The resting-state human electroencephalogram power spectrum is dominated by alpha and theta oscillations, and also includes non-oscillatory broadband activity inversely related to frequency. Gratton proposed that alpha and theta oscillations are both related to cognitive control function, though in a complementary manner. Alpha activity is hypothesized to facilitate the maintenance of representations, such as task sets in preparation for expected task conditions. In contrast, theta activity would facilitate changes in representations, such as the updating of task sets in response to (...) unpredicted task demands. Therefore, theta should be related to reactive control, while alpha may be more relevant to proactive control. Less is known about the possible relationship between 1/f activity and cognitive control, which was analyzed here in an exploratory fashion. To investigate these hypothesized relationships, we recorded eyes-open and eyes-closed resting-state EEG from younger and older adults and subsequently tested their performance on a cued flanker task, expected to elicit both proactive and reactive control processes. Results showed that alpha power and 1/f offset were smaller in older than younger adults, whereas theta power did not show age-related reductions. Resting alpha power and 1/f offset were associated with proactive control processes, whereas theta power was related to reactive control as measured by the cued flanker task. All associations were present over and above the effect of age, suggesting that these resting-state EEG correlates could be indicative of trait-like individual differences in cognitive control performance, which may be already evident in younger adults, and are still similarly present in healthy older adults. (shrink)
Different hypotheses about the mechanisms underlying working memory lead to different predictions about working memory capacity when information is distributed across the two hemispheres. We present preliminary data suggesting that memory scanning time (a parameter often associated with working memory capacity) varies depending on how information is subdivided across hemispheres. The data are consistent with a distributed model of working memory.