Evidence map›Paper›PMID 42707257›Full record

ArticleFrontiers in aging neuroscience2026

Target-level convergence of directional prefrontal connectivity across Alzheimer's disease stages: an fNIRS study.

Nida Mateen, Rana Muhammad Kaleem Ullah, Jisoo Baik, Keum-Shik Hong, Min-Kyoung Kang, Chang-Seok Kim, Yong-Il Shin

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Article in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Nida MateenDepartment of Cogno-Mechatronics Engineering, Pusan National University, Busan, Republic of Korea.
Rana Muhammad Kaleem UllahDepartment of Cogno-Mechatronics Engineering, Pusan National University, Busan, Republic of Korea.
Jisoo BaikBiomedical Research Institute, Pusan National University Yangsan Hospital, Yangsan, Gyeongsangnam-do, Republic of Korea.
Keum-Shik HongInstitute for Future, School of Automation, Qingdao University, Qingdao, China.
Min-Kyoung KangInstitute for Industrial Artificial Intelligence, School of Mechanical Engineering, Pusan National University, Busan, Republic of Korea.
Chang-Seok KimDepartment of Cogno-Mechatronics Engineering, Pusan National University, Busan, Republic of Korea.
Yong-Il ShinDepartment of Rehabilitation Medicine, School of Medicine, Pusan National University Yangsan Hospital, Yangsan-si, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Alzheimer's disease (AD) is increasingly recognized as involving network-level dysfunction rather than isolated regional impairment. Although functional and effective connectivity have been studied in dementia, the reorganization of directional information flow within prefrontal networks remains incompletely characterized, particularly with functional near-infrared spectroscopy (fNIRS). Objective: This study investigated whether target-level convergence of directional effective connectivity within the prefrontal cortex differs across clinically defined cognitive groups, with emphasis on the mild cognitive impairment (MCI) vs. AD contrast. Methods: fNIRS signals were recorded from 60 participants (healthy controls (HC), MCI, and AD) during resting state and cognitive paradigms, including working memory (2-back), semantic verbal fluency (SVFT), and Stroop tasks. Signals from 48 prefrontal channels were aggregated into eight anatomically defined regions. Directional interactions were quantified using transfer entropy (TE) with adaptive hyperparameter tuning. Group differences were assessed using linear mixed-effects models with covariate adjustment and target-wise false discovery rate correction. Robustness was evaluated through parameter sensitivity, covariate, and surrogate-normalization analyses. Results: The analysis revealed structured target-level convergence patterns of directional connectivity across clinically defined cognitive groups, with the most prominent alterations observed in the MCI vs. AD comparison. Compared with MCI, AD showed reduced directed information flow to the right frontopolar cortex (FPC-R) during the 2-back and SVFT tasks ( Conclusion: These findings suggest that MCI and AD are associated with distinct patterns of directional information flow within prefrontal networks, characterized by reduced convergence toward FPC-R and increased directional influence toward DLPFC-L. Collectively, the results indicate that TE applied to task-based fNIRS can capture directional alterations in network connectivity, highlighting the potential of directional connectivity metrics for studying network-level changes associated with cognitive decline.

Indexed as

Alzheimer’s diseaseeffective connectivityfunctional near-infrared spectroscopymild cognitive impairmentprefrontal cortextransfer entropy

Identifiers

PMID42707257
PMCPMC13547515

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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.