No abstract

While it is well-established that monitoring the environment for the occurrence of relevant events represents a key executive function, it is still unclear whether such a function is mediated by domain-general or domain-specific mechanisms. We investigated this issue by combining event-related potentials (ERPs) with a behavioral paradigm in which monitoring processes (non-monitoring vs. monitoring) and cognitive domains (spatial vs. verbal) were orthogonally manipulated in the same group of participants. They had to categorize 3-dimensional visually presented words on the basis of either spatial or verbal rules. In monitoring blocks, they additionally had to check whether the word displayed a specific spatial configuration or whether it contained a certain consonant. The behavioral results showed slower responses for both spatial and verbal monitoring trials compared to non-monitoring trials. The ERP results revealed that monitoring did not interact with domain, thus suggesting the involvement of common underlying mechanisms. Specifically, monitoring acted on low-level perceptual processes (as expressed by an enhanced visual N1 wave and a sustained posterior negativity for monitoring trials) and on higher-level cognitive processes (involving larger positive modulations by monitoring trials over frontal and parietal scalp regions). The source reconstruction analysis of the ERP data confirmed that monitoring was associated with increased activity in visual areas and in right prefrontal and parietal regions (i.e., superior and inferior frontal gyri and posterior parietal cortex), which previous studies have linked to spatial and temporal monitoring. Our findings extend this research by supporting the domain-general nature of monitoring in the spatial and verbal domains.

No abstract

The ability to flexibly switch between tasks is a hallmark of cognitive control. Despite previous studies that have investigated whether different task-switching types would be mediated by distinct or overlapping neural mechanisms, no definitive consensus has been reached on this question yet. Here, we aimed at directly addressing this issue by recording the event-related potentials (ERPs) elicited by two types of task-switching occurring in the context of spatial and verbal cognitive domains. Source analysis was also applied to the ERP data in order to track the spatial dynamics of brain activity underlying task-switching abilities. In separate blocks of trials, participants had to perform either spatial or verbal switching tasks both of which employed the same type of stimuli. The ERP analysis, which was carried out through a channel- and time-uninformed mass univariate approach, showed no significant differences between the spatial and verbal domains in the modulation of switch and repeat trials. Specifically, relative to repeat trials, switch trials in both domains were associated with a first larger positivity developing over left parieto-occipital electrodes and with a subsequent larger negativity distributed over mid-left fronto-central sites. The source analysis reconstruction for the two ERP components complemented these findings by highlighting the involvement of left-lateralized prefrontal areas in task-switching. Overall, our results join and extend recent research confirming the existence of left-lateralized domain-general task-switching processes.

Functional near infrared spectroscopy and electroencephalography are non-invasive techniques that rely on sensors placed over the scalp. The spatial localization of the measured brain activity requires the precise individuation of sensor positions and, when individual anatomical information is not available, the accurate registration of these sensor positions to a head atlas. Both these issues could be successfully addressed using a photogrammetry-based method. In this study we demonstrate that sensor positions can be accurately detected from a video recorded with a smartphone, with a median localization error of 0.7 mm, comparable if not lower, to that of conventional approaches. Furthermore, we demonstrate that the additional information of the shape of the participant’s head can be further exploited to improve the registration of the sensor’s positions to a head atlas, reducing the median sensor localization error of 31% compared to the standard registration approach.