced age, suggesting neural-level reorganization. In particular, our findings support the notion of a decreased segregation of functional brain networks, deterioration of network integrity within different networks and/or compensation by reorganization as factors driving associations between individual WMC and within-network RSFC in older adults. Thus, using multivariate pattern regression provided novel insights into age-related brain reorganization by linking cognitive capacity to brain network integrity.

Indexed as

ConnectomeMemory, Short-TermAgedBrainCognitionHumansMagnetic Resonance ImagingYoung AdultAgingBrain networksMachine learningPerformance predictionRelevance vector machineResting-state fMRIWorking memory

Identifiers

PMID33065515
PMCPMC7778730
OpenAlexW3081850123

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.