Search

Our perception of time varies with the degree of cognitive engagement in tasks. The perceived passage of time accelerates while working on demanding tasks, whereas time appears to drag during boring situations. Our experiment aimed at investigating whether this relationship is mutual: Can manipulated announcements of elapsed time systematically affect the attentional resources applied to a cognitive task? We measured behavioral performance and the EEG in a whole report working memory paradigm with six items of different colors that each had to be reported after a short delay period. The 32 participants were informed about the current time after each 20 trials, while the clock was running at either 100% (normal), 120% (fast), or 80% (slow) of normal clock speed depending on the experimental block. The mean number of correctly reported colors per trial was significantly increased in the fast as compared to the slow and normal clock conditions. In the EEG, we focused on neural oscillations during working memory encoding and storage. As an electrophysiological correlate of task engagement, frontal theta power during the storage interval was increased in the fast clock condition. Also, the power of frontal theta oscillations predicted the number of correctly reported colors on a single-trial basis. This shows that a covert manipulation of clock speed can lead to an improvement in cognitive performance, presumably mediated by a higher allocation of attentional resources resulting from an adaptation of the subjective passage of time during an experiment. [ABSTRACT FROM AUTHOR]

How coherent neural oscillations are involved in task execution is a fundamental question in neuroscience. Although several electrophysiological studies have tackled this issue, the brain-wide task modulation of neural coherence remains uncharacterized. Here, with a fast fMRI technique, we studied shifts of brain-wide neural coherence across different task states in the ultraslow frequency range (0.01–0.7 Hz). First, we examined whether the shifts of the brain-wide neural coherence occur in a frequency-dependent manner. We quantified the shift of a region's average neural coherence by the inter-state variance of the mean coherence between the region and the rest of the brain. A clustering analysis based on the variance's spatial correlation between frequency components revealed four frequency bands (0.01–0.15 Hz, 0.15–0.37 Hz, 0.37–0.53 Hz, and 0.53–0.7 Hz) showing band-specific shifts of the brain-wide neural coherence. Next, we investigated the similarity of the inter-state variance's spectra between all pairs of regions. We found that regions showing similar spectra correspond to those forming functional modules of the brain network. Then, we investigated the relationship between identified frequency bands and modules' inter-state variances. We found that modules showing the highest variance are those made up of parieto-occipital regions at 0.01–0.15 Hz, while it is replaced with another consisting of frontal regions above 0.15 Hz. Furthermore, these modules showed specific shifting patterns of the mean coherence across states at 0.01–0.15 Hz and above 0.15 Hz, suggesting that identified frequency bands differentially contribute to neural interactions during task execution. Our results highlight that usage of the fast fMRI enables brain-wide investigation of neural coherence up to 0.7 Hz, which opens a promising track for assessment of the large-scale neural interactions in the ultraslow frequency range. [ABSTRACT FROM AUTHOR]