ReviewNeuropsychology2017
Quantitative modeling of category learning deficits in various patient populations.
Review in Neuropsychology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 7 citations in OpenAlex.
- Identifying motor learning deficits in neurological conditions: a critical analysis of a perennial problem.Experimental brain research · 2026Review
- Procedural auditory category learning is selectively disrupted in developmental language disorder.Psychonomic bulletin & review · 2024Article
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 1 country.
Funding
Abstract
objectiveTo provide a select review of our applications of quantitative modeling to highlight the utility of such approaches to better understand the neuropsychological deficits associated with various neurologic and psychiatric diseases.
methodWe review our work examining category learning in various patient populations, including individuals with basal ganglia disorders (Huntington's Disease and Parkinson's disease), amnesia and Eating Disorders.
resultsOur review suggests that the use of quantitative models has enabled a better understanding of the learning deficits often observed in these conditions and has allowed us to form novel hypotheses about the neurobiological bases of their deficits.
conclusionsWe feel that the use of neurobiologically inspired quantitative modeling holds great promise in neuropsychological assessment and that future clinical measures should incorporate the use of such models as part of their standard scoring. Appropriate studies need to be completed, however, to determine whether such modeling techniques adhere to the rigorous psychometric properties necessary for a valid and reliable application in a clinical setting. (PsycINFO Database Record
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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.