ReviewNeuroImage2017
Ten problems and solutions when predicting individual outcome from lesion site after stroke.
Review in NeuroImage, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 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
53 citing papers in PubMed, 96 citations in OpenAlex.
- Uncovering hidden pathways: structural brain networks under connected speech in post-stroke aphasia.Brain communications · 2026Article
- The nonlinear trajectory of post-stroke aphasia recovery.Frontiers in human neuroscience · 2026Review
- Extending voxel-based lesion mapping to neurosurgical oncology: applications in intracranial meningiomas.Frontiers in oncology · 2026Article
- Using unsupervised dimensionality reduction to identify lesion patterns predictive of post-stroke aphasia severity.Cortex; a journal devoted to the study of the nervous system and behavior · 2025Article
- Target Selection Signals Causally Influence Human Perceptual Decision-Making.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Visual feature processing in a large stroke cohort: evidence against modular organization.Brain : a journal of neurology · 2025Article
- An Introduction to Machine Learning for Speech-Language Pathologists: Concepts, Terminology, and Emerging Applications.Perspectives of the ASHA special interest groups · 2025Article
- From acute neglect to chronic constructional deficits: parietotemporal contributions to long-term post-stroke impairments.Brain communications · 2025Article
- Alterations in brain function in patients with post-stroke cognitive impairment: a resting-state functional magnetic resonance imaging study.Frontiers in aging neuroscience · 2025Article
- AI-assisted assessment and treatment of aphasia: a review.Frontiers in public health · 2024Review
- Stem cell therapy: a new hope for stroke and traumatic brain injury recovery and the challenge for rural minorities in South Carolina.Frontiers in neurology · 2024Review
- Normative connectome-based analysis of sensorimotor deficits in acute subcortical stroke.Frontiers in neuroscience · 2024Article
- Behavioral and neuroanatomical correlates of facial emotion processing in post-stroke depression.NeuroImage. Clinical · 2024Article
- The Misguided Veneration of Averageness in Clinical Neuroscience: A Call to Value Diversity over Typicality.Brain sciences · 2023Review
- Structural disconnections associated with language impairments in chronic post-stroke aphasia using disconnectome maps.Cortex; a journal devoted to the study of the nervous system and behavior · 2022Article
- Understanding, facilitating and predicting aphasia recovery after rehabilitation.International journal of speech-language pathology · 2022Review
- Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence.Brain : a journal of neurology · 2022Review
- Context-sensitive computational mechanistic explanation in cognitive neuroscience.Frontiers in psychology · 2022Review
- Understanding Language Reorganization With Neuroimaging: How Language Adapts to Different Focal Lesions and Insights Into Clinical Applications.Frontiers in human neuroscience · 2022Review
- Tackling the Complexity of Lesion-Symptoms Mapping: How to Bridge the Gap Between Data Scientists and Clinicians?Acta neurochirurgica. Supplement · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
In this paper, we consider solutions to ten of the challenges faced when trying to predict an individual's functional outcome after stroke on the basis of lesion site. A primary goal is to find lesion-outcome associations that are consistently observed in large populations of stroke patients because consistent associations maximise confidence in future individualised predictions. To understand and control multiple sources of inter-patient variability, we need to systematically investigate each contributing factor and how each factor depends on other factors. This requires very large cohorts of patients, who differ from one another in typical and measurable ways, including lesion site, lesion size, functional outcome and time post stroke (weeks to decades). These multivariate investigations are complex, particularly when the contributions of different variables interact with one another. Machine learning algorithms can help to identify the most influential variables and indicate dependencies between different factors. Multivariate lesion analyses are needed to understand how the effect of damage to one brain region depends on damage or preservation in other brain regions. Such data-led investigations can reveal predictive relationships between lesion site and outcome. However, to understand and improve the predictions we need explanatory models of the neural networks and degenerate pathways that support functions of interest. This will entail integrating the results of lesion analyses with those from functional imaging (fMRI, MEG), transcranial magnetic stimulation (TMS) and diffusor tensor imaging (DTI) studies of healthy participants and patients.
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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.