Left-prefrontal alpha-dynamics predict executive working-memory functioning in elderly people.

Recent findings suggest that electroencephalography (EEG) oscillations in the theta and alpha frequency-bands reflect synchronized interregional neuronal activity and are considered to reflect cognitive-control, and executive working memory mechanisms in humans. Above the age of 50 years, hypothesized pronounced alterations in alpha and theta-band power at resting or across different WM-functioning brain states may well be due to pre-dementia cognitive impairments, or increasing severity of age-related neurological disorders. Executive working memory (EWM) functioning was assessed in older-adult participants (54 to 83 years old) by obtaining their WM-related EEG oscillations and WM performance scores. WM performance and WM brain-state EEG were recorded during online-WM periods as well as during specific online WM events within EWM periods, and during resting offline-WM periods that preceded online-WM periods. Left-prefrontal alpha-power was enhanced during offline-WM periods versus online-WM periods and was significantly related to WM accuracy. Left-prefrontal alpha power and left prefrontal-parietal theta power anterior-posterior difference-gradient during online WM activity were related to reaction times (RT's). Importantly, during active-storage events, WM-offset offline-periods, and preparatory pre-retrieval events, excessive left-prefrontal alpha activity was related to poor EWM performance. The potential for developing targeted noninvasive cognition-enhancing interventions and developing clinical-monitoring EEG-based biomarkers of pathological cognitive-decline in elderly people is discussed.

Integrated Development Environment for EEG-Driven Cognitive-Neuropsychological Research.

Background: EEG-driven research is paramount in cognitive-neuropsychological studies, as it provides a non-invasive window to the underlying neural mechanisms of cognition and behavior. A myriad collection of software and hardware frameworks has been developed to alleviate some of the technical barriers involved in EEG-driven research. Methods: we propose an integrated development environment which encompasses the entire technical "data-collection pipeline" of cognitive-neuropsychological research, including experiment design, data acquisition, data exploration and analysis in a state-of-the-art user interface. Our framework is based on a unique integration between a python-based web framework, time-oriented databases and object-based data schemes. Results: we demonstrated our framework with the recording and analysis of an n-Back task completed by 15 elderly (ages 50 to 80) participants. This case study demonstrates the highly utilized nature of our integrated framework with a challenging target population. Furthermore, our results may provide new insights into the correlation between brain activity and working memory performance in elderly people, who are prone to experience accelerated decline in executive prefrontal cortex functioning. Conclusion: our framework extends the range of EEG-driven experimental methods for assessing cognition available for cognitive-neuroscientists, allowing them to concentrate on the creative part of their work instead of technical aspects.