ArticleScientific reports2025
Decoding dynamic brain networks in Parkinson's disease with temporal attention.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Functional, Structural, and AI-Based MRI Analysis: A Comprehensive Review of Recent Advances.Diagnostics (Basel, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Detecting brief, clinically meaningful changes in brain activity is crucial for understanding neurological disorders. Conventional imaging analyses often overlook these subtle events due to computational demands. IMPACT (Integrative Multimodal Pipeline for Advanced Connectivity and Time-series) addresses this challenge by converting 3D/4D fMRI scans into time-series signals using a standardized brain atlas. This approach integrates regional signals, network patterns, and dynamic connectivity, and employs machine learning to detect subtle fluctuations. In Parkinson's disease diagnosis across two independent cohorts (n=43 and n=40), it achieves high accuracy (area under the curve = 0.97-0.98), outperforming conventional methods. Analyses reveal transient connectivity disruptions that align with dopaminergic mechanisms, while interpretability highlights the critical time windows and regions driving classification. This reproducible, standardized pipeline is readily adaptable to other conditions where short-lived brain changes serve as key diagnostic markers.
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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 Socratic graph.