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Multiple aspects of brain functioning, including arousal, motivation, and cognitive performance, are governed by circadian rhythmicity. Although the recent rise in the use of magnetic resonance imaging (MRI) has enabled investigations into the macroscopic correlates of the diurnal brain processes, neuroanatomical studies are scarce. The current work investigated how time-of-day (TOD) impacts white (WM) and grey matter (GM) volumes using voxel-based morphometry (VBM) in a large dataset (N = 72) divided into two equal, comparable subsamples to assess the replicability of effects. Furthermore, we aimed to assess how the magnitude of these diurnal differences was related to actigraphy-derived indices of sleep health. The results extend the current knowledge by reporting that TOD is predominantly associated with regional WM volume decreases. Additionally, alongside corroborating previously observed volumetric GM decreases, we provide the first evidence for positive TOD effects. Higher replicability was observed for WM, with the only two replicated GM clusters being volumetric increases in the amygdala and hippocampus, and decreases in the retrosplenial cortex, with the latter more pronounced in individuals with shorter sleep times. These findings implicate the existence of region-specific mechanisms behind GM effects, which might be related to cognitive processes taking place during wakefulness and homeostatic sleep pressure.

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Multiple aspects of human psychophysiology, including mood and cognition, are subjected to diurnal rhythms. While the previous magnetic resonance imaging (MRI) studies have focused solely on the morningness-eveningness (ME) preference dichotomy, i.e. the circadian phase, the second key dimension of the diurnal rhythms, i.e. the strength of these preferences (amplitude; AM), has been completely overlooked. Uncovering the neural correlates of AM is especially important considering its link with negative emotionality. Structural T1-weighted neuroimaging data from 79 early (EC) and 74 late (LC) chronotypes were analysed to compare grey matter (GM) volume and cortical thickness. The study aimed to elucidate whether the subjective AM and its interaction with ME was a significant predictor of individual brain structure. Both GM volume and cortical thickness of the left primary visual cortex was negatively correlated with AM scores across the entire sample. Furthermore, EC and LC differed in their association between AM scores and the GM volume in the right middle temporal gyrus, with the positive and negative correlations reported respectively in the two groups. The current study underlines the importance of the visual system in circadian rhythmicity and provides possible neural correlates for AM-related differences in negative affect processing. Furthermore, the presence of the opposite correlations between brain anatomy and AM in the two groups suggests that the behavioural and neuronal chronotype differences might become more pronounced in individuals with extreme diurnal differences in mood and cognition, highlighting the necessity to additionally account for AM in neuroimaging studies.

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Both conflict and error processing have been linked to the midfrontal theta power (4-8 Hz) increase as indicated by EEG studies and greater hemodynamic activity in the anterior midcingulate cortex (aMCC) as indicated by fMRI studies. Conveniently, the source of the midfrontal theta power was estimated in or nearby aMCC. However, previous studies using concurrent EEG and fMRI recordings in resting-state or other cognitive tasks observed only a negative relationship between theta power and BOLD signal in the brain regions typically showing task-related deactivations. In this study, we used a simultaneous EEG-fMRI technique to investigate a trial-by-trial coupling between theta power and hemodynamic activity during the performance of two conflict tasks. Independent component analysis (ICA) was applied to denoise the EEG signal and select individual midfrontal EEG components, whereas group ICA was applied to fMRI data to obtain a functional parcellation of the frontal cortex. Using a linear mixed-effect model, theta power was coupled with the peak of hemodynamic responses from various frontal, cingulate, and insular cortical sites to unravel the potential brain sources that contribute to conflict- and error-related theta variability. Although several brain regions exhibited conflict-related increases in hemodynamic activity, the conflict pre-response theta showed only a negative correlation to BOLD signal in the midline area 9 (MA9), a region exhibiting conflict-sensitive deactivation. Conversely, and more expectedly, error-related theta showed a positive relationship to activity in the aMCC. Our results provide novel evidence suggesting that the amplitude of pre-response theta reflects the process of active inhibition that suppresses the MA9 activity. This process is affected independently by the stimulus congruency, reaction times variance, and is susceptible to the time-on-task effect. Finally, it predicts the commitment of an omission error. Together, our findings highlight that conflict- and error-related theta oscillations represent fundamentally different processes.

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The dataset contains structural T1-weighted magnetic resonance brain imaging data from 136 young individuals (87 females; age range from 18 to 35 years old) along with questionnaire-assessed measurements of trait-like chronotype, sleep quality and daytime sleepiness. The recruitment criteria excluded individuals with self-reported history of psychiatric or neurological conditions and current medication use. All the brain imaging sessions were performed between 5:20 PM and 8:55 PM in order to control the effect of time of day on acquired images. The data is mostly useful to scientists interested in circadian rhythmicity. It can be deployed in large-scale multicenter meta-analyzes investigating the structural brain correlates of chronotypes in humans. Additionally, the data could be of use in investigations into the effects of sleeping habits and latitude on brain anatomy.

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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.

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Background: Cataracts are associated with progressive blindness, and despite the decline in prevalence in recent years, it remains a major global health problem. Cataract extraction is reported to influence not only perception, attention and memory but also daytime sleepiness, ability to experience pleasure and positive and negative affect. However, when it comes to the latter, the magnitude and prevalence of this effect still remains uncertain. The current study aims to evaluate the hemodynamic basis of daytime sleepiness, ability to experience pleasure and positive and negative affect in cataract patients after the intraocular lens (IOL) implantation. Methods: Thirty-four cataract patients underwent resting-state functional magnetic resonance imaging evaluation before and after cataract extraction and intraocular lens implantation. Both global and local graph metrics were calculated in order to investigate the hemodynamic basis of excessive sleepiness (ESS), experiencing pleasure (SHAPS) as well as positive and negative affect (PANAS) in cataract patients. Results: Eigenvector centrality and clustering coefficient alterations associated with cataract extraction are significantly correlated with excessive sleepiness, experiencing pleasure as well as positive and negative affect. Conclusions: The current study reveals the hemodynamic basis of sleepiness, pleasure and affect in patients after cataract extraction and intraocular lens implantation. The aforementioned mechanism constitutes a proof for changes in functional network activity associated with postoperative vision improvement.

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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.

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The short wavelength, i.e., blue light, is crucial for non-image forming effects such as entrainment of the circadian system in humans. Moreover, many studies showed that blue light enhances alertness and performance in cognitive tasks. However, most scientific reports in this topic are based on experiments using short exposure to blue or blue-enriched light, and only a few focused on the effects of its reduced transmittance, especially in longer periods. The latter could potentially give insight into understanding if age-related sleep problems and cognitive decline are related to less amount of blue light reaching the retina, as the eyes' lenses yellow with age. In this study, we investigated the effects of prolonged blocking of blue light on cognitive functioning, in particular-sustained attention and visuospatial working memory, as well as on sleep, and melatonin and cortisol levels. A group of young, healthy participants was randomly allocated to either blue light blocking or control group. Depending on the group, participants wore amber contact lenses, reducing the transmittance of blue light by ∼90% or regular contact lenses for a period of 4 weeks. No changes were observed for measurements related to sleep and sleep-wake rhythm. Dim light melatonin onset, evening levels of melatonin, and morning cortisol answer did not show any significant alterations during blue light (BL) blockade. The significant effects were revealed both for sustained attention and visuospatial memory, i.e., the longer blocking the blue light lasted, the greater decrease in performance observed. Additionally, the follow-up session conducted ∼1 week after taking off the blue-blocking lenses revealed that in case of sustained attention, this detrimental effect of blocking BL is fully reversible. Our findings provide evidence that prolonged reduction of BL exposure directly affects human cognitive functioning regardless of circadian rhythmicity.

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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.

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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.

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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.

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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.

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Unravelling the neural mechanisms, which determine performance accuracy, is one of the key concepts in cognitive neuroscience. When compared to correct responses, shorter reaction times are commonly observed behavioural feature of errors committed in typical conflict tasks. Yet, little is known about the origins of this phenomenon. In this study, EEG and fMRI experiments were conducted using the numerical version of the Stroop paradigm, which yielded unique behavioural outcomes. Particularly, errors in numerical comparison had shorter reaction times than correct trials, whereas physical comparison resulted in the opposite pattern. This criss-crossing interaction effect was used as a marker when exploring time-courses of brain activity. Group independent component analysis was applied to neurophysiological data and event-related analysis was conducted on the components' time-courses. Results revealed one centro-parietal EEG component and one temporo-parietal fMRI neural network, which exhibited significant task and accuracy interactions. Showing linear increase that peaked right after the response onset, the activity of centro-parietal EEG component was linked to the decision variable signal, which reflects a process of accumulating evidence until reaching an action-triggering threshold. Both amplitude measurements and linear fits to the signal provided evidence for distinctive characteristics between numerical and physical comparisons, thereby explaining the behavioural outcomes: errors are committed due to accumulation of evidence in favour of the other (wrong) task instruction. The architecture of the temporo-parietal network, which comprises bilateral inferior temporal and intraparietal regions, is highly consistent with the recently established core "number network". These findings link perceptual decisions with the generalized magnitude system and impart novel insights into the neural determinants of errors in humans.

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Effective functioning in a complex environment requires adjusting of behavior according to changing situational demands. To do so, organisms must learn new, more adaptive behaviors by extracting the necessary information from externally provided feedback. Not surprisingly, feedback-guided learning has been extensively studied using multiple research paradigms. The purpose of the present study was to test the newly designed Paired Associate Deterministic Learning task (PADL), in which participants were presented with either positive or negative deterministic feedback. Moreover, we manipulated the level of motivation in the learning process by comparing blocks with strictly cognitive, informative feedback to blocks where participants were additionally motivated by anticipated monetary reward or loss. Our results proved the PADL to be a useful tool not only for studying the learning process in a deterministic environment, but also, due to the varying task conditions, for assessing differences in learning patterns. Particularly, we show that the learning process itself is influenced by manipulating both the type of feedback information and the motivational significance associated with the expected monetary reward.

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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.

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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.

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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.

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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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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.

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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.

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