Morning-evening variation in human brain metabolism and memory circuits

Functional brain connectivity changes associated with day-to-day fluctuations in affective states

Affective neuroscience has traditionally relied on cross-sectional studies to uncover the brain correlates of affects, emotions, and moods. Such findings obfuscate intraindividual variability that may reveal meaningful changing affect states. The few functional magnetic resonance imaging longitudinal studies that have linked changes in brain function to the ebbs and flows of affective states over time have mostly investigated a single individual. In this study, we explored how the functional connectivity of brain areas associated with affective processes can explain within-person fluctuations in self-reported positive and negative affects across several subjects. To do so, we leveraged the Day2day dataset that includes 40 to 50 resting-state functional magnetic resonance imaging scans along self-reported positive and negative affectivity from a sample of six healthy participants. Sparse multivariate mixed-effect linear models could explain 15% and 11% of the within-person variation in positive and negative affective states, respectively. Evaluation of these models' generalizability to new data demonstrated the ability to predict approximately 5% and 2% of positive and negative affect variation. The functional connectivity of limbic areas, such as the amygdala, hippocampus, and insula, appeared most important to explain the temporal dynamics of affects over days, weeks, and months.

Longitudinal single-subject neuroimaging study reveals effects of daily environmental, physiological, and lifestyle factors on functional brain connectivity

Our behavior and mental states are constantly shaped by our environment and experiences. However, little is known about the response of brain functional connectivity to environmental, physiological, and behavioral changes on different timescales, from days to months. This gives rise to an urgent need for longitudinal studies that collect high-frequency data. To this end, for a single subject, we collected 133 days of behavioral data with smartphones and wearables and performed 30 functional magnetic resonance imaging (fMRI) scans measuring attention, memory, resting state, and the effects of naturalistic stimuli. We find traces of past behavior and physiology in brain connectivity that extend up as far as 15 days. While sleep and physical activity relate to brain connectivity during cognitively demanding tasks, heart rate variability and respiration rate are more relevant for resting-state connectivity and movie-watching. This unique data set is openly accessible, offering an exceptional opportunity for further discoveries. Our results demonstrate that we should not study brain connectivity in isolation, but rather acknowledge its interdependence with the dynamics of the environment, changes in lifestyle, and short-term fluctuations such as transient illnesses or restless sleep. These results reflect a prolonged and sustained relationship between external factors and neural processes. Overall, precision mapping designs such as the one employed here can help to better understand intraindividual variability, which may explain some of the observed heterogeneity in fMRI findings. The integration of brain connectivity, physiology data and environmental cues will propel future environmental neuroscience research and support precision healthcare.

Complexity organization of resting-state functional-MRI networks

Entropy measures are increasingly being used to analyze the structure of neural activity observed by functional magnetic resonance imaging (fMRI), with resting-state networks (RSNs) being of interest for their reproducible descriptions of the brain's functional architecture. Temporal correlations have shown a dichotomy among these networks: those that engage with the environment, known as extrinsic, which include the visual and sensorimotor networks; and those associated with executive control and self-referencing, known as intrinsic, which include the default mode network and the frontoparietal control network. While these inter-voxel temporal correlations enable the assessment of synchrony among the components of individual networks, entropic measures introduce an intra-voxel assessment that quantifies signal features encoded within each blood oxygen level-dependent (BOLD) time series. As a result, this framework offers insights into comprehending the representation and processing of information within fMRI signals. Multiscale entropy (MSE) has been proposed as a useful measure for characterizing the entropy of neural activity across different temporal scales. This measure of temporal entropy in BOLD data is dependent on the length of the time series; thus, high-quality data with fine-grained temporal resolution and a sufficient number of time frames is needed to improve entropy precision. We apply MSE to the Midnight Scan Club, a highly sampled and well-characterized publicly available dataset, to analyze the entropy distribution of RSNs and evaluate its ability to distinguish between different functional networks. Entropy profiles are compared across temporal scales and RSNs. Our results have shown that the spatial distribution of entropy at infra-slow frequencies (0.005-0.1 Hz) reproduces known parcellations of RSNs. We found a complexity hierarchy between intrinsic and extrinsic RSNs, with intrinsic networks robustly exhibiting higher entropy than extrinsic networks. Finally, we found new evidence that the topography of entropy in the posterior cerebellum exhibits high levels of entropy comparable to that of intrinsic RSNs.

Psilocybin desynchronizes the human brain

A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials1-4. In animal models, psilocybin induces neuroplasticity in cortex and hippocampus5-8. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics. Here we tracked individual-specific brain changes with longitudinal precision functional mapping (roughly 18 magnetic resonance imaging visits per participant). Healthy adults were tracked before, during and for 3 weeks after high-dose psilocybin (25 mg) and methylphenidate (40 mg), and brought back for an additional psilocybin dose 6-12 months later. Psilocybin massively disrupted functional connectivity (FC) in cortex and subcortex, acutely causing more than threefold greater change than methylphenidate. These FC changes were driven by brain desynchronization across spatial scales (areal, global), which dissolved network distinctions by reducing correlations within and anticorrelations between networks. Psilocybin-driven FC changes were strongest in the default mode network, which is connected to the anterior hippocampus and is thought to create our sense of space, time and self. Individual differences in FC changes were strongly linked to the subjective psychedelic experience. Performing a perceptual task reduced psilocybin-driven FC changes. Psilocybin caused persistent decrease in FC between the anterior hippocampus and default mode network, lasting for weeks. Persistent reduction of hippocampal-default mode network connectivity may represent a neuroanatomical and mechanistic correlate of the proplasticity and therapeutic effects of psychedelics.

Diurnal Fluctuations in Steroid Hormones Tied to Variation in Intrinsic Functional Connectivity in a Densely Sampled Male

Most of mammalian physiology is under the control of biological rhythms, including the endocrine system with time-varying hormone secretion. Precision neuroimaging studies provide unique insights into how the endocrine system dynamically regulates aspects of the human brain. Recently, we established estrogen's ability to drive widespread patterns of connectivity and enhance the global efficiency of large-scale brain networks in a woman sampled every 24 h across 30 consecutive days, capturing a complete menstrual cycle. Steroid hormone production also follows a pronounced sinusoidal pattern, with a peak in testosterone between 6 and 7 A.M. and nadir between 7 and 8 P.M. To capture the brain's response to diurnal changes in hormone production, we carried out a companion precision imaging study of a healthy adult man who completed MRI and venipuncture every 12-24 h across 30 consecutive days. Results confirmed robust diurnal fluctuations in testosterone, 17β-estradiol-the primary form of estrogen-and cortisol. Standardized regression analyses revealed widespread associations between testosterone, estradiol, and cortisol concentrations and whole-brain patterns of coherence. In particular, functional connectivity in the Dorsal Attention Network was coupled with diurnally fluctuating hormones. Further, comparing dense-sampling datasets between a man and a naturally cycling woman revealed that fluctuations in sex hormones are tied to patterns of whole-brain coherence in both sexes and to a heightened degree in the male. Together, these findings enhance our understanding of steroid hormones as rapid neuromodulators and provide evidence that diurnal changes in steroid hormones are associated with patterns of whole-brain functional connectivity.

Investigating the relationship between hippocampus/dentate gyrus volume and hypothalamus metabolism in participants with major depressive disorder

Reduced hippocampal volume occurs in major depressive disorder (MDD), potentially due to elevated glucocorticoids from an overactivated hypothalamus-pituitary-adrenal (HPA) axis. To examine this in humans, hippocampal volume and hypothalamus (HPA axis) metabolism was quantified in participants with MDD before and after antidepressant treatment. 65 participants (n = 24 males, n = 41 females) with MDD were treated in a double-blind, randomized clinical trial of escitalopram. Participants received simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) before and after treatment. Linear mixed models examined the relationship between hippocampus/dentate gyrus volume and hypothalamus metabolism. Chi-squared tests and multivariable logistic regression examined the association between hippocampus/dentate gyrus volume change direction and hypothalamus activity change direction with treatment. Multiple linear regression compared these changes between remitter and non-remitter groups. Covariates included age, sex, and treatment type. No significant linear association was found between hippocampus/dentate gyrus volume and hypothalamus metabolism. 62% (38 of 61) of participants experienced a decrease in hypothalamus metabolism, 43% (27 of 63) of participants demonstrated an increase in hippocampus size (51% [32 of 63] for the dentate gyrus) following treatment. No significant association was found between change in hypothalamus activity and change in hippocampus/dentate gyrus volume, and this association did not vary by sex, medication, or remission status. As this multimodal study, in a cohort of participants on standardized treatment, did not find an association between hypothalamus metabolism and hippocampal volume, it supports a more complex pathway between hippocampus neurogenesis and hypothalamus metabolism changes in response to treatment.

Test-retest reliability and time-of-day variations of perfusion imaging at rest and during a vigilance task

Arterial spin-labeled perfusion and blood oxygenation level-dependent functional MRI are indispensable tools for noninvasive human brain imaging in clinical and cognitive neuroscience, yet concerns persist regarding the reliability and reproducibility of functional MRI findings. The circadian rhythm is known to play a significant role in physiological and psychological responses, leading to variability in brain function at different times of the day. Despite this, test-retest reliability of brain function across different times of the day remains poorly understood. This study examined the test-retest reliability of six repeated cerebral blood flow measurements using arterial spin-labeled perfusion imaging both at resting-state and during the psychomotor vigilance test, as well as task-induced cerebral blood flow changes in a cohort of 38 healthy participants over a full day. The results demonstrated excellent test-retest reliability for absolute cerebral blood flow measurements at rest and during the psychomotor vigilance test throughout the day. However, task-induced cerebral blood flow changes exhibited poor reliability across various brain regions and networks. Furthermore, reliability declined over longer time intervals within the day, particularly during nighttime scans compared to daytime scans. These findings highlight the superior reliability of absolute cerebral blood flow compared to task-induced cerebral blood flow changes and emphasize the importance of controlling time-of-day effects to enhance the reliability and reproducibility of future brain imaging studies.

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.

Resting-State fMRI Study of Vigilance Under Circadian and Homeostatic Modulation Based on Fractional Amplitude of Low-Frequency Fluctuation and Regional Homogeneity in Humans Under Normal Entrained Conditions

BACKGROUND

How brain neural activity changes at multiple time points throughout the day and the neural mechanisms underlying time-dependent modulation of vigilance are less clear.

PURPOSE

To explore the effect of circadian rhythms and homeostasis on brain neural activity and the potential neural basis of time-dependent modulation of vigilance.

STUDY TYPE

Prospective.

SUBJECTS

A total of 30 healthy participants (22-27 years old).

FIELD STRENGTH/SEQUENCE

A 3.0 T, T1-weighted imaging, echo-planar functional MRI (fMRI).

ASSESSMENT

Six resting-state fMRI (rs-fMRI) scanning sessions were performed at fixed times (9:00 h, 13:00 h, 17:00 h, 21:00 h, 1:00 h, and 5:00 h) to investigate fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) diurnal variation. The fALFF/ReHo and the result of the psychomotor vigilance task were used to assess local neural activity and vigilance.

STATISTICAL TESTS

One-way repeated measures analysis of variance (ANOVA) was used to assess changes in vigilance (P < 0.05) and neural activity in the whole brain (P < 0.001 at the voxel level and P < 0.01 at the cluster level, Gaussian random field [GRF] corrected). Correlation analysis was used to examine the relationship between neural activity and vigilance at all-time points of the day.

RESULTS

The fALFF/ReHo in the thalamus and some perceptual cortices tended to increase from 9:00 h to 13:00 h and from 21:00 h to 5:00 h, whereas the key nodes of the default mode network (DMN) tended to decrease from 21:00 h to 5:00 h. The vigilance tended to decrease from 21:00 h to 5:00 h. The fALFF/ReHo in the thalamus and some perceptual cortices was negatively correlated with vigilance at all-time points of the day, whereas the fALFF/ReHo in the key nodes of the DMN was positively correlated with vigilance.

DATA CONCLUSION

Neural activities in the thalamus and some perceptual cortices show similar trends throughout the day, whereas the key nodes of the DMN show roughly opposite trends. Notably, diurnal variation of the neural activity in these brain regions may be an adaptive or compensatory response to changes in vigilance.

EVIDENCE LEVEL

1.

TECHNICAL EFFICACY

1.

Modulatory effects of fMRI acquisition time of day, week and year on adolescent functional connectomes across spatial scales: Implications for inference

Metabolic, hormonal, autonomic and physiological rhythms may have a significant impact on cerebral hemodynamics and intrinsic brain synchronization measured with fMRI (the resting-state connectome). The impact of their characteristic time scales (hourly, circadian, seasonal), and consequently scan timing effects, on brain topology in inherently heterogeneous developing connectomes remains elusive. In a cohort of 4102 early adolescents with resting-state fMRI (median age = 120.0 months; 53.1 % females) from the Adolescent Brain Cognitive Development Study, this study investigated associations between scan time-of-day, time-of-week (school day vs weekend) and time-of-year (school year vs summer vacation) and topological properties of resting-state connectomes at multiple spatial scales. On average, participants were scanned around 2 pm, primarily during school days (60.9 %), and during the school year (74.6 %). Scan time-of-day was negatively correlated with multiple whole-brain, network-specific and regional topological properties (with the exception of a positive correlation with modularity), primarily of visual, dorsal attention, salience, frontoparietal control networks, and the basal ganglia. Being scanned during the weekend (vs a school day) was correlated with topological differences in the hippocampus and temporoparietal networks. Being scanned during the summer vacation (vs the school year) was consistently positively associated with multiple topological properties of bilateral visual, and to a lesser extent somatomotor, dorsal attention and temporoparietal networks. Time parameter interactions suggested that being scanned during the weekend and summer vacation enhanced the positive effects of being scanned in the morning. Time-of-day effects were overall small but spatially extensive, and time-of-week and time-of-year effects varied from small to large (Cohen's f ≤ 0.1, Cohen's d<0.82, p < 0.05). Together, these parameters were also positively correlated with temporal fMRI signal variability but only in the left hemisphere. Finally, confounding effects of scan time parameters on relationships between connectome properties and cognitive task performance were assessed using the ABCD neurocognitive battery. Although most relationships were unaffected by scan time parameters, their combined inclusion eliminated associations between properties of visual and somatomotor networks and performance in the Matrix Reasoning and Pattern Comparison Processing Speed tasks. Thus, scan time of day, week and year may impact measurements of adolescent brain's functional circuits, and should be accounted for in studies on their associations with cognitive performance, in order to reduce the probability of incorrect inference.

Diurnal fluctuations in steroid hormones tied to variation in intrinsic functional connectivity in a densely sampled male

Most of mammalian physiology is under the control of biological rhythms, including the endocrine system with time-varying hormone secretion. Precision neuroimaging studies provide unique insights into the means through which our endocrine system regulates dynamic properties of the human brain. Recently, we established estrogen's ability to drive widespread patterns of connectivity and enhance the functional efficiency of large-scale brain networks in a woman sampled every 24h across 30 consecutive days, capturing a complete menstrual cycle. Steroid hormone production also follows a pronounced sinusoidal pattern, with a peak in testosterone between 6-7am and nadir between 7-8pm. To capture the brain's response to diurnal changes in hormone production, we carried out a companion precision imaging study of a healthy adult man who completed MRI and venipuncture every 12-24 hours across 30 consecutive days. Results confirmed robust diurnal fluctuations in testosterone, cortisol, and estradiol. Standardized regression analyses revealed predominantly positive associations between testosterone, cortisol, and estradiol concentrations and whole-brain patterns of coherence. In particular, functional connectivity in Dorsal Attention and Salience/Ventral Attention Networks were coupled with diurnally fluctuating hormones. Further, comparing dense-sampling datasets between a man and naturally-cycling woman revealed that fluctuations in sex hormones are tied to patterns of whole-brain coherence to a comparable degree in both sexes. Together, these findings enhance our understanding of steroid hormones as rapid neuromodulators and provide evidence that diurnal changes in steroid hormones are tied to patterns of whole-brain functional connectivity.

Psilocybin desynchronizes brain networks

1The relationship between the acute effects of psychedelics and their persisting neurobiological and psychological effects is poorly understood. Here, we tracked brain changes with longitudinal precision functional mapping in healthy adults before, during, and for up to 3 weeks after oral psilocybin and methylphenidate (17 MRI visits per participant) and again 6+ months later. Psilocybin disrupted connectivity across cortical networks and subcortical structures, producing more than 3-fold greater acute changes in functional networks than methylphenidate. These changes were driven by desynchronization of brain activity across spatial scales (area, network, whole brain). Psilocybin-driven desynchronization was observed across association cortex but strongest in the default mode network (DMN), which is connected to the anterior hippocampus and thought to create our sense of self. Performing a perceptual task reduced psilocybin-induced network changes, suggesting a neurobiological basis for grounding, connecting with physical reality during psychedelic therapy. The acute brain effects of psilocybin are consistent with distortions of space-time and the self. Psilocybin induced persistent decrease in functional connectivity between the anterior hippocampus and cortex (and DMN in particular), lasting for weeks but normalizing after 6 months. Persistent suppression of hippocampal-DMN connectivity represents a candidate neuroanatomical and mechanistic correlate for psilocybin's pro-plasticity and anti-depressant effects.

Time of day dependent longitudinal changes in resting-state fMRI

Longitudinal studies have become more common in the past years due to their superiority over cross-sectional samples. In light of the ongoing replication crisis, the factors that may introduce variability in resting-state networks have been widely debated. This publication aimed to address the potential sources of variability, namely, time of day, sex, and age, in longitudinal studies within individual resting-state fMRI data. DCM was used to analyze the fMRI time series, extracting EC connectivity measures and parameters that define the BOLD signal. In addition, a two-way ANOVA was used to assess the change in EC and parameters that define the BOLD signal between data collection waves. The results indicate that time of day and gender have significant model evidence for the parameters that define the BOLD signal but not EC. From the ANOVA analysis, findings indicate that there was a significant change in the two nodes of the DMN and their connections with the fronto-parietal network. Overall, these findings suggest that in addition to age and gender, which are commonly accounted for in the fMRI data collection, studies should note the time of day, possibly treating it as a covariate in longitudinal samples.

Investigating The Relationship Between Hippocampus:Dentate Gyrus Volume and Hypothalamus Metabolism in Participants with Major Depressive Disorder

Reduced hippocampal volume occurs in major depressive disorder (MDD), theoretically due to elevated glucocorticoids from an overactivated hypothalamus-pituitary-adrenal (HPA) axis. To examine this in humans, hippocampal volume, and hypothalamus (HPA axis) metabolism was quantified in participants with MDD before and after antidepressant treatment. 65 participants (n = 24 males, n = 41 females) with MDD were treated in a double-blind, randomized clinical trial of escitalopram. Participants received simultaneous positron emission tomography (PET) / magnetic resonance imaging (MRI) before and after treatment. Linear mixed models examined the relationship between hippocampus/dentate gyrus volume and hypothalamus metabolism. Chi-squared tests and multivariable logistic regression examined the association between hippocampus/dentate gyrus volume change direction and hypothalamus activity change direction with treatment. Multiple linear regression compared these changes between remitter and non-remitter groups. Covariates included age, sex, and treatment type. No significant linear association was found between hippocampus/dentate gyrus volume and hypothalamus metabolism. 62% (38 of 61) of participants experienced a decrease in hypothalamus metabolism, 43% (27 of 63) of participants demonstrated an increase in hippocampus size (51% [32 of 63] for the dentate gyrus) following treatment. No significant association was found between change in hypothalamus activity and change in hippocampus/dentate gyrus volume, and this association did not vary by sex, medication, or remission status. As this multimodal study, in a cohort of participants on standardized treatment, did not find an association between hypothalamus metabolism and hippocampal volume, it supports a more complex pathway between hippocampus neurogenesis and treatment response.

Understanding neuron-glia crosstalk and biological clocks in insomnia

According to the World Health Organization, about one-third of the population experiences insomnia symptoms, and about 10-15% suffer from chronic insomnia, the most common sleep disorder. Sleeping difficulties associated with insomnia are often linked to chronic sleep deprivation, which has a negative health impact partly due to disruption in the internal synchronisation of biological clocks. These are regulated by clock genes and modulate most biological processes. Most studies addressing circadian rhythm regulation have focused on the role of neurons, yet glial cells also impact circadian rhythms and sleep regulation. Chronic insomnia and sleep loss have been associated with glial cell activation, exacerbated neuroinflammation, oxidative stress, altered neuronal metabolism and synaptic plasticity, accelerated age-related processes and decreased lifespan. It is, therefore, essential to highlight the importance of glia-neuron interplay on sleep/circadian regulation and overall healthy brain function. Hence, in this review, we aim to address the main neurobiological mechanisms involved in neuron-glia crosstalk, with an emphasis on microglia and astrocytes, in both healthy sleep, chronic sleep deprivation and chronic insomnia.

Detecting change points in neural population activity with contrastive metric learning

Finding points in time where the distribution of neural responses changes (change points) is an important step in many neural data analysis pipelines. However, in complex and free behaviors, where we see different types of shifts occurring at different rates, it can be difficult to use existing methods for change point (CP) detection because they can't necessarily handle different types of changes that may occur in the underlying neural distribution. Additionally, response changes are often sparse in high dimensional neural recordings, which can make existing methods detect spurious changes. In this work, we introduce a new approach for finding changes in neural population states across diverse activities and arousal states occurring in free behavior. Our model follows a contrastive learning approach: we learn a metric for CP detection based on maximizing the Sinkhorn divergences of neuron firing rates across two sides of a labeled CP. We apply this method to a 12-hour neural recording of a freely behaving mouse to detect changes in sleep stages and behavior. We show that when we learn a metric, we can better detect change points and also yield insights into which neurons and sub-groups are important for detecting certain types of switches that occur in the brain.

Hyperactivity of the default mode network in schizophrenia and free energy: A dialogue between Freudian theory of psychosis and neuroscience

The economic conceptualization of Freudian metapsychology, based on an energetics model of the psyche's workings, offers remarkable commonalities with some recent discoveries in neuroscience, notably in the field of neuroenergetics. The pattern of cerebral activity at resting state and the identification of a default mode network (DMN), a network of areas whose activity is detectable at baseline conditions by neuroimaging techniques, offers a promising field of research in the dialogue between psychoanalysis and neuroscience. In this article we study one significant clinical application of this interdisciplinary dialogue by looking at the role of the DMN in the psychopathology of schizophrenia. Anomalies in the functioning of the DMN have been observed in schizophrenia. Studies have evidenced the existence of hyperactivity in this network in schizophrenia patients, particularly among those for whom a positive symptomatology is dominant. These data are particularly interesting when considered from the perspective of the psychoanalytic understanding of the positive symptoms of psychosis, most notably the Freudian hypothesis of delusions as an "attempt at recovery." Combining the data from research in neuroimaging of schizophrenia patients with the Freudian hypothesis, we propose considering the hyperactivity of the DMN as a consequence of a process of massive reassociation of traces occurring in schizophrenia. This is a process that may constitute an attempt at minimizing the excess of free energy present in psychosis. Modern models of active inference and the free energy principle (FEP) may shed some light on these processes.

Regional brain dysfunction in insomnia after ischemic stroke: A resting-state fMRI study

Objective

This study aimed to explore the abnormality of local brain function in patients with post-stroke insomnia (PSI) based on fMRI and explore the possible neuropathological mechanisms of insomnia in patients with PSI in combination with the Pittsburgh sleep quality index (PSQI) score and provide an objective evaluation index for the follow-up study of acupuncture treatment of PSI.

Methods

A total of 27 patients with insomnia after stroke were enrolled, and the PSQI was used to evaluate their sleep status. Twenty-seven healthy participants who underwent physical examinations during the same period were selected as controls. Resting-state brain function images and structural images of the two groups of participants were collected, and the abnormal changes in the regional brain function in patients with PSI were analyzed using three methods: regional homogeneity (ReHo), the amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF), and a correlation analysis with the PSQI scale score.

Results

Compared with the HCs, the ReHo values of the PSI group in the bilateral lingual gyrus, right cuneus, right precentral and postcentral gyri were significantly lower, and the ReHo values of the left supramarginal gyrus were significantly higher. In the PSI group, the ALFF values in the bilateral lingual gyrus were significantly decreased, whereas those in the bilateral middle temporal gyrus, right inferior temporal gyrus, right inferior frontal gyrus, right limbic lobe, right precuneus, left posterior cingulate gyrus, and left middle occipital gyrus were significantly increased. Compared with HCs, the fALFF values of the bilateral lingual gyrus, bilateral inferior occipital gyrus, and bilateral cuneus in the PSI group were significantly higher. The ReHo value of the left supramarginal gyrus in the PSI group was significantly negatively correlated with the total PSQI score.

Conclusion

Patients with PSI have abnormal local activities in multiple brain regions, including the visual processing-related cortex, sensorimotor cortex, and some default-mode network (DMN) regions. Over-arousal of the DMN and over-sensitivity of the audiovisual stimuli in patients with PSI may be the main mechanisms of insomnia and can lead to a decline in cognitive function and abnormalities in emotion regulation simultaneously.

Infraslow closed-loop brain training for anxiety and depression (ISAD): a protocol for a randomized, double-blind, sham-controlled pilot trial in adult females with internalizing disorders

BACKGROUND

The core intrinsic connectivity networks (core-ICNs), encompassing the default-mode network (DMN), salience network (SN) and central executive network (CEN), have been shown to be dysfunctional in individuals with internalizing disorders (IDs, e.g. major depressive disorder, MDD; generalized anxiety disorder, GAD; social anxiety disorder, SOC). As such, source-localized, closed-loop brain training of electrophysiological signals, also known as standardized low-resolution electromagnetic tomography (sLORETA) neurofeedback (NFB), targeting key cortical nodes within these networks has the potential to reduce symptoms associated with IDs and restore normal core ICN function. We intend to conduct a randomized, double-blind (participant and assessor), sham-controlled, parallel-group (3-arm) trial of sLORETA infraslow (<0.1 Hz) fluctuation neurofeedback (sLORETA ISF-NFB) 3 times per week over 4 weeks in participants (n=60) with IDs. Our primary objectives will be to examine patient-reported outcomes (PROs) and neurophysiological measures to (1) compare the potential effects of sham ISF-NFB to either genuine 1-region ISF-NFB or genuine 2-region ISF-NFB, and (2) assess for potential associations between changes in PRO scores and modifications of electroencephalographic (EEG) activity/connectivity within/between the trained regions of interest (ROIs). As part of an exploratory analysis, we will investigate the effects of additional training sessions and the potential for the potentiation of the effects over time.

METHODS

We will randomly assign participants who meet the criteria for MDD, GAD, and/or SOC per the MINI (Mini International Neuropsychiatric Interview for DSM-5) to one of three groups: (1) 12 sessions of posterior cingulate cortex (PCC) ISF-NFB up-training (n=15), (2) 12 sessions of concurrent PCC ISF up-training and dorsal anterior cingulate cortex (dACC) ISF-NFB down-training (n=15), or (3) 6 sessions of yoked-sham training followed by 6 sessions genuine ISF-NFB (n=30). Transdiagnostic PROs (Hospital Anxiety and Depression Scale, HADS; Inventory of Depression and Anxiety Symptoms - Second Version, IDAS-II; Multidimensional Emotional Disorder Inventory, MEDI; Intolerance of Uncertainty Scale - Short Form, IUS-12; Repetitive Thinking Questionnaire, RTQ-10) as well as resting-state neurophysiological measures (full-band EEG and ECG) will be collected from all subjects during two baseline sessions (approximately 1 week apart) then at post 6 sessions, post 12 sessions, and follow-up (1 month later). We will employ Bayesian methods in R and advanced source-localisation software (i.e. exact low-resolution brain electromagnetic tomography; eLORETA) in our analysis.

DISCUSSION

This protocol will outline the rationale and research methodology for a clinical pilot trial of sLORETA ISF-NFB targeting key nodes within the core-ICNs in a female ID population with the primary aims being to assess its potential efficacy via transdiagnostic PROs and relevant neurophysiological measures.

TRIAL REGISTRATION

Our study was prospectively registered with the Australia New Zealand Clinical Trials Registry (ANZCTR; Trial ID: ACTRN12619001428156). Registered on October 15, 2019.

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.

Evaluation of functional MRI-based human brain parcellation: a review

Brain parcellations play a crucial role in the analysis of brain imaging data sets, as they can significantly affect the outcome of the analysis. In recent years, several novel approaches for constructing MRI-based brain parcellations have been developed with promising results. In the absence of ground truth, several evaluation approaches have been used to evaluate currently available brain parcellations. In this article, we review and critique methods used for evaluating functional brain parcellations constructed using fMRI data sets. We also describe how some of these evaluation methods have been used to estimate the optimal parcellation granularity. We provide a critical discussion of the current approach to the problem of identifying the optimal brain parcellation that is suited for a given neuroimaging study. We argue that the criteria for an optimal brain parcellation must depend on the application the parcellation is intended for. We describe a teleological approach to the evaluation of brain parcellations, where brain parcellations are evaluated in different contexts and optimal brain parcellations for each context are identified separately. We conclude by discussing several directions for further research that would result in improved evaluation strategies.

Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response

Fast fMRI enables the detection of neural dynamics over timescales of hundreds of milliseconds, suggesting it may provide a new avenue for studying subsecond neural processes in the human brain. The magnitudes of these fast fMRI dynamics are far greater than predicted by canonical models of the hemodynamic response. Several studies have established nonlinear properties of the hemodynamic response that have significant implications for fast fMRI. We first review nonlinear properties of the hemodynamic response function that may underlie fast fMRI signals. We then illustrate the breakdown of canonical hemodynamic response models in the context of fast neural dynamics. We will then argue that the canonical hemodynamic response function is not likely to reflect the BOLD response to neuronal activity driven by sparse or naturalistic stimuli or perhaps to spontaneous neuronal fluctuations in the resting state. These properties suggest that fast fMRI is capable of tracking surprisingly fast neuronal dynamics, and we discuss the neuroscientific questions that could be addressed using this approach.

Time-of-Day Effects in Resting-State Functional Magnetic Resonance Imaging: Changes in Effective Connectivity and Blood Oxygenation Level Dependent Signal

Introduction:

In the light of the ongoing replication crisis in the field of neuroimaging, it is necessary to assess the possible exogenous and endogenous factors that may affect functional magnetic resonance imaging (fMRI). The current project investigated time-of-day effects in the spontaneous fluctuations (<0.1 Hz) of the blood oxygenation level dependent (BOLD) signal.

Method:

Using data from the human connectome project release S1200, cross-spectral density dynamic causal modeling (DCM) was used to analyze time-dependent effects on the hemodynamic response and effective connectivity parameters. The DCM analysis covered three networks, namely the default mode network, the central executive network, and the saliency network. Hierarchical group-parametric empirical Bayes (PEB) was used to test varying design-matrices against the time-of-day model.

Results:

Hierarchical group-PEB found no support for changes in effective connectivity, whereas the hemodynamic parameters exhibited a significant time-of-day dependent effect, indicating a diurnal vascular effect that might affect the measured BOLD signal in the absence of any diurnal variations of the underlying neuronal activations and effective connectivity.

Conclusion:

We conclude that these findings urge the need to account for the time of data acquisition in future MRI studies and suggest that time-of-day dependent metabolic variations contribute to reduced reliability in resting-state fMRI studies.

Impact statement

The results from this study suggest that the circadian mechanism influences the blood oxygenation level dependent signal in resting-state functional magnetic resonance imaging (fMRI). The current study urges to record and report the time of fMRI scan acquisition in future research, as it may increase the replicability of findings. Both exploratory and clinical studies would benefit by incorporating this small change in fMRI protocol, which to date has been often overlooked.

Physiological and motion signatures in static and time-varying functional connectivity and their subject identifiability

Human brain connectivity yields significant potential as a noninvasive biomarker. Several studies have used fMRI-based connectivity fingerprinting to characterize individual patterns of brain activity. However, it is not clear whether these patterns mainly reflect neural activity or the effect of physiological and motion processes. To answer this question, we capitalize on a large data sample from the Human Connectome Project and rigorously investigate the contribution of the aforementioned processes on functional connectivity (FC) and time-varying FC, as well as their contribution to subject identifiability. We find that head motion, as well as heart rate and breathing fluctuations, induce artifactual connectivity within distinct resting-state networks and that they correlate with recurrent patterns in time-varying FC. Even though the spatiotemporal signatures of these processes yield above-chance levels in subject identifiability, removing their effects at the preprocessing stage improves identifiability, suggesting a neural component underpinning the inter-individual differences in connectivity.

Resting-state functional connectivity and quantitation of glutamate and GABA of the PCC/precuneus by magnetic resonance spectroscopy at 7T in healthy individuals

The default mode network (DMN) is the main large-scale network of the resting brain and the PCC/precuneus is a major hub of this network. Glutamate and GABA (γ-amino butyric acid) are the main excitatory and inhibitory neurotransmitters in the CNS, respectively. We studied glutamate and GABA concentrations in the PCC/precuneus via magnetic resonance spectroscopy (MRS) at 7T in relation to age and correlated them with functional connectivity between this region and other DMN nodes in ten healthy right-handed volunteers ranging in age between 23–68 years. Mean functional connectivity of the PCC/precuneus to the other DMN nodes and the glutamate/GABA ratio significantly correlated with age (r = 0.802, p = 0.005 and r = 0.793, p = 0.006, respectively) but not with each other. Glutamate and GABA alone did not significantly correlate with age nor with functional connectivity within the DMN. The glutamate/GABA ratio and functional connectivity of the PCC/precuneus are, therefore, independent age-related biomarkers of the DMN and may be combined in a multimodal pipeline to study DMN alterations in various disease states.

Circadian/multidien Molecular Oscillations and Rhythmicity of Epilepsy (MORE)

The occurrence of seizures at specific times of the day has been consistently observed for centuries in individuals with epilepsy. Electrophysiological recordings provide evidence that seizures have a higher probability of occurring at a given time during the night and day cycle in individuals with epilepsy here referred to as the seizure rush hour. Which mechanisms underlie such circadian rhythmicity of seizures? Why don't they occur every day at the same time? Which mechanisms may underlie their occurrence outside the rush hour? In this commentary, I present a hypothesis: MORE - Molecular Oscillations and Rhythmicity of Epilepsy, a conceptual framework to study and understand the mechanisms underlying the circadian rhythmicity of seizures and their probabilistic nature. The core of the hypothesis is the existence of ~24-hour oscillations of gene and protein expression throughout the body in different cells and organs. The orchestrated molecular oscillations control the rhythmicity of numerous body events, such as feeding and sleep. The concept developed here is that molecular oscillations may favor seizure genesis at preferred times, generating the condition for a seizure rush hour. However, the condition is not sufficient, as other factors are necessary for a seizure to occur. Studying these molecular oscillations may help us understand seizure genesis mechanisms and find new therapeutic targets and predictive biomarkers. The MORE hypothesis can be generalized to comorbidities and the slower multidien (week/month period) rhythmicity of seizures, a phenomenon addressed in another article in this issue of Epilepsia.

Neural Connectivity Changes Facilitated by Familiar Auditory Sensory Training in Disordered Consciousness: A TBI Pilot Study

For people with disordered consciousness (DoC) after traumatic brain injury (TBI), relationships between treatment-induced changes in neural connectivity and neurobehavioral recovery have not been explored. To begin building a body of evidence regarding the unique contributions of treatments to changes in neural network connectivity relative to neurobehavioral recovery, we conducted a pilot study to identify relationships meriting additional examination in future research. To address this objective, we examined previously unpublished neural connectivity data derived from a randomized clinical trial (RCT). We leveraged these data because treatment efficacy, in the RCT, was based on a comparison of a placebo control with a specific intervention, the familiar auditory sensory training (FAST) intervention, consisting of autobiographical auditory-linguistic stimuli. We selected a subgroup of RCT participants with high-quality imaging data (FAST n = 4 and placebo n = 4) to examine treatment-related changes in brain network connectivity and how and if these changes relate to neurobehavioral recovery. To discover promising relationships among the FAST intervention, changes in neural connectivity, and neurobehavioral recovery, we examined 26 brain regions and 19 white matter tracts associated with default mode, salience, attention, and language networks, as well as three neurobehavioral measures. Of the relationships discovered, the systematic filtering process yielded evidence supporting further investigation of the relationship among the FAST intervention, connectivity of the left inferior longitudinal fasciculus, and auditory-language skills. Evidence also suggests that future mechanistic research should focus on examining the possibility that the FAST supports connectivity changes by facilitating redistribution of brain resources. For a patient population with limited treatment options, the reported findings suggest that a simple, yet targeted, passive sensory stimulation treatment may have altered functional and structural connectivity. If replicated in future research, then these findings provide the foundation for characterizing the unique contributions of the FAST intervention and could inform development of new treatment strategies. For persons with severely damaged brain networks, this report represents a first step toward advancing understanding of the unique contributions of treatments to changing brain network connectivity and how these changes relate to neurobehavioral recovery for persons with DoC after TBI.

Clinical Trial Registry: NCT00557076, The Efficacy of Familiar Voice Stimulation During Coma Recovery (http://www.clinicaltrials.gov).

The circadian dynamics of the hippocampal transcriptome and proteome is altered in experimental temporal lobe epilepsy

Gene and protein expressions display circadian oscillations, which can be disrupted in diseases in most body organs. Whether these oscillations occur in the healthy hippocampus and whether they are altered in epilepsy are not known. We identified more than 1200 daily oscillating transcripts in the hippocampus of control mice and 1600 in experimental epilepsy, with only one-fourth oscillating in both conditions. Comparison of gene oscillations in control and epilepsy predicted time-dependent alterations in energy metabolism, which were verified experimentally. Although aerobic glycolysis remained constant from morning to afternoon in controls, it increased in epilepsy. In contrast, oxidative phosphorylation increased in control and decreased in epilepsy. Thus, the control hippocampus shows circadian molecular remapping, which is altered in epilepsy. We suggest that the hippocampus operates in a different functioning mode in epilepsy. These alterations need to be considered when studying epilepsy mechanisms, designing drug treatments, and timing their delivery.

Resting-state functional MRI of the default mode network in epilepsy

The default mode network (DMN) is a major neuronal network that deactivates during goal-directed tasks. Recent advances in neuroimaging have shed light on its structure and function. Alterations in the DMN are increasingly recognized in a range of neurological and psychiatric conditions including epilepsy. This review first describes the current understanding of the DMN in health, normal aging, and disease as it is acquired via resting-state functional magnetic resonance imaging (MRI), before focusing on how it is affected in various types of focal and generalized epilepsy. These findings support the potential use of DMN parameters as future biomarkers in epilepsy research, diagnosis, and management.

Predictive modeling of neurobehavioral state and trait variation across development

A key goal of human neurodevelopmental research is to map neural and behavioral trajectories across both health and disease. A growing number of developmental consortia have begun to address this gap by providing open access to cross-sectional and longitudinal 'big data' repositories. However, it remains challenging to develop models that enable prediction of both within-subject and between-subject neurodevelopmental variation. Here, we present a conceptual and analytical perspective of two essential ingredients for mapping neurodevelopmental trajectories: state and trait components of variance. We focus on mapping variation across a range of neural and behavioral measurements and consider concurrent alterations of state and trait variation across development. We present a quantitative framework for combining both state- and trait-specific sources of neurobehavioral variation across development. Specifically, we argue that non-linear mixed growth models that leverage state and trait components of variance and consider environmental factors are necessary to comprehensively map brain-behavior relationships. We discuss this framework in the context of mapping language neurodevelopmental changes in early childhood, with an emphasis on measures of functional connectivity and their reliability for establishing robust neurobehavioral relationships. The ultimate goal is to statistically unravel developmental trajectories of neurobehavioral relationships that involve a combination of individual differences and age-related changes.

Dark control: The default mode network as a reinforcement learning agent

The default mode network (DMN) is believed to subserve the baseline mental activity in humans. Its higher energy consumption compared to other brain networks and its intimate coupling with conscious awareness are both pointing to an unknown overarching function. Many research streams speak in favor of an evolutionarily adaptive role in envisioning experience to anticipate the future. In the present work, we propose a process model that tries to explain how the DMN may implement continuous evaluation and prediction of the environment to guide behavior. The main purpose of DMN activity, we argue, may be described by Markov decision processes that optimize action policies via value estimates through vicarious trial and error. Our formal perspective on DMN function naturally accommodates as special cases previous interpretations based on (a) predictive coding, (b) semantic associations, and (c) a sentinel role. Moreover, this process model for the neural optimization of complex behavior in the DMN offers parsimonious explanations for recent experimental findings in animals and humans.

Plasticity and Spontaneous Activity Pulses in Disused Human Brain Circuits

To induce brain plasticity in humans, we casted the dominant upper extremity for 2 weeks and tracked changes in functional connectivity using daily 30-min scans of resting-state functional MRI (rs-fMRI). Casting caused cortical and cerebellar regions controlling the disused extremity to functionally disconnect from the rest of the somatomotor system, while internal connectivity within the disused sub-circuit was maintained. Functional disconnection was evident within 48 h, progressed throughout the cast period, and reversed after cast removal. During the cast period, large, spontaneous pulses of activity propagated through the disused somatomotor sub-circuit. The adult brain seems to rely on regular use to maintain its functional architecture. Disuse-driven spontaneous activity pulses may help preserve functionally disconnected sub-circuits.

Time of day is associated with paradoxical reductions in global signal fluctuation and functional connectivity

The brain exhibits substantial diurnal variation in physiology and function, but neuroscience studies rarely report or consider the effects of time of day. Here, we examined variation in resting-state functional MRI (fMRI) in around 900 individuals scanned between 8 AM and 10 PM on two different days. Multiple studies across animals and humans have demonstrated that the brain’s global signal (GS) amplitude (henceforth referred to as “fluctuation”) increases with decreased arousal. Thus, in accord with known circadian variation in arousal, we hypothesised that GS fluctuation would be lowest in the morning, increase in the midafternoon, and dip in the early evening. Instead, we observed a cumulative decrease in GS fluctuation as the day progressed. Although respiratory variation also decreased with time of day, control analyses suggested that this did not account for the reduction in GS fluctuation. Finally, time of day was associated with marked decreases in resting-state functional connectivity across the whole brain. The magnitude of decrease was significantly stronger than associations between functional connectivity and behaviour (e.g., fluid intelligence). These findings reveal time of day effects on global brain activity that are not easily explained by expected arousal state or physiological artefacts. We conclude by discussing potential mechanisms for the observed diurnal variation in resting brain activity and the importance of accounting for time of day in future studies.

The brain exhibits substantial diurnal variation in physiology and function. A large-scale fMRI study reveals that the brain’s global signal amplitude, typically elevated during drowsy states, unexpectedly reduces steadily as the day progresses.

Functional connectivity underpinning changes in life-space mobility in older adults with mild cognitive impairment: A 12-month prospective study

Subtle changes in mobility exist among older adults with mild cognitive impairment (MCI). Life-space mobility defines the frequency and extent of movements in the environment, and lower life-space mobility is associated with adverse health outcomes and MCI. Currently, the underlying mechanism of this association is not well understood. This study examined the functional neural correlates of life-space mobility in community-dwelling older adults with MCI. We first conducted a cross-sectional investigation of the association between resting-state default mode network (DMN) and sensori-motor network (SMN) connectivity and life-space mobility (assessed by the Life-Space Assessment (LSA)) among 60 community-dwelling older adults with MCI using aggregated data from two studies - baseline data from a randomized controlled trial (n = 20) and baseline data from a 12-month prospective study (n = 40). Using data from the 12-month prospective study (n = 35), we then examined whether baseline internetwork connectivity predicts reduced life-space mobility over 12 months. The cross-sectional analysis showed higher DMN-SMN connectivity was associated with lower LSA scores after adjusting for baseline global cognitive function and baseline age (p < 0.01). A significant reduction in LSA scores was observed in the 35 participants of the 12-month prospective study (paired sample t-test mean change = -6.53, p = 0.01). Greater baseline DMN-SMN connectivity was associated with greater reduction in life-space mobility at 12 months (p = 0.04) after adjusting for baseline age, global cognitive function, and LSA score. Our findings suggest that lower and reduced life-space mobility in older adults with MCI may be due to altered functional architecture of the brain such that normal neuro-cognitive motor behaviours may be disrupted.

Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain

A growing number of studies are focusing on methods to estimate and analyze the functional connectome of the human brain. Graph theoretical measures are commonly employed to interpret and synthesize complex network-related information. While resting state functional MRI (rsfMRI) is often employed in this context, it is known to exhibit poor reproducibility, a key factor which is commonly neglected in typical cohort studies using connectomics-related measures as biomarkers. We aimed to fill this gap by analyzing and comparing the inter- and intra-subject variability of connectivity matrices, as well as graph-theoretical measures, in a large (n = 1003) database of young healthy subjects which underwent four consecutive rsfMRI sessions. We analyzed both directed (Granger Causality and Transfer Entropy) and undirected (Pearson Correlation and Partial Correlation) time-series association measures and related global and local graph-theoretical measures. While matrix weights exhibit a higher reproducibility in undirected, as opposed to directed, methods, this difference disappears when looking at global graph metrics and, in turn, exhibits strong regional dependence in local graphs metrics. Our results warrant caution in the interpretation of connectivity studies, and serve as a benchmark for future investigations by providing quantitative estimates for the inter- and intra-subject variabilities in both directed and undirected connectomic measures.

Dissociative identity as a continuum from healthy mind to psychiatric disorders: Epistemological and neurophenomenological implications approached through hypnosis

The topic of multiple personality, redefined as Dissociative Identity Disorders (DIDs) in the DSM-5, is an intriguing and still debated disorder with a long history and deep cultural and epistemological implications, extending up to the idea of possession. Hypnosis is an appealing and valuable model to manipulate subjective experience and get an insight on both the physiology and the pathophysiology of the mind-brain functioning; it and has been closely connected with DIDs and possession since its origin in 18th century and as recently proved the capacity to yield a loss of sense of agency, mimicking delusions of alien control and spirit possession. In this study we report on five very uncommon "hypnotic virtuosos" (HVs) free from any psychiatric disorder, spontaneously undergoing the emergence of multiple identities during neutral hypnosis; this allowed us to check the relationship between their experience and fMRI data. During hypnosis the subjects underwent spontaneous non-intrusive experiences of other selves which were not recalled after the end of the session, due to post-hypnotic amnesia. The fMRI showed a significant decrease of connectivity in the Default Mode Network (DMN) especially between the posterior cingulate cortex and the medial prefrontal cortex. Our results and their contrast with the available data on fMRI in DIDs allows to draw the hypothesis of a continuum between healthy mind - where multiple identities may coexist at unconscious level and may sometimes emerge to the consciousness - and DIDs, where multiple personalities emerge as dissociated, ostensibly autonomous components yielding impaired functioning, subject's loss of control and suffering. If this is the case, it seems more reasonable to refrain from seeking for a clear-cut limit between normality (anyway a conventional, statistical concept) and pathology, and accept a grey area in between, where ostensibly odd but non-pathological experiences may occur (including so-called non-ordinary mental expressions) without calling for treatment but, rather, for being properly understood.

Biogenic amines and activity levels alter the neural energetic response to aggressive social cues in the honey bee Apis mellifera

Mitochondrial activity is highly dynamic in the healthy brain, and it can reflect both the signaling potential and the signaling history of neural circuits. Recent studies spanning invertebrates to mammals have highlighted a role for neural mitochondrial dynamics in learning and memory processes as well as behavior. In the current study, we investigate the interplay between biogenic amine signaling and neural energetics in the honey bee, Apis mellifera. In this species, aggressive behaviors are regulated by neural energetic state and biogenic amine titers, but it is unclear how these mechanisms are linked to impact behavioral expression. We show that brain mitochondrial number is highest in aggression-relevant brain regions and in individual bees that are most responsive to aggressive cues, emphasizing the importance of energetics in modulating this phenotype. We also show that the neural energetic response to alarm pheromone, an aggression inducing social cue, is activity dependent, modulated by the "fight or flight" insect neurotransmitter octopamine. Two other neuroactive compounds known to cause variation in aggression, dopamine, and serotonin, also modulate neural energetic state in aggression-relevant regions of the brain. However, the effects of these compounds on respiration at baseline and following alarm pheromone exposure are distinct, suggesting unique mechanisms underlying variation in mitochondrial respiration in these circuits. These results motivate new explanations for the ways in which biogenic amines alter sensory perception in the context of aggression. Considering neural energetics improves predictions about the regulation of complex and context-dependent behavioral phenotypes.

High-density diffuse optical tomography for imaging human brain function

This review describes the unique opportunities and challenges for noninvasive optical mapping of human brain function. Diffuse optical methods offer safe, portable, and radiation free alternatives to traditional technologies like positron emission tomography or functional magnetic resonance imaging (fMRI). Recent developments in high-density diffuse optical tomography (HD-DOT) have demonstrated capabilities for mapping human cortical brain function over an extended field of view with image quality approaching that of fMRI. In this review, we cover fundamental principles of the diffusion of near infrared light in biological tissue. We discuss the challenges involved in the HD-DOT system design and implementation that must be overcome to acquire the signal-to-noise necessary to measure and locate brain function at the depth of the cortex. We discuss strategies for validation of the sensitivity, specificity, and reliability of HD-DOT acquired maps of cortical brain function. We then provide a brief overview of some clinical applications of HD-DOT. Though diffuse optical measurements of neurophysiology have existed for several decades, tremendous opportunity remains to advance optical imaging of brain function to address a crucial niche in basic and clinical neuroscience: that of bedside and minimally constrained high fidelity imaging of brain function.

The Role of Glia in Sleep Regulation and Function

The cellular mechanisms governing the expression, regulation, and function of sleep are not entirely understood. The traditional view is that these mechanisms are neuronal. An alternative view is that glial brain cells may play important roles in these processes. Their ubiquity in the central nervous system makes them well positioned to modulate neuronal circuits that gate sleep and wake. Their ability to respond to chemical neuronal signals suggests that they form feedback loops with neurons that may globally regulate neuronal activity. Their potential role in detoxifying the brain, regulating neuronal metabolism, and promoting synaptic plasticity raises the intriguing possibility that glia mediate important functions ascribed to sleep.

Finding the baby in the bath water - evidence for task-specific changes in resting state functional connectivity evoked by training

Resting-state functional connectivity (rsFC) between brain regions has been used for studying training-related changes in brain function during the offline period of skill learning. However, it is difficult to infer whether the observed training-related changes in rsFC measured between two scans occur as a consequence of task performance, whether they are specific to a given task, or whether they reflect confounding factors such as diurnal fluctuations in brain physiology that impact the MRI signal. Here, we sought to elucidate whether task-specific changes in rsFC are dissociable from time-of-day related changes by evaluating rsFC changes after participants were provided training in either a visuospatial task or a motor sequence task compared to a non-training condition. Given the nature of the tasks, we focused on changes in rsFC of the hippocampal and sensorimotor cortices after short-term training, while controlling for the effect of time-of-day. We also related the change in rsFC of task-relevant brain regions to performance improvement in each task. Our results demonstrate that, even in the absence of any experimental manipulation, significant changes in rsFC can be detected between two resting state functional MRI scans performed just a few hours apart, suggesting time-of-day has a significant impact on rsFC. However, by estimating the magnitude of the time-of-day effect, our findings also suggest that task-specific changes in rsFC can be dissociated from the changes attributed to time-of-day. Taken together, our results show that rsFC can provide insights about training-related changes in brain function during the offline period of skill learning. However, demonstrating the specificity of the changes in rsFC to a given task requires a rigorous experimental design that includes multiple active and passive control conditions, and robust behavioral measures.

Phosphocreatine Levels in the Left Thalamus Decline during Wakefulness and Increase after a Nap

Scientists have hypothesized that the availability of phosphocreatine (PCr) and its ratio to inorganic phosphate (Pi) in cerebral tissue form a substrate of wakefulness. It follows then, according to this hypothesis, that the exhaustion of PCr and the decline in the ratio of PCr to Pi form a substrate of fatigue. We used 31P-magnetic resonance spectroscopy (31P-MRS) to investigate quantitative levels of PCr, the γ-signal of ATP, and Pi in 30 healthy humans (18 female) in the morning, in the afternoon, and while napping (n = 15) versus awake controls (n = 10). Levels of PCr (2.40 mM at 9 A.M.) decreased by 7.0 ± 0.8% (p = 7.1 × 10-6, t = -5.5) in the left thalamus between 9 A.M. and 5 P.M. Inversely, Pi (0.74 mM at 9 A.M.) increased by 17.1 ± 5% (p = 0.005, t = 3.1) and pH levels dropped by 0.14 ± 0.07 (p = 0.002; t = 3.6). Following a 20 min nap after 5 P.M., local PCr, Pi, and pH were restored to morning levels. We did not find respective significant changes in the contralateral thalamus or in other investigated brain regions. Left hemispheric PCr was signficantly lower than right hemispheric PCr only at 5 P.M. in the thalamus and at all conditions in the temporal region. Thus, cerebral daytime-related and sleep-related molecular changes are accessible in vivo Prominent changes were identified in the thalamus. This region is heavily relied on for a series of energy-consuming tasks, such as the relay of sensory information to the cortex. Furthermore, our data confirm that lateralization of brain function is regionally dynamic and includes PCr.SIGNIFICANCE STATEMENT The metabolites phosphocreatine (PCr) and inorganic phosphate (Pi) are assumed to inversely reflect the cellular energy load. This study detected a diurnal decrease of intracellular PCr and a nap-associated reincrease in the left thalamus. Pi behaved inversely. This outcome corroborates the role of the thalamus as a region of high energy consumption in agreement with its function as a gateway that relays and modulates information flow. Conversely to the dynamic lateralization of thalamic PCr, a constantly significant lateralization was observed in other regions. Increasing fatigue over the course of the day may also be a matter of cerebral energy supply. Comparatively fast restoration of that supply may be part of the biological basis for the recreational value of "power napping."

Cerebral blood flow changes after a day of wake, sleep, and sleep deprivation

Elucidating the neurobiological effects of sleep and wake is an important goal of the neurosciences. Whether and how human cerebral blood flow (CBF) changes during the sleep-wake cycle remain to be clarified. Based on the synaptic homeostasis hypothesis of sleep and wake, we hypothesized that a day of wake and a night of sleep deprivation would be associated with gray matter resting CBF (rCBF) increases and that sleep would be associated with rCBF decreases. Thirty-eight healthy adult males (age 22.1 ± 2.5 years) underwent arterial spin labeling perfusion magnetic resonance imaging 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 = 19) or a night of sleep (n = 19). All analyses were adjusted for hematocrit and head motion. rCBF increased from morning to evening and decreased after a night of sleep. These effects were most prominent in bilateral hippocampus, amygdala, thalamus, and in the occipital and sensorimotor cortices. Group × time interaction analyses for evening versus next morning revealed significant interaction in bilateral lateral and medial occipital cortices and in bilateral insula, driven by rCBF increases in the sleep deprived individuals and decreases in the sleepers, respectively. Furthermore, group × time interaction analyses for first morning versus next morning showed significant effects in medial and lateral occipital cortices, in anterior cingulate gyrus, and in the insula, in both hemispheres. These effects were mainly driven by CBF increases from TP1 to TP3 in the sleep deprived individuals. There were no associations between the rCBF changes and sleep characteristics, vigilant attention, or subjective sleepiness that remained significant after adjustments for multiple analyses. Altogether, these results encourage future studies to clarify mechanisms underlying sleep-related rCBF changes.

Dissociated resting-state functional networks between the dream recall frequency and REM sleep percentage

Rapid eye movement (REM) sleep has been frequently associated with dreaming. However, mounting evidence obtained from behavioral, pharmacological, and brain imaging studies suggests that REM sleep is not indicative of the dream report and may originate from diverse neural substrates in brain functionality. The aim of the current study was to investigate the functional systems associated with inter-individual differences in dream recall and REM sleep through assessments of the resting-state functional connectivity. We collected resting-state functional magnetic resonance imaging (fMRI) data for functional connectivity evaluations from 43 healthy adult volunteers (23 men) before and after sleep. For assessment of the dream recall frequency, a 2-week sleep diary was maintained by all volunteers. In addition, whole-night polysomnography was performed for measuring the REM sleep percentage. Voxel-wise correlation analyses of 12 functional connectivity networks of interest with the dream recall frequency and REM sleep percentage were conducted using general linear model analysis. Both the dream recall frequency and REM sleep percentage showed negative associations with multiple brain functional networks. However, the dream recall frequency was mainly related to functional connectivity within the lateral visual network and thalamus, whereas the REM sleep percentage was mainly associated with connectivity within the frontoparietal networks and cerebellum. In addition, the dream recall frequency showed stronger coupling with the lateral visual network connectivity at night, whereas the coupling between the REM sleep percentage and cerebellum was higher in the morning. This indicated a significant time of day effect. Our results provide neuroimaging evidence that the functional system associated with the dream recall frequency is different from that associated with the REM sleep percentage.

Neuroanatomy of conversion disorder: towards a network approach

The pathophysiology of conversion disorder is not well understood, although studies using functional brain imaging in patients with motor and sensory symptoms are progressively increasing. We conducted a systematic review of the literature with the aim of summarising the available data on the neuroanatomical features of this disorder. We also propose a general model of the neurobiological disturbance in motor conversion disorder. We systematically searched articles in Medline using the Medical Subject Headings terms ‘(conversion disorder or hysterical motor disorder) and (neuropsychology or cognition) or (functional magnetic resonance imaging or positron emission tomography or neuroimaging) or (genetics or polymorphisms or epigenetics) or (biomarkers or biology)’, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Two authors independently reviewed the retrieved records and abstracts, assessed the exhaustiveness of data abstraction, and confirmed the quality rating. Analysis of the available literature data shows that multiple specialised brain networks (self-agency, action monitoring, salience system, and memory suppression) influence action selection and modulate supplementary motor area activation. Some findings suggest that conceptualisation of movement and motor intention is preserved in patients with limb weakness. More studies are needed to fully understand the brain alterations in conversion disorders and pave the way for the development of effective therapeutic strategies.