ArticleBrain sciences2024
Changes in Structural Neural Networks in the Recovery Process of Motor Paralysis after Stroke.
Article in Brain sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 3 of them syntheses that pooled it.
What it found
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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.
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.
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Who cites it
5 citing papers in PubMed, 3 syntheses or guidelines pooled it, 7 citations in OpenAlex.
- Systematic review of repetitive transcranial magnetic stimulation for post-stroke hemiplegic shoulder pain.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Pooled it
- Examining the effectiveness of motor imagery combined with non-invasive brain stimulation for upper limb recovery in stroke patients: a systematic review and meta-analysis of randomized clinical trials.Journal of neuroengineering and rehabilitation · 2024Pooled it
- Global research trends in transcranial magnetic stimulation for stroke (1994-2023): promising, yet requiring further practice.Frontiers in neurology · 2024Pooled it
- Adaptive Sliding-Mode Controller with Grey Wolf Optimization and Interval Type-2 Fuzzy Logic System for Rehabilitation Lower-Limb Exoskeletons.Biomimetics (Basel, Switzerland) · 2026Article
- Generative Diffusion-Based Task Incremental Learning Method for Decoding Motor Imagery EEG.Brain sciences · 2025Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, neurorehabilitation has been actively used to treat motor paralysis after stroke. However, the impacts of rehabilitation on neural networks in the brain remain largely unknown. Therefore, we investigated changes in structural neural networks after rehabilitation therapy in patients who received a combination of low-frequency repetitive transcranial magnetic stimulation (LF-rTMS) and intensive occupational therapy (intensive-OT) as neurorehabilitation. Fugl-Meyer assessment (FMA) for upper extremity (FMA-UE) and Action Research Arm Test (ARAT), both of which reflected upper limb motor function, were conducted before and after rehabilitation therapy. At the same time, diffusion tensor imaging (DTI) and three-dimensional T1-weighted imaging (3D T1WI) were performed. After analyzing the structural connectome based on DTI data, measures related to connectivity in neural networks were calculated using graph theory. Rehabilitation therapy prompted a significant increase in connectivity with the isthmus of the cingulate gyrus in the ipsilesional hemisphere (
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Registered trials
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.