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The last two decades of electrophysiological and neuroimaging research converged that the activity in the medial frontal cortex plays a pivotal role in cognitive control processes. Notably, the midfrontal theta (MFT) oscillatory EEG power, as well as activity in the anterior midcingulate cortex (aMCC) or pre-supplementary motor area (preSMA), were consistently proclaimed as markers of conflict processing. However, these brain signals are strongly correlated with response time (RT) variability in various non-conflict tasks, which overshadows the true nature of their involvement. Our previous study (Beldzik et al., 2022) successfully identified these brain signals during a simultaneous EEG-fMRI experiment implementing Stroop and Simon tasks. Based on the assumption that overcoming the habitual prepotent response during high interference trials require additional neural resources beyond simple decision variable represented in RTs, here we aim to verify if these markers exhibit a congruency effect beyond RT variations. Furthermore, we explored if these brain signals represent either proactive or reactive cognitive control mechanisms by investigating two widely known behavioral phenomena observed in conflict tasks: proportion congruency and congruency sequence effects. The results revealed partially null findings for MFT activity, yet a distinct cognitive control specialization between aMCC and preSMA. Our study provides novel evidence that the former is involved in proactive control mechanisms, possibly contingency learning, whereas the latter reflects reactive control mechanisms by exhibiting a strong congruency effect regardless of RT variation and responding to adaptive behavior.

In recent decades magnetic resonance imaging (MRI) has established itself as the golden standard for studying human brain structure. As a result, it has become increasingly more important to identify technical and physiological factors that may influence study outcomes and contribute to misleading conclusions. This work set out to investigate and compare the variability in voxel-based morphometry (VBM) associated with data quality and time-of-day (TOD) when images are collected using a large longitudinal dataset (N = 72). To test the replicability of the results connected to each factor, the analyses were conducted in two comparable cohorts (each N = 36). The replicated TOD differences were further tested for their correlation with indices of sleep. We report that TOD is a significant and partially replicable predictor of the variability in VBM with the magnitude of the observed differences regionally connected to sleep length. Although data quality also has a prevalent impact on VBM, the affected areas were inconsistent across the two datasets. Interestingly, certain overlapping regions were identified in both analyses, showing that longitudinal results could be misattributed to image quality unless this factor is accounted for. All in all, both TOD and data quality are crucial variables to be considered and controlled for at the stage of experimental planning, as well as data acquisition and analysis. Inclusion of these parameters in the study designs can greatly improve the reliability and replicability of the reported MRI results.

Background: Cataract is one of the most common age-related vision deteriorations, leading to opacification of the lens and therefore visual impairment as well as blindness. Both cataract extraction and the implantation of blue light filtering lens are believed to improve not only vision but also overall functioning. Methods: Thirty-four cataract patients were subject to resting-state functional magnetic resonance imaging before and after cataract extraction and intraocular lens implantation (IOL). Global and local graph metrics were calculated in order to investigate the reorganization of functional network architecture associated with alterations in blue light transmittance. Psychomotor vigilance task (PVT) was conducted. Results: Graph theory-based analysis revealed decreased eigenvector centrality after the cataract extraction and IOL replacement in inferior occipital gyrus, superior parietal gyrus and many cerebellum regions as well as increased clustering coefficient in superior and inferior parietal gyrus, middle temporal gyrus and various cerebellum regions. PVT results revealed significant change between experimental sessions as patients responded faster after IOL replacement. Moreover, a few regions were correlated with the difference in blue light transmittance and the time reaction in PVT. Conclusion: Current study revealed substantial functional network architecture reorganization associated with cataract extraction and alteration in blue light transmittance.

Humans can be classified as early, intermediate and late chronotypes based on the preferred sleep and wakefulness patterns. The anatomical basis of these distinctions remains largely unexplored. Using magnetic resonance imaging data from 113 healthy young adults (71 females), we aimed to replicate cortical thickness and grey matter volume chronotype differences reported earlier in the literature using a greater sample size, as well as to explore the volumetric white matter variation linked to contrasting circadian phenotypes. Instead of comparing the chronotypes, we correlated the individual chronotype scores with their morphometric brain measures. The results revealed one cluster in the left fusiform and entorhinal gyri showing increased cortical thickness with increasing preference for eveningness, potentially providing an anatomical substrate for chronotype-sensitive affective processing. No significant results were found for grey and white matter volume. We failed to replicate cortical thickness and volumetric grey matter distinctions in the brain regions reported in the literature. Furthermore, we found no association between white matter volume and chronotype. Thus, while this study confirms that circadian preference is associated with specific structural substrates, it adds to the growing concerns that reliable and replicable neuroimaging research requires datasets much larger than those commonly used.

The error-related negativity (ERN) is a negative deflection in the event-related potential that is maximal approximately 50 ms after the commission of an error. The ERN is generated in the anterior cingulate cortex (ACC), a region implicated in both cognitive and emotional processing. Despite a growing body of research concerning the ERN, discussion regarding its functional significance remains open. The conflict and reinforcement-learning theories point at specific, ACC-related processes, involved in generation of the ERN and describe the process of error monitoring itself in human brain. Above mentioned theories explain what happens on neuronal level when individual commits an error, but they do not emphasize the crucial role of individual differences in modulating the ERN magnitude. On the other hand, there is a dynamically growing area of research suggesting that ERN is heritable, stable over time and linked with several dimensions of personality, that may interact with motivational, contextual factors and moderate the magnitude of the ERN. This approach defines ERN as a neural marker of a neurobehavioral trait and variation in its amplitude is linked with individual differences having impact on emotional or motivational aspects of error processing. Therefore, we would focus on selective literature review concerning ERN in the light of motivational factors and individual differences and present implications and future research directions in this area.

Melanopsin, a G family coupled receptor, found within the ganglion cell layer in the retina, plays an important role in non-image-forming visual functions, including hormone secretion, entrainment of circadian rhythms, cognitive and affective processes. Diffuse projections of melanopsin-containing cells to many brain areas suggest that different responses may involve different neural projections, thus different melanopsin cells. Considering the complexity of the melanopsin system, its contribution to so many different biological functions is not surprising. In this review, we summarize the current knowledge about melanopsin in terms of its photophysics, photochemistry, mechanisms of activation, cell signaling, morphology, and physiology. In the last part, the role of melanopsin in image and non-image forming processes and cognitive and affective functioning of animals and humans, are discussed. Although in recent years considerable insight has been gained into the melanopsin system, it still remains an open question of how one protein expressed by several thousand cells in the retina, could be responsible for so many diverse functions and what activation mechanism(s) it uses.

Sleep is a complex and dynamic process for maintaining homeostasis, and a lack of sleep can disrupt whole-body functioning. No organ is as vulnerable to the loss of sleep as the brain. Accordingly, we examined a set of task-based functional magnetic resonance imaging (fMRI) data by using graph theory to assess brain topological changes in subjects in a state of chronic sleep restriction, and then identified diurnal variability in the graph-theoretic measures. Task-based fMRI data were collected in a 1.5T MR scanner from the same participants on two days: after a week of fully restorative sleep and after a week with 35% sleep curtailment. Each day included four scanning sessions throughout the day (at approximately 10:00 AM, 2:00 PM, 6:00 PM, and 10:00 PM). A modified spatial cueing task was applied to evaluate sustained attention. After sleep restriction, the characteristic path length significantly increased at all measurement times, and small-worldness significantly decreased. Assortativity, a measure of network fault tolerance, diminished over the course of the day in both conditions. Local graph measures were altered primarily across the limbic system (particularly in the hippocampus, parahippocampal gyrus, and amygdala), default mode network, and visual network.

There is a growing interest in human gamma-band oscillatory activity due to its direct link to neuronal populations, its associations with many cognitive processes, and its positive relationship with fMRI BOLD signal. Visual gamma has been successfully detected using concurrent EEG-fMRI recordings and linked to activity in the visual cortex using voxel-wise regression analysis. As gamma-band oscillations reflect predominantly feedforward projections between brain regions, its inclusion in functional connectivity analysis is highly recommended; however, very few studies have investigated this line of research. In the current study, we aimed to explore this gap by asking which fMRI brain network is related to gamma activity induced by the color discrimination task. Advanced denoising strategies and multitaper spectral decomposition were applied to EEG data to detect gamma oscillations, and group independent component analysis was performed on fMRI data to identify task-related neural networks. Despite using only trials without motor response (50% of the trials), the two neural measures were successfully coupled. One of the six task-related networks, the occipito-parietal network, exhibited significant trial-by-trial covariations with gamma oscillations. In addition to the expected extrastriate visual cortex, the network encompasses extensive brain activations in the precuneus, bilateral intraparietal, and anterior insular cortices. We argue that the visual cortex is the source of gamma, whereas the remaining brain regions exhibit feedforward and feedback connections related to this oscillatory activity. Our findings provide evidence for the electrophysiological basis of the connectivity revealed by BOLD signal and impart novel insights into the neural mechanism of color discrimination.

Have you ever been to Krakow? If so, then you may recognize the Wawel Royal Castle from a picture due to your personal semantic memory, which stores all autobiographically significant concepts and repeated events of your past. If not, then you might still recognize the Wawel Royal Castle and be able to locate it on a map due to your spatial semantic memory. When recognizing a familiar landmark, how does neural activity depend on your memory related to that place? To address this question, we combined a novel task - the Krakow paradigm - with fMRI. In this task, participants are presented with a set of pictures showing various Krakow landmarks, each followed by two questions - one about its location, and the other about seeing the place in real-life, to trigger spatial and/or personal semantic memory, respectively. Group independent component analysis of fMRI data revealed several brain networks sensitive to the task conditions. Most sensitive was the medial temporal lobe network comprising bilateral hippocampus, parahippocampal, retrosplenial, and angular gyri, as well as distinct frontal areas. In agreement with the contextual continuum perspective, this network exhibited robust stimulus-related activity when the two memory types were combined, medium for spatial memory, and the weakest for baseline condition. The medial prefrontal network showed the same, pronounced deactivation for spatial memory and baseline conditions, yet far less deactivation for places seen in real-life. This effect was interpreted as self-referential processes counterbalancing the suppression of the brain's 'default mode.' In contrast, the motor, frontoparietal, and cingulo-opercular networks exhibited the strongest response-related activity for the spatial condition. These findings indicate that recognizing places based solely on general semantic knowledge requires more evidence accumulation, additional verbal semantics, and greater top-down control. Thus, the study imparts a novel insight into the neural mechanisms of place recognition. The Krakow paradigm has the potential to become a useful tool in future longitudinal or clinical studies.

There is a close relationship between progress in learning and the error-monitoring system. EEG and fMRI studies using probabilistic learning have revealed the distinct dynamics of this system after response and feedback, i.e. an increase of error-related and a decrease of feedback-related activity in the anterior cingulate cortex (ACC). Based on the existing theories, it can be presumed that during deterministic learning feedback-related activity in ACC would also increase. Since these assumptions have not yet been confirmed, it can be only speculated based on the data from the probabilistic paradigms how the information is being integrated within the ACC during deterministic learning. Here we implemented the Paired Associate Deterministic Learning task to the EEG and fMRI experiments. The analysis of EEG data showed a significant increase in the amplitude for both ERN and FN. Similarly, the fMRI results showed an increase in response-related and feedback-related activity of the ACC in erroneous trials. Our findings are in line with the current theories of ACC function: increasing ACC activity can be linked to the detected discrepancy between expected and obtained outcomes. We argue that expectancy violations in the course of deterministic learning are signalled by both, internal and external evaluation system.

Behavioural research has revealed the influence of motivation conditions on cognitive task performance and demonstrated that these influences are modulated by temperament factors. Modern neuroimaging methods enable analysis of neuropsychological mechanisms through which individual differences in reinforcement sensitivity may influence cognitive functioning. In the study, fifty-six participants were scored on the Cloninger's Temperament and Character Inventory to assess punishment and reward sensitivity. Then, subjects participated in an EEG experiment using the numerical Stroop task under different motivational conditions. In one condition, they were punished for erroneous responses; in the other, they were rewarded for correct performance. We analysed event related changes in EEG spectral power to investigate the influence of temperamentally driven differences on error-related oscillatory brain activity. In agreement with previous findings, after incorrect responses an increase in frontocentral theta (3-7 Hz) and a decrease in occipital alpha (10-11 Hz) power were observed. Moreover, a multivariate regression analysis showed that these spectral markers were modulated by temperamental trait Novelty Seeking in the reward condition. To our knowledge, we are the first to demonstrate such a relationship between individual differences and error-related oscillatory activity. This neuronal pattern may explain why participants that score high on Novelty Seeking trait are highly motivated and strongly engaged in a task when a reward might be earned. Thus, in conclusion we emphasise that to understand an individual's response to errors, it is necessary to account simultaneously for motivational conditions as well as temperament traits.

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. As respiratory fluctuations have 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.

Item does not contain fulltext General linear model (GLM) is a standard and widely used fMRI analysis tool. It enables the detection of hypothesis-driven brain activations. In contrast, Independent Component Analysis (ICA) is a powerful technique, which enables the detection of data-driven spatially independent networks. Hybrid approaches that combine and take advantage of GLM and ICA have been proposed. Yet the choice of the best method is still a challenge, considering that the techniques may yield slightly different results regarding the number of brain regions involved in a task. A poor statistical power or the deviance from the predicted hemodynamic response functions is possible cause for GLM failures in extracting some activations picked by ICA. However, there might be another explanation for different results obtained with GLM and ICA approaches, such as networks cancelation. In this paper, we propose a new supplementary method that can give more insight into the functional data as well as help to clarify inconsistencies between the results of studies using GLM and ICA. We introduce a contributive sources analysis (CSA), which provides a measure of the number and the strength of the neural networks that significantly contribute to brain activation. CSA, applied to fMRI data of anti-saccades, enabled us to verify whether the brain regions involved in the task are dominated by a single network or serve as key nodes for particular networks interaction. Moreover, when applying CSA to the atlas-defined regions-of-interest, results indicated that activity of the parieto-medial temporal network was suppressed by the eye field network and the default mode network. Thus, this effect of networks cancelation explains the absence of parieto-medial temporal activation within the GLM results. Together, those findings indicate that brain activations are a result of complex network interactions. Applying CSA appears to be a useful tool to reveal additional findings outside the scope of the "fixed-model" GLM and data-driven ICA approaches.

Motor activity of humans displays complex temporal fluctuations which can be characterized by scale-invariant statistics, thus documenting that structure and fluctuations of such kinetics remain similar over a broad range of time scales. Former studies on humans regularly deprived of sleep or suffering from sleep disorders predicted change in the invariant scale parameters with respect to those representative for healthy subjects. In this study we investigate the signal patterns from actigraphy recordings by means of characteristic measures of fractional point processes. We analyse spontaneous locomotor activity of healthy individuals recorded during a week of regular sleep and a week of chronic partial sleep deprivation. Behavioural symptoms of lack of sleep can be evaluated by analysing statistics of duration times during active and resting states, and alteration of behavioural organization can be assessed by analysis of power laws detected in the event count distribution, distribution of waiting times between consecutive movements and detrended fluctuation analysis of recorded time series. We claim that among different measures characterizing complexity of the actigraphy recordings and their variations implied by chronic sleep distress, the exponents characterizing slopes of survival functions in resting states are the most effective biomarkers distinguishing between healthy and sleep-deprived groups., Communicated at UPON2015, 14-17 July 2015, Barcelona. 21 pages, 11 figures; updated: figures 4-7, text revised, expanded Sec. 1,3,5

The saccadic eye movement system provides an excellent model for investigating basic cognitive processes and flexible control over behaviour. While the mechanism of pro-saccades (PS) is well known, in the case of the anti-saccade task (AS) it is still not clear which brain regions play a role in the inhibition of reflexive saccade to the target, nor what is the exact mechanism of vector inversion (i.e. orienting in the opposite direction). Independent component analysis (ICA) is one of the methods being used to establish temporally coherent brain regions, i.e. neural networks related to the task. In the present study ICA was applied to fMRI data from PS and AS experiments. The study revealed separate networks responsible for saccade generation into the desired direction, the inhibition of automatic responses, as well as vector inversion. The first function is accomplished by the eye fields network. The inhibition of automatic responses is associated with the executive control network. Vector inversion seems to be accomplished by the network comprising a large set of areas, including intraparietal sulcus, precuneus/posterior cingulate cortices, retrosplenial and parahippocampal. Those regions are associated with the parieto-medial temporal pathway, so far linked only to navigation. These results provide a new insight into understanding of the processes of the inhibition and vector inversion.

Establishing a role of the dorsal medial frontal cortex in the performance monitoring and cognitive control has been a challenge to neuroscientists for the past decade. In light of recent findings, the conflict monitoring hypothesis has been elaborated to an action-outcome predictor theory. One of the findings that led to this re-evaluation was the fMRI study in which conflict-related brain activity was investigated in terms of the so-called time on task effect, i.e., a linear increase of the BOLD signal with longer response times. The aim of this study was to investigate brain regions involved in the processing of saccadic response conflict and to account for the time on task effect. A modified spatial cueing task was implemented in the event-related fMRI study with oculomotor responses. The results revealed several brain regions which show higher activity for incongruent trials in comparison to the congruent ones, including pre-supplementary motor area together with the frontal and parietal regions. Further analysis accounting for the effect of response time provided evidence that these brain activations were not sensitive to time on task but reflected purely the congruency effect.

Circadian rhythms and restricted sleep length affect cognitive functions and, consequently, the performance of day to day activities. To date, no more than a few studies have explored the consequences of these factors on oculomotor behaviour. We have implemented a spatial cuing paradigm in an eye tracking experiment conducted four times of the day after one week of rested wakefulness and after one week of chronic partial sleep restriction. Our aim was to verify whether these conditions affect the number of a variety of saccadic task errors. Interestingly, we found that failures in response selection, i.e. premature responses and direction errors, were prone to time of day variations, whereas failures in response execution, i.e. omissions and commissions, were considerably affected by sleep deprivation. The former can be linked to the cue facilitation mechanism, while the latter to wake state instability and the diminished ability of top-down inhibition. Together, these results may be interpreted in terms of distinctive sensitivity of orienting and alerting systems to fatigue. Saccadic eye movements proved to be a novel and effective measure with which to study the susceptibility of attentional systems to time factors, thus, this approach is recommended for future research.

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. Fil: Ochab, Jeremi K.. Uniwersytet Jagielloński W Krakowie; Polonia Fil: Tyburczyk, Jacek. Uniwersytet Jagielloński W Krakowie; Polonia Fil: Beldzik, Ewa. Uniwersytet Jagielloński W Krakowie; Polonia Fil: Chialvo, Dante Renato. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina Fil: Domagalik, Aleksandra. Uniwersytet Jagielloński W Krakowie; Polonia Fil: Fafrowicz, Magdalena. Uniwersytet Jagielloński W Krakowie; Polonia Fil: Gudowska Nowak, Ewa. Uniwersytet Jagielloński W Krakowie; Polonia Fil: Marek, Tadeusz. Uniwersytet Jagielloński W Krakowie; Polonia Fil: Nowak, Maciej A.. Uniwersytet Jagielloński W Krakowie; Polonia Fil: Oginska, Halszka. Uniwersytet Jagielloński W Krakowie; Polonia Fil: Szwed, Jerzy. Uniwersytet Jagielloński W Krakowie; Polonia

Reaction time (RT), a widely used measure of human performance in experimental psychology, has recently been included as a regressor of interest in functional magnetic resonance imaging (fMRI) data analysis. Few studies reported RT-related brain regions, but the nature of this activity is not fully understood. We aimed at exploring this topic by implementing a simple saccadic task which evokes fast and homogeneous reactions that require only the basic neural processes. Thus, a spatial cueing paradigm was chosen and implemented in a simultaneous fMRI and eye-tracking experiment. As a result, we found a wide set of brain regions showing trial-by-trial correlations of blood-oxygenation-level-dependent (BOLD) signal with saccadic RT. These regions included medial and lateral frontal lobes, bilateral intraparietal sulci, anterior insular cortices as well as the right thalamus and medial visual cortex. Further analysis was conducted in order to verify quantitatively the impact of a “time on task” effect on task-related hemodynamic responses (HDRs). The results provide evidence that even a small difference in RTs can be linked with significant increase of HDR in task-related areas. Moreover, this increase is not linear, but rather quadratic. Our findings highlight the importance of controlling for RT in fMRI data analysis when contrasting conditions that vary in RT to avoid the misinterpretation of results.

Objectives Independent Component Analysis (ICA) is a powerful data-driven technique, which separates EEG signals into functionally and physiologically distinct source activities. The aim of this study was to identify the neural sources, which contribute to scalp ERPs including N450. Methods Dense-array EEG data were obtained from 20 participants performing numerical Stroop task. By applying ICA, artifacts were identified and removed. The remaining neural sources underwent clustering and further clusters’ ERP analysis. Results While the traditional channels’ ERP analysis confirmed the occurrence of conflict-related N450 potential, the ICA results revealed two sources contributing to its variance: the mid-parietal cluster with source estimated in posterior cingulate cortex (PCC) and fronto-central cluster with source in anterior cingulate cortex (ACC). The former showed increased (prolonged) activity before the response for cognitively demanding trials, whereas the latter showed negative deflection after the response. PCC activity was decreased (shortened) before erroneous responses, while ACC showed strong error-related negativity. Conclusions PCC is responsible for stimulus evaluation, while ACC is responsible for evaluating the action–outcome. Moreover, errors are committed due to insufficient stimuli processing within PCC. Significance ICA proved to be reliable and effective method for ERP analysis, which shed new light into the brain potentials evoked by the numerical Stroop task.

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.