Electroencephalographic markers of subjective cognitive performance: implications towards electrophysiological prediction of early cognitive decline
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1
University of Technology, Sydney, School of Life Sciences, Australia
Background: Our cognitive skills are the means through which we perceive and interact with our environment and everything it contains. As such adequate cognitive performance is vital to our everyday functioning and life. Because of this, declines in cognitive performance or cognitive impairment can have repercussions that can affect both our occupational and personal lives. Currently, identifying cognitive impairment is mostly limited to retrospective medical audits using subjective tools; however the dynamic nature of brain activity and electroencephalography may prove to be a more effective alternative.
Methods: Data recorded from 21 nurses (14 Females, aged 32.67 ± 8.58 years) and 21 healthy adult controls (14 females, aged 34.76 ± 9.15 years) was analysed in the current study. Brain activity was recorded with a 32-lead electroencephalogram which was measured for both a resting baseline phase and during an active phase involving cognitive processing using the neuropsychological Stroop test. The cognitive performance of each participant was also assessed using the Mini-Mental State Exam (MMSE) and the Cognistat assessment tools.
Results: Numerous electroencephalographic variables (both baseline and changes from baseline to active phase) such as delta, theta, alpha, beta and gamma activity were significantly associated to both global and domain specific cognitive performance derived from the MMSE and Cognistat (p<0.05). Subsequent multiple regression analysis yielded initial predictive models identifying individual EEG variables that were the strongest predictors of the different cognitive variable such as global cognition, memory and spatial construction.
Conclusions: The study tentatively demonstrates that the dynamic nature of brain activity may allow prediction of not only global cognitive performance, but also domain specific performance in cognitive domains such as memory and spatial construction. The current predictor models can be further developed using hybridisation, and/or more advanced analysis such as Support Vector Machines and Neural Network that may enhance predictive capabilities.
Keywords:
Electroencephalography,
Cognition,
cognitive impairment,
biomarker,
prediction
Conference:
ASP2015 - 25th Annual Conference of the Australasian Society for Psychophysiology, Sydney, Australia, 2 Dec - 4 Dec, 2015.
Presentation Type:
Oral Presentation
Topic:
Psychophysiology
Citation:
Lees
T,
Maharaj
S and
Lal
S
(2015). Electroencephalographic markers of subjective cognitive performance: implications towards electrophysiological prediction of early cognitive decline.
Conference Abstract:
ASP2015 - 25th Annual Conference of the Australasian Society for Psychophysiology.
doi: 10.3389/conf.fnhum.2015.219.00057
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Received:
25 Sep 2015;
Published Online:
30 Nov 2015.
*
Correspondence:
Mr. Ty Lees, University of Technology, Sydney, School of Life Sciences, Ultimo, New South Wales, Australia, Ty.Lees@live.com.au