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The brain is always intrinsically active, using energy at high rates while cycling through global functional modes. Awake brain modes are tied to corresponding behavioural states. During goal-directed behaviour, the brain enters an action-mode of function. In the action-mode, arousal is heightened, attention is focused externally and action plans are created, converted to goal-directed movements and continuously updated on the basis of relevant feedback, such as pain. Here, we synthesize classical and recent human and animal evidence that the action-mode of the brain is created and maintained by an action-mode network (AMN), which we had previously identified and named the cingulo-opercular network on the basis of its anatomy. We discuss how rather than continuing to name this network anatomically, annotating it functionally as controlling the action-mode of the brain increases its distinctiveness from spatially adjacent networks and accounts for the large variety of the associated functions of an AMN, such as increasing arousal, processing of instructional cues, task general initiation transients, sustained goal maintenance, action planning, sympathetic drive for controlling physiology and internal organs (connectivity to adrenal medulla), and action-relevant bottom-up signals such as physical pain, errors and viscerosensation. In the functional mode continuum of the awake brain, the AMN-generated action-mode sits opposite the default-mode for self-referential, emotional and memory processing, with the default-mode network and AMN counterbalancing each other as yin and yang., Competing Interests: Competing interests: N.U.F.D. has a financial interest in Turing Medical Inc. and may benefit financially if the company is successful in marketing FIRMM motion monitoring software products. N.U.F.D. and E.M.G. may receive royalty income based on technology developed at Washington University School of Medicine and Oregon Health and Sciences University and licensed to Turing Medical Inc. N.U.F.D. is a co-founder of Turing Medical Inc. These potential conflicts of interest have been reviewed and are managed by Washington University School of Medicine. The other authors declare no competing interests., (© 2025. Springer Nature Limited.)

Childhood exposure to social disadvantage is a major risk factor for psychiatric disorders and poor developmental, educational, and occupational outcomes, presumably because adverse exposures alter the neurodevelopmental processes that contribute to risk trajectories. Yet, given the limited social mobility in the United States and other countries, childhood social disadvantage is frequently preceded by maternal social disadvantage during pregnancy, potentially altering fetal brain development during a period of high neuroplasticity through hormonal, microbiome, epigenetic, and immune factors that cross the placenta and fetal blood-brain barrier. The current study examines prenatal social disadvantage to determine whether these exposures in utero are associated with alterations in functional brain networks as early as birth. As part of the Early Life Adversity and Biological Embedding study, mothers were recruited during pregnancy, prenatal social disadvantage was assessed across trimesters, and their healthy, full-term offspring were imaged using resting-state functional magnetic resonance imaging during the first weeks of life. Multivariate machine learning methods revealed that neonatal functional connectivity (FC) varied as a function of prenatal exposure to social disadvantage (n = 261, R = 0.43, R 2 = 0.18), with validation in an independent sample. Alterations in FC associated with prenatal social disadvantage occurred brain-wide and were most pronounced in association networks (fronto-parietal, ventral attention, dorsal attention) and the somatomotor network. Amygdala FC was altered at birth, with a pattern shared across subcortical structures. These findings provide critical insights into how early in development functional networks begin to diverge in the context of social disadvantage and elucidate the functional networks that are most impacted., Competing Interests: Competing interests statement:M.E.R. and D.S. (one of the reviewers) are on a commentary in 2023 as part of two large consortium.

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 trials 1-4 . In animal models, psilocybin induces neuroplasticity in cortex and hippocampus 5-8 . 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., (© 2024. The Author(s).)

Background: Currently, brain tissue atrophy serves as an in vivo MRI biomarker of neurodegeneration in Alzheimer's disease (AD). However, postmortem histopathological studies show that neuronal loss in AD exceeds volumetric loss of tissue and that loss of memory in AD begins when neurons and synapses are lost. Therefore, in vivo detection of neuronal loss prior to detectable atrophy in MRI is essential for early AD diagnosis., Objective: To apply a recently developed quantitative Gradient Recalled Echo (qGRE) MRI technique for in vivo evaluation of neuronal loss in human hippocampus., Methods: Seventy participants were recruited from the Knight Alzheimer Disease Research Center, representing three groups: Healthy controls [Clinical Dementia Rating® (CDR®) = 0, amyloid β (Aβ)-negative, n = 34]; Preclinical AD (CDR = 0, Aβ-positive, n = 19); and mild AD (CDR = 0.5 or 1, Aβ-positive, n = 17)., Results: In hippocampal tissue, qGRE identified two types of regions: one, practically devoid of neurons, we designate as "Dark Matter", and the other, with relatively preserved neurons, "Viable Tissue". Data showed a greater loss of neurons than defined by atrophy in the mild AD group compared with the healthy control group; neuronal loss ranged between 31% and 43%, while volume loss ranged only between 10% and 19%. The concept of Dark Matter was confirmed with histopathological study of one participant who underwent in vivo qGRE 14 months prior to expiration., Conclusion: In vivo qGRE method identifies neuronal loss that is associated with impaired AD-related cognition but is not recognized by MRI measurements of tissue atrophy, therefore providing new biomarkers for early AD detection.

In Alzheimer's disease, brain amyloid deposition has a distinct topography that correlates with aerobic glycolysis (AG), that is, the use of glucose beyond that predicted by oxygen consumption. The causes for this relationship remain unclear but might provide crucialinsight into how amyloid deposition begins. Here we develop methods to study the earliest topography of amyloid deposition based on amyloid imaging and investigate its spatiotemporal evolution with respect to the topography of AG in adults. We find that the spatiotemporal dynamics of amyloid deposition are largely explained by 1 factor, defined here as the amyloid topography dissimilarity index (ATDI). ATDI is bimodal, more highly dynamic during early amyloid accumulation, and predicts which individuals will cross a conservative quantitative threshold at least 3-5 years in advance. Using ATDI, we demonstrate that subthreshold amyloid accumulates primarily in regions that have high AG during early adulthood. Our findings suggest that early on-target subthreshold amyloid deposition mirrors its later regional pattern, which best corresponds to the topography of young adult brain AG., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Patterns of low frequency brain-wide activity have drawn attention across multiple disciplines in neuroscience. Brain-wide activity patterns are often described through correlations, which capture concurrent increases and decreases in neural activity. More recently, several groups have described reproducible temporal sequences across the brain, illustrating precise long-distance control over the timing of low frequency activity. Features of correlation and temporal organization both point to a systems-level structure of brain activity consisting of large-scale networks and their mutual interactions. Yet a unified view for understanding large networks and their interactions remains elusive. Here, we propose a framework for computing probabilistic flow in brain-wide activity. We demonstrate how flow probabilities are modulated across rest and task states and show that the probabilistic perspective captures both intra- and inter-network dynamics. Finally, we suggest that a probabilistic framework may prove fruitful in characterizing low frequency brain-wide activity in health and disease., (Copyright © 2020. Published by Elsevier Inc.)

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., Competing Interests: The authors declare no competing interest.

Spontaneous infra-slow (<0.1 Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals are temporally correlated within large-scale functional brain networks, motivating their use for mapping systems-level brain organization. However, recent electrophysiological and hemodynamic evidence suggest state-dependent propagation of infra-slow fluctuations, implying a functional role for ongoing infra-slow activity. Crucially, the study of infra-slow temporal lag structure has thus far been limited to large groups, as analyzing propagation delays requires extensive data averaging to overcome sampling variability. Here, we use resting-state fMRI data from 11 extensively-sampled individuals to characterize lag structure at the individual level. In addition to stable individual-specific features, we find spatiotemporal topographies in each subject similar to the group average. Notably, we find a set of early regions that are common to all individuals, are preferentially positioned proximal to multiple functional networks, and overlap with brain regions known to respond to diverse behavioral tasks-altogether consistent with a hypothesized ability to broadly influence cortical excitability. Our findings suggest that, like correlation structure, temporal lag structure is a fundamental organizational property of resting-state infra-slow activity., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Glucose and oxygen metabolism are tightly coupled in the human brain, with the preponderance of the brain's glucose supply used to generate ATP via oxidative phosphorylation. A fraction of glucose is consumed outside of oxidative phosphorylation despite the presence of sufficient oxygen to do so. We refer to this process as aerobic glycolysis. A recent positron emission tomography study reported that aerobic glycolysis is uniform within gray matter. Here, we analyze the same data and demonstrate robust regional differences in aerobic glycolysis within gray matter, a finding consistent with previously published data.

Accumulating evidence indicates that resting-state functional magnetic resonance imaging (rsfMRI) signals correspond to propagating electrophysiological infra-slow activity (<0.1 Hz). Thus, pairwise correlations (zero-lag functional connectivity (FC)) and temporal delays among regional rsfMRI signals provide useful, complementary descriptions of spatiotemporal structure in infra-slow activity. However, the slow nature of fMRI signals implies that practical scan durations cannot provide sufficient independent temporal samples to stabilize either of these measures. Here, we examine factors affecting sampling variability in both time delay estimation (TDE) and FC. Although both TDE and FC accuracy are highly sensitive to data quantity, we use surrogate fMRI time series to study how the former is additionally related to the magnitude of a given pairwise correlation and, to a lesser extent, the temporal sampling rate. These contingencies are further explored in real data comprising 30-min rsfMRI scans, where sampling error (i.e., limited accuracy owing to insufficient data quantity) emerges as a significant but underappreciated challenge to FC and, even more so, to TDE. Exclusion of high-motion epochs exacerbates sampling error; thus, both sides of the bias-variance (or data quality-quantity) tradeoff associated with data exclusion should be considered when analyzing rsfMRI data. Finally, we present strategies for TDE in motion-corrupted data, for characterizing sampling error in TDE and FC, and for mitigating the influence of sampling error on lag-based analyses., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Sex differences influence brain morphology and physiology during both development and aging. Here we apply a machine learning algorithm to a multiparametric brain PET imaging dataset acquired in a cohort of 20- to 82-year-old, cognitively normal adults ( n = 205) to define their metabolic brain age. We find that throughout the adult life span the female brain has a persistently lower metabolic brain age-relative to their chronological age-compared with the male brain. The persistence of relatively younger metabolic brain age in females throughout adulthood suggests that development might in part influence sex differences in brain aging. Our results also demonstrate that trajectories of natural brain aging vary significantly among individuals and provide a method to measure this., Competing Interests: The authors declare no conflict of interest., (Copyright © 2019 the Author(s). Published by PNAS.)

fMRI revolutionized neuroscience by allowing in vivo real-time detection of human brain activity. While the nature of the fMRI signal is understood as resulting from variations in the MRI signal due to brain-activity-induced changes in the blood oxygenation level (BOLD effect), these variations constitute a very minor part of a baseline MRI signal. Hence, the fundamental (and not addressed) questions are how underlying brain cellular composition defines this baseline MRI signal and how a baseline MRI signal relates to fMRI. Herein we investigate these questions by using a multimodality approach that includes quantitative gradient recalled echo (qGRE), volumetric and functional connectivity MRI, and gene expression data from the Allen Human Brain Atlas. We demonstrate that in vivo measurement of the major baseline component of a GRE signal decay rate parameter (R2t*) provides a unique genetic perspective into the cellular constituents of the human cortex and serves as a previously unidentified link between cortical tissue composition and fMRI signal. Data show that areas of the brain cortex characterized by higher R2t* have high neuronal density and have stronger functional connections to other brain areas. Interestingly, these areas have a relatively smaller concentration of synapses and glial cells, suggesting that myelinated cortical axons are likely key cortical structures that contribute to functional connectivity. Given these associations, R2t* is expected to be a useful signal in assessing microstructural changes in the human brain during development and aging in health and disease., Competing Interests: The authors declare no conflict of interest., (Copyright © 2018 the Author(s). Published by PNAS.)

Glucose is the predominant fuel supporting brain function. If the brain's entire glucose supply is consumed by oxidative phosphorylation, the molar ratio of oxygen to glucose consumption (OGI) is equal to 6. An OGI of less than 6 is evidence of non-oxidative glucose metabolism. Several studies have reported that the OGI in the resting human brain is less than 6.0, but the exact value remains uncertain. Additionally, it is not clear if lactate efflux accounts for the difference between OGI and its theoretical value of 6.0. To address these issues, we conducted a meta-analysis of OGI and oxygen-to-carbohydrate (glucose + 0.5*lactate; OCI) ratios in healthy young and middle-aged adults. We identified 47 studies that measured at least one of these ratios using arterio-venous differences of glucose, lactate, and oxygen. Using a Bayesian random effects model, the population median OGI was 5.46 95% credible interval (5.25-5.66), indicating that approximately 9% of the brain's glucose metabolism is non-oxidative. The population median OCI was 5.60 (5.36-5.84), suggesting that lactate efflux does not account for all non-oxidative glucose consumption. Significant heterogeneity across studies was observed, which implies that further work is needed to characterize how demographic and methodological factors influence measured cerebral metabolic ratios., Competing Interests: The authors have declared that no competing interests exist.

Appraising success in meeting the world's nutritional needs has largely focused on infant mortality and anthropometric measurements with an emphasis on the first 1,000 days (conception to approximately age 2 years). This ignores the unique nutritional needs of the human brain. Although the intrauterine environment and the early postnatal years are important, equally critical periods follow during which the brain's intricate wiring is established for a lifetime of experience-driven remodeling. At the peak of this process during childhood, the human brain may account for 50% of the body's basal nutritional requirement. Thus, the consequences of proper nutritional management of the brain play out over a lifetime. Our motivation in preparing this review was to move the human brain into a more central position in the planning of nutritional programs. Here we review the macro- and micronutrient requirements of the human brain and how they are delivered, from conception to adulthood.

Research of the human brain metabolism in vivo has largely focused on total glucose use (via fluorodeoxyglucose positron emission tomography) and, until recently, did not examine the use of glucose outside oxidative phosphorylation, which is known as aerobic glycolysis (AG). AG supports important functions including biosynthesis and neuroprotection but decreases dramatically with aging. This multitracer positron emission tomography study evaluated the relationship between AG, total glucose use (CMRGlc), oxygen metabolism (CMRO 2 ), tau, and amyloid deposition in 42 individuals, including those at preclinical and symptomatic stages of Alzheimer's disease. Our findings demonstrate that in individuals with amyloid burden, lower AG is associated with higher tau deposition. No such correlation was observed for CMRGlc or CMRO 2 . We suggest that aging-related loss of AG leading to decreased synaptic plasticity and neuroprotection may accelerate tauopathy in individuals with amyloid burden. Longitudinal AG and Alzheimer's disease pathology studies are needed to verify causality., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Adequate nutrition is critical for human brain development, which depends particularly upon glucose. The adult human brain accounts for 20% to 25% of total body resting glucose consumption, and studies indicate that the developing brain requires an even greater percentage of glucose. Here we critically review the currently available data on glucose requirements for early childhood brain development. Implications of these findings are then discussed in the context of childhood malnutrition and future areas of investigation.

Systems-level organization in spontaneous infra-slow (<0.1Hz) brain activity, measured using blood oxygen signals in fMRI and optical imaging, has become a major theme in the study of neural function in both humans and animal models. Yet the neurophysiological basis of infra-slow activity (ISA) remains unresolved. In particular, is ISA a distinct physiological process, or is it a low-frequency analog of faster neural activity? Here, using whole-cortex calcium/hemoglobin imaging in mice, we show that ISA in each of these modalities travels through the cortex along stereotypical spatiotemporal trajectories that are state dependent (wake versus anesthesia) and distinct from trajectories in delta (1-4 Hz) activity. Moreover, mouse laminar electrophysiology reveals that ISA travels through specific cortical layers and is organized into unique cross-laminar temporal dynamics that are different from higher frequency local field potential activity. These findings suggest that ISA is a distinct neurophysiological process that is reflected in fMRI blood oxygen signals., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Models of Alzheimer's disease propose a sequence of amyloid β (Aβ) accumulation, hypometabolism, and structural decline that precedes the onset of clinical dementia. These pathological features evolve both temporally and spatially in the brain. In this study, we aimed to characterise where in the brain and when in the course of the disease neuroimaging biomarkers become abnormal., Methods: Between Jan 1, 2009, and Dec 31, 2015, we analysed data from mutation non-carriers, asymptomatic carriers, and symptomatic carriers from families carrying gene mutations in presenilin 1 (PSEN1), presenilin 2 (PSEN2), or amyloid precursor protein (APP) enrolled in the Dominantly Inherited Alzheimer's Network. We analysed 11 C-Pittsburgh Compound B ( 11 C-PiB) PET, 18 F-Fluorodeoxyglucose ( 18 F-FDG) PET, and structural MRI data using regions of interest to assess change throughout the brain. We estimated rates of biomarker change as a function of estimated years to symptom onset at baseline using linear mixed-effects models and determined the earliest point at which biomarker trajectories differed between mutation carriers and non-carriers. This study is registered at ClinicalTrials.gov (number NCT00869817) FINDINGS: 11 C-PiB PET was available for 346 individuals (162 with longitudinal imaging), 18 F-FDG PET was available for 352 individuals (175 with longitudinal imaging), and MRI data were available for 377 individuals (201 with longitudinal imaging). We found a sequence to pathological changes, with rates of Aβ deposition in mutation carriers being significantly different from those in non-carriers first (across regions that showed a significant difference, at a mean of 18·9 years [SD 3·3] before expected onset), followed by hypometabolism (14·1 years [5·1] before expected onset), and lastly structural decline (4·7 years [4·2] before expected onset). This biomarker ordering was preserved in most, but not all, regions. The temporal emergence within a biomarker varied across the brain, with the precuneus being the first cortical region for each method to show divergence between groups (22·2 years before expected onset for Aβ accumulation, 18·8 years before expected onset for hypometabolism, and 13·0 years before expected onset for cortical thinning)., Interpretation: Mutation carriers had elevations in Aβ deposition, reduced glucose metabolism, and cortical thinning compared with non-carriers which preceded the expected onset of dementia. Accrual of these pathologies varied throughout the brain, suggesting differential regional and temporal vulnerabilities to Aβ, metabolic decline, and structural atrophy, which should be taken into account when using biomarkers in a clinical setting as well as designing and evaluating clinical trials., Funding: US National Institutes of Health, the German Center for Neurodegenerative Diseases, and the Medical Research Council Dementias Platform UK., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Directed signaling among and within the large-scale networks of the human brain is functionally critical. Recent advances in our understanding of spontaneous fluctuations of the fMRI BOLD signal have provided strategies to study the spatial-temporal properties of directed signaling at infra-slow frequencies. Herein we explore the relationship between two canonical systems of the human brain, the default mode network (DMN) and the dorsal attention network (DAN) whose anti-correlated relationship is well known but poorly understood. We find that within the DMN, activity moves from retrosplenial to prefrontal cortex whereas in the DAN activity moves from the frontal eye fields to the parietal cortex. Bi-directional communication between the two networks occurs via their earliest elements (i.e., from the retrosplenial cortex of the DMN to the frontal eye fields of the DAN). This framework for network communication appears to generalize across all networks providing an expanded basis for understanding human brain function., (© 2018 Scandinavian Psychological Associations and John Wiley & Sons Ltd.)

The normal aging human brain experiences global decreases in metabolism, but whether this affects the topography of brain metabolism is unknown. Here we describe PET-based measurements of brain glucose uptake, oxygen utilization, and blood flow in cognitively normal adults from 20 to 82 years of age. Age-related decreases in brain glucose uptake exceed that of oxygen use, resulting in loss of brain aerobic glycolysis (AG). Whereas the topographies of total brain glucose uptake, oxygen utilization, and blood flow remain largely stable with age, brain AG topography changes significantly. Brain regions with high AG in young adults show the greatest change, as do regions with prolonged developmental transcriptional features (i.e., neoteny). The normal aging human brain thus undergoes characteristic metabolic changes, largely driven by global loss and topographic changes in brain AG., (Copyright © 2017 Elsevier Inc. All rights reserved.)

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

Background: Alzheimer disease (AD) affects at least 5 million individuals in the USA alone stimulating an intense search for disease prevention and treatment therapies as well as for diagnostic techniques allowing early identification of AD during a long pre-symptomatic period that can be used for the initiation of prevention trials of disease-modifying therapies in asymptomatic individuals., Methods: Our approach to developing such techniques is based on the Gradient Echo Plural Contrast Imaging (GEPCI) technique that provides quantitative in vivo measurements of several brain-tissue-specific characteristics of the gradient echo MRI signal (GEPCI metrics) that depend on the integrity of brain tissue cellular structure. Preliminary data were obtained from 34 participants selected from the studies of aging and dementia at the Knight Alzheimer's Disease Research Center at Washington University in St. Louis. Cognitive status was operationalized with the Clinical Dementia Rating (CDR) scale. The participants, assessed as cognitively normal (CDR=0; n=23) or with mild AD dementia (CDR=0.5 or 1; n=11) underwent GEPCI MRI, a collection of cognitive performance tests and CSF amyloid (Aβ) biomarker Aβ 42 . A subset of 19 participants also underwent PET PiB studies to assess their brain Aβ burden. According to the Aβ status, cognitively normal participants were divided into normal (Aβ negative; n=13) and preclinical (Aβ positive; n=10) groups., Results: GEPCI quantitative measurements demonstrated significant differences between all the groups: normal and preclinical, normal and mild AD, and preclinical and mild AD. GEPCI quantitative metrics characterizing tissue cellular integrity in the hippocampus demonstrated much stronger correlations with psychometric tests than the hippocampal atrophy. Importantly, GEPCI-determined changes in the hippocampal tissue cellular integrity were detected even in the hippocampal areas not affected by the atrophy. Our studies also uncovered strong correlations between GEPCI brain tissue metrics and beta-amyloid (Aβ) burden defined by positron emission tomography (PET) - the current in vivo gold standard for detection of cortical Aβ, thus supporting GEPCI as a potential surrogate marker for Aβ imaging - a known biomarker of early AD. Remarkably, the data show significant correlations not only in the areas of high Aβ accumulation (e.g. precuneus) but also in some areas of medial temporal lobe (e.g. parahippocampal cortex), where Aβ accumulation is relatively low., Conclusion: We have demonstrated that GEPCI provides a new approach for the in vivo evaluation of AD-related tissue pathology in the preclinical and early symptomatic stages of AD. Since MRI is a widely available technology, the GEPCI surrogate markers of AD pathology have a potential for improving the quality of AD diagnostic, and the evaluation of new disease-modifying therapies., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Initially regarded as 'noise', spontaneous (intrinsic) activity accounts for a large portion of the brain's metabolic cost. Moreover, it is now widely known that infra-slow (less than 0.1 Hz) spontaneous activity, measured using resting state functional magnetic resonance imaging of the blood oxygen level-dependent (BOLD) signal, is correlated within functionally defined resting state networks (RSNs). However, despite these advances, the temporal organization of spontaneous BOLD fluctuations has remained elusive. By studying temporal lags in the resting state BOLD signal, we have recently shown that spontaneous BOLD fluctuations consist of remarkably reproducible patterns of whole brain propagation. Embedded in these propagation patterns are unidirectional 'motifs' which, in turn, give rise to RSNs. Additionally, propagation patterns are markedly altered as a function of state, whether physiological or pathological. Understanding such propagation patterns will likely yield deeper insights into the role of spontaneous activity in brain function in health and disease.This article is part of the themed issue 'Interpreting blood oxygen level-dependent: a dialogue between cognitive and cellular neuroscience'., (© 2016 The Author(s).)

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

Lateralization of function is a fundamental feature of the human brain as exemplified by the left hemisphere dominance of language. Despite the prominence of lateralization in the lesion, split-brain and task-based fMRI literature, surprisingly little asymmetry has been revealed in the increasingly popular functional imaging studies of spontaneous fluctuations in the fMRI BOLD signal (so-called resting-state fMRI). Here, we show the global signal, an often discarded component of the BOLD signal in resting-state studies, reveals a leftward asymmetry that maps onto regions preferential for semantic processing in left frontal and temporal cortex and the right cerebellum and a rightward asymmetry that maps onto putative attention-related regions in right frontal, temporoparietal, and parietal cortex. Hemispheric asymmetries in the global signal resulted from amplitude modulation of the spontaneous fluctuations. To confirm these findings obtained from normal, healthy, right-handed subjects in the resting-state, we had them perform 2 semantic processing tasks: synonym and numerical magnitude judgment and sentence comprehension. In addition to establishing a new technique for studying lateralization through functional imaging of the resting-state, our findings shed new light on the physiology of the global brain signal., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

The human gut contains a microbial community composed of tens of trillions of organisms that normally assemble during the first 2-3 y of postnatal life. We propose that brain development needs to be viewed in the context of the developmental biology of this "microbial organ" and its capacity to metabolize the various diets we consume. We hypothesize that the persistent cognitive abnormalities seen in children with undernutrition are related in part to their persistent gut microbiota immaturity and that specific regions of the brain that normally exhibit persistent juvenile (neotenous) patterns of gene expression, including those critically involved in various higher cognitive functions such as the brain's default mode network, may be particularly vulnerable to the effects of microbiota immaturity in undernourished children. Furthermore, we postulate that understanding the interrelationships between microbiota and brain metabolism in childhood undernutrition could provide insights about responses to injury seen in adults. We discuss approaches that can be used to test these hypotheses, their ramifications for optimizing nutritional recommendations that promote healthy brain development and function, and the potential societal implications of this area of investigation.

Propagation of slow intrinsic brain activity has been widely observed in electrophysiogical studies of slow wave sleep (SWS). However, in human resting state fMRI (rs-fMRI), intrinsic activity has been understood predominantly in terms of zero-lag temporal synchrony (functional connectivity) within systems known as resting state networks (RSNs). Prior rs-fMRI studies have found that RSNs are generally preserved across wake and sleep. Here, we use a recently developed analysis technique to study propagation of infra-slow intrinsic blood oxygen level dependent (BOLD) signals in normal adults during wake and SWS. This analysis reveals marked changes in propagation patterns in SWS vs. wake. Broadly, ordered propagation is preserved within traditionally defined RSNs but lost between RSNs. Additionally, propagation between cerebral cortex and subcortical structures reverses directions, and intra-cortical propagation becomes reorganized, especially in visual and sensorimotor cortices. These findings show that propagated rs-fMRI activity informs theoretical accounts of the neural functions of sleep.

Background: Blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been used to study the effects of anesthetic agents on correlated intrinsic neural activity. Previous studies have focused primarily on intravenous agents. The authors studied the effects of sevoflurane, an inhaled anesthetic., Methods: Resting-state BOLD fMRI was acquired from 10 subjects before sedation and from 9 subjects rendered unresponsive by 1.2% sevoflurane. The fMRI data were analyzed taking particular care to minimize the impact of artifact generated by head motion., Results: BOLD correlations were specifically weaker within the default mode network and ventral attention network during sevoflurane-induced unconsciousness, especially between anterior and posterior midline regions. Reduced functional connectivity between these same networks and the thalamus was also spatially localized to the midline frontal regions. The amplitude of BOLD signal fluctuations was substantially reduced across all brain regions. The importance of censoring epochs contaminated by head motion was demonstrated by comparative analyses., Conclusions: Sevoflurane-induced unconsciousness is associated with both globally reduced BOLD signal amplitudes and selectively reduced functional connectivity within cortical networks associated with consciousness (default mode network) and orienting to salient external stimuli (ventral attention network). Scrupulous attention to minimizing the impact of head motion artifact is critical in fMRI studies using anesthetic agents.

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

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

The mechanism underlying temporal correlations among blood oxygen level-dependent signals is unclear. We used oxygen polarography to better characterize oxygen fluctuations and their correlation and to gain insight into the driving mechanism. The power spectrum of local oxygen fluctuations is inversely proportional to frequency raised to a power (1/f) raised to the beta, with an additional positive band-limited component centered at 0.06 Hz. In contrast, the power of the correlated oxygen signal is band limited from ∼ 0.01 Hz to 0.4 Hz with a peak at 0.06 Hz. These results suggest that there is a band-limited mechanism (or mechanisms) driving interregional oxygen correlation that is distinct from the mechanism(s) driving local (1/f) oxygen fluctuations. Candidates for driving interregional oxygen correlation include rhythmic or pseudo-oscillatory mechanisms.

It has been widely reported that intrinsic brain activity, in a variety of animals including humans, is spatiotemporally structured. Specifically, propagated slow activity has been repeatedly demonstrated in animals. In human resting-state fMRI, spontaneous activity has been understood predominantly in terms of zero-lag temporal synchrony within widely distributed functional systems (resting-state networks). Here, we use resting-state fMRI from 1,376 normal, young adults to demonstrate that multiple, highly reproducible, temporal sequences of propagated activity, which we term "lag threads," are present in the brain. Moreover, this propagated activity is largely unidirectional within conventionally understood resting-state networks. Modeling experiments show that resting-state networks naturally emerge as a consequence of shared patterns of propagation. An implication of these results is that common physiologic mechanisms may underlie spontaneous activity as imaged with fMRI in humans and slowly propagated activity as studied in animals.

The discovery that spontaneous fluctuations in blood oxygen level-dependent (BOLD) signals contain information about the functional organization of the brain has caused a paradigm shift in neuroimaging. It is now well established that intrinsic brain activity is organized into spatially segregated resting-state networks (RSNs). Less is known regarding how spatially segregated networks are integrated by the propagation of intrinsic activity over time. To explore this question, we examined the latency structure of spontaneous fluctuations in the fMRI BOLD signal. Our data reveal that intrinsic activity propagates through and across networks on a timescale of ∼1 s. Variations in the latency structure of this activity resulting from sensory state manipulation (eyes open vs. closed), antecedent motor task (button press) performance, and time of day (morning vs. evening) suggest that BOLD signal lags reflect neuronal processes rather than hemodynamic delay. Our results emphasize the importance of the temporal structure of the brain's spontaneous activity., (Copyright © 2014 the American Physiological Society.)

Aerobic glycolysis (AG; i.e., nonoxidative metabolism of glucose despite the presence of abundant oxygen) accounts for 10%-12% of glucose used by the adult human brain. AG varies regionally in the resting state. Brain AG may support synaptic growth and remodeling; however, data supporting this hypothesis are sparse. Here, we report on investigations on the role of AG in the human brain. Meta-analysis of prior brain glucose and oxygen metabolism studies demonstrates that AG increases during childhood, precisely when synaptic growth rates are highest. In resting adult humans, AG correlates with the persistence of gene expression typical of infancy (transcriptional neoteny). In brain regions with the highest AG, we find increased gene expression related to synapse formation and growth. In contrast, regions high in oxidative glucose metabolism express genes related to mitochondria and synaptic transmission. Our results suggest that brain AG supports developmental processes, particularly those required for synapse formation and growth., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Major imaging biomarkers of Alzheimer's disease include amyloid deposition [imaged with [(11)C]Pittsburgh compound B (PiB) PET], altered glucose metabolism (imaged with [(18)F]fluro-deoxyglucose PET), and structural atrophy (imaged by MRI). Recently we published the initial subset of imaging findings for specific regions in a cohort of individuals with autosomal dominant Alzheimer's disease. We now extend this work to include a larger cohort, whole-brain analyses integrating all three imaging modalities, and longitudinal data to examine regional differences in imaging biomarker dynamics. The anatomical distribution of imaging biomarkers is described in relation to estimated years from symptom onset. Autosomal dominant Alzheimer's disease mutation carrier individuals have elevated PiB levels in nearly every cortical region 15 y before the estimated age of onset. Reduced cortical glucose metabolism and cortical thinning in the medial and lateral parietal lobe appeared 10 and 5 y, respectively, before estimated age of onset. Importantly, however, a divergent pattern was observed subcortically. All subcortical gray-matter regions exhibited elevated PiB uptake, but despite this, only the hippocampus showed reduced glucose metabolism. Similarly, atrophy was not observed in the caudate and pallidum despite marked amyloid accumulation. Finally, before hypometabolism, a hypermetabolic phase was identified for some cortical regions, including the precuneus and posterior cingulate. Additional analyses of individuals in which longitudinal data were available suggested that an accelerated appearance of volumetric declines approximately coincides with the onset of the symptomatic phase of the disease.

There has been a dramatic increase in the number of studies using resting state functional magnetic resonance imaging (rs-fMRI), a recent addition to imaging analysis techniques. The technique analyzes ongoing low-frequency fluctuations in the blood oxygen level-dependent signal. Through patterns of spatial coherence, these fluctuations can be used to identify the networks within the brain. Multiple brain networks are present simultaneously, and the relationships within and between networks are in constant dynamic flux. Resting state fMRI functional connectivity analysis is increasingly used to detect subtle brain network differences and, in the case of pathophysiology, subtle abnormalities in illnesses such as Alzheimer's disease (AD). The sequence of events leading up to dementia has been hypothesized to begin many years or decades before any clinical symptoms occur. Here we review the findings across rs-fMRI studies in the spectrum of preclinical AD to clinical AD. In addition, we discuss evidence for underlying preclinical AD mechanisms, including an important relationship between resting state functional connectivity and brain metabolism and how this results in a distinctive pattern of amyloid plaque deposition in default mode network regions., (Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

It has been posited that a critical function of sleep is synaptic renormalization following a net increase in synaptic strength during wake. We hypothesized that wake would alter the resting-state functional organization of the brain and increase its metabolic cost. To test these hypotheses, two experiments were performed. In one, we obtained morning and evening resting-state functional MRI scans to assess changes in functional brain organization. In the second experiment, we obtained quantitative positron emission tomography measures of glucose and oxygen consumption to assess the cost of wake. We found selective changes in brain organization. Most prominently, bilateral medial temporal regions were locally connected in the morning but in the evening exhibited strong correlations with frontal and parietal brain regions involved in memory retrieval. We speculate that these changes may reflect aspects of memory consolidation recurring on a daily basis. Surprisingly, these changes in brain organization occurred without increases in brain metabolism.

A recent paradigm shift in systems neuroscience is the division of the human brain into functional networks. Functional networks are collections of brain regions with strongly correlated activity both at rest and during cognitive tasks, and each network is believed to implement a different aspect of cognition. We propose here that anxiety disorders and high trait anxiety are associated with a particular pattern of functional network dysfunction: increased functioning of the cingulo-opercular and ventral attention networks as well as decreased functioning of the fronto-parietal and default mode networks. This functional network model can be used to differentiate the pathology of anxiety disorders from other psychiatric illnesses such as major depression and provides targets for novel treatment strategies., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

We present a history of the concepts and developments that have led us to focus on the resting state as an object of study. We then discuss resting state research performed in our laboratory since 2005 with an emphasis on papers of particular interest., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Alzheimer's disease (AD) is the most common cause of dementia. Much is known concerning AD pathophysiology but our understanding of the disease at the systems level remains incomplete. Previous AD research has used resting-state functional connectivity magnetic resonance imaging (rs-fcMRI) to assess the integrity of functional networks within the brain. Most studies have focused on the default-mode network (DMN), a primary locus of AD pathology. However, other brain regions are inevitably affected with disease progression. We studied rs-fcMRI in five functionally defined brain networks within a large cohort of human participants of either gender (n = 510) that ranged in AD severity from unaffected [clinical dementia rating (CDR) 0] to very mild (CDR 0.5) to mild (CDR 1). We observed loss of correlations within not only the DMN but other networks at CDR 0.5. Within the salience network (SAL), increases were seen between CDR 0 and CDR 0.5. However, at CDR 1, all networks, including SAL, exhibited reduced correlations. Specific networks were preferentially affected at certain CDR stages. In addition, cross-network relations were consistently lost with increasing AD severity. Our results demonstrate that AD is associated with widespread loss of both intranetwork and internetwork correlations. These results provide insight into AD pathophysiology and reinforce an integrative view of the brain's functional organization.

Brain region-specific deposition of extracellular amyloid plaques principally composed of aggregated amyloid-β (Aβ) peptide is a pathological signature of Alzheimer's disease (AD). Recent human neuroimaging data suggest that resting-state functional connectivity strength is reduced in patients with AD, cognitively normal elderly harboring elevated amyloid burden, and in advanced aging. Interestingly, there exists a striking spatial correlation between functional connectivity strength in cognitively normal adults and the location of Aβ plaque deposition in AD. However, technical limitations have heretofore precluded examination of the relationship between functional connectivity, Aβ deposition, and normal aging in mouse models. Using a novel functional connectivity optical intrinsic signal (fcOIS) imaging technique, we demonstrate that Aβ deposition is associated with significantly reduced bilateral functional connectivity in multiple brain regions of older APP/PS1 transgenic mice. The amount of Aβ deposition in each brain region was associated with the degree of local, age-related bilateral functional connectivity decline. Normal aging was associated with reduced bilateral functional connectivity specifically in retrosplenial cortex. Furthermore, we found that the magnitude of regional bilateral functional correlation in young APP/PS1 mice before Aβ plaque formation was proportional to the amount of region-specific plaque deposition seen later in older APP/PS1 mice. Together, these findings suggest that Aβ deposition and normal aging are associated with region-specific disruption of functional connectivity and that the magnitude of local bilateral functional connectivity predicts regional vulnerability to subsequent Aβ deposition in mouse brain.

The default mode network (DMN) in humans has been suggested to support a variety of cognitive functions and has been implicated in an array of neuropsychological disorders. However, its function(s) remains poorly understood. We show that rats possess a DMN that is broadly similar to the DMNs of nonhuman primates and humans. Our data suggest that, despite the distinct evolutionary paths between rodent and primate brain, a well-organized, intrinsically coherent DMN appears to be a fundamental feature in the mammalian brain whose primary functions might be to integrate multimodal sensory and affective information to guide behavior in anticipation of changing environmental contingencies.

Tracking arterial spin labeled (ASL) water in the human brain with magnetic resonance imaging can provide important information on the dynamics of the trans-capillary and trans-membrane water exchange. This information however, is not only important from a basic biological standpoint, but also is essential for deciphering positron emission tomography and MRI perfusion experiments based on the movement of labeled water. While substantial information exists on water exchange through cellular membranes in vitro, the in vivo information remains limited and controversial. In this MRI study, we use a combination of pulsed ASL and recently developed quantitative blood-oxygen-level-dependent technique to address this question. Our approach is based on the measurements of the intrinsic MR transverse relaxation (T2*) properties of the ASL-labeled water. We discovered that T2* of the ASL-labeled water in the extravascular space is 87 ms ± 10 ms while T2* of the corresponding tissue water is much shorter, 50 ms ± 4 ms. This suggests that the ASL-labeled water does not reach equilibrium with the extravascular tissue and is mostly localized to the extraneuronal space. We estimated that the water transport time through the neuronal membranes is on the order of several tens of seconds; a finding consistent with older PET tracer kinetic studies using (15)O-water., (Copyright © 2011 Wiley Periodicals, Inc.)

One of the most intriguing recent discoveries concerning brain function is that intrinsic neuronal activity manifests as spontaneous fluctuations of the blood oxygen level-dependent (BOLD) functional MRI signal. These BOLD fluctuations exhibit temporal synchrony within widely distributed brain regions known as resting-state networks. Resting-state networks are present in the waking state, during sleep, and under general anesthesia, suggesting that spontaneous neuronal activity plays a fundamental role in brain function. Despite its ubiquitous presence, the physiological role of correlated, spontaneous neuronal activity remains poorly understood. One hypothesis is that this activity is critical for the development of synaptic connections and maintenance of synaptic homeostasis. We had a unique opportunity to test this hypothesis in a 5-y-old boy with severe epileptic encephalopathy. The child developed marked neurologic dysfunction in association with a seizure disorder, resulting in a 1-y period of behavioral regression and progressive loss of developmental milestones. His EEG showed a markedly abnormal pattern of high-amplitude, disorganized slow activity with frequent generalized and multifocal epileptiform discharges. Resting-state functional connectivity MRI showed reduced BOLD fluctuations and a pervasive lack of normal connectivity. The child underwent successful corpus callosotomy surgery for treatment of drop seizures. Postoperatively, the patient's behavior returned to baseline, and he resumed development of new skills. The waking EEG revealed a normal background, and functional connectivity MRI demonstrated restoration of functional connectivity architecture. These results provide evidence that intrinsic, coherent neuronal signaling may be essential to the development and maintenance of the brain's functional organization.

Background: Blast-related traumatic brain injuries have been common in the Iraq and Afghanistan wars, but fundamental questions about the nature of these injuries remain unanswered., Methods: We tested the hypothesis that blast-related traumatic brain injury causes traumatic axonal injury, using diffusion tensor imaging (DTI), an advanced form of magnetic resonance imaging that is sensitive to axonal injury. The subjects were 63 U.S. military personnel who had a clinical diagnosis of mild, uncomplicated traumatic brain injury. They were evacuated from the field to the Landstuhl Regional Medical Center in Landstuhl, Germany, where they underwent DTI scanning within 90 days after the injury. All the subjects had primary blast exposure plus another, blast-related mechanism of injury (e.g., being struck by a blunt object or injured in a fall or motor vehicle crash). Controls consisted of 21 military personnel who had blast exposure and other injuries but no clinical diagnosis of traumatic brain injury., Results: Abnormalities revealed on DTI were consistent with traumatic axonal injury in many of the subjects with traumatic brain injury. None had detectable intracranial injury on computed tomography. As compared with DTI scans in controls, the scans in the subjects with traumatic brain injury showed marked abnormalities in the middle cerebellar peduncles (P<0.001), in cingulum bundles (P=0.002), and in the right orbitofrontal white matter (P=0.007). In 18 of the 63 subjects with traumatic brain injury, a significantly greater number of abnormalities were found on DTI than would be expected by chance (P<0.001). Follow-up DTI scans in 47 subjects with traumatic brain injury 6 to 12 months after enrollment showed persistent abnormalities that were consistent with evolving injuries., Conclusions: DTI findings in U.S. military personnel support the hypothesis that blast-related mild traumatic brain injury can involve axonal injury. However, the contribution of primary blast exposure as compared with that of other types of injury could not be determined directly, since none of the subjects with traumatic brain injury had isolated primary blast injury. Furthermore, many of these subjects did not have abnormalities on DTI. Thus, traumatic brain injury remains a clinical diagnosis. (Funded by the Congressionally Directed Medical Research Program and the National Institutes of Health; ClinicalTrials.gov number, NCT00785304.).

The transition from quiet wakeful rest to sleep represents a period over which attention to the external environment fades. Neuroimaging methodologies have provided much information on the shift in neural activity patterns in sleep, but the dynamic restructuring of human brain networks in the transitional period from wake to sleep remains poorly understood. Analysis of electrophysiological measures and functional network connectivity of these early transitional states shows subtle shifts in network architecture that are consistent with reduced external attentiveness and increased internal and self-referential processing. Further, descent to sleep is accompanied by the loss of connectivity in anterior and posterior portions of the default-mode network and more locally organized global network architecture. These data clarify the complex and dynamic nature of the transitional period between wake and sleep and suggest the need for more studies investigating the dynamics of these processes., (Copyright © 2011 Elsevier B.V. All rights reserved.)

The pressing need to better understand human brain organization is appreciated by all who have labored to explain the uniqueness of human behavior in health and disease. Early work on the cytoarchitectonics of the human brain by Brodmann and others accompanied by several centuries of lesion behavior work, although valuable, has left us far short of what we need. Fortunately, modern brain imaging techniques have, over the past 40 years, substantially changed the situation by permitting the safe appraisal of both anatomical and functional relationships within the living human brain. An unexpected feature of this work is the critical importance of ongoing, intrinsic activity, which accounts for the majority of brain's energy consumption and exhibits a surprising level of organization that emerges with dimensions of both space and time. In this essay, some of the unique features of intrinsic activity are reviewed, as it relates to our understanding of brain organization.

Amyloid-β (Aβ) plaque deposition can precede the clinical manifestations of dementia of the Alzheimer type (DAT) by many years and can be associated with changes in brain metabolism. Both the Aβ plaque deposition and the changes in metabolism appear to be concentrated in the brain's default-mode network. In contrast to prior studies of brain metabolism which viewed brain metabolism from a unitary perspective that equated glucose utilization with oxygen consumption, we here report on regional glucose use apart from that entering oxidative phosphorylation (so-called "aerobic glycolysis"). Using PET, we found that the spatial distribution of aerobic glycolysis in normal young adults correlates spatially with Aβ deposition in individuals with DAT and cognitively normal participants with elevated Aβ, suggesting a possible link between regional aerobic glycolysis in young adulthood and later development of Alzheimer pathology.

Aerobic glycolysis is defined as glucose utilization in excess of that used for oxidative phosphorylation despite sufficient oxygen to completely metabolize glucose to carbon dioxide and water. Aerobic glycolysis is present in the normal human brain at rest and increases locally during increased neuronal activity; yet its many biological functions have received scant attention because of a prevailing energy-centric focus on the role of glucose as substrate for oxidative phosphorylation. As an initial step in redressing this neglect, we measured the regional distribution of aerobic glycolysis with positron emission tomography in 33 neurologically normal young adults at rest. We show that the distribution of aerobic glycolysis in the brain is differentially present in previously well-described functional areas. In particular, aerobic glycolysis is significantly elevated in medial and lateral parietal and prefrontal cortices. In contrast, the cerebellum and medial temporal lobes have levels of aerobic glycolysis significantly below the brain mean. The levels of aerobic glycolysis are not strictly related to the levels of brain energy metabolism. For example, sensory cortices exhibit high metabolic rates for glucose and oxygen consumption but low rates of aerobic glycolysis. These striking regional variations in aerobic glycolysis in the normal human brain provide an opportunity to explore how brain systems differentially use the diverse cell biology of glucose in support of their functional specializations in health and disease.