2nd Annual Angeliki Georgopoulos Lecture
Lecturer: Dr. Carol A. Barnes

November 7th 2023


This fall we are hosting the 2nd Annual Angeliki Georgopoulos Lecture, in memory of Dr. Angeliki "Lily" Georgopoulos dedicated physician and scientist who helped initiate the Healthy Brain Aging study.

This year's lecture "Contribution of synapse change to cognitive decline in aging" will be presented by Dr. Carol A. Barnes. Dr. Barnes is Regents Professor of Psychology, Neurology and Neuroscience at the University of Arizona, Tucson.

2023-11-07

Dependence of cognitive ability on Synchronous Neural InteractionsSynchronous Neural Interactions (SNI)Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG. determined by magnetoencephalography

Previous studies have shown that Synchronous Neural InteractionsSynchronous Neural Interactions (SNI)Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG. (SNIs) underlying healthy brain function can be readily distinguished from neural anomalies associated with diseases including dementia; however, it is imperative to identify biomarkers that facilitate early identification of individuals at risk for cognitive decline before the onset of clinical symptoms. Here, we evaluated whether variation in brain function, controlling for age, corresponds with subtle decrements in cognitive performance in cognitively healthy women. A total of 251 women (age range 24-102 yr) who performed above established cutoffs on the Montreal Cognitive AssessmentMontreal Cognitive Assessment (MoCA)Cognitive function assessment. It consists of 30 questions that test visuospatial/ executive functioning, ability to name objects, memory, attention, general language skills (fluency), abstraction, delayed recall, and orientation. also underwent a task-free magnetoencephalography scan from which SNIs were computed. The results demonstrated that increased SNISynchronous Neural Interactions (SNI)Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG. was significantly associated with decreased cognitive performance (r2 = 0.923, P = 0.009), controlling for age. Compared with the lowest performers with normal cognition (MoCAMontreal Cognitive Assessment (MoCA)Cognitive function assessment. It consists of 30 questions that test visuospatial/ executive functioning, ability to name objects, memory, attention, general language skills (fluency), abstraction, delayed recall, and orientation. = 26), SNISynchronous Neural Interactions (SNI)Zero-lag partial correlations in pairs of MEG time series and denote the strength and polarity (positive or negative) of neuronal interactions. Anomalies in SNIs as assessed by MEG differentiate psychiatric disorders from healthy brain functioning and can discriminate among various brain diseases. From this research, a highly distinctive, unique PTSD SNI signature characterized by miscommunication of temporal and parietal and/or parieto-occipital right hemispheric areas with other brain areas has emerged. These findings, in addition to the growing research applying MEG to other psychiatric disorders, highlight the utility of MEG in identifying biomarkers of disease and underscore the potential for broader clinical applications of MEG. of the highest performers (MoCAMontreal Cognitive Assessment (MoCA)Cognitive function assessment. It consists of 30 questions that test visuospatial/ executive functioning, ability to name objects, memory, attention, general language skills (fluency), abstraction, delayed recall, and orientation. = 30) was associated with decorrelation primarily in the right...