The timing and dynamics of many diverse behaviors of mammals, e.g., patterns of animal foraging or human communication in social networks exhibit complex self-similar properties reproducible over multiple time scales. In this paper, we analyze spontaneous locomotor activity of healthy individuals recorded in two different conditions: during a week of regular sleep and a week of chronic partial sleep deprivation. After separating activity from rest with a pre-defined activity threshold, we have detected distinct statistical features of duration times of these two states. The cumulative distributions of activity periods follow a stretched exponential shape, and remain similar for both control and sleep deprived individuals. In contrast, rest periods, which follow power-law statistics over two orders of magnitude, have significantly distinct distributions for these two groups and the difference emerges already after the first night of shortened sleep. We have found steeper distributions for sleep deprived individuals, which indicates fewer long rest periods and more turbulent behavior. This separation of power-law exponents is the main result of our investigations, and might constitute an objective measure demonstrating the severity of sleep deprivation and the effects of sleep disorders.

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Attentional processes are fundamental to good cognitive functioning of human operators. The purpose of this study was to analyze the activity of neuronal networks involved in the orienting attention and executive control processes from the perspective of diurnal variability. Twenty-three healthy male volunteers meeting magnetic resonance (MR) inclusion criteria performed the Stroop Color-Word task (block design) in the MR scanner five times/day (06:00, 10:00, 14:00, 18:00, 22:00 h). The first scanning session was scheduled 1-1.5 h after waking. Between MR sessions, subjects performed simulated driving tasks in stable environmental conditions, with controlled physical activity and diet. Significant activation was found in brain regions related to the orienting attentional system: the parietal lobe (BA40) and frontal eye-fields (FEFs). There were also activations in areas of the executive control system: the fronto-insular cortex (FIC), dorsal anterior cingulate cortex (dACC), presupplementary motor area (preSMA), supplementary motor area (SMA), basal ganglia, middle temporal (MT; BA21), and dorsolateral prefrontal cortex (DLPFC), as a part of the central executive network. Significant deactivations were observed in the rostral anterior cingulate cortex (rACC), posterior cingulate cortex (PCC), superior frontal gyrus (SF), parietal lobe (BA39), and parahippocampal that are thought to comprise the default mode network (DMN). Additionally, the activated regions included bilaterally lingual gyrus and fusiform gyrus. The insula was bilaterally deactivated. Visual attention controlled by the goal-oriented attention system and comprising top-down and bottom-up mechanisms, activated by Stroop-like task, turned out to be prone to diurnal changes. The study results show the occurrence of time-of-day-related variations in neural activity of brain regions linked to the orienting attentional system (left parietal lobe-BA40, left and right FEFs), simultaneously providing arguments for temporal stability of the executive system and default mode network. These results also seem to suggest that the involuntary, exogenous (bottom-up) mechanism of attention is more vulnerable to circadian and fatigue factors than the voluntary (top-down) mechanism, which appear to be maintained at the same functional level during the day. The above phenomena were observed at the neural level.

The posterior midline region (PMR) –considered a core of the default mode network- is deactivated during successful performance in different cognitive tasks. The extent of PMR-deactivations is correlated with task-demands and associated with successful performance in various cognitive domains. In the domain of episodic memory, functional MRI (fMRI) studies found that PMR-deactivations reliably predict learning (successful encoding). Yet, it is unclear what explains this relation. One intriguing possibility is that PMR-deactivations are partially-mediated by respiratory artifacts. There is evidence that the fMRI signal in PMR is particularly prone to respiratory artifacts, because of its large surrounding blood vessels. Since respiratory fluctuations has been shown to track changes in attention, it is critical for the general interpretation of fMRI results to clarify the relation between respiratory fluctuations, cognitive performance, and fMRI signal. Here, we investigated this issue by measuring respiration during word encoding, together with a breath-holding condition during fMRI-scanning. Stimulus-locked respiratory analyses showed that respiratory fluctuations predicted successful encoding via a respiratory phase-locking mechanism. At the same time, the fMRI analyses showed that PMR-deactivations associated with learning were reduced during breath-holding and correlated with individual differences in the respiratory phase-locking effect during normal breathing. A left frontal region –used as a control region– did not show these effects. These findings indicate that respiration is a critical factor in explaining the link between PMR-deactivation and successful cognitive performance. Further research is necessary to demonstrate whether our findings are restricted to episodic memory encoding, or also extend to other cognitive domains.

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