A comparison of resting state EEG and structural MRI for classifying Alzheimer's disease and mild cognitive impairment.

Alzheimer's disease (AD) is the leading cause of dementia, accounting for 70% of cases worldwide. By 2050, dementia prevalence will have tripled, with most new cases occurring in low- and middle-income countries. Mild cognitive impairment (MCI) is a stage between healthy aging and dementia, marked by cognitive deficits that do not impair daily living. People with MCI are at increased risk of dementia, with an average progression rate of 39% within 5 years. There is urgent need for low-cost, accessible and objective methods to facilitate early dementia detection. Electroencephalography (EEG) has potential to address this need due to its low cost and portability. Here, we collected resting state EEG, structural MRI (sMRI) and rich neuropsychological data from older adults (55+ years) with AD, amnestic MCI (aMCI) and healthy controls (~60 per group). We evaluated a range of candidate EEG markers (i.e., frequency band power and functional connectivity) for AD and aMCI classification and compared their performance with sMRI. We also tested a combined EEG and cognitive classification model (using Mini-Mental State Examination; MMSE). sMRI outperformed resting state EEG at classifying AD (AUCs â€‹= â€‹1.00 vs 0.76, respectively). However, both EEG and sMRI were only moderately good at distinguishing aMCI from healthy aging (AUCs â€‹= â€‹0.67-0.73), and neither method achieved sensitivity above 70%. The addition of EEG to MMSE scores had no added benefit relative to MMSE scores alone. This is the first direct comparison of EEG and sMRI for classification of AD and aMCI.

What does the broken brain say to the neuroscientist? Oscillations and connectivity in schizophrenia, Alzheimer's disease, and bipolar disorder.

The application of the concept and methods of brain oscillations has been an important research area in neurosciences. In the last decades, besides the application in cognitive processes, the study of changes in brain oscillations in diseases has also become an important focal point of research. In the present paper, some remarkable examples in three different diseases are taken into consideration: 1) schizophrenia (SZ), 2) Alzheimer's disease (AD), 3) bipolar disorders (BD). In the current literature, decreased oscillations in cortical recordings are observed in most of the pathologies. For example, decrease of gamma activity in SZ, decrease of delta activity in almost all diseases, as well as frequency shifts in alpha and the lower frequencies were recorded. However, there are also paradoxical cases in which an increase of oscillatory activities is observed. In BD, whereas alpha activity is greatly decreased, a huge increase of beta activity is observed. Or, in SZ, a paradoxical increase of gamma activity can be observed during cognitive loading. We also observed paradoxical changes in the analysis of connectivity. In AD, we find that alpha, delta, and theta coherences between distant parts of the cortex are greatly decreased, whereas in the gamma band, event-related coherences attain very high values. The comparison of the results and paradoxical changes in diseases may lead to important conclusions related to the web of oscillations and neurotransmitters. In turn, we could gain new insights to approach "brain function", in general.