ReviewTrends in cognitive sciences2018
Interpreting and Utilising Intersubject Variability in Brain Function.
Review in Trends in cognitive sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers, 1 of them a synthesis that pooled it.
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.
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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.
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Who cites it
126 citing papers in PubMed, 1 synthesis or guideline pooled it.
- White matter variability, cognition, and disorders: a systematic review.Brain structure & function · 2022Pooled it
- Article
- Selectivity for high-level language processing is highly localized in individual brains.bioRxiv : the preprint server for biology · 2026Article
- Individualized parcellation reveals functional boundaries in human prefrontal cortex.bioRxiv : the preprint server for biology · 2026Article
- A causal role of the ventromedial prefrontal cortex in regulating anticipated regret and risk behaviors in trait anxiety.Psychological medicine · 2026Article
- Beyond GLM: Inter-Subject Variability as a Complementary Approach to Detect Longitudinal Changes in Emotion Processing in Multiple Sclerosis.Journal of imaging · 2026Article
- Slow wave canonical activity deviation concept: Toward a slow wave-based EEG-fMRI reference map for health-associated network function.iScience · 2026Article
- Disentangling individual heterogeneity reveals robust network and molecular signatures of major depressive disorder with suicidal ideation.Translational psychiatry · 2026Article
- VarCoNet: A Variability-Aware Self-Supervised Framework for Functional Connectome Extraction From Resting-State fMRI.Human brain mapping · 2026Article
- Predicting functional topography of the human visual cortex from cortical anatomy at scale.bioRxiv : the preprint server for biology · 2026Article
- The nonlinear trajectory of post-stroke aphasia recovery.Frontiers in human neuroscience · 2026Review
- Heterogeneity-Aware, Multiscale Annotation of Shared and Specific Neurobiological Signatures among Major Neurodevelopmental Disorders.Research (Washington, D.C.) · 2026Article
- Object Naming After Thalamic Damage: Evidence From a Large-Scale, Chronic-Phase Study of Left Hemisphere Stroke Survivors.Neurobiology of language (Cambridge, Mass.) · 2026Article
- Individualized brain-computer interface for people with disabilities: a review.Frontiers in human neuroscience · 2026Review
- Inter-individual alignment of multimodal brain networks with anatomical constraints.Network neuroscience (Cambridge, Mass.) · 2026Article
- Sex difference in the neural correlates of volitional eyes closing.Scientific reports · 2025Article
- Brain‑heart axis: Neurostimulation techniques in ischemic heart disease (Review).International journal of molecular medicine · 2025Review
- Dedifferentiation and Transfer in Executive Function and Math Ability Following a Five-Year Abacus Training in Schoolchildren.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Personalized mapping of inhibitory spinal cord circuits in humans via noninvasive neural decoding and in silico modeling.Science advances · 2025Article
- Learning from missteps: Potential of transcranial electrical stimulation in neuropsychological rehabilitation.Journal of neuropsychology · 2025Review
66 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
We consider between-subject variance in brain function as data rather than noise. We describe variability as a natural output of a noisy plastic system (the brain) where each subject embodies a particular parameterisation of that system. In this context, variability becomes an opportunity to: (i) better characterise typical versus atypical brain functions; (ii) reveal the different cognitive strategies and processing networks that can sustain similar tasks; and (iii) predict recovery capacity after brain damage by taking into account both damaged and spared processing pathways. This has many ramifications for understanding individual learning preferences and explaining the wide differences in human abilities and disabilities. Understanding variability boosts the translational potential of neuroimaging findings, in particular in clinical and educational neuroscience.
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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.