Evidence map›Paper›PMID 38835646›Full record

ArticleFrontiers in human neuroscience2024

Motor network dynamic resting state fMRI connectivity of neurotypical children in regions affected by cerebral palsy.

Varina L Boerwinkle, Bethany L Sussman, Laura de Lima Xavier, Sarah N Wyckoff, William Reuther, Michael C Kruer, Martin Arhin, Justin M Fine

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2024. 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.

No citing paper in PubMed yet.

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

8 authors.

Varina L Boerwinkle *Division of Pediatric Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Bethany L Sussman *Division of Neurosciences, Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, AZ, United States.
Laura de Lima XavierDivision of Pediatric Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Sarah N WyckoffDivision of Neurosciences, Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, AZ, United States.
William ReutherDivision of Pediatric Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Michael C KruerDivision of Neurosciences, Barrow Neurological Institute at Phoenix Children's Hospital, Phoenix, AZ, United States.
Martin ArhinDivision of Pediatric Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
Justin M FineDepartment of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.

Funding

NICHD NIH HHS HHSN275200900018C
6 · The paper itself

Abstract

Background: Normative childhood motor network resting-state fMRI effective connectivity is undefined, yet necessary for translatable dynamic resting-state-network-informed evaluation in pediatric cerebral palsy. Methods: Cross-spectral dynamic causal modeling of resting-state-fMRI was investigated in 50 neurotypically developing 5- to 13-year-old children. Fully connected six-node network models per hemisphere included primary motor cortex, striatum, subthalamic nucleus, globus pallidus internus, thalamus, and contralateral cerebellum. Parametric Empirical Bayes with exhaustive Bayesian model reduction and Bayesian modeling averaging informed the model; Purdue Pegboard Test scores of hand motor behavior were the covariate at the group level to determine the effective-connectivity-functional behavior relationship. Results: Although both hemispheres exhibited similar effective connectivity of motor cortico-basal ganglia-cerebellar networks, magnitudes were slightly greater on the right, except for left-sided connections of the striatum which were more numerous and of opposite polarity. Inter-nodal motor network effective connectivity remained consistent and robust across subjects. Age had a greater impact on connections to the contralateral cerebellum, bilaterally. Motor behavior, however, affected different connections in each hemisphere, exerting a more prominent effect on the left modulatory connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Discussion: This study revealed a consistent pattern of directed resting-state effective connectivity in healthy children aged 5-13 years within the motor network, encompassing cortical, subcortical, and cerebellar regions, correlated with motor skill proficiency. Both hemispheres exhibited similar effective connectivity within motor cortico-basal ganglia-cerebellar networks reflecting inter-nodal signal direction predicted by other modalities, mainly differing from task-dependent studies due to network differences at rest. Notably, age-related changes were more pronounced in connections to the contralateral cerebellum. Conversely, motor behavior distinctly impacted connections in each hemisphere, emphasizing its role in modulating left sided connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Motor network effective connectivity was correlated with motor behavior, validating its physiological significance. This study is the first to evaluate a normative effective connectivity model for the pediatric motor network using resting-state functional MRI correlating with behavior and serves as a foundation for identifying abnormal findings and optimizing targeted interventions like deep brain stimulation, potentially influencing future therapeutic approaches for children with movement disorders.

Indexed as

cerebral palsyeffective connectivitymotor network connectivitynormativeresting state functional MRI

Identifiers

PMID38835646
PMCPMC11148452

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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.