AI Summary of Peer-Reviewed Research
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- ✔ Peer-reviewed source
- ✔ Published in indexed journal
- ✔ No retraction or integrity flags
What the study found
The study found that a machine learning model based on brain functional connectivity could predict cognitive decline in people with type 2 diabetes. The model showed a strong relationship between predicted and observed Montreal Cognitive Assessment scores.
Why the authors say this matters
The authors say the findings suggest that using functional connectivity information may help forecast cognitive deterioration in type 2 diabetes. They conclude this could support early identification and intervention plans, potentially reducing the effects of cognitive deficits in this group.
What the researchers tested
The researchers studied 40 people with type 2 diabetes and 30 control participants, all middle-aged and right-handed. Participants completed neuropsychological assessments and fMRI scans while doing an emotional Stroop task, and the team used a fully connected network machine learning approach to predict cognitive decline from connectivity patterns.
What worked and what didn't
The fully connected network accurately forecasted Montreal Cognitive Assessment scores in the type 2 diabetes group, with a robust relationship between predicted and observed scores in both training and testing sets. The analysis also identified connectivity patterns in the anterior cingulate cortex and other cognitive control regions as important for prediction.
What to keep in mind
The abstract says further studies should confirm the results in larger and more varied samples. It also does not describe other limitations beyond the need to improve applicability and relevance for clinical practice.
Key points
- A machine learning model using brain functional connectivity predicted Montreal Cognitive Assessment scores in people with type 2 diabetes.
- The study included 40 participants with type 2 diabetes and 30 control participants.
- Participants completed neuropsychological testing and fMRI during an emotional Stroop task.
- Connectivity patterns in the anterior cingulate cortex and other cognitive control regions were important for prediction.
- The authors say larger and more varied samples are needed to confirm the findings.
Disclosure
- Research title:
- Connectivity pattern predicted cognitive decline in type 2 diabetes
- Authors:
- Yawei Cheng, Li Wei, Yu-Hsin Chen, Yang‐Teng Fan, Yen-Nung Lin, Róger Marcelo Martínez, Kah Kheng Goh, Yu-Chun Chen, Hong-Yu Jian, Chenyi Chen
- Institutions:
- Hsing Wu University, Hsing Wu University, Hsing Wu University, Hsing Wu University, Hsing Wu University, Ministry of Health and Welfare, Ministry of Health and Welfare, National Autonomous University of Honduras, National Chengchi University, National Taiwan University of Sport, National Taiwan University of Sport, National Yang Ming Chiao Tung University, National Yang Ming Chiao Tung University, National Yang Ming Chiao Tung University, Taipei City Hospital, Taipei City Hospital, Taipei Medical University, Taipei Medical University, Taipei Medical University, Taipei Medical University, Taipei Medical University, Taipei Medical University Hospital, Taipei Municipal YangMing Hospital, Wan Fang Hospital, Wan Fang Hospital, Wan Fang Hospital, Wan Fang Hospital, Wan Fang Hospital, Yuan Ze University
- Publication date:
- 2026-02-25
- OpenAlex record:
- View
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