Dementia rates in the US, UK, Netherlands, Sweden, France, and several other high-income countries have been falling for decades, despite population aging. The standard explanation — improved cardiovascular care, more education, and less smoking in later-born cohorts — is real but incomplete. Research Highlights Dementia incidence has been falling about 13% per decade in Western …
A 2026 medRxiv meta-analysis of 27 trials found that transcranial direct current stimulation added to cognitive training improved global cognition immediately after treatment by SMD 0.36 compared with cognitive training alone.1 The signal was small, short-term, and rated very low certainty, so it is not evidence that tDCS is a durable cognitive-rehabilitation shortcut. Research Highlights …
A 2026 medRxiv preprint found that older adults with mild-cognitive-impairment-level MoCA-J scores showed distinct resting facial action-unit patterns: AU10 upper lip raiser, AU23 lip tightener, and AU28 lip suck differed after correction in 45 analyzable participants.1 The result supports facial-expression screening research, but it does not show that a face video can diagnose MCI or …
A 2026 community study of 101 older adults found that pulse-wave harmonics changed in a more organized way during a subtraction task in cognitively intact participants than in people with MoCA-defined mild cognitive impairment: amplitude-coherence scores averaged 9.00 vs. 6.40, a 2.60-point gap on a 0-10 scale. Research Highlights Cognitive stress exposed the signal: resting …
A 2026 TADPOLE modeling study reported that a sequential neural process with normalizing flows predicted future Alzheimer diagnostic stage with mAUC 0.965 ± 0.006, ahead of the authors’ earlier sequential-neural-process model at 0.937 ± 0.014.1 The result is a strong benchmark signal for uncertainty-aware disease-progression AI, but it is still retrospective modeling evidence rather than …
A 2026 medRxiv preprint found that REDDI, a resting-state magnetoencephalography machine-learning pipeline, separated mild cognitive impairment, multiple sclerosis, Parkinson’s disease, and amyotrophic lateral sclerosis with 0.81 ± 0.04 balanced accuracy across 5 folds.1 That is a meaningful jump over the prior 67.1% MEG benchmark, but it is still research-stage decision support rather than a clinical …
A 2026 ADNI study reported 85.23% accuracy for ANA-GNN, a graph neural network that combined structural MRI regional features with clinical variables to classify cognitively normal controls, mild cognitive impairment, and Alzheimer’s disease.1 The result is useful, but the clinical-feature ablation dropped accuracy to 68.35%, so the model should be read as multimodal decision-support research, …