Brain state dynamics differ between eyes open and eyes closed rest.

The human brain exhibits spatio-temporally complex activity even in the absence of external stimuli, cycling through recurring patterns of activity known as brain states. Thus far, brain state analysis has primarily been restricted to unimodal neuroimaging data sets, resulting in a limited definition of state and a poor understanding of the spatial and temporal relationships between states identified from different modalities. Here, we applied hidden Markov model (HMM) to concurrent electroencephalography-functional magnetic resonance imaging (EEG-fMRI) eyes open (EO) and eyes closed (EC) resting-state data, training models on the EEG and fMRI data separately, and evaluated the models' ability to distinguish dynamics between the two rest conditions. Additionally, we employed a general linear model approach to identify the BOLD correlates of the EEG-defined states to investigate whether the fMRI data could be used to improve the spatial definition of the EEG states. Finally, we performed a sliding window-based analysis on the state time courses to identify slower changes in the temporal dynamics, and then correlated these time courses across modalities. We found that both models could identify expected changes during EC rest compared to EO rest, with the fMRI model identifying changes in the activity and functional connectivity of visual and attention resting-state networks, while the EEG model correctly identified the canonical increase in alpha upon eye closure. In addition, by using the fMRI data, it was possible to infer the spatial properties of the EEG states, resulting in BOLD correlation maps resembling canonical alpha-BOLD correlations. Finally, the sliding window analysis revealed unique fractional occupancy dynamics for states from both models, with a selection of states showing strong temporal correlations across modalities. Overall, this study highlights the efficacy of using HMMs for brain state analysis, confirms that multimodal data can be used to provide more in-depth definitions of state and demonstrates that states defined across different modalities show similar temporal dynamics.

Across the adult lifespan the ipsilateral sensorimotor cortex negative BOLD response exhibits decreases in magnitude and spatial extent suggesting declining inhibitory control.

Ipsilateral sensorimotor (iSM1) cortex negative BOLD responses (NBR) are observed to unilateral tasks and are thought to reflect a functionally relevant component of sensorimotor inhibition. Evidence suggests that sensorimotor inhibitory mechanisms degrade with age, along with aspects of motor ability and dexterity. However, understanding of age-related changes to NBR is restricted by limited comparisons between young vs old adults groups with relatively small samples sizes. Here we analysed a BOLD fMRI dataset (obtained from the CamCAN repository) of 581 healthy subjects, gender-balanced, sampled from the whole adult lifespan performing a motor response task to an audiovisual stimulus. We aimed to investigate how sensorimotor and default-mode NBR characteristics of magnitude, spatial extent and response shape alter at every decade of the aging process. We observed a linear decrease in iSM1 NBR magnitude across the whole lifespan, whereas the contralateral sensorimotor (cSM1) PBR magnitude was unchanged. An age-related decrease in the spatial extent of NBR and an increase in the ipsilateral positive BOLD response (PBR) was observed. This occurred alongside an increasing negative correlation between subject's iSM1 NBR and cSM1 PBR magnitude, reflecting a change in the balance between cortical excitation and inhibition. Conventional GLM analysis, using a canonical haemodynamic response (HR) function, showed disappearance of iSM1 NBR in subjects over 50 years of age. However, a deconvolution analysis showed that the shape of the iSM1 HR altered throughout the lifespan, with significantly delayed time-to-peak and decreased magnitude. The most significant decreases in iSM1 HR magnitude occurred in older age (>60 years) but the first changes in HR shape and timing occurred as early as 30 years, suggesting the possibility of separate mechanisms underlying these alterations. Reanalysis using data-driven HRs for each decade detected significant sensorimotor NBR into late older age, showing the importance of taking changes in HR morphology into account in fMRI aging studies. These results may reflect fMRI measures of the age-related decreases in transcollosal inhibition exerted upon ipsilateral sensorimotor cortex and alterations to the excitatory-inhibitory balance in the sensorimotor network.

Proof-of-concept evidence for trimodal simultaneous investigation of human brain function.

The link between spatial (where) and temporal (when) aspects of the neural correlates of most psychological phenomena is not clear. Elucidation of this relation, which is crucial to fully understand human brain function, requires integration across multiple brain imaging modalities and cognitive tasks that reliably modulate the engagement of the brain systems of interest. By overcoming the methodological challenges posed by simultaneous recordings, the present report provides proof-of-concept evidence for a novel approach using three complementary imaging modalities: functional magnetic resonance imaging (fMRI), event-related potentials (ERPs), and event-related optical signals (EROS). Using the emotional oddball task, a paradigm that taps into both cognitive and affective aspects of processing, we show the feasibility of capturing converging and complementary measures of brain function that are not currently attainable using traditional unimodal or other multimodal approaches. This opens up unprecedented possibilities to clarify spatiotemporal integration of brain function.

Role of the Ipsilateral Primary Motor Cortex in the Visuo-Motor Network During Fine Contractions and Accurate Performance.

It is widely recognized that continuous sensory feedback plays a crucial role in accurate motor control in everyday life. Feedback information is used to adapt force output and to correct errors. While primary motor cortex contralateral to the movement (cM1) plays a dominant role in this control, converging evidence supports the idea that ipsilateral primary motor cortex (iM1) also directly contributes to hand and finger movements. Similarly, when visual feedback is available, primary visual cortex (V1) and its interactions with the motor network also become important for accurate motor performance. To elucidate this issue, we performed and integrated behavioral and electroencephalography (EEG) measurements during isometric compression of a compliant rubber bulb, at 10% and 30% of maximum voluntary contraction, both with and without visual feedback. We used a semi-blind approach (functional source separation (FSS)) to identify separate functional sources of mu-frequency (8-13[Formula: see text]Hz) EEG responses in cM1, iM1 and V1. Here for the first time, we have used orthogonal FSS to extract multiple sources, by using the same functional constraint, providing the ability to extract different sources that oscillate in the same frequency range but that have different topographic distributions. We analyzed the single-trial timecourses of mu power event-related desynchronization (ERD) in these sources and linked them with force measurements to understand which aspects are most important for good task performance. Whilst the amplitude of mu power was not related to contraction force in any of the sources, it was able to provide information on performance quality. We observed stronger ERDs in both contralateral and ipsilateral motor sources during trials where contraction force was most consistently maintained. This effect was most prominent in the ipsilateral source, suggesting the importance of iM1 to accurate performance. This ERD effect was sustained throughout the duration of visual feedback trials, but only present at the start of no feedback trials, consistent with more variable performance in the absence of feedback. Overall, we found that the behavior of the ERD in iM1 was the most informative aspect concerning the accuracy of the contraction performance, and the ability to maintain a steady level of contraction. This new approach of using FSS to extract multiple orthogonal sources provides the ability to investigate both contralateral and ipsilateral nodes of the motor network without the need for additional information (e.g. electromyography). The enhanced signal-to-noise ratio provided by FSS opens the possibility of extracting complex EEG features on an individual trial basis, which is crucial for a more nuanced understanding of fine motor performance, as well as for applications in brain-computer interfacing.

Characterisation of Haemodynamic Activity in Resting State Networks by Fractal Analysis.

Intrinsic brain activity is organized into large-scale networks displaying specific structural-functional architecture, known as resting-state networks (RSNs). RSNs reflect complex neurophysiological processes and interactions, and have a central role in distinct sensory and cognitive functions, making it crucial to understand and quantify their anatomical and functional properties. Fractal dimension (FD) provides a parsimonious way of summarizing self-similarity over different spatial and temporal scales but despite its suitability for functional magnetic resonance imaging (fMRI) signal analysis its ability to characterize and investigate RSNs is poorly understood. We used FD in a large sample of healthy participants to differentiate fMRI RSNs and examine how the FD property of RSNs is linked with their functional roles. We identified two clusters of RSNs, one mainly consisting of sensory networks (C1, including auditory, sensorimotor and visual networks) and the other more related to higher cognitive (HCN) functions (C2, including dorsal default mode network and fronto-parietal networks). These clusters were defined in a completely data-driven manner using hierarchical clustering, suggesting that quantification of Blood Oxygen Level Dependent (BOLD) signal complexity with FD is able to characterize meaningful physiological and functional variability. Understanding the mechanisms underlying functional RSNs, and developing tools to study their signal properties, is essential for assessing specific brain alterations and FD could potentially be used for the early detection and treatment of neurological disorders.

The same, but different: Preserved distractor suppression in old age is implemented through an age-specific reactive ventral fronto-parietal network.

Previous studies have shown age-related impairments in the ability to suppress salient distractors. One possibility is that this is mediated by age-related impairments in the recruitment of the left intraparietal sulcus (Left IPS), which has been shown to mediate the suppression of salient distractors in healthy, young participants. Alternatively, this effect may be due to a shift in engagement from proactive control to reactive control, possibly to compensate for age-related impairments in proactive control. Another possibility is that this is due to changes in the functional specificity of brain regions that mediate salience suppression, expressed in changes in spontaneous connectivity of these regions. We assessed these possibilities by having participants engage in a proactive distractor suppression task while in an fMRI scanner. Although we did not find any age-related differences in behavior, the young (N = 15) and older (N = 15) cohorts engaged qualitatively distinctive brain networks to complete the task. Younger participants engaged the predicted proactive control network, including the Left IPS. On the other hand, older participants simultaneously engaged both a proactive and a reactive network, but this was not a consequence of reduced network specificity as resting state functional connectivity was largely comparable in both age groups. Furthermore, improved behavioral performance for older adults was associated with increased resting state functional connectivity between these two networks. Overall, the results of this study suggest that age-related differences in the recruitment of a left lateralized ventral fronto-parietal network likely reflect the specific recruitment of reactive control mechanisms for distractor inhibition.

Spatially congruent negative BOLD responses to different stimuli do not summate in visual cortex.

The negative BOLD response (NBR) is a prevalent feature of brain activity during sensory and cognitive tasks. It is thought to reflect suppression or deactivation of cortical areas unrequired for task performance, but much remains to be understood regarding its response properties and generative pathways. Here we study a unique property of sensory cortex NBR that most distinguishes it from positive BOLD responses (PBR), its appearance in a single location due to different stimuli. We investigate whether such NBR are additive, as a means of studying whether stimulus driven NBR arise via a single or multiple pathways. During fMRI, subject's passively viewed separate checkerboard stimulation of the foveal and middle-eccentricity areas of the left visual field and a third condition that stimulated both areas concurrently. PBR was observed in the contralateral primary visual cortex and NBR was seen throughout the ipsilateral cortex as well as in contralateral regions superior and anterior to the PBR. Strong spatial overlap of NBRs to all three conditions was observed. We found that neither PBR nor NBR were additive. NBR amplitudes to combined stimuli were equal to those of the strongest (foveal) stimulus alone, despite the mid-eccentricity stimulus inducing substantial NBR on its own. The lack of summation of NBRs, both in the same and opposite hemispheres to the PBR, suggests that they arise from a single pathway. Our findings suggest that although individual stimuli each exert a separate inhibitory effect on non-stimulated regions, once in combination these effects operate as a binary system. Deactivation of a given visual area is driven by a single signal, representing only the largest of the contributing sources.

Alpha/beta power decreases track the fidelity of stimulus-specific information.

Massed synchronised neuronal firing is detrimental to information processing. When networks of task-irrelevant neurons fire in unison, they mask the signal generated by task-critical neurons. On a macroscopic level, such synchronisation can contribute to alpha/beta (8-30 Hz) oscillations. Reducing the amplitude of these oscillations, therefore, may enhance information processing. Here, we test this hypothesis. Twenty-one participants completed an associative memory task while undergoing simultaneous EEG-fMRI recordings. Using representational similarity analysis, we quantified the amount of stimulus-specific information represented within the BOLD signal on every trial. When correlating this metric with concurrently-recorded alpha/beta power, we found a significant negative correlation which indicated that as post-stimulus alpha/beta power decreased, stimulus-specific information increased. Critically, we found this effect in three unique tasks: visual perception, auditory perception, and visual memory retrieval, indicating that this phenomenon transcends both stimulus modality and cognitive task. These results indicate that alpha/beta power decreases parametrically track the fidelity of both externally-presented and internally-generated stimulus-specific information represented within the cortex.

Two Spatially Distinct Posterior Alpha Sources Fulfill Different Functional Roles in Attention.

Directing attention helps to extract relevant information and suppress distracters. Alpha brain oscillations (8-12 Hz) are crucial for this process, with power decreases facilitating processing of important information and power increases inhibiting brain regions processing irrelevant information. Evidence for this phenomenon arises from visual attention studies (Worden et al., 2000); however, the effect also exists in other modalities, including the somatosensory system (Haegens et al., 2011) and intersensory attention tasks (Foxe and Snyder, 2011). We investigated in human participants (10 females, 10 males) the role of alpha oscillations in focused (0/100%) versus divided (40/60%) attention, both across modalities (visual/somatosensory; Experiment 1) and within the same modality (visual domain: across hemifields; Experiment 2) while recording EEG over 128 scalp electrodes. In Experiment 1, participants divided their attention between visual and somatosensory modality to determine the temporal/spatial frequency of a target stimulus (vibrotactile stimulus/Gabor grating). In Experiment 2, participants divided attention between two visual hemifields to identify the orientation of a Gabor grating. In both experiments, prestimulus alpha power in visual areas decreased linearly with increasing attention to visual stimuli. In contrast, prestimulus alpha power in parietal areas was lower when attention was divided between modalities/hemifields compared with focused attention. These results suggest there are two alpha sources, one of which reflects the "visual spotlight of attention" and the other reflects attentional effort. To our knowledge, this is the first study to show that attention recruits two spatially distinct alpha sources in occipital and parietal brain regions, acting simultaneously but serving different functions in attention.SIGNIFICANCE STATEMENT Attention to one spatial location/sensory modality leads to power changes of alpha oscillations (∼10 Hz) with decreased power over regions processing relevant information and power increases to actively inhibit areas processing "to-be-ignored" information. Here, we used detailed source modeling to investigate EEG data recorded during separate unimodal (visual) and multimodal (visual and somatosensory) attention tasks. Participants either focused their attention on one modality/spatial location or directed it to both. We show for the first time two distinct alpha sources are active simultaneously but play different roles. A sensory (visual) alpha source was linearly modulated by attention representing the "visual spotlight of attention." By contrast, a parietal alpha source was modulated by attentional effort, showing lowest alpha power when attention was divided.

The relationship between negative BOLD responses and ERS and ERD of alpha/beta oscillations in visual and motor cortex.

Previous work has investigated the electrophysiological origins of the intra-modal (within the stimulated sensory cortex) negative BOLD fMRI response (NBR, decrease from baseline) but little attention has been paid to the origin of cross-modal NBRs, those in a different sensory cortex. In the current study we use simultaneous EEG-fMRI recordings to assess the neural correlates of both intra- and cross-modal responses to left-hemifield visual stimuli and right-hand motor tasks, and evaluate the balance of activation and deactivation between the visual and motor systems. Within- and between-subject covariations of EEG and fMRI responses to both tasks are assessed to determine how patterns of event-related desynchronization/synchronisation (ERD/ERS) of alpha/beta frequency oscillations relate to the NBR in the two sensory cortices. We show that both visual and motor tasks induce intra-modal NBR and cross-modal NBR (e.g. visual stimuli evoked NBRs in both visual and motor cortices). In the EEG data, bilateral intra-modal alpha/beta ERD were consistently observed to both tasks, whilst the cross-modal EEG response varied across subjects between alpha/beta ERD and ERS. Both the mean cross-modal EEG and fMRI response amplitudes showed a small increase in magnitude with increasing task intensity. In response to the visual stimuli, subjects displaying cross-modal ERS of motor beta power displayed a significantly larger magnitude of cross-modal NBR in motor cortex. However, in contrast to the motor stimuli, larger cross-modal ERD of visual alpha power was associated with larger cross-modal visual NBR. Single-trial correlation analysis provided further evidence of relationship between EEG signals and the NBR, motor cortex beta responses to motor tasks were significantly negatively correlated with cross-modal visual cortex NBR amplitude, and positively correlated with intra-modal motor cortex PBR. This study provides a new body of evidence that the coupling between BOLD and low-frequency (alpha/beta) sensory cortex EEG responses extends to cross-modal NBR.

Addressing challenges of high spatial resolution UHF fMRI for group analysis of higher-order cognitive tasks: An inter-sensory task directing attention between visual and somatosensory domains.

Functional MRI at ultra-high field (UHF, ≥7 T) provides significant increases in BOLD contrast-to-noise ratio (CNR) compared with conventional field strength (3 T), and has been exploited for reduced field-of-view, high spatial resolution mapping of primary sensory areas. Applying these high spatial resolution methods to investigate whole brain functional responses to higher-order cognitive tasks leads to a number of challenges, in particular how to perform robust group-level statistical analyses. This study addresses these challenges using an inter-sensory cognitive task which modulates top-down attention at graded levels between the visual and somatosensory domains. At the individual level, highly focal functional activation to the task and task difficulty (modulated by attention levels) were detectable due to the high CNR at UHF. However, to assess group level effects, both anatomical and functional variability must be considered during analysis. We demonstrate the importance of surface over volume normalisation and the requirement of no spatial smoothing when assessing highly focal activity. Using novel group analysis on anatomically parcellated brain regions, we show that in higher cognitive areas (parietal and dorsal-lateral-prefrontal cortex) fMRI responses to graded attention levels were modulated quadratically, whilst in visual cortex and VIP, responses were modulated linearly. These group fMRI responses were not seen clearly using conventional second-level GLM analyses, illustrating the limitations of a conventional approach when investigating such focal responses in higher cognitive regions which are more anatomically variable. The approaches demonstrated here complement other advanced analysis methods such as multivariate pattern analysis, allowing UHF to be fully exploited in cognitive neuroscience.

Objective and subjective measures of prior sleep-wake behavior predict functional connectivity in the default mode network during NREM sleep.

INTRODUCTION: Prior sleep behavior has been shown to correlate with waking resting-state functional connectivity (FC) in the default mode network (DMN). However, the impact of sleep history on FC during sleep has not been investigated. The aim of this study was to establish whether there is an association between intersubject variability in habitual sleep behaviors and the strength of FC within the regions of the DMN during non-rapid eye movement (NREM) sleep. METHODS: Wrist actigraphy and sleep questionnaires were used as objective and subjective measures of habitual sleep behavior, and EEG-functional MRI during NREM sleep was used to quantify sleep. RESULTS: There was a significant, regionally specific association between the interindividual variability in objective (total sleep time on the night before scanning) and subjective (Insomnia Severity Index) measures of prior sleep-wake behavior and the strength of DMN FC during subsequent wakefulness and NREM sleep. In several cases, FC was related to sleep measures independently of sleep stage, suggesting that previous sleep history effects sleep FC globally across the stages. CONCLUSIONS: This work highlights the need to consider a subject's prior sleep history in studies utilizing FC analysis during wakefulness and sleep, and indicates the complexity of the impact of sleep on the brain both in the short and long term.

Thalamic functional connectivity and its association with behavioral performance in older age.

Introduction: Despite the thalamus' dense connectivity with both cortical and subcortical structures, few studies have specifically investigated how thalamic connectivity changes with age and how such changes are associated with behavior. This study investigated the effect of age on thalamo-cortical and thalamo-hippocampal functional connectivity (FC) and the association between thalamic FC and visual-spatial memory and reaction time (RT) performance in older adults. Methods: Resting-state functional magnetic resonance images were obtained from younger (n = 20) and older (n = 20) adults. A seed-based approach was used to assess the FC between the thalamus and (1) sensory resting-state networks; (2) the hippocampus. Participants also completed visual-spatial memory and RT tasks, from the Cambridge Neuropsychological Test Automated Battery (CANTAB). Results: Older adults exhibited a loss of specificity in the FC between sensory thalamic subregions and corresponding sensory cortex. Greater thalamo-motor FC in older adults was associated with faster RTs. Furthermore, older adults exhibited greater thalamo-hippocampal FC compared to younger adults, which was greatest for those with the poorest visual-spatial memory performance. Conclusion: Although older adults exhibited poorer visual-spatial memory and slower reaction times compared to younger adults, "good" and "poorer" older performers exhibited different patterns of thalamo-cortical and thalamo-hippocampal FC. These results highlight the potential role of thalamic connectivity in supporting reaction times and memory in aging. Furthermore, these results highlight the importance of including the thalamus in studies of aging to fully understand how brain changes with age may be associated with behavior.

Exploring the advantages of multiband fMRI with simultaneous EEG to investigate coupling between gamma frequency neural activity and the BOLD response in humans.

We established an optimal combination of EEG recording during sparse multiband (MB) fMRI that preserves high-resolution, whole-brain fMRI coverage while enabling broad-band EEG recordings which are uncorrupted by MRI gradient artefacts (GAs). We first determined the safety of simultaneous EEG recording during MB fMRI. Application of MB factor = 4 produced <1°C peak heating of electrode/hardware during 20 min of GE-EPI data acquisition. However, higher SAR sequences require specific safety testing, with greater heating observed using PCASL with MB factor = 4. Heating was greatest in the electrocardiogram channel, likely due to it possessing longest lead length. We investigated the effect of MB factor on the temporal signal-to-noise ratio for a range of GE-EPI sequences (varying MB factor and temporal interval between slice acquisitions). We found that, for our experimental purpose, the optimal acquisition was achieved with MB factor = 3, 3mm isotropic voxels, and 33 slices providing whole head coverage. This sequence afforded a 2.25 s duration quiet period (without GAs) in every 3 s TR. Using this sequence, we demonstrated the ability to record gamma frequency (55-80 Hz) EEG oscillations, in response to right index finger abduction, that are usually obscured by GAs during continuous fMRI data acquisition. In this novel application of EEG-MB fMRI to a motor task, we observed a positive correlation between gamma and BOLD responses in bilateral motor regions. These findings support and extend previous work regarding coupling between neural and hemodynamic measures of brain activity in humans and showcase the utility of EEG-MB fMRI for future investigations.

fMRI characterisation of widespread brain networks relevant for behavioural variability in fine hand motor control with and without visual feedback.

A bilateral visuo-parietal-motor network is responsible for fine control of hand movements. However, the sub-regions which are devoted to maintenance of contraction stability and how these processes fluctuate with trial-quality of task execution and in the presence/absence of visual feedback remains unclear. We addressed this by integrating behavioural and fMRI measurements during right-hand isometric compression of a compliant rubber bulb, at 10% and 30% of maximum voluntary contraction, both with and without visual feedback of the applied force. We quantified single-trial behavioural performance during 1) the whole task period and 2) stable contraction maintenance, and regressed these metrics against the fMRI data to identify the brain activity most relevant to trial-by-trial fluctuations in performance during specific task phases. fMRI-behaviour correlations in a bilateral network of visual, premotor, primary motor, parietal and inferior frontal cortical regions emerged during performance of the entire feedback task, but only in premotor, parietal cortex and thalamus during the stable contraction period. The trials with the best task performance showed increased bilaterality and amplitude of fMRI responses. With feedback, stronger BOLD-behaviour coupling was found during 10% compared to 30% contractions. Only a small subset of regions in this network were weakly correlated with behaviour without feedback, despite wider network activated during this task than in the presence of feedback. These findings reflect a more focused network strongly coupled to behavioural fluctuations when providing visual feedback, whereas without it the task recruited widespread brain activity almost uncoupled from behavioural performance.

Habitual sleep durations and subjective sleep quality predict white matter differences in the human brain.

Self-imposed short sleep durations are increasingly commonplace in society, and have considerable health and performance implications for individuals. Reduced sleep duration over multiple nights has similar behavioural effects to those observed following acute total sleep deprivation, suggesting that lack of sleep affects brain function cumulatively. A link between habitual sleep patterns and functional connectivity has previously been observed, and the effect of sleep duration on the brain's intrinsic functional architecture may provide a link between sleep status and cognition. However, it is currently not known whether differences in habitual sleep patterns across individuals are related to changes in the brain's white matter, which underlies structural connectivity. In the present study we use diffusion-weighted imaging and a group comparison application of tract based spatial statistics (TBSS) to investigate changes to fractional anisotropy (FA) and mean diffusivity (MD) in relation to sleep duration and quality, hypothesising that white matter metrics would be positively associated with sleep duration and quality. Diffusion weighted imaging data was acquired from a final cohort of 33 (23-29 years, 10 female, mean 25.4 years) participants. Sleep patterns were assessed for a 14 day period using wrist actigraphs and sleep diaries, and subjective sleep quality with the Pittsburgh Sleep Quality Index (PSQI). Median splits based on total sleep time and PSQI were used to create groups of shorter/longer and poorer/better sleepers, whose imaging data was compared using TBSS followed by post-hoc correlation analysis in regions identified as significantly different between the groups. There were significant positive correlations between sleep duration and FA in the left orbito-frontal region and the right superior corona radiata, and significant negative correlations between sleep duration and MD in right orbito-frontal white matter and the right inferior longitudinal fasciculus. Improved sleep quality was positively correlated with FA in left caudate nucleus, white matter tracts to the left orbito-frontal region, the left anterior cingulum bundle and the white matter tracts associated with the right operculum and insula, and negatively correlated with MD in left orbito-frontal white matter and the left anterior cingulum bundle. Our findings suggest that reduced cumulative total sleep time (cTST) and poorer subjective sleep quality are associated with subtle white matter micro-architectural changes. The regions we identified as being related to habitual sleep patterns were restricted to the frontal and temporal lobes, and the functions they support are consistent with those which have previously been demonstrated as being affected by short sleep durations (e.g., attention, cognitive control, memory). Examining how inter-individual differences in brain structure are related to habitual sleep patterns could help to shed light on the mechanisms by which sleep habits are associated with brain function, behaviour and cognition, as well as potentially the networks and systems responsible for variations in sleep patterns themselves.

Gender Specific Re-organization of Resting-State Networks in Older Age.

Advancing age is commonly associated with changes in both brain structure and function. Recently, the suggestion that alterations in brain connectivity may drive disruption in cognitive abilities with age has been investigated. However, the interaction between the effects of age and gender on the re-organization of resting-state networks is not fully understood. This study sought to investigate the effect of both age and gender on intra- and inter-network functional connectivity (FC) and the extent to which resting-state network (RSN) node definition may alter with older age. We obtained resting-state functional magnetic resonance images from younger (n = 20) and older (n = 20) adults and assessed the FC of three main cortical networks: default mode (DMN), dorsal attention (DAN), and saliency (SN). Older adults exhibited reduced DMN intra-network FC and increased inter-network FC between the anterior cingulate cortex (ACC) and nodes of the DAN, in comparison to younger participants. Furthermore, this increase in ACC-DAN inter-network FC with age was driven largely by male participants. However, further analyses suggested that the spatial location of ACC, bilateral anterior insula and orbitofrontal cortex RSN nodes changed with older age and that age-related gender differences in FC may reflect spatial re-organization rather than increases or decreases in FC strength alone. These differences in both the FC and spatial distribution of RSNs between younger and older adults provide evidence of re-organization of fundamental brain networks with age, which is modulated by gender. These results highlight the need to further investigate changes in both intra- and inter-network FC with age, whilst also exploring the modifying effect of gender. They also emphasize the difficulties in directly comparing the FC of RSN nodes between groups and suggest that caution should be taken when using the same RSN node definitions for different age or patient groups to investigate FC.

Variability in Cumulative Habitual Sleep Duration Predicts Waking Functional Connectivity.

STUDY OBJECTIVES: We examined whether interindividual differences in habitual sleep patterns, quantified as the cumulative habitual total sleep time (cTST) over a 2-w period, were reflected in waking measurements of intranetwork and internetwork functional connectivity (FC) between major nodes of three intrinsically connected networks (ICNs): default mode network (DMN), salience network (SN), and central executive network (CEN). METHODS: Resting state functional magnetic resonance imaging (fMRI) study using seed-based FC analysis combined with 14-d wrist actigraphy, sleep diaries, and subjective questionnaires (N = 33 healthy adults, mean age 34.3, standard deviation ± 11.6 y). Data were statistically analyzed using multiple linear regression. Fourteen consecutive days of wrist actigraphy in participant's home environment and fMRI scanning on day 14 at the Birmingham University Imaging Centre. Seed-based FC analysis on ICNs from resting-state fMRI data and multiple linear regression analysis performed for each ICN seed and target. cTST was used to predict FC (controlling for age). RESULTS: cTST was specific predictor of intranetwork FC when the mesial prefrontal cortex (MPFC) region of the DMN was used as a seed for FC, with a positive correlation between FC and cTST observed. No significant relationship between FC and cTST was seen for any pair of nodes not including the MPFC. Internetwork FC between the DMN (MPFC) and SN (right anterior insula) was also predicted by cTST, with a negative correlation observed between FC and cTST. CONCLUSIONS: This study improves understanding of the relationship between intranetwork and internetwork functional connectivity of intrinsically connected networks (ICNs) in relation to habitual sleep quality and duration. The cumulative amount of sleep that participants achieved over a 14-d period was significantly predictive of intranetwork and inter-network functional connectivity of ICNs, an observation that may underlie the link between sleep status and cognitive performance.