Morning-evening variation in human brain metabolism and memory circuits

Neuroendocrine Associations Underlying the Persistent Therapeutic Effects of Classic Serotonergic Psychedelics

Recent reports on the effects of psychedelic-assisted therapies for mood disorders and addiction, as well as the effects of psychedelics in the treatment of cluster headache, have demonstrated promising therapeutic results. In addition, the beneficial effects appear to persist well after limited exposure to the drugs, making them particularly appealing as treatments for chronic neuropsychiatric and headache disorders. Understanding the basis of the long-lasting effects, however, will be critical for the continued use and development of this drug class. Several mechanisms, including biological and psychological ones, have been suggested to explain the long-lasting effects of psychedelics. Actions on the neuroendocrine system are some such mechanisms that warrant further investigation in the study of persisting psychedelic effects. In this report, we review certain structural and functional neuroendocrinological pathologies associated with neuropsychiatric disorders and cluster headache. We then review the effects that psychedelic drugs have on those systems and provide preliminary support for potential long-term effects. The circadian biology of cluster headache is of particular relevance in this area. We also discuss methodologic considerations for future investigations of neuroendocrine system involvement in the therapeutic benefits of psychedelic drugs.

Effects of resting state condition on reliability, trait specificity, and network connectivity of brain function measured with arterial spin labeled perfusion MRI

Resting state fMRI (rs-fMRI) provides imaging biomarkers of task-independent brain function that can be associated with clinical variables or modulated by interventions such as behavioral training or pharmacological manipulations. These biomarkers include time-averaged regional brain function as manifested by regional cerebral blood flow (CBF) measured using arterial spin labeled (ASL) perfusion MRI and correlated temporal fluctuations of function across brain networks with either ASL or blood oxygenation level dependent (BOLD) fMRI. Resting-state studies are typically carried out using just one of several prescribed state conditions such as eyes closed (EC), eyes open (EO), or visual fixation on a cross-hair (FIX), which may affect the reliability and specificity of rs-fMRI. In this study, we collected test-retest ASL MRI data during 4 resting-state task conditions: EC, EO, FIX and PVT (low-frequency psychomotor vigilance task), and examined the effects of these task conditions on reliability and reproducibility as well as trait specificity of regional brain function. We also acquired resting-state BOLD fMRI under FIX and compared the network connectivity reliabilities between the four ASL conditions and the BOLD FIX condition. For resting-state ASL data, EC provided the highest CBF reliability, reproducibility, trait specificity, and network connectivity reliability, followed by EO, while FIX was lowest on all of these measures. PVT demonstrated lower CBF reliability, reproducibility and trait specificity than EO and EC. Overall network connectivity reliability was comparable between ASL and BOLD. Our findings confirm ASL CBF as a reliable, stable, and consistent measure of resting-state regional brain function and support the use of EC or EO over FIX and PVT as the resting-state condition.

Functional connectivity between salience, default mode and frontoparietal networks in post-stroke depression

BACKGROUND

Previous studies have demonstrated altered resting state functional connectivity (rsFC) in patients with post-stroke depression (PSD). It remains unclear whether rsFC is changed at the network level as was shown for major depressive disorder (MDD). To address this question, we investigated rsFC of resting sate networks (RSNs) in PSD.

METHODS

Eleven subjects with PSD underwent fMRI scanning at rest before and after treatment. The severity of depression was assessed using the aphasic depression rating scale (ADRS). We performed functional network connectivity (FNC) analysis for RSNs, region of interest - FC analysis (ROI-FC) and calculation of brain matter volumes in ROIs overlapping with RSNs and in other brain regions associated with mood maintenance.

RESULTS

We found positive correlation of FNC between anterior default mode network (aDMN) and salience network (SAL) with depression severity before treatment, the latter accompanied by the increase of white matter in the middle frontal and left angular gyri. FNC of aDMN and left frontoparietal network (LFP) decreased after treatment. ROI-FC and the brain matter volumes of several regions of DMN, LFP and SAL also showed a correlation with ADRS or significant change after treatment.

LIMITATIONS

Limitations include small sample size and methodological issues concerning altered hemodynamics in stroke. However, we took complex preprocessing steps to overcome these issues.

CONCLUSION

Present results of altered rsFC in PSD are consistent with previous findings in MDD. The convergence of results obtained in PSD and MDD supports the validity of rsFC approach for investigation of brain network dysfunctions underling these psychiatric symptoms.

Brain mitochondrial bioenergetics change with rapid and prolonged shifts in aggression in the honey bee, Apis mellifera

Neuronal function demands high-level energy production, and as such, a decline in mitochondrial respiration characterizes brain injury and disease. A growing number of studies, however, link brain mitochondrial function to behavioral modulation in non-diseased contexts. In the honey bee, we show for the first time that an acute social interaction, which invokes an aggressive response, may also cause a rapid decline in brain mitochondrial bioenergetics. The degree and speed of this decline has only been previously observed in the context of brain injury. Furthermore, in the honey bee, age-related increases in aggressive tendency are associated with increased baseline brain mitochondrial respiration, as well as increased plasticity in response to metabolic fuel type in vitro. Similarly, diet restriction and ketone body feeding, which commonly enhance mammalian brain mitochondrial function in vivo, cause increased aggression. Thus, even in normal behavioral contexts, brain mitochondria show a surprising degree of variation in function over both rapid and prolonged timescales, with age predicting both baseline function and plasticity in function. These results suggest that mitochondrial function is integral to modulating aggression-related neuronal signaling. We hypothesize that variation in function reflects mitochondrial calcium buffering activity, and that shifts in mitochondrial function signal to the neuronal soma to regulate gene expression and neural energetic state. Modulating brain energetic state is emerging as a critical component of the regulation of behavior in non-diseased contexts.

Making group inferences using sparse representation of resting-state functional mRI data with application to sleep deprivation

Past studies on drawing group inferences for functional magnetic resonance imaging (fMRI) data usually assume that a brain region is involved in only one functional brain network. However, recent evidence has demonstrated that some brain regions might simultaneously participate in multiple functional networks. Here, we presented a novel approach for making group inferences using sparse representation of resting-state fMRI data and its application to the identification of changes in functional networks in the brains of 37 healthy young adult participants after 36 h of sleep deprivation (SD) in contrast to the rested wakefulness (RW) stage. Our analysis based on group-level sparse representation revealed that multiple functional networks involved in memory, emotion, attention, and vigilance processing were impaired by SD. Of particular interest, the thalamus was observed to contribute to multiple functional networks in which differentiated response patterns were exhibited. These results not only further elucidate the impact of SD on brain function but also demonstrate the ability of the proposed approach to provide new insights into the functional organization of the resting-state brain by permitting spatial overlap between networks and facilitating the description of the varied relationships of the overlapping regions with other regions of the brain in the context of different functional systems. Hum Brain Mapp 38:4671-4689, 2017. © 2017 Wiley Periodicals, Inc.

Learning performance is linked to procedural memory consolidation across both sleep and wakefulness

We investigated whether learning performance in a procedural finger tapping task before nocturnal sleep would predict performance gains after sleep in 60 young adults. Gains were defined as change in correctly tapped digit sequences between learning (12 trials administered in the evening) and retesting (3 trials administered in the morning after sleep). The same task was also administered to a separate wake group (N = 54 young adults), which learned in the morning and was retested in the evening. Learning performance was determined by either using the average performance on the last three learning trials or the average performance on the best three learning trials. Our results demonstrated an inverse association between learning performance and gains in procedural skill, i.e., good learners exhibited smaller performance gains across both wakefulness and sleep than poor learners. Regardless of learning performance, gains in finger tapping skills were greater after sleep than daytime wakefulness. Importantly, some of our findings were influenced by how learning performance was estimated. Collectively, these results suggest that learning performance and the method through which it is estimated may influence performance gains in finger tapping skills across both sleep and wakefulness.

Precision Functional Mapping of Individual Human Brains

Human functional MRI (fMRI) research primarily focuses on analyzing data averaged across groups, which limits the detail, specificity, and clinical utility of fMRI resting-state functional connectivity (RSFC) and task-activation maps. To push our understanding of functional brain organization to the level of individual humans, we assembled a novel MRI dataset containing 5 hr of RSFC data, 6 hr of task fMRI, multiple structural MRIs, and neuropsychological tests from each of ten adults. Using these data, we generated ten high-fidelity, individual-specific functional connectomes. This individual-connectome approach revealed several new types of spatial and organizational variability in brain networks, including unique network features and topologies that corresponded with structural and task-derived brain features. We are releasing this highly sampled, individual-focused dataset as a resource for neuroscientists, and we propose precision individual connectomics as a model for future work examining the organization of healthy and diseased individual human brains.

Heidelberg Neuro-Music Therapy Enhances Task-Negative Activity in Tinnitus Patients

Background: Suffering from tinnitus causes mental distress in most patients. Recent findings point toward a diminished activity of the brain's default-mode network (DMN) in subjects with mental disorders including depression or anxiety and also recently in subjects with tinnitus-related distress. We recently developed a therapeutic intervention, namely the Heidelberg Neuro-Music Therapy (HNMT), which shows an effective reduction of tinnitus-related distress following a 1-week short-term treatment. This approach offers the possibility to evaluate the neural changes associated with the improvements in tinnitus distress. We previously reported gray matter (GM) reorganization in DMN regions and in primary auditory areas following HNMT in cases of recent-onset tinnitus. Here we evaluate on the same patient group, using functional MRI (fMRI), the activity of the DMN following the improvements tinnitus-related distress related to the HNMT intervention.

Methods: The DMN activity was estimated by the task-negative activation (TNA) during long inter-trial intervals in a word recognition task. The level of TNA was evaluated twice, before and after the 1-week study period, in 18 treated tinnitus patients (“treatment group,” TG), 21 passive tinnitus controls (PTC), and 22 active healthy controls (AC). During the study, the participants in TG and AC groups were treated with HNMT, whereas PTC patients did not receive any tinnitus-specific treatment. Therapy-related effects on DMN activity were assessed by comparing the pairs of fMRI records from the TG and PTC groups.

Results: Treatment of the TG group with HNMT resulted in an augmented DMN activity in the PCC by 2.5% whereas no change was found in AC and PTC groups. This enhancement of PCC activity correlated with a reduction in tinnitus distress (Spearman Rho: −0.5; p < 0.005).

Conclusion: Our findings show that an increased DMN activity, especially in the PCC, underlies the improvements in tinnitus-related distress triggered by HNMT and identify the DMN as an important network involved in therapeutic improvements.

Resting-state fMRI correlations: From link-wise unreliability to whole brain stability

The functional architecture of spontaneous BOLD fluctuations has been characterized in detail by numerous studies, demonstrating its potential relevance as a biomarker. However, the systematic investigation of its consistency is still in its infancy. Here, we analyze within- and between-subject variability and test-retest reliability of resting-state functional connectivity (FC) in a unique data set comprising multiple fMRI scans (42) from 5 subjects, and 50 single scans from 50 subjects. We adopt a statistical framework that enables us to identify different sources of variability in FC. We show that the low reliability of single links can be significantly improved by using multiple scans per subject. Moreover, in contrast to earlier studies, we show that spatial heterogeneity in FC reliability is not significant. Finally, we demonstrate that despite the low reliability of individual links, the information carried by the whole-brain FC matrix is robust and can be used as a functional fingerprint to identify individual subjects from the population.

Evidence for cortical structural plasticity in humans after a day of waking and sleep deprivation

Sleep is an evolutionarily conserved process required for human health and functioning. Insufficient sleep causes impairments across cognitive domains, and sleep deprivation can have rapid antidepressive effects in mood disorders. However, the neurobiological effects of waking and sleep are not well understood. Recently, animal studies indicated that waking and sleep are associated with substantial cortical structural plasticity. Here, we hypothesized that structural plasticity can be observed after a day of waking and sleep deprivation in the human cerebral cortex. To test this hypothesis, 61 healthy adult males underwent structural magnetic resonance imaging (MRI) at three time points: in the morning after a regular night's sleep, the evening of the same day, and the next morning, either after total sleep deprivation (N=41) or a night of sleep (N=20). We found significantly increased right prefrontal cortical thickness from morning to evening across all participants. In addition, pairwise comparisons in the deprived group between the two morning scans showed significant thinning of mainly bilateral medial parietal cortices after 23h of sleep deprivation, including the precuneus and posterior cingulate cortex. However, there were no significant group (sleep vs. sleep deprived group) by time interactions and we can therefore not rule out that other mechanisms than sleep deprivation per se underlie the bilateral medial parietal cortical thinning observed in the deprived group. Nonetheless, these cortices are thought to subserve wakefulness, are among the brain regions with highest metabolic rate during wake, and are considered some of the most sensitive cortical regions to a variety of insults. Furthermore, greater thinning within the left medial parietal cluster was associated with increased sleepiness after sleep deprivation. Together, these findings add to a growing body of data showing rapid structural plasticity within the human cerebral cortex detectable with MRI. Further studies are needed to clarify whether cortical thinning is one neural substrate of sleepiness after sleep deprivation.

Quantitative hemodynamic PET imaging using image-derived arterial input function and a PET/MR hybrid scanner

Positron emission tomography (PET) with ¹⁵O-tracers is commonly used to measure brain hemodynamic parameters such as cerebral blood flow, cerebral blood volume, and cerebral metabolic rate of oxygen. Conventionally, the absolute quantification of these parameters requires an arterial input function that is obtained invasively by sampling blood from an artery. In this work, we developed and validated an image-derived arterial input function technique that avoids the unreliable and burdensome arterial sampling procedure for full quantitative ¹⁵O-PET imaging. We then compared hemodynamic PET imaging performed on a PET/MR hybrid scanner against a conventional PET only scanner. We demonstrated the proposed imaging-based technique was able to generate brain hemodynamic parameter measurements in strong agreement with the traditional arterial sampling based approach. We also demonstrated that quantitative ¹⁵O-PET imaging can be successfully implemented on a PET/MR hybrid scanner.

The respiratory control of carbon dioxide in children and adolescents referred for treatment of psychogenic non-epileptic seizures

Psychogenic non-epileptic seizures (PNES) are a common problem in paediatric neurology and psychiatry that can best be understood as atypical responses to threat. Threats activate the body for action by mediating increases in arousal, respiration, and motor readiness. In previous studies, a range of cardiac, endocrine, brain-based, attention-bias, and behavioral measures have been used to demonstrate increases in arousal, vigilance, and motor readiness in patients with PNES. The current study uses respiratory measures to assess both the motor readiness of the respiratory system and the respiratory regulation of CO₂. Baseline respiratory rates during clinical assessment and arterial CO₂ levels during the hyperventilation component of routine video electroencephalogram were documented in 60 children and adolescents referred for treatment of PNES and in 50 controls. Patients showed elevated baseline respiratory rates [t(78) = 3.34, p = .001], with 36/52 (69%) of patients [vs. 11/28 (39%) controls] falling above the 75th percentile (χ² = 6.7343; df = 1; p = .009). Twenty-eight (47%) of patients [vs. 4/50 (8%) controls] showed a skewed hyperventilation-challenge profile—baseline PCO₂ <36 mmHg, a trough PCO₂ ≤ 20 mmHg, or a final PCO₂ <36 mmHg after 15 min of recovery—signaling difficulties with CO₂ regulation (χ² = 19.77; df = 1; p < .001). Children and adolescents with PNES present in a state of readiness-for-action characterized by high arousal coupled with activation of the respiratory motor system, increases in ventilation, and a hyperventilation-challenge profile shifted downward from homeostatic range. Breathing interventions that target arousal, decrease respiratory rate, and normalize ventilation and arterial CO₂ may help patients shift brain–body state and avert PNES episodes.

Relapse prediction: A meteorology-inspired mobile model

Predicting relapses to binge drinking in non-dependent drinkers may now be possible with smartphones. Smartphones have been shown to help individuals reduce their drinking and may help binge drinkers accelerate that process. Predicting the weather has improved greatly over the past 50 years, but predicting a binge drinking episode may be less difficult. It is hypothesized that the number of factors with high predictive value for any particular individual may not be large. Collecting data over time, a smartphone should be able to learn which combination of factors has a high probability of leading to an episode of binge drinking.

Brain aerobic glycolysis and motor adaptation learning

Ten percent to 15% of glucose used by the brain is metabolized nonoxidatively despite adequate tissue oxygenation, a process termed aerobic glycolysis (AG). Because of the known role of glycolysis in biosynthesis, we tested whether learning-induced synaptic plasticity would lead to regionally appropriate, learning-dependent changes in AG. Functional MRI (fMRI) before, during, and after performance of a visual-motor adaptation task demonstrated that left Brodmann area 44 (BA44) played a key role in adaptation, with learning-related changes to activity during the task and altered resting-state, functional connectivity after the task. PET scans before and after task performance indicated a sustained increase in AG in left BA 44 accompanied by decreased oxygen consumption. Intersubject variability in behavioral adaptation rate correlated strongly with changes in AG in this region, as well as functional connectivity, which is consistent with a role for AG in synaptic plasticity.

The brain functional connectome is robustly altered by lack of sleep

Sleep is a universal phenomenon necessary for maintaining homeostasis and function across a range of organs. Lack of sleep has severe health-related consequences affecting whole-body functioning, yet no other organ is as severely affected as the brain. The neurophysiological mechanisms underlying these deficits are poorly understood. Here, we characterize the dynamic changes in brain connectivity profiles inflicted by sleep deprivation and how they deviate from regular daily variability. To this end, we obtained functional magnetic resonance imaging data from 60 young, adult male participants, scanned in the morning and evening of the same day and again the following morning. 41 participants underwent total sleep deprivation before the third scan, whereas the remainder had another night of regular sleep. Sleep deprivation strongly altered the connectivity of several resting-state networks, including dorsal attention, default mode, and hippocampal networks. Multivariate classification based on connectivity profiles predicted deprivation state with high accuracy, corroborating the robustness of the findings on an individual level. Finally, correlation analysis suggested that morning-to-evening connectivity changes were reverted by sleep (control group)-a pattern which did not occur after deprivation. We conclude that both, a day of waking and a night of sleep deprivation dynamically alter the brain functional connectome.

Functional System and Areal Organization of a Highly Sampled Individual Human Brain

Resting state functional MRI (fMRI) has enabled description of group-level functional brain organization at multiple spatial scales. However, cross-subject averaging may obscure patterns of brain organization specific to each individual. Here, we characterized the brain organization of a single individual repeatedly measured over more than a year. We report a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject-specific task activations. Highly convergent correlation network estimates can be derived from this parcellation if sufficient data are collected-considerably more than typically acquired. Notably, within-subject correlation variability across sessions exhibited a heterogeneous distribution across the cortex concentrated in visual and somato-motor regions, distinct from the pattern of intersubject variability. Further, although the individual's systems-level organization is broadly similar to the group, it demonstrates distinct topological features. These results provide a foundation for studies of individual differences in cortical organization and function, especially for special or rare individuals. VIDEO ABSTRACT.

Widespread changes in white matter microstructure after a day of waking and sleep deprivation

Background

Elucidating the neurobiological effects of sleep and waking remains an important goal of the neurosciences. Recently, animal studies indicated that sleep is important for cell membrane and myelin maintenance in the brain and that these structures are particularly susceptible to insufficient sleep. Here, we tested the hypothesis that a day of waking and sleep deprivation would be associated with changes in diffusion tensor imaging (DTI) indices of white matter microstructure sensitive to axonal membrane and myelin alterations.

Methods

Twenty-one healthy adult males underwent DTI in the morning [7:30AM; time point (TP)1], after 14 hours of waking (TP2), and then after another 9 hours of waking (TP3). Whole brain voxel-wise analysis was performed with tract based spatial statistics.

Results

A day of waking was associated with widespread increases in white matter fractional anisotropy, which were mainly driven by radial diffusivity reductions, and sleep deprivation was associated with widespread fractional anisotropy decreases, which were mainly explained by reductions in axial diffusivity. In addition, larger decreases in axial diffusivity after sleep deprivation were associated with greater sleepiness. All DTI changes remained significant after adjusting for hydration measures.

Conclusions

This is the first DTI study of sleep deprivation in humans. Although previous studies have observed localized changes in DTI indices of cerebral microstructure over the course of a few hours, further studies are needed to confirm widespread DTI changes within hours of waking and to clarify whether such changes in white matter microstructure serve as neurobiological substrates of sleepiness.

The restless brain: how intrinsic activity organizes brain function

Traditionally studies of brain function have focused on task-evoked responses. By their very nature such experiments tacitly encourage a reflexive view of brain function. While such an approach has been remarkably productive at all levels of neuroscience, it ignores the alternative possibility that brain functions are mainly intrinsic and ongoing, involving information processing for interpreting, responding to and predicting environmental demands. I suggest that the latter view best captures the essence of brain function, a position that accords well with the allocation of the brain's energy resources, its limited access to sensory information and a dynamic, intrinsic functional organization. The nature of this intrinsic activity, which exhibits a surprising level of organization with dimensions of both space and time, is revealed in the ongoing activity of the brain and its metabolism. As we look to the future, understanding the nature of this intrinsic activity will require integrating knowledge from cognitive and systems neuroscience with cellular and molecular neuroscience where ion channels, receptors, components of signal transduction and metabolic pathways are all in a constant state of flux. The reward for doing so will be a much better understanding of human behaviour in health and disease.

The brain's default mode network

The brain's default mode network consists of discrete, bilateral and symmetrical cortical areas, in the medial and lateral parietal, medial prefrontal, and medial and lateral temporal cortices of the human, nonhuman primate, cat, and rodent brains. Its discovery was an unexpected consequence of brain-imaging studies first performed with positron emission tomography in which various novel, attention-demanding, and non-self-referential tasks were compared with quiet repose either with eyes closed or with simple visual fixation. The default mode network consistently decreases its activity when compared with activity during these relaxed nontask states. The discovery of the default mode network reignited a longstanding interest in the significance of the brain's ongoing or intrinsic activity. Presently, studies of the brain's intrinsic activity, popularly referred to as resting-state studies, have come to play a major role in studies of the human brain in health and disease. The brain's default mode network plays a central role in this work.

Sleep, clocks, and synaptic plasticity

Sleep is widely believed to play an essential role in synaptic plasticity. However, the precise mechanisms governing this presumptive function are largely unknown. There is also evidence for independent circadian oscillations in synaptic strength and morphology. Therefore, synaptic changes observed after sleep reflect interactions between state-dependent (e.g., wake versus sleep) and state-independent (circadian) processes. In this review we consider how sleep and biological clocks influence synaptic plasticity. We discuss these findings in the context of current plasticity-based theories of sleep function and propose a new model that integrates circadian and brain-state influences on synaptic plasticity.

Circadian and homeostatic modulation of functional connectivity and regional cerebral blood flow in humans under normal entrained conditions

Diurnal rhythms have been observed in human behaviors as diverse as sleep, olfaction, and learning. Despite its potential impact, time of day is rarely considered when brain responses are studied by neuroimaging techniques. To address this issue, we explicitly examined the effects of circadian and homeostatic regulation on functional connectivity (FC) and regional cerebral blood flow (rCBF) in healthy human volunteers, using whole-brain resting-state functional magnetic resonance imaging (rs-fMRI) and arterial spin labeling (ASL). In common with many circadian studies, we collected salivary cortisol to represent the normal circadian activity and functioning of the hypothalamic-pituitary-adrenal (HPA) axis. Intriguingly, the changes in FC and rCBF we observed indicated fundamental decreases in the functional integration of the default mode network (DMN) moving from morning to afternoon. Within the anterior cingulate cortex (ACC), our results indicate that morning cortisol levels are negatively correlated with rCBF. We hypothesize that the homeostatic mechanisms of the HPA axis has a role in modulating the functional integrity of the DMN (specifically, the ACC), and for the purposes of using fMRI as a tool to measure changes in disease processes or in response to treatment, we demonstrate that time of the day is important when interpreting resting-state data.

Neuroimaging, cognition, light and circadian rhythms

In humans, sleep and wakefulness and the associated cognitive processes are regulated through interactions between sleep homeostasis and the circadian system. Chronic disruption of sleep and circadian rhythmicity is common in our society and there is a need for a better understanding of the brain mechanisms regulating sleep, wakefulness and associated cognitive processes. This review summarizes recent investigations which provide first neural correlates of the combined influence of sleep homeostasis and circadian rhythmicity on cognitive brain activity. Markers of interindividual variations in sleep-wake regulation, such as chronotype and polymorphisms in sleep and clock genes, are associated with changes in cognitive brain responses in subcortical and cortical areas in response to manipulations of the sleep-wake cycle. This review also includes recent data showing that cognitive brain activity is regulated by light, which is a powerful modulator of cognition and alertness and also directly impacts sleep and circadian rhythmicity. The effect of light varied with age, psychiatric status, PERIOD3 genotype and changes in sleep homeostasis and circadian phase. These data provide new insights into the contribution of demographic characteristics, the sleep-wake cycle, circadian rhythmicity and light to brain functioning.

Lag structure in resting-state fMRI

The discovery that spontaneous fluctuations in blood oxygen level-dependent (BOLD) signals contain information about the functional organization of the brain has caused a paradigm shift in neuroimaging. It is now well established that intrinsic brain activity is organized into spatially segregated resting-state networks (RSNs). Less is known regarding how spatially segregated networks are integrated by the propagation of intrinsic activity over time. To explore this question, we examined the latency structure of spontaneous fluctuations in the fMRI BOLD signal. Our data reveal that intrinsic activity propagates through and across networks on a timescale of ∼1 s. Variations in the latency structure of this activity resulting from sensory state manipulation (eyes open vs. closed), antecedent motor task (button press) performance, and time of day (morning vs. evening) suggest that BOLD signal lags reflect neuronal processes rather than hemodynamic delay. Our results emphasize the importance of the temporal structure of the brain's spontaneous activity.

Sleep and the price of plasticity: from synaptic and cellular homeostasis to memory consolidation and integration

Sleep is universal, tightly regulated, and its loss impairs cognition. But why does the brain need to disconnect from the environment for hours every day? The synaptic homeostasis hypothesis (SHY) proposes that sleep is the price the brain pays for plasticity. During a waking episode, learning statistical regularities about the current environment requires strengthening connections throughout the brain. This increases cellular needs for energy and supplies, decreases signal-to-noise ratios, and saturates learning. During sleep, spontaneous activity renormalizes net synaptic strength and restores cellular homeostasis. Activity-dependent down-selection of synapses can also explain the benefits of sleep on memory acquisition, consolidation, and integration. This happens through the offline, comprehensive sampling of statistical regularities incorporated in neuronal circuits over a lifetime. This Perspective considers the rationale and evidence for SHY and points to open issues related to sleep and plasticity.

Zen and the brain: mutually illuminating topics

Zen Buddhist meditative practices emphasize the long-term, mindful training of attention and awareness during one's ordinary daily-life activities, the shedding of egocentric behaviors, and the skillful application of one's innate compassionate resources of insight-wisdom toward others and oneself. This review focuses on how such a comprehensive approach to training the brain could relate to a distinctive flavor of Zen: its emphasis on direct experience, with special reference to those major acute states of awakening that create deep transformations of consciousness and behavior. In Japanese, these advanced states are called kensho and satori. Ten key concepts are reviewed. They begin by distinguishing between the concentrative and receptive forms of meditation, noticing the complementary ways that they each train our normal “top–down” and “bottom–up” modes of attentive processing. Additional concepts distinguish between our two major processing pathways. The self-centered, egocentric frame of reference processes information in relation to our body (our soma) or to our mental functions (our psyche). The other-centered frame of reference processes information anonymously. Its prefix, allo- simply means “other” in Greek. Subsequent concepts consider how these useful Greek words—ego/allo, soma/psyche—correlate with the normal functional anatomy of important thalamo ↔ cortical connections. A plausible model then envisions how a triggering stimulus that captures attention could prompt the reticular nucleus to release GABA; how its selective inhibition of the dorsal thalamus could then block both our higher somatic and psychic cortical functions; so as to: (a) delete the maladaptive aspects of selfhood, while also (b) releasing the direct, all-inclusive, globally-unified experience of other. Two final concepts consider how the long-term meditative training of intuitive functions relates to certain kinds of word-free spatial tasks that involve insightful creative problem-solving.

Clinical applications of the functional connectome

Central to the development of clinical applications of functional connectomics for neurology and psychiatry is the discovery and validation of biomarkers. Resting state fMRI (R-fMRI) is emerging as a mainstream approach for imaging-based biomarker identification, detecting variations in the functional connectome that can be attributed to clinical variables (e.g., diagnostic status). Despite growing enthusiasm, many challenges remain. Here, we assess evidence of the readiness of R-fMRI based functional connectomics to lead to clinically meaningful biomarker identification through the lens of the criteria used to evaluate clinical tests (i.e., validity, reliability, sensitivity, specificity, and applicability). We focus on current R-fMRI-based prediction efforts, and survey R-fMRI used for neurosurgical planning. We identify gaps and needs for R-fMRI-based biomarker identification, highlighting the potential of emerging conceptual, analytical and cultural innovations (e.g., the Research Domain Criteria Project (RDoC), open science initiatives, and Big Data) to address them. Additionally, we note the need to expand future efforts beyond identification of biomarkers for disease status alone to include clinical variables related to risk, expected treatment response and prognosis.

Standardizing the intrinsic brain: towards robust measurement of inter-individual variation in 1000 functional connectomes

As researchers increase their efforts to characterize variations in the functional connectome across studies and individuals, concerns about the many sources of nuisance variation present and their impact on resting state fMRI (R-fMRI) measures continue to grow. Although substantial within-site variation can exist, efforts to aggregate data across multiple sites such as the 1000 Functional Connectomes Project (FCP) and International Neuroimaging Data-sharing Initiative (INDI) datasets amplify these concerns. The present work draws upon standardization approaches commonly used in the microarray gene expression literature, and to a lesser extent recent imaging studies, and compares them with respect to their impact on relationships between common R-fMRI measures and nuisance variables (e.g., imaging site, motion), as well as phenotypic variables of interest (age, sex). Standardization approaches differed with regard to whether they were applied post-hoc vs. during pre-processing, and at the individual vs. group level; additionally they varied in whether they addressed additive effects vs. additive+multiplicative effects, and were parametric vs. non-parametric. While all standardization approaches were effective at reducing undesirable relationships with nuisance variables, post-hoc approaches were generally more effective than global signal regression (GSR). Across approaches, correction for additive effects (global mean) appeared to be more important than for multiplicative effects (global SD) for all R-fMRI measures, with the exception of amplitude of low frequency fluctuations (ALFF). Group-level post-hoc standardizations for mean-centering and variance-standardization were found to be advantageous in their ability to avoid the introduction of artifactual relationships with standardization parameters; though results between individual and group-level post-hoc approaches were highly similar overall. While post-hoc standardization procedures drastically increased test-retest (TRT) reliability for ALFF, modest reductions were observed for other measures after post-hoc standardizations-a phenomena likely attributable to the separation of voxel-wise from global differences among subjects (global mean and SD demonstrated moderate TRT reliability for these measures). Finally, the present work calls into question previous observations of increased anatomical specificity for GSR over mean centering, and draws attention to the near equivalence of global and gray matter signal regression.

Astroglial regulation of sleep homeostasis

Mammalian sleep is regulated by two distinct mechanisms. A circadian oscillator provides timing signals that organize sleep and wake across the 24 hour day. A homeostatic mechanism increases sleep drive and sleep amounts (or intensity) as a function of prior time awake. The cellular mechanisms of sleep homeostasis are poorly defined, but are thought to be primarily neuronal. According to one view, sleep homeostasis arises from interactions between subcortical neurons that register sleep pressure and other neurons that promote either sleep or wakefulness. Alternatively, sleep drive may arise independently among neurons throughout the brain in a use-dependent fashion. Implicit in both views is the idea that sleep homeostasis is solely the product of neurons. In this article, I discuss an emerging view that glial astrocytes may play an essential role in sleep homeostasis.