We presented a novel, predictive model of functional decline at CTAD 2018. The model suggests that CANTAB PAL and SWM provide essential screening information when recruiting patients with amnestic mild cognitive impairment into Alzheimer’s disease clinical trials.
At CTAD 2018 we shared our new data on why a Bayesian approach is best to describe normative cognitive performance, especially when making scientifically robust comparisons to neurologically impaired groups.
PhD researcher, Rosalyn Hithersay, spoke to us about her recent publication on which cognitive tests are most sensitive to the early stages of dementia in Down syndrome.
Neural Network classification of longitudinal cognitive data for prediction of individual-level chan
For the first time, Neural Network classifiers have been applied to changes in CANTAB PAL performance between baseline and 10 months to accurately predict the development of MCI at 20 months. Dr Elizabeth Baker, Statistical Scientist at Cambridge Cognition, presented the novel findings at AAIC 2018.
Cognitive dysfunction is a leading cause of disability in multiple sclerosis (MS), yet practical restraints mean it often goes unassessed in routine clinical care. Promising new research, published in Frontiers in Neurology, suggests the Cambridge Neuropsychological Test Automated Battery (CANTAB) may offer a brief and sensitive technological solution.
Comparing visuospatial associative learning for a middle-aged birth cohort and patients with schizop
Visuospatial memory is extremely heterogeneous in schizophrenia. In a large population study, around a fifth of patients with schizophrenia showed similar errors rates to the top 50% of the general population. Conversely, half of the patients sampled showed substantial impairments.
Enriching participant eligibility for clinical trials through pre-screening for cognitive deficit.