IntroductionMagnetic resonance imaging (MRI) and electroencephalography (EEG) are a promising means to an objectified assessment of cognitive impairment in Alzheimer's disease (AD). Individually, however, these modalities tend to lack precision in both AD diagnosis and AD staging. A joint MRI–EEG approach that combines structural with functional information has the potential to overcome these limitations.Materials and MethodsThis cross‐sectional study systematically investigated the link between MRI and EEG markers and the global cognitive status in early AD. We hypothesized that the joint modalities would identify cognitive deficits with higher accuracy than the individual modalities. In a cohort of 111 AD patients, we combined MRI measures of cortical thickness and regional brain volume with EEG measures of rhythmic activity, information processing and functional coupling in a generalized multiple regression model. Machine learning classification was used to evaluate the markers’ utility in accurately separating the subjects according to their cognitive score.ResultsWe found that joint measures of temporal volume, cortical thickness, and EEG slowing were well associated with the cognitive status and explained 38.2% of ifs variation. The inclusion of the covariates age, sex, and education considerably improved the model. The joint markers separated the subjects with an accuracy of 84.7%, which was considerably higher than by using individual modalities.ConclusionsThese results suggest that including joint MRI–EEG markers may be beneficial in the diagnostic workup, thus allowing for adequate treatment. Further studies in larger populations, with a longitudinal design and validated against functional‐metabolic imaging are warranted to confirm the results.

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There is an interaction between gender and cognitive function, most notable in verbal episodic memory; female patients in the early stage of AD performed worse on verbal episodic memory than men. This indicates that the gender-specificities of neuropsychological functions should be given careful consideration in clinical diagnosis of dementia.

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This study investigated whether sequential difficulty effects emerge during processing of a mixed set of small, easy and large, more difficult arithmetic problems. Furthermore, we assessed if these sequential difficulty effects are reflected in event-related (de-)synchronization (ERS/ERD) patterns. To this end, we analyzed data of 65 participants, who solved two separate blocks (additions and subtractions) of arithmetic problems while their EEG was recorded. In each block, half of the problems were difficult problems (two-digit/two-digit with carry/borrow), and the other half were easy problems (one-digit/one-digit). Half of the problems were preceded by a problem of the same difficulty (repeat trials), and half were preceded by problems of the other difficulty (switch trials). In subtractions a sequential difficulty effects pattern emerged. Participants solved easy repeat trials faster than easy switch trials, while difficult repeat trials were solved slower and less accurately than difficult switch trials. In the EEG, we found the strongest effects in left hemispheric beta band (13–30 Hz) ERD. Specifically, participants showed a stronger beta band ERD in easy switch trials than in easy repeat trials. Furthermore, beta band ERD was stronger in difficult problems than in easy problems within repeat trials, but stronger in easy problems than in difficult problems within switch trials. In summary, our results are in line with the presence of sequential difficulty effects, as processing of easy and difficult problems was impaired if they were preceded by a difficult problem. Furthermore, these sequential difficulty effects are reflected in ERD patterns.

The inverse relationship between test anxiety and test performance is commonly explained by test-anxious students’ tendency to worry about a test and the consequences of failing. However, other cognitive facets of test anxiety have been identified that could account for this link, including interference by test-irrelevant thoughts and lack of confidence. In this study, we compare different facets of test anxiety in predicting test performance. Seven hundred thirty university students filled out the German Test Anxiety Inventory after completing a battery of standardized tests assessing general intelligence and mathematical competencies. Multiple regressions revealed that interference and lack of confidence but not worry or arousal explained unique variance in students’ test performance. No evidence was found for a curvilinear relationship between arousal and performance. The present results call for revisiting the role of worries in explaining the test anxiety-performance link and can help educators to identify students who are especially at risk of underperforming on tests.