In the face of multiple sensory streams, there may be competition for processing resources in multimodal cortical areas devoted to establishing representations. In such cases, alpha oscillations may serve to maintain the relevant representations and protect them from interference, whereas theta band activity may facilitate their updating when needed. It can be hypothesized that these oscillations would differ in response to an auditory stimulus when the eyes are open or closed, as intermodal resource competition may be more prominent in the former than in the latter case. Across two studies we investigated the role of alpha and theta power in multimodal competition using an auditory task with the eyes open and closed, respectively enabling and disabling visual processing in parallel with the incoming auditory stream. In a passive listening task (Study 1a), we found alpha suppression following a pip tone with both eyes open and closed, but subsequent alpha enhancement only with closed eyes. We replicated this eyes-closed alpha enhancement in an independent sample (Study 1b). In an active auditory oddball task (Study 2), we again observed the eyes open/eyes closed alpha pattern found in Study 1 and also demonstrated that the more attentionally demanding oddball trials elicited the largest oscillatory effects. Theta power did not interact with eye status in either study. We propose a hypothesis to account for the findings in which alpha may be endemic to multimodal cortical areas in addition to visual ones.

EEG alpha power varies under many circumstances requiring visual attention. However, mounting evidence indicates that alpha may not only serve visual processing, but also the processing of stimuli presented in other sensory modalities, including hearing. We previously showed that alpha dynamics during an auditory task vary as a function of competition from the visual modality (Clements et al., 2022) suggesting that alpha may be engaged in multimodal processing. Here we assessed the impact of allocating attention to the visual or auditory modality on alpha dynamics at parietal and occipital electrodes, during the preparatory period of a cued-conflict task. In this task, bimodal precues indicated the modality (vision, hearing) relevant to a subsequent reaction stimulus, allowing us to assess alpha during modality-specific preparation and while switching between modalities. Alpha suppression following the precue occurred in all conditions, indicating that it may reflect general preparatory mechanisms. However, we observed a switch effect when preparing to attend to the auditory modality, in which greater alpha suppression was elicited when switching to the auditory modality compared to repeating. No switch effect was evident when preparing to attend to visual information (although robust suppression did occur in both conditions). In addition, waning alpha suppression preceded error trials, irrespective of sensory modality. These findings indicate that alpha can be used to monitor the level of preparatory attention to process both visual and auditory information, and support the emerging view that alpha band activity may index a general attention control mechanism used across modalities.

Interest in broadband aperiodic brain activity (1/ f phenomenon) has increased exponentially over recent years, partly fueled by the development of tools to parameterize it (i.e., estimate its offset/intercept and exponent/slope) using the M/EEG power spectrum. Broadband aperiodic activity needs to be separated from narrowband periodic activity before its parameters are computed. A popular method, the fooof toolbox, is based on the data‐driven detection of narrowband‐periodic peaks, whose maximum number is set by the user. While increasing analytic flexibility, variability in the number of detected peaks may increase sensitivity to noise and reduce the reliability of aperiodic parameter estimates and the power of analytic pipelines. Here, we present an investigation of the effects of analytic choices (e.g., number of peaks, spectral estimation method) on metrics indicating the adequacy of spectral parametrization. These include the internal consistency (odd‐even reliability) of aperiodic estimates, the number of outliers generated, and their ability to detect effects. Across two different data sets (resting state and task‐based), we found a decrease in the reliability of intercept and slope estimates as more peaks were allowed to be extracted. To ameliorate this problem, we propose a theory‐driven modification of fooof labeled censored regression , whereby a theory‐driven range of frequencies expected to contain periodic activity is removed from all spectra, and the remaining power values are regressed on the remaining frequencies to obtain parameter estimates. This method shows more reliable and robust estimates compared to fooof , while avoiding overfitting.

White matter (WM) microstructural health declines with increasing age, with evidence suggesting that improved cardiorespiratory fitness (CRF) may mitigate this decline. Specifically, higher fit older adults tend to show preserved WM microstructural integrity compared to their lower fit counterparts. However, the extent to which fitness and aging independently impact WM integrity across the adult lifespan is still an open question, as is the extent to which cerebrovascular health mediates these relationships. In a large sample (N = 125, aged 25–72), we assessed the impact of age and estimated cardiorespiratory fitness on fractional anisotropy (FA, derived using diffusion weighted imaging, dwMRI) and probed the mediating role of cerebrovascular health (derived using diffuse optical tomography of the cerebral arterial pulse, pulse‐DOT) in these relationships. After orthogonalizing age and estimated fitness and computing a PCA on whole brain WM regions, we found several WM regions impacted by age that were independent from the regions impacted by estimated fitness (hindbrain areas, including brainstem and cerebellar tracts), whereas other areas showed interactive effects of age and estimated fitness (midline areas, including fornix and corpus callosum). Critically, cerebrovascular health mediated both relationships suggesting that vascular health plays a linking role between age, fitness, and brain health. Secondarily, we assessed potential sex differences in these relationships and found that, although females and males generally showed the same age‐related FA declines, males exhibited somewhat steeper declines than females. Together, these results suggest that age and fitness impact specific WM regions and highlight the mediating role of cerebrovascular health in maintaining WM health across adulthood.

The broadband shape of the EEG spectrum, summarized using a 1/ f ^x function, is thought to reflect the balance between excitation and inhibition in cortical regions (E:I balance). This balance is an important characteristic of neural circuits and could inform studies of aging, as older adults show a relative inhibitory activity deficit. Thus far, no studies have leveraged the event-related temporal dynamics of 1/ f ^x activity to better understand the phases of information processing, especially in the context of aging. Here, for the first time, we examined variations of this activity during the foreperiod of a cued flanker task in younger (YA) and older adults (OA), with picture cues varying in task relevance, relative novelty, and valence. We report a biphasic change in the spectral exponent (corresponding to negative slopes in log-log space) after cue presentation, independent of cue-elicited ERPs, with an initial period of increased negativity (indicating cortical inhibition, similar in YA and OA) followed by decreased negativity (indicating cortical excitation, especially in OA). The decrease in the exponent negativity was associated with lower performance and greater congruency costs in the flanker task. Finally, more novel cues reduced the shift towards excitation in OA, partly restoring their E:I balance, and diminishing congruency costs. These findings demonstrate that the broadband shape of the EEG spectrum varies dynamically in a manner that is predictive of subsequent behavior. They also expand our understanding of how neural communication shapes cognition in YA and OA and have implications for neuroscientific models of cognitive processing and age-related cognitive decline.

The resting-state human EEG power spectrum is dominated by alpha (8-12 Hz) and theta (4-8Hz) oscillations, and also includes non-oscillatory broadband activity inversely related to frequency (1/ f activity). Gratton (2018) 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 (which may prompt changes in task representations), while alpha may be more relevant to proactive control (which implies the maintenance of current task representations). 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 slope were smaller in older than younger adults, whereas theta power did not show age-related reductions. Resting alpha power and 1/ f slope were predictive of proactive control processes, whereas theta power was related to reactive control as measured by the cued flanker task. All predictive 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.