Aperiodic activity differences in individuals with high and low temporal processing efficiency.

It is known that Temporal Information Processing (TIP) underpins our cognitive functioning. Previous research has focused on the relationship between TIP efficiency and oscillatory brain activity, especially the gamma rhythm; however, non-oscillatory (aperiodic or 1/f) brain activity has often been missed. Recent studies have identified the 1/f component as being important for the functioning of the brain. Therefore, the current study aimed to verify whether TIP efficiency is associated with specific EEG resting state cortical activity patterns, including oscillatory and non-oscillatory (aperiodic) brain activities. To measure individual TIP efficiency, we used two behavioral tasks in which the participant judges the order of two sounds separated by millisecond intervals. Based on the above procedure, participants were classified into two groups with high and low TIP efficiency. Using cluster-based permutation analyses, we examined between-group differences in oscillatory and non-oscillatory (aperiodic) components across the 1-90 Hz range. The results revealed that the groups differed in the aperiodic component across the 30-80 Hz range in fronto-central topography. In other words, participants with low TIP efficiency exhibited higher levels of aperiodic activity, and thus a flatter frequency spectrum compared to those with high TIP efficiency. We conclude that participants with low TIP efficiency display higher levels of 'neural noise', which is associated with poorer quality and speed of neural processing.

A common timing mechanism across different millisecond domains: evidence from perceptual and motor tasks.

Temporal information processing (TIP) constitutes a complex construct that underlies many cognitive functions and operates in a few hierarchically ordered time domains. This study aimed to verify the relationship between the tens of milliseconds and hundreds of milliseconds domains, referring to perceptual and motor timing, respectively. Sixty four young healthy individuals participated in this study. They underwent two auditory temporal order judgement tasks to assess their performance in the tens of milliseconds domain; on this basis, groups of high-level performers (HLP) and low-level performers (LLP) were identified. Then, a maximum tapping task was used to evaluate performance in the hundreds of milliseconds domain. The most remarkable result was that HLP achieved a faster tapping rate and synchronised quicker with their "internal clock" during the tapping task than did LLP. This result shows that there is a relationship between accuracy in judging temporally asynchronous stimuli and ability to achieve and maintain the pace of a movement adequate to one's internal pacemaker. This could indicate the strong contribution of a common timing mechanism, responsible for temporal organisation and coordination of behaviours across different millisecond domains.

Theta and Alpha Oscillatory Activity During Working Memory Maintenance in Long-Term Cannabis Users: The Importance of the Polydrug Use Context.

Background: Impairments in various subdomains of memory have been associated with chronic cannabis use, but less is known about their neural underpinnings, especially in the domain of the brain's oscillatory activity. Aims: To investigate neural oscillatory activity supporting working memory (WM) in regular cannabis users and non-using controls. We focused our analyses on frontal midline theta and posterior alpha asymmetry as oscillatory fingerprints for the WM's maintenance process. Methods: 30 non-using controls (CG) and 57 regular cannabis users-27 exclusive cannabis users (CU) and 30 polydrug cannabis users (PU) completed a Sternberg modified WM task with a concurrent electroencephalography recording. Theta, alpha and beta frequency bands were examined during WM maintenance. Results: When compared to non-using controls, the PU group displayed increased frontal midline theta (FMT) power during WM maintenance, which was positively correlated with RT. The posterior alpha asymmetry during the maintenance phase, on the other hand, was negatively correlated with RT in the CU group. WM performance did not differ between groups. Conclusions: Both groups of cannabis users (CU and PU), when compared to the control group, displayed differences in oscillatory activity during WM maintenance, unique for each group (in CU posterior alpha and in PU FMT correlated with performance). We interpret those differences as a reflection of compensatory strategies, as there were no differences between groups in task performance. Understanding the psychophysiological processes in regular cannabis users may provide insight on how chronic use may affect neural networks underlying cognitive processes, however, a polydrug use context (i.e., combining cannabis with other illegal substances) seems to be an important factor.