Evidence map›Paper›PMID 36250457›Full record

ReviewThe Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry2024

The Prediction of Brain Activity from Connectivity: Advances and Applications.

Michal Bernstein-Eliav, Ido Tavor

Abstract readReview
In one paragraph

Review in The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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  9. Continuous Diffusion-Detected Neuroplasticity during Motor Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
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  10. Review
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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

2 authors.

Michal Bernstein-EliavSackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
Ido TavorSackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.ORCID 0000-0002-9117-4449

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The human brain is composed of multiple, discrete, functionally specialized regions that are interconnected to form large-scale distributed networks. Using advanced brain-imaging methods and machine-learning analytical approaches, recent studies have demonstrated that regional brain activity during the performance of various cognitive tasks can be accurately predicted from patterns of task-independent brain connectivity. In this review article, we first present evidence for the predictability of brain activity from structural connectivity (i.e., white matter connections) and functional connectivity (i.e., temporally synchronized task-free activations). We then discuss the implications of such predictions to clinical populations, such as patients diagnosed with psychiatric disorders or neurologic diseases, and to the study of brain-behavior associations. We conclude that connectivity may serve as an infrastructure that dictates brain activity, and we pinpoint several open questions and directions for future research.

Indexed as

BrainBrain MappingConnectomeHumansMachine LearningNerve NetNeural Pathwaysbrain activitybrain–behavior associationsclinical populationsfunctional connectivityindividual traitsprediction modelsresting-state fMRIstructural connectivitytask fMRI

Identifiers

PMID36250457
PMCPMC11107130

What OpenQuestion holds

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LicenceCC BY-NC
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.