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The sleep-wake cycle is a master regulator of metabolic and neuronal activity and when altered, can have profound effects on metabolic health and disease. Although consideration is given to how fluctuations in blood glucose affect peripheral physiology and metabolism, less is known about how glucose dysregulation impacts the intrinsic cooperation between brain metabolism and neuronal activity to regulate sleep. To understand the effect of peripheral hyper- and hypoglycemia on these relationships, we paired biosensors measuring hippocampal interstitial fluid (ISF) levels of glucose and lactate with cortical EEG/EMG recordings to produce simultaneous subsecond recordings of ISF glucose, lactate, and sleep-wake states. First, we describe a conserved temporal relationships between ISF glucose and lactate based on their intrinsic oscillations, diurnal rhythms, and sleep/wake cycles. ISF glucose and lactate oscillations are largely anti-correlated but the frequency of their oscillations dictate their power, coherence, and phase. While ISF glucose and lactate both have diurnal fluctuations, only ISF lactate is consistently elevated during wake. During wake, fluctuations in ISF lactate are associated with changes in the EEG power spectrum, suggesting wake-related activity is more closely associated with ISF lactate. Modulation of glucose availability via both hyper- or hypoglycemia disrupts the relationship between peripheral metabolism, brain metabolism, and sleep. Hyper- and hypo-glycemia increase ISF lactate, decrease NREM, and alter EEG spectral activity, again demonstrating ISF lactate drives wake-associated behaviors and disrupts sleep. Taken together, these studies demonstrate that peripheral glucose homeostasis is necessary for maintaining the relationships between brain metabolism, neuronal activity, and sleep-wake patterns and deviations in blood glucose levels are sufficient to disrupt the metabolic signature of sleep-wake states, putting the brain at risk in diseases like type-2-diabetes and Alzheimer’s disease.Graphical Abstract. Peripheral glucose homeostasis directly modifies sleep/wake patterns

The human brain is organized into large-scale networks identifiable using resting-state functional connectivity (RSFC). These functional networks correspond with broad cognitive domains; for example, the Default-mode network (DMN) is engaged during internally oriented cognition. However, functional networks may contain hierarchical substructures corresponding with more specific cognitive functions. Here, we used individual-specific precision RSFC to test whether network substructures could be identified in 10 healthy human brains. Across all subjects and networks, individualized network subdivisions were more valid-more internally homogeneous and better matching spatial patterns of task activation-than canonical networks. These measures of validity were maximized at a hierarchical scale that contained ∼83 subnetworks across the brain. At this scale, nine DMN subnetworks exhibited topographical similarity across subjects, suggesting that this approach identifies homologous neurobiological circuits across individuals. Some DMN subnetworks matched known features of brain organization corresponding with cognitive functions. Other subnetworks represented separate streams by which DMN couples with other canonical large-scale networks, including language and control networks. Together, this work provides a detailed organizational framework for studying the DMN in individual humans.

Electrophysiological recordings have established that GABAergic interneurons regulate excitability, plasticity, and computational function within local neural circuits. Importantly, GABAergic inhibition is focally disrupted around sites of brain injury. However, it remains unclear whether focal imbalances in inhibition/excitation lead to widespread changes in brain activity. Here, we test the hypothesis that focal perturbations in excitability disrupt large-scale brain network dynamics. We used viral chemogenetics in mice to reversibly manipulate parvalbumin interneuron (PV-IN) activity levels in whisker barrel somatosensory cortex. We then assessed how this imbalance affects cortical network activity in awake mice using wide-field optical neuroimaging of pyramidal neuron GCaMP dynamics as well as local field potential recordings. We report 1) that local changes in excitability can cause remote, network-wide effects, 2) that these effects propagate differentially through intra- and interhemispheric connections, and 3) that chemogenetic constructs can induce plasticity in cortical excitability and functional connectivity. These findings may help to explain how focal activity changes following injury lead to widespread network dysfunction.

Traveling waves spatiotemporally organize brain-wide activity in synchrony with ongoing arousal fluctuations., We propose and empirically support a parsimonious account of intrinsic, brain-wide spatiotemporal organization arising from traveling waves linked to arousal. We hypothesize that these waves are the predominant physiological process reflected in spontaneous functional magnetic resonance imaging (fMRI) signal fluctuations. The correlation structure (“functional connectivity”) of these fluctuations recapitulates the large-scale functional organization of the brain. However, a unifying physiological account of this structure has so far been lacking. Here, using fMRI in humans, we show that ongoing arousal fluctuations are associated with global waves of activity that slowly propagate in parallel throughout the neocortex, thalamus, striatum, and cerebellum. We show that these waves can parsimoniously account for many features of spontaneous fMRI signal fluctuations, including topographically organized functional connectivity. Last, we demonstrate similar, cortex-wide propagation of neural activity measured with electrocorticography in macaques. These findings suggest that traveling waves spatiotemporally pattern brain-wide excitability in relation to arousal.

Accumulating evidence indicates that resting-state functional magnetic resonance imaging (rsfMRI) signals correspond to propagating electrophysiological infra-slow activity (

Significance Slow waves are the predominant feature of brain activity during sleep and anesthesia. Slow waves are associated with plasticity, memory consolidation, and other brain functions. However, much remains unknown about the brain circuits that coordinate slow wave propagation. Here, we demonstrate that somatosensory stimulation evokes bilateral activation of primary somatosensory cortices (S1). Under anesthesia, S1 activation is followed by a global, front-to-back cortical slow wave. Using a focal lesion model, we show that evoked global slow waves depend on bilateral S1 activation, whereas spontaneous slow wave initiation does not depend on S1. These results demonstrate the existence of mechanisms by which focal injury may disrupt brain network dynamics., Slow waves (SWs) are globally propagating, low-frequency (0.5- to 4-Hz) oscillations that are prominent during sleep and anesthesia. SWs are essential to neural plasticity and memory. However, much remains unknown about the mechanisms coordinating SW propagation at the macroscale. To assess SWs in the context of macroscale networks, we recorded cortical activity in awake and ketamine/xylazine-anesthetized mice using widefield optical imaging with fluorescent calcium indicator GCaMP6f. We demonstrate that unilateral somatosensory stimulation evokes bilateral waves that travel across the cortex with state-dependent trajectories. Under anesthesia, we observe that rhythmic stimuli elicit globally resonant, front-to-back propagating SWs. Finally, photothrombotic lesions of S1 show that somatosensory-evoked global SWs depend on bilateral recruitment of homotopic primary somatosensory cortices. Specifically, unilateral lesions of S1 disrupt somatosensory-evoked global SW initiation from either hemisphere, while spontaneous SWs are largely unchanged. These results show that evoked SWs may be triggered by bilateral activation of specific, homotopically connected cortical networks.

Multimodal evidence suggests that brain regions accumulate information over timescales that vary according to anatomical hierarchy. Thus, these experimentally defined "temporal receptive windows" are longest in cortical regions that are distant from sensory input. Interestingly, spontaneous activity in these regions also plays out over relatively slow timescales (i.e., exhibits slower temporal autocorrelation decay). These findings raise the possibility that hierarchical timescales represent an intrinsic organizing principle of brain function. Here, using resting-state functional MRI, we show that the timescale of ongoing dynamics follows hierarchical spatial gradients throughout human cerebral cortex. These intrinsic timescale gradients give rise to systematic frequency differences among large-scale cortical networks and predict individual-specific features of functional connectivity. Whole-brain coverage permitted us to further investigate the large-scale organization of subcortical dynamics. We show that cortical timescale gradients are topographically mirrored in striatum, thalamus, and cerebellum. Finally, timescales in the hippocampus followed a posterior-to-anterior gradient, corresponding to the longitudinal axis of increasing representational scale. Thus, hierarchical dynamics emerge as a global organizing principle of mammalian brains.

The amygdala is central to the pathophysiology of many psychiatric illnesses. An imprecise understanding of how the amygdala fits into the larger network organization of the human brain, however, limits our ability to create models of dysfunction in individual patients to guide personalized treatment. Therefore, we investigated the position of the amygdala and its functional subdivisions within the network organization of the brain in 10 highly sampled individuals (5 h of fMRI data per person). We characterized three functional subdivisions within the amygdala of each individual. We discovered that one subdivision is preferentially correlated with the default mode network; a second is preferentially correlated with the dorsal attention and fronto-parietal networks; and third subdivision does not have any networks to which it is preferentially correlated relative to the other two subdivisions. All three subdivisions are positively correlated with ventral attention and somatomotor networks and negatively correlated with salience and cingulo-opercular networks. These observations were replicated in an independent group dataset of 120 individuals. We also found substantial across-subject variation in the distribution and magnitude of amygdala functional connectivity with the cerebral cortex that related to individual differences in the stereotactic locations both of amygdala subdivisions and of cortical functional brain networks. Finally, using lag analyses, we found consistent temporal ordering of fMRI signals in the cortex relative to amygdala subdivisions. Altogether, this work provides a detailed framework of amygdala–cortical interactions that can be used as a foundation for models relating aberrations in amygdala connectivity to psychiatric symptoms in individual patients.

An important aspect of network-based analysis is robust node definition. This issue is critical for functional brain network analyses, as poor node choice can lead to spurious findings and misleading inferences about functional brain organization. Two sets of functional brain nodes from our group are well represented in the literature: (1) 264 volumetric regions of interest (ROIs) reported in Power et al., 2011 and (2) 333 surface parcels reported in Gordon et al., 2016. However, subcortical and cerebellar structures are either incompletely captured or missing from these ROI sets. Therefore, properties of functional network organization involving the subcortex and cerebellum may be underappreciated thus far. Here, we apply a winner-take-all partitioning method to resting-state fMRI data and careful consideration of anatomy to generate novel functionally-constrained ROIs in the thalamus, basal ganglia, amygdala, hippocampus, and cerebellum. We validate these ROIs in three datasets via several anatomical and functional criteria, including known anatomical divisions and functions, as well as agreement with existing literature. Further, we demonstrate that combining these ROIs with established cortical ROIs recapitulates and extends previously described functional network organization. This new set of ROIs is made publicly available for general use, including a full list of MNI coordinates and functional network labels.

Electrophysiological recordings have established that GABAergic interneurons regulate excitability, plasticity, and computational function within local neural circuits. Importantly, GABAergic inhibition is focally disrupted around sites of brain injury. However, it remains unclear whether focal imbalances in inhibition/excitation lead to widespread changes in brain activity. Here, we test the hypothesis that focal perturbations in excitability disrupt large-scale brain network dynamics. We used viral chemogenetics in mice to reversibly manipulate parvalbumin interneuron (PV-IN) activity levels in whisker barrel somatosensory cortex. We then assessed how this imbalance affects cortical network activity in awake mice using wide-field optical neuroimaging of pyramidal neuron GCaMP dynamics as well as local field potential recordings. We report 1) that local changes in excitability can cause remote, network-wide effects, 2) that these effects propagate differentially through intra- and interhemispheric connections, and 3) that chemogenetic constructs can induce plasticity in cortical excitability and functional connectivity. These findings may help to explain how focal activity changes following injury lead to widespread network dysfunction.

Functional MRI (fMRI) is well-established for the study of brain function in healthy populations, although its clinical application has proven more challenging. Specifically, cerebrovascular reactivity (CVR), which allows the assessment of the vascular response that serves as the basis for fMRI, has been shown to be reduced in healthy aging as well as in a range of diseases, including chronic stroke. However, the timing of when this occurs relative to the stroke event is unclear. We used a breath-hold fMRI task to evaluate CVR across gray matter in a group of acute stroke patients (, Highlights • Breath-holding can be used to assess the validity of fMRI in stroke patients. • Vascular reactivity, estimated by breath-hold fMRI, was greatest in young controls. • Acute stroke patients and age-matched controls had similar vascular reactivity. • Modeling the breath-hold response on an individual basis can improve results.

Summary 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.

Summary The cerebellum contains the majority of neurons in the human brain and is unique for its uniform cytoarchitecture, absence of aerobic glycolysis, and role in adaptive plasticity. Despite anatomical and physiological differences between the cerebellum and cerebral cortex, group-average functional connectivity studies have identified networks related to specific functions in both structures. Recently, precision functional mapping of individuals revealed that functional networks in the cerebral cortex exhibit measurable individual specificity. Using the highly sampled Midnight Scan Club (MSC) dataset, we found the cerebellum contains reliable, individual-specific network organization that is significantly more variable than the cerebral cortex. The frontoparietal network, thought to support adaptive control, was the only network overrepresented in the cerebellum compared to the cerebral cortex (2.3-fold). Temporally, all cerebellar resting state signals lagged behind the cerebral cortex (125–380 ms), supporting the hypothesis that the cerebellum engages in a domain-general function in the adaptive control of all cortical processes.

The cerebellum contains the majority of neurons in the human brain and is unique for its uniform cytoarchitecture, absence of aerobic glycolysis, and role in adaptive plasticity. Despite anatomical and physiological differences between the cerebellum and cerebral cortex, group-average functional connectivity studies have identified networks related to specific functions in both structures. Recently, precision functional mapping of individuals revealed that functional networks in the cerebral cortex exhibit individual-specific topography. Using the highly-sampled Midnight Scan Club (MSC) dataset, we found the cerebellum contains reliable, individual-specific network organization that is significantly more variable than the cerebral cortex. The frontoparietal network, thought to support adaptive control, was the only network overrepresented in the cerebellum compared to the cerebral cortex (2.3-fold). Temporally, all cerebellar resting state signals lagged behind the cerebral cortex (125-380ms), most prominently within association networks. Our findings suggest a domain-general cerebellar function may be ultimate correction of all cortical motor and cognitive processes.

Introduction: Despite its prevalence in stroke research, the vascular dependence of functional MRI (fMRI) makes it susceptible to changes in factors such as vascular reactivity that may occur over the course of stroke recovery, potentially confounding longitudinal findings. Scaling fMRI data with respect to vascular properties may account for some of the high variability often observed in patterns of motor task activation throughout recovery. Hypothesis: We hypothesized that scaling fMRI data by the amplitude of resting-state fluctuations (RSFA), an estimate of vascular reactivity, would reduce intersubject variability of motor task activation in both patients and similarly-aged controls while minimizing between-group differences and revealing a more consistent pattern of changes in activation associated with stroke recovery. Methods: 24 ischemic stroke patients (ages 44-84 years, mean = 64) were scanned at early (2-12 days, mean = 5) and late (mean = 11 months) stages after onset. 20 healthy controls (ages 47-74 years, mean = 59) were also scanned, 11 of whom were scanned again after ~6 months. Subjects performed two 20-second-block finger-tapping tasks, one with each hand, and a 10-minute resting-state fMRI scan, from which the scaling factor (RSFA) was computed. Percent signal change and activation volume before and after scaling were measured across several bilateral motor areas and compared between groups and within each group longitudinally. Results: Scaling with RSFA significantly reduced intersubject variability of intensity and extent of activation in both groups while mitigating between-group differences in activation in multiple motor areas. Further, scaling revealed a significant reduction of activation across motor regions in stroke patients over time that was not apparent without scaling. This pattern more closely resembled that of controls, for which it was evident both before and after scaling. Conclusions: Our findings point to a role for fMRI calibration in longitudinal studies of plasticity and recovery after stroke, and suggest that the large variability often observed in activation patterns associated with recovery may in part be vascular in origin.

Functional magnetic resonance imaging (fMRI) is used clinically to map visual cortex prior to brain surgery or other invasive treatments in order to achieve an optimal balance between therapeutic effect and the avoidance of post-operative vision deficits. Clinically optimized stimuli, behavioral task, analysis and displays permit identification of cortical subregions supporting high acuity central vision that is critical for reading and other essential visual functions. A novel data display permits instant appreciation of the functional relationship between the pattern of fMRI brain activation and the pattern of vision loss and preservation within the patient’s field of view. Neurovascular uncoupling and its detection in visual cortex are key issues for the interpretation of fMRI results in patients with existing brain pathology. Emerging techniques such as resting state fMRI may facilitate the use of fMRI-based vision mapping with a broader range of patients.