Comparative study of machine learning methods for modeling associations between risk factors and future dementia cases.

A substantial portion of dementia risk can be attributed to modifiable risk factors that can be affected by lifestyle changes. Identifying the contributors to dementia risk could prove valuable. Recently, machine learning methods have been increasingly applied to healthcare data.

Blunted Cardiovascular Reactivity Predicts Worse Performance in Working Memory Tasks.

When we experience psychological challenges in the environment, our heart rate usually rises to make us more able to solve the task, but there is an individual difference in cardiovascular reactivity (CVR). Extreme CVR to environmental demands has been associated with worse health outcomes, with blunted CVR (little or no rise in heart rate) related to maladaptive behavior, including depression. The blunted CVR has been explained by motivational disengagement, which involves giving up on a task when facing obstacles.

Exposure factors associated with dementia among older adults in Iceland: the AGES-Reykjavik study.

The study aimed to assess whether factors related to cognitive performance were associated with the development of dementia. Additionally, the study aimed to establish whether cognitive performance at baseline or change in cognition between baseline and follow-up (five-year period) had a stronger association with whether an individual would fulfill a dementia criterion at follow-up. The data was collected from 2002 to 2011.

Cognition and brain health among older adults in Iceland: the AGES-Reykjavik study.

The paper aimed to compare how factors previously identified as predictive factors for cognitive decline and dementia related to cognitive performance on the one hand and brain health on the other. To that aim, multiple linear regression was applied to the AGES-Reykjavik study epidemiological data. Additionally, a regression analysis was performed for change in cognition over 5 years, using the same exposure factors.

P300 Analysis Using High-Density EEG to Decipher Neural Response to rTMS in Patients With Schizophrenia and Auditory Verbal Hallucinations.

Schizophrenia is a complex disorder about which much is still unknown. Potential treatments, such as transcranial magnetic stimulation (TMS), have not been exploited, in part because of the variability in behavioral response. This can be overcome with the use of response biomarkers.

Schizophrenia, cognition, and aging: cognitive deficits and the relationship between test performance and aging.

Most measures of cognitive function decline with age during adulthood. Research indicates that people with schizophrenia experience considerable cognitive deficits. These deficits appear to become more troublesome with increasing age, but this has been debated.