Diurnal variations of resting-state fMRI data: A graph-based analysis.

Circadian rhythms (lasting approximately 24 h) control and entrain various physiological processes, ranging from neural activity and hormone secretion to sleep cycles and eating habits. Several studies have shown that time of day (TOD) is associated with human cognition and brain functions. In this study, utilizing a chronotype-based paradigm, we applied a graph theory approach on resting-state functional MRI (rs-fMRI) data to compare whole-brain functional network topology between morning and evening sessions and between morning-type (MT) and evening-type (ET) participants. Sixty-two individuals (31 MT and 31 ET) underwent two fMRI sessions, approximately 1 hour (morning) and 10 h (evening) after their wake-up time, according to their declared habitual sleep-wake pattern on a regular working day. In the global analysis, the findings revealed the effect of TOD on functional connectivity (FC) patterns, including increased small-worldness, assortativity, and synchronization across the day. However, we identified no significant differences based on chronotype categories. The study of the modular structure of the brain at mesoscale showed that functional networks tended to be more integrated with one another in the evening session than in the morning session. Local/regional changes were affected by both factors (i.e., TOD and chronotype), mostly in areas associated with somatomotor, attention, frontoparietal, and default networks. Furthermore, connectivity and hub analyses revealed that the somatomotor, ventral attention, and visual networks covered the most highly connected areas in the morning and evening sessions: the latter two were more active in the morning sessions, and the first was identified as being more active in the evening. Finally, we performed a correlation analysis to determine whether global and nodal measures were associated with subjective assessments across participants. Collectively, these findings contribute to an increased understanding of diurnal fluctuations in resting brain activity and highlight the role of TOD in future studies on brain function and the design of fMRI experiments.

Measuring individual vulnerability to sleep loss--the CHICa scale.

The aim of this project was to construct a psychometrically satisfying scale to describe subjective reactions to sleep deprivation. First, on the basis of a literature review, a list of items was generated which reflected the negatively affected mood and reduced wellbeing associated with sleep loss. Additionally, psychology students were asked to describe their cognitive and emotional symptoms following a night with curtailed sleep. As a result, 69 items were included in the experimental set. University students (n = 102, females, mean age 22.5 ± 1.9 years) completed the form several times during 1 week in June (while preparing for examinations) and on a free day in September; a total of 460 forms were collected. The final, 26-item version of the scale was validated in a sleep deficit experiment lasting 1 week, conducted with 25 female participants (mean age 23.4 ± 1.9 years). Factor analysis showed 71.7% of total variance explained by four components: impaired thermoregulation (C for cold), disrupted appetite (H for hunger), affective problems (I for irritability) and lowered level of cognitive functioning (Ca for cognitive attenuation). A Polish version of the CHICa scale showed satisfactory psychometric properties. Cronbach's alpha of the subscales were between 0.90 and 0.95. All four subscales exhibited a significant increase with an experimental 3-h daily sleep restriction over a period of 1 week; cognitive attenuation was the most symptomatic. Cognitive problems (reduced concentration, comprehension and accuracy) and a lack of energy seem to be the most specific subjective manifestations of the chronic sleep deficit state. CHICa may be helpful in research on inter-and intra-individual differences and on the efficacy of various counteractive treatments for the consequences of sleep deprivation.

Tracing diurnal differences in brain anatomy with voxel-based morphometry - associations with sleep characteristics.

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.

Contributive sources analysis: a measure of neural networks' contribution to brain activations.

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.

The effects of diurnal variability and modality on false memories formation.

The main objective of the current study was to investigate the effect of time of day on visual and auditory, short-term memory (STM), and long-term memory (LTM) distortions using a hybrid Deese-Roediger-McDermott procedure. In Experiment 1, we used semantically related words, whereas in Experiment 2 - words were characterized by phonological similarity. The results showed a relationship between modality and types of stimuli. In STM, more semantic errors were found in the evening for items presented visually and more errors following auditory presentation for phonologically similar words. In LTM, the analysis revealed a higher rate of semantic distortions in the evening hours for auditorily presented words. For words with phonological similarity, we observed more errors in the evening without the effect of modality. The results support the hypothesis that more reliance is placed on elaborative processing in the evening and more on maintenance processing in the morning; however, this is not modality invariant.

The subjective amplitude of the diurnal rhythm matters - Chronobiological insights for neuroimaging studies.

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.

Dynamics of working memory process revealed by independent component analysis in an fMRI study.

Human memory is prone to errors in many everyday activities but also when cultivating hobbies such as traveling and/or learning a new language. For instance, while visiting foreign countries, people erroneously recall foreign language words that are meaningless to them. Our research simulated such errors in a modified Deese-Roediger-McDermott paradigm for short-term memory with phonologically related stimuli aimed at uncovering behavioral and neuronal indices of false memory formation with regard to time-of-day, a variable known to influence memory. Fifty-eight participants were tested in a magnetic resonance (MR) scanner twice. The results of an Independent Component Analysis revealed encoding-related activity of the medial visual network preceding correct recognition of positive probes and correct rejection of lure probes. The engagement of this network preceding false alarms was not observed. We also explored if diurnal rhythmicity influences working memory processes. Diurnal differences were seen in the default mode network and the medial visual network with lower deactivation in the evening hours. The GLM results showed greater activation of the right lingual gyrus, part of the visual cortex and the left cerebellum in the evening. The study offers new insight into the mechanisms associated with false memories, suggesting that deficient engagement of the medial visual network during the memorization phase of a task results in short-term memory distortions. The results shed new light on the dynamics of working memory processes by taking into account the effect of time-of-day on memory performance.

When practice does not make a perfect - paradoxical learning curve in schizophrenia and bipolar disorder revealed by different serial reaction time task variants.

Introduction: Our previous studies identified a paradoxical implicit motor learning curve in schizophrenia (SZ) and bipolar disorder (BD) patients. This study aimed to verify whether those previously observed deficits may be captured by a new version of the ambidextrous serial reaction time task (SRTT), prepared for use in the MRI. Methods: This study involved 186 participants. A total of 97 participants (33 BD, 33 SZ, and 31 healthy controls, HCs) completed the original, unlimited time response variant of SRTT. A total of 90 individuals (30 BD, 30 SZ, and 30 HCs) underwent a newer, limited response time version of this procedure. Results: There was no significant difference in terms of implicit motor learning indices between both limited and unlimited response time SRTT. Compared to HCs, SZ, and BD patients presented decreased indices of implicit motor learning. Both clinical groups showed a paradoxical learning pattern that differed significantly from the HCs. Moreover, in the SZ group, the pattern depended on the hand performing SRTT. Discussion: The limited response time SRTT variant allowed us to replicate the findings of disrupted implicit motor learning in SZ and BD. The use of this paradigm in further neuroimaging studies may help to determine the neuronal underpinnings of this cognitive dysfunction in the abovementioned clinical groups.

Neural networks related to pro-saccades and anti-saccades revealed by independent component analysis.

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.

Analysis of fMRI Signals from Working Memory Tasks and Resting-State of Brain: Neutrosophic-Entropy-Based Clustering Algorithm.

This study applies a neutrosophic-entropy-based clustering algorithm (NEBCA) to analyze the fMRI signals. We consider the data obtained from four different working memory tasks and the brain's resting state for the experimental purpose. Three non-overlapping clusters of data related to temporal brain activity are determined and statistically analyzed. Moreover, we used the Uniform Manifold Approximation and Projection (UMAP) method to reduce system dimensionality and present the effectiveness of NEBCA. The results show that using NEBCA, we are able to distinguish between different working memory tasks and resting-state and identify subtle differences in the related activity of brain regions. By analyzing the statistical properties of the entropy inside the clusters, the various regions of interest (ROIs), according to Automated Anatomical Labeling (AAL) atlas crucial for clustering procedure, are determined. The inferior occipital gyrus is established as an important brain region in distinguishing the resting state from the tasks. Moreover, the inferior occipital gyrus and superior parietal lobule are identified as necessary to correct the data discrimination related to the different memory tasks. We verified the statistical significance of the results through the two-sample t-test and analysis of surrogates performed by randomization of the cluster elements. The presented methodology is also appropriate to determine the influence of time of day on brain activity patterns. The differences between working memory tasks and resting-state in the morning are related to a lower index of small-worldness and sleep inertia in the first hours after waking. We also compared the performance of NEBCA to two existing algorithms, KMCA and FKMCA. We showed the advantage of the NEBCA over these algorithms that could not effectively accumulate fMRI signals with higher variability.

Neural spatio-temporal patterns of information processing related to cognitive conflict and correct or false recognitions.

Using a visual short-term memory task and employing a new methodological approach, we analyzed neural responses from the perspective of the conflict level and correctness/erroneous over a longer time window. Sixty-five participants performed the short-term memory task in the fMRI scanner. We explore neural spatio-temporal patterns of information processing in the context of correct or erroneous response and high or low level of cognitive conflict using classical fMRI analysis, surface-based cortical data, temporal analysis of interpolated mean activations, and machine learning classifiers. Our results provide evidence that information processing dynamics during the retrieval process vary depending on the correct or false recognition-for stimuli inducing a high level of cognitive conflict and erroneous response, information processing is prolonged. The observed phenomenon may be interpreted as the manifestation of the brain's preparation for future goal-directed action.

Task-dependent fractal patterns of information processing in working memory.

We applied detrended fluctuation analysis, power spectral density, and eigenanalysis of detrended cross-correlations to investigate fMRI data representing a diurnal variation of working memory in four visual tasks: two verbal and two nonverbal. We show that the degree of fractal scaling is regionally dependent on the engagement in cognitive tasks. A particularly apparent difference was found between memorisation in verbal and nonverbal tasks. Furthermore, the detrended cross-correlations between brain areas were predominantly indicative of differences between resting state and other tasks, between memorisation and retrieval, and between verbal and nonverbal tasks. The fractal and spectral analyses presented in our study are consistent with previous research related to visuospatial and verbal information processing, working memory (encoding and retrieval), and executive functions, but they were found to be more sensitive than Pearson correlations and showed the potential to obtain other subtler results. We conclude that regionally dependent cognitive task engagement can be distinguished based on the fractal characteristics of BOLD signals and their detrended cross-correlation structure.

Brain Under Fatigue - Can Perceived Fatigability in Multiple Sclerosis Be Seen on the Level of Functional Brain Network Architecture?

Background: Fatigue is one of the most common symptoms of multiple sclerosis (MS), significantly affecting the functioning of the patients. However, the neural underpinnings of physical and mental fatigue in MS are still vague. The aim of our study was to investigate the functional architecture of resting-state networks associated with fatigue in patients with MS. Methods: The sum of 107 high-functioning patients underwent a resting-state scanning session and filled out the 9-item Fatigue Severity Scale (FSS). Based on the FSS score, we identified patients with different levels of fatigue using the cluster analysis. The low-fatigue group consisted of n = 53 subjects, while the high-fatigue group n = 48. The neuroimaging data were analyzed in terms of functional connectivity (FC) between various resting-state networks as well as amplitude of low-frequency fluctuation (ALFF) and fractional amplitude of low-frequency fluctuations (fALFF). Results: Two-sample t-test revealed between-group differences in FC of posterior salience network (SN). No differences occurred in default mode network (DMN) and sensorimotor network (SMN). Moreover, differences in fALFF were shown in the right middle frontal gyrus and right superior frontal gyrus, however, no ALFF differences took place. Conclusion: Current study revealed significant functional network (FN) architecture between-group differences associated with fatigue. Present results suggest the higher level of fatigue is related to deficits in awareness as well as higher interoceptive awareness and nociception.

Neuroimaging of chronotype, sleep quality and daytime sleepiness: Structural T1-weighted magnetic resonance brain imaging data from 136 young adults.

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.

Vergence eye movements impairments in schizophrenia and bipolar disorder.

One of the most evaluated eye tracking tasks in schizophrenia (SZ) and bipolar disorder (BD) are smooth pursuit eye movements. They rely on the maintenance of slowly moving object on the fovea. While most of the studies evaluated tracking of a target that moves in the fronto-parallel plane, only two assessed vergence eye movements (VEM), which relies on the pursuit of object that moves in depth. The aim of our study was to compare VEM performance in SZ and BD. We evaluated 28 SZ patients, 32 BD patients and 25 healthy controls (HC). Participants underwent thorough optometric examination before eye tracking task. VEM were measured with the use of infrared eye tracker and dedicated vergence stimuli generator. SZ patients showed higher mean break and recovery points of fusion and shorter correct tracking time than HC. BD individuals revealed tracking accuracy deficits and higher number of saccades than HC. Compared to BD, SZ patients showed decrease of maximal convergence and divergence. Moreover, they presented tracking accuracy deficits of non-dominant eye: altered eyes positioning error during convergence and divergence gain. Exploratory analysis revealed significant gender differences between groups in terms of binocular VEM parameters. In this study we have recognized pattern of eye movement disturbances differentiating abovementioned groups. SZ patients showed decreased vergence tracking range with shorter tracking time and impaired accuracy of non-dominant eye, while BD patients showed higher number of saccades with decreased tracking accuracy. Neuroimaging studies are necessary to identify neuronal underpinnings of VEM impairments in SZ and BD.

Brain networks involved in place recognition based on personal and spatial semantics.

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.

Time-of-day effects on objective and subjective short-term memory task performance.

The time-of-day along with the synchrony effect (better performance at optimal times of the day according to the chronotype) on the cognitive performance has been well established in previous research. This influence is mediated by both circadian and homeostatic processes consistent with the Borbély two-process model. This experiment focused on the objective and subjective performance of the visual short-term memory task requiring holistic processing. Sixty-five young, healthy participants including 40 females were divided into morning and evening types and performed a given task in two sessions - in the morning and in the evening. Type division was made according to the chronotype questionnaire and polymorphism of the PER3 clock gene. The task was a modified version of Deese-Roediger-McDermott paradigm adjusted to study short-term memory, in which visual, abstract stimuli were used. The analysis was based on an exploratory approach investigating the influence of circadian and individual (sex) factors on execution of memory task. Evening types were more accurate in the task compared to morning types, regardless of the part of the day. The time-of-day effect was revealed on objective measures (reaction times for hits and false alarms) and subjective effort put into the performance. The reaction times were slower in the morning unlike the effort that was greater in the evening. The time-of-day × sex interaction was observed in the case of subjective effort: men described the task as more demanding in the evening. The results could be explained by differences in hemispheric dominance depending on the time-of-day. The report provides new patterns of behavioral data analysis, investigating sex aspects and use of self-assessment scales of performance.

Non-linear Functional Brain Co-activations in Short-Term Memory Distortion Tasks.

Recent works shed light on the neural correlates of true and false recognition and the influence of time of day on cognitive performance. The current study aimed to investigate the modulation of the false memory formation by the time of day using a non-linear correlation analysis originally designed for fMRI resting-state data. Fifty-four young and healthy participants (32 females, mean age: 24.17 ± 3.56 y.o.) performed in MR scanner the modified Deese-Roediger-McDermott paradigm in short-term memory during one session in the morning and another in the evening. Subjects' responses were modeled with a general linear model, which includes as a predictor the non-linear correlations of regional BOLD activity with the stimuli, separately for encoding and retrieval phases. The results show the dependence of the non-linear correlations measures with the time of day and the type of the probe. In addition, the results indicate differences in the correlations measures with hippocampal regions between positive and lure probes. Besides confirming previous results on the influence of time-of-day on cognitive performance, the study demonstrates the effectiveness of the non-linear correlation analysis method for the characterization of fMRI task paradigms.

Brain Functional Network Architecture Reorganization and Alterations of Positive and Negative Affect, Experiencing Pleasure and Daytime Sleepiness in Cataract Patients after Intraocular Lenses Implantation.

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.

Identifying Diurnal Variability of Brain Connectivity Patterns Using Graph Theory.

Significant differences exist in human brain functions affected by time of day and by people's diurnal preferences (chronotypes) that are rarely considered in brain studies. In the current study, using network neuroscience and resting-state functional MRI (rs-fMRI) data, we examined the effect of both time of day and the individual's chronotype on whole-brain network organization. In this regard, 62 participants (39 women; mean age: 23.97 ± 3.26 years; half morning- versus half evening-type) were scanned about 1 and 10 h after wake-up time for morning and evening sessions, respectively. We found evidence for a time-of-day effect on connectivity profiles but not for the effect of chronotype. Compared with the morning session, we found relatively higher small-worldness (an index that represents more efficient network organization) in the evening session, which suggests the dominance of sleep inertia over the circadian and homeostatic processes in the first hours after waking. Furthermore, local graph measures were changed, predominantly across the left hemisphere, in areas such as the precentral gyrus, putamen, inferior frontal gyrus (orbital part), inferior temporal gyrus, as well as the bilateral cerebellum. These findings show the variability of the functional neural network architecture during the day and improve our understanding of the role of time of day in resting-state functional networks.