ArticleJournal of Alzheimer's disease : JAD2018
Dynamic Causal Modeling of Preclinical Autosomal-Dominant Alzheimer's Disease.
Article in Journal of Alzheimer's disease : JAD, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 19 citations in OpenAlex.
- Dynamic causal modeling of low-density resting-state EEG in long-term meditation practitioners.Scientific reports · 2026Article
- Early detection of dementia with default-mode network effective connectivity.Nature. Mental health · 2024Article
- A survey of brain network analysis by electroencephalographic signals.Cognitive neurodynamics · 2022Article
- A Triple-Network Dynamic Connection Study in Alzheimer's Disease.Frontiers in psychiatry · 2022Article
- Persistence of information flow: A multiscale characterization of human brain.Network neuroscience (Cambridge, Mass.) · 2021Article
- Shaping a data-driven era in dementia care pathway through computational neurology approaches.BMC medicine · 2020Review
- Lateralized memory circuit dropout in Alzheimer's disease patients.Brain communications · 2020Article
- A guide to group effective connectivity analysis, part 2: Second level analysis with PEB.NeuroImage · 2019Article
- Biological and Cognitive Markers of Presenilin1 E280A Autosomal Dominant Alzheimer's Disease: A Comprehensive Review of the Colombian Kindred.The journal of prevention of Alzheimer's disease · 2019Review
- Computational Causal Modeling of the Dynamic Biomarker Cascade in Alzheimer's Disease.Computational and mathematical methods in medicine · 2019Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 5 countries.
Funding
Abstract
Dynamic causal modeling (DCM) is a framework for making inferences about changes in brain connectivity using neuroimaging data. We fitted DCMs to high-density EEG data from subjects performing a semantic picture matching task. The subjects are carriers of the PSEN1 mutation, which leads to early onset Alzheimer's disease, but at the time of EEG acquisition in 1999, these subjects were cognitively unimpaired. We asked 1) what is the optimal model architecture for explaining the event-related potentials in this population, 2) which connections are different between this Presymptomatic Carrier (PreC) group and a Non-Carrier (NonC) group performing the same task, and 3) which network connections are predictive of subsequent Mini-Mental State Exam (MMSE) trajectories. We found 1) a model with hierarchical rather than lateral connections between hemispheres to be optimal, 2) that a pathway from right inferotemporal cortex (IT) to left medial temporal lobe (MTL) was preferentially activated by incongruent items for subjects in the PreC group but not the NonC group, and 3) that increased effective connectivity among left MTL, right IT, and right MTL was predictive of subsequent MMSE scores.
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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.