ArticleAmerican journal of translational research2024
Altered connectivity between frontal cortex and supplementary motor area in various types of Parkinson's disease.
Article in American journal of translational research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed.
- Symptom-Specific Networks and the DBS-Modulated Network in Parkinson's Disease: A Connectivity-Based Review.Brain sciences · 2025Review
- Network localization of regional homogeneity alterations in Parkinson's disease.Frontiers in aging neuroscience · 2025Article
- Single scan, subject-specific component extraction in dynamic functional connectivity using dictionary learning.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Static and Dynamic Functional Network Connectivity in Parkinson's Disease Patients With Postural Instability and Gait Disorder.CNS neuroscience & therapeutics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTremor-dominant (TD) and postural instability/gait difficulty (PIGD) are common subtypes of Parkinson's disease, each with distinct clinical manifestations and prognoses. The neural mechanisms underlying these subtypes remain unclear. This study aimed to investigate the altered connectivity of the frontal cortex and supplementary motor area (SMA) in different types of Parkinson's disease.
methodsData of 173 participants, including 41 TD patients, 65 PIGD patients, and 67 healthy controls, were retrospectively analyzed. All subjects underwent resting-state functional magnetic resonance imaging (rs-fMRI) and clinical assessments. Differences in amplitude of low frequency fluctuation (ALFF), voxel-wise functional connectivity (FC), and functional network connectivity (FNC) among the three groups were compared, followed by partial correlation analysis.
resultsCompared to healthy controls, the left dorsolateral superior frontal gyrus (DLSFG) ALFF was significantly increased in both PIGD and TD patients. The FC between the left DLSFG and the left SMA, as well as between the left paracentral lobule and the right DLSFG, was significantly decreased. Similarly, the FNC between the visual network and the auditory network was reduced. Compared to TD patients, PIGD patients showed a significantly higher ALFF in the left DLSFG and a notably reduced FC between the left DLSFG and left SMA. Additionally, the FC of the left DLSFG-SMA was inversely correlated with the PIGD score exclusively in PIGD patients. The FNC of the visual-auditory network was inversely associated with the tremor score only in TD patients.
conclusionDecreases in the left DLSFG-SMA connectivity may be a key feature of the PIGD subtype, while reduced VN-AUD connectivity may characterize the TD subtype.
Indexed as
Identifiers
What OpenQuestion holds
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.