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Lavrencic, L. M.

Publications and source records attributed to Lavrencic, L. M..

2 recordsLinked to original sources

Associations between EEG functional brain connectivity and a cognitive reserve proxy in healthy older adults

Cognitive reserve is a concept that explains individual differences in vulnerability to cognitive impairment due to age and dementia-related brain changes. Mechanisms underlying the cognitive reserve effect are poorly understood. We investigated associations between a comprehensive cognitive reserve proxy (Lifetime Experiences Questionnaire/LEQ) and functional connectivity of the prefrontal cortex across the whole scalp, covarying for the level of current cognitive functioning (Addenbrookes Cognitive Examination Revised/ACE-R), using multiblock parallel and orthogonalized partial least squares regression. EEG data were collected from 34 healthy older adults (63 to 83 years) in eyes-open and eyes-closed resting-states, and during 0-back and 1-back tasks. Functional connectivity was estimated using imaginary coherence in the theta and alpha frequency bands, as these bands have been heavily implicated in cognitive ageing, attention and executive function. We found three clusters of electrodes where the absolute values of the regression coefficient were above threshold when covarying for ACE-R: (1) a cluster approximating the right frontocentral region during the eyes-open condition in the theta band with seed electrodes approximating the left prefrontal cortex with positive associations of medium effect size; (2) a cluster approximating the right parietotemporal region during the 0-back task in the theta band with seed electrodes approximating the right prefrontal cortex with negative associations of medium to large effect sizes; and (3) a cluster approximating the occipitoparietal region in the eyes-closed condition in the alpha band with seed electrodes approximating the left prefrontal cortex with negative associations of medium effect size. These relationships between a cognitive reserve proxy and functional connectivity, within key networks and frequency bands associated with attention and executive function, may reflect greater neural capacity and efficiency.

bioengineering↗

Characterization of young and old adult brains: An EEG functional connectivity analysis

Brain connectivity studies have reported that functional networks change with older age. We aim to (1) investigate whether electroencephalography (EEG) data can be used to distinguish between individual functional networks of young and old adults; and (2) identify the functional connections that contribute to this classification. Two eyes-open resting-state EEG recording sessions with 64 electrodes for each of 22 younger adults (19-37 years) and 22 older adults (63-85 years) were conducted. For each session, imaginary coherence matrices in theta, alpha, beta and gamma bands were computed. A range of machine learning classification methods were utilized to distinguish younger and older adult brains. A support vector machine (SVM) classifier was 94% accurate in classifying the brains by age group. We report decreased functional connectivity with older age in theta, alpha and gamma bands, and increased connectivity with older age in beta band. Most connections involving frontal, temporal, and parietal electrodes, and approximately two-thirds of connections involving occipital electrodes, showed decreased connectivity with older age. Just over half of the connections involving central electrodes showed increased connectivity with older age. Functional connections showing decreased strength with older age had significantly longer electrode-to-electrode distance than those that increased with older age. Most of the connections used by the classifier to distinguish participants by age group belonged to the alpha band. Findings suggest a decrease in connectivity in key networks and frequency bands associated with attention and awareness, and an increase in connectivity of the sensorimotor functional networks with ageing during a resting state.

neuroscience↗