ReviewFrontiers in human neuroscience2025
Precision neurodiversity: personalized brain network architecture as a window into cognitive variability.
Review in Frontiers in human neuroscience, 2025. 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
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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.
- A unified theory of restrictive and addictive eating: a life course model integrating generational transmission, neurodevelopmental risk, and ultra-processed food use disorder-a theoretical review.Journal of eating disorders · 2026Review
- Challenging the prescientific frameworks of criminal justice: neurobiology and criminolytic interventions in the legalome era.Frontiers in psychology · 2026Review
- Bridging the translational gap in systems neuroscience: from circuit mechanisms to clinical therapeutics.Frontiers in pharmacology · 2026Review
- Neurodevelopmental disorders in children: the role of MRI in early detection and intervention planning.Frontiers in neuroscience · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Precision neurodiversity marks a shift in neuroscience from pathological models to personalized frameworks that view neurological differences as adaptive variations. This review synthesizes current knowledge on the Personalized Brain Network architecture and its relationship with cognitive variability in both typical and neurodiverse populations. The study examines advancements in connectome-based prediction modeling, normative modeling, dynamic fingerprinting, and machine learning methods that characterize individual-specific neural networks. Recent findings indicate that the Personalized Brain Network profile reliably predicts cognitive, behavioral, and sensory phenomena. Additionally, deep generative models demonstrate high fidelity in synthesizing connective cells. Recent studies have identified distinct neurobiological subgroups in conditions such as attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder that were previously undetectable by conventional diagnostic criteria. However, research has revealed significant network-level differences among these subgroups. Researchers have identified age-resistant biomarkers in specific brain regions, and genetic mutations significantly influence the connectivity patterns of individuals. Clinical applications span a range of neurodevelopmental conditions, including autism, ADHD, dyslexia, and talent. Network variability predicts executive functioning, social perception, and sensory processing abilities. However, successful translation requires overcoming challenges related to statistical power, reproducibility, ethical implementation and community participation. The convergence of advanced neuroimaging, artificial intelligence, and personalized medicine offers unprecedented opportunities for tailored interventions, while celebrating neurological diversity as a source of human strength.
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Identifiers
What Socratic 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 Socratic graph.