In this dissertation, I have addressed the question of how resting-state EEG markers primarily in the alpha frequency range are linked to general cognitive performance and age. In the three studies presented in the work, I show that alpha power, frequency, and temporal dynamics, have distinct contributions to cognitive control functions in different age groups. Moreover, individual alpha peak frequency as well as the slope of 1/f decay of the PSD shows consistent age-related alterations, while alpha power is linked to structural alterations in the white matter. Our research extends further existing literature by specifying relevant neural networks as well as important methodological considerations that should be taken into account when analysing properties of oscillations.

Background: Methamphetamine (MA) abuse is a global crisis that exacerbates sociopolitico-economic burdens in South Africa. MA use is associated with a myriad of neural abnormalities of structure and function, with associated neurocognitive deficits, particularly executive function (EF). Working memory (WM) training has been identified as a potential adjunct to treatment of substance use disorder (SUD) to improve EF in the hope of reducing relapse rates. Neuroimaging suggests MA alters intrinsic resting state functional connectivity (rsFC), and this may contribute to neuropsychological deficits observed in methamphetamine use disorder (MUD). Methods: This nested study analysed data described in Brooks et al. (2016), in which WM training was used as an adjunct to inpatient treatment of MUD. Healthy controls (HC, N = 25) were compared to two MUD groups, one receiving treatment as usual (TAU, N = 17), and one receiving additional cognitive training (CT, N = 24) in the form of a modified version of the ‘N-back' task (C-Ya). This task was also used to assess WMA in the neural scanner, using conditions of 0-back and 1-back across groups. The current research explored these data in a novel manner through examining rsFC. Hypotheses: It was predicted that: 1) HC and MUD participants would differ on measures of WMA, but WMA would improve in MA groups at follow-up compared to baseline and this would be augmented in the CT group; 2) rsFC networks of neural regions supporting WM would be predictive of ability to perform well and improve on WM tasks; and 3) MA groups would display heightened rsFC activity within and between resting state neural networks of the default mode network (DMN) and canonical cognitive control networks (CCNs). Results: Significant differences were observed between HC and MA groups in race and level of education, but not on WMA as tested in the scanner. The CT group, who completed WMA 3-back conditions, demonstrated significant improvement on this task post- intervention. Exploratory regression models showed the WM rsFC network did not demonstrate significant relationships with any clinical, demographic, or WM variables when controlling for multiple comparisons. Heightened connectivity within and between the DMN and CCNs was observed in the MUD compared to the HC group, which provided support for hypothesis 3. Exploratory multivariate regression models demonstrated race, age, education, duration of drug use, and an interaction of group and abstinence may impact rsFC in these networks. Post-hoc analyses identified pairwise network combinations affected by these variables. Conclusions: Despite limitations of this small study, it offers tentative preliminary insights into the largely unexplored field of rsFC in MA populations. This study supports limited research demonstrating hyperconnectivity within and between CCNs and DMN of MA users. This study also offers support for recent research suggesting that easier conditions of the Nback task may not reliably test all aspects of WM function. Exploratory analyses of covariates potentially affecting rsFC provide a platform for directions of future research.