Baseline brain energy supports the state of consciousness

In vivo neuropil density from anatomical MRI and machine learning

Brain energy budgets specify metabolic costs emerging from underlying mechanisms of cellular and synaptic activities. While current bottom-up energy budgets use prototypical values of cellular density and synaptic density, predicting metabolism from a person's individualized neuropil density would be ideal. We hypothesize that in vivo neuropil density can be derived from magnetic resonance imaging (MRI) data, consisting of longitudinal relaxation (T1) MRI for gray/white matter distinction and diffusion MRI for tissue cellularity (apparent diffusion coefficient, ADC) and axon directionality (fractional anisotropy, FA). We present a machine learning algorithm that predicts neuropil density from in vivo MRI scans, where ex vivo Merker staining and in vivo synaptic vesicle glycoprotein 2A Positron Emission Tomography (SV2A-PET) images were reference standards for cellular and synaptic density, respectively. We used Gaussian-smoothed T1/ADC/FA data from 10 healthy subjects to train an artificial neural network, subsequently used to predict cellular and synaptic density for 54 test subjects. While excellent histogram overlaps were observed both for synaptic density (0.93) and cellular density (0.85) maps across all subjects, the lower spatial correlations both for synaptic density (0.89) and cellular density (0.58) maps are suggestive of individualized predictions. This proof-of-concept artificial neural network may pave the way for individualized energy atlas prediction, enabling microscopic interpretations of functional neuroimaging data.

Lactate as a supplemental fuel for synaptic transmission and neuronal network oscillations: Potentials and limitations

Lactate shuttled from the blood circulation, astrocytes, oligodendrocytes or even activated microglia (resident macrophages) to neurons has been hypothesized to represent a major source of pyruvate compared to what is normally produced endogenously by neuronal glucose metabolism. However, the role of lactate oxidation in fueling neuronal signaling associated with complex cortex function, such as perception, motor activity, and memory formation, is widely unclear. This issue has been experimentally addressed using electrophysiology in hippocampal slice preparations (ex vivo) that permit the induction of different neural network activation states by electrical stimulation, optogenetic tools or receptor ligand application. Collectively, these studies suggest that lactate in the absence of glucose (lactate only) impairs gamma (30-70 Hz) and theta-gamma oscillations, which feature high energy demand revealed by the cerebral metabolic rate of oxygen (CMRO2, set to 100%). The impairment comprises oscillation attenuation or moderate neural bursts (excitation-inhibition imbalance). The bursting is suppressed by elevating the glucose fraction in energy substrate supply. By contrast, lactate can retain certain electric stimulus-induced neural population responses and intermittent sharp wave-ripple activity that features lower energy expenditure (CMRO2 of about 65%). Lactate utilization increases the oxygen consumption by about 9% during sharp wave-ripples reflecting enhanced adenosine-5'-triphosphate (ATP) synthesis by oxidative phosphorylation in mitochondria. Moreover, lactate attenuates neurotransmission in glutamatergic pyramidal cells and fast-spiking, γ-aminobutyric acid (GABA)ergic interneurons by reducing neurotransmitter release from presynaptic terminals. By contrast, the generation and propagation of action potentials in the axon is regular. In conclusion, lactate is less effective than glucose and potentially detrimental during neural network rhythms featuring high energetic costs, likely through the lack of some obligatory ATP synthesis by aerobic glycolysis at excitatory and inhibitory synapses. High lactate/glucose ratios might contribute to central fatigue, cognitive impairment, and epileptic seizures partially seen, for instance, during exhaustive physical exercise, hypoglycemia and neuroinflammation.

Type-1 cannabinoid receptors and their ever-expanding roles in brain energy processes

The brain requires large quantities of energy to sustain its functions. At the same time, the brain is isolated from the rest of the body, forcing this organ to develop strategies to control and fulfill its own energy needs. Likely based on these constraints, several brain-specific mechanisms emerged during evolution. For example, metabolically specialized cells are present in the brain, where intercellular metabolic cycles are organized to separate workload and optimize the use of energy. To orchestrate these strategies across time and space, several signaling pathways control the metabolism of brain cells. One of such controlling systems is the endocannabinoid system, whose main signaling hub in the brain is the type-1 cannabinoid (CB1) receptor. CB1 receptors govern a plethora of different processes in the brain, including cognitive function, emotional responses, or feeding behaviors. Classically, the mechanisms of action of CB1 receptors on brain function had been explained by its direct targeting of neuronal synaptic function. However, new discoveries have challenged this view. In this review, we will present and discuss recent data about how a small fraction of CB1 receptors associated to mitochondrial membranes (mtCB1), are able to exert a powerful control on brain functions and behavior. mtCB1 receptors impair mitochondrial functions both in neurons and astrocytes. In the latter cells, this effect is linked to an impairment of astrocyte glycolytic function, resulting in specific behavioral outputs. Finally, we will discuss the potential implications of (mt)CB1 expression on oligodendrocytes and microglia metabolic functions, with the aim to encourage interdisciplinary approaches to better understand the role of (mt)CB1 receptors in brain function and behavior.

A Human Brain Map of Mitochondrial Respiratory Capacity and Diversity

Mitochondrial oxidative phosphorylation (OxPhos) powers brain activity1,2, and mitochondrial defects are linked to neurodegenerative and neuropsychiatric disorders3,4, underscoring the need to define the brain's molecular energetic landscape5-10. To bridge the cognitive neuroscience and cell biology scale gap, we developed a physical voxelization approach to partition a frozen human coronal hemisphere section into 703 voxels comparable to neuroimaging resolution (3×3×3 mm). In each cortical and subcortical brain voxel, we profiled mitochondrial phenotypes including OxPhos enzyme activities, mitochondrial DNA and volume density, and mitochondria-specific respiratory capacity. We show that the human brain contains a diversity of mitochondrial phenotypes driven by both topology and cell types. Compared to white matter, grey matter contains >50% more mitochondria. We show that the more abundant grey matter mitochondria also are biochemically optimized for energy transformation, particularly among recently evolved cortical brain regions. Scaling these data to the whole brain, we created a backward linear regression model integrating several neuroimaging modalities11, thereby generating a brain-wide map of mitochondrial distribution and specialization that predicts mitochondrial characteristics in an independent brain region of the same donor brain. This new approach and the resulting MitoBrainMap of mitochondrial phenotypes provide a foundation for exploring the molecular energetic landscape that enables normal brain functions, relating it to neuroimaging data, and defining the subcellular basis for regionalized brain processes relevant to neuropsychiatric and neurodegenerative disorders.

A Human Brain Map of Mitochondrial Respiratory Capacity and Diversity

Mitochondrial oxidative phosphorylation (OxPhos) powers brain activity1,2, and mitochondrial defects are linked to neurodegenerative and neuropsychiatric disorders3,4, underscoring the need to define the brain's molecular energetic landscape5-10. To bridge the cognitive neuroscience and cell biology scale gap, we developed a physical voxelization approach to partition a frozen human coronal hemisphere section into 703 voxels comparable to neuroimaging resolution (3×3×3 mm). In each cortical and subcortical brain voxel, we profiled mitochondrial phenotypes including OxPhos enzyme activities, mitochondrial DNA and volume density, and mitochondria-specific respiratory capacity. We show that the human brain contains a diversity of mitochondrial phenotypes driven by both topology and cell types. Compared to white matter, grey matter contains >50% more mitochondria. We show that the more abundant grey matter mitochondria also are biochemically optimized for energy transformation, particularly among recently evolved cortical brain regions. Scaling these data to the whole brain, we created a backward linear regression model integrating several neuroimaging modalities11, thereby generating a brain-wide map of mitochondrial distribution and specialization that predicts mitochondrial characteristics in an independent brain region of the same donor brain. This new approach and the resulting MitoBrainMap of mitochondrial phenotypes provide a foundation for exploring the molecular energetic landscape that enables normal brain functions, relating it to neuroimaging data, and defining the subcellular basis for regionalized brain processes relevant to neuropsychiatric and neurodegenerative disorders.

Deep rest: An integrative model of how contemplative practices combat stress and enhance the body's restorative capacity

Engaging in contemplative practice like meditation, yoga, and prayer, is beneficial for psychological and physical well-being. Recent research has identified several underlying psychological and biological pathways that explain these benefits. However, there is not yet consensus on the underlying overlapping physiological mechanisms of contemplative practice benefits. In this article, we integrate divergent scientific literatures on contemplative practice interventions, stress science, and mitochondrial biology, presenting a unified biopsychosocial model of how contemplative practices reduce stress and promote physical health. We argue that engaging in contemplative practice facilitates a restorative state termed "deep rest," largely through safety signaling, during which energetic resources are directed toward cellular optimization and away from energy-demanding stress states. Our model thus presents a framework for how contemplative practices enhance positive psychological and physiological functioning by optimizing cellular energy consumption. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A functional account of stimulation-based aerobic glycolysis and its role in interpreting BOLD signal intensity increases in neuroimaging experiments

In aerobic glycolysis, oxygen is abundant, and yet cells metabolize glucose without using it, decreasing their ATP per glucose yield by 15-fold. During task-based stimulation, aerobic glycolysis occurs in localized brain regions, presenting a puzzle: why produce ATP inefficiently when, all else being equal, evolution should favor the efficient use of metabolic resources? The answer is that all else is not equal. We propose that a tradeoff exists between efficient ATP production and the efficiency with which ATP is spent to transmit information. Aerobic glycolysis, despite yielding little ATP per glucose, may support neuronal signaling in thin (< 0.5 µm), information-efficient axons. We call this the efficiency tradeoff hypothesis. This tradeoff has potential implications for interpretations of task-related BOLD "activation" observed in fMRI. We hypothesize that BOLD "activation" may index local increases in aerobic glycolysis, which support signaling in thin axons carrying "bottom-up" information, or "prediction error"-i.e., the BIAPEM (BOLD increases approximate prediction error metabolism) hypothesis. Finally, we explore implications of our hypotheses for human brain evolution, social behavior, and mental disorders.

A 3D atlas of functional human brain energetic connectome based on neuropil distribution

The human brain is energetically expensive, yet the key factors governing its heterogeneous energy distributions across cortical regions to support its diversity of functions remain unexplored. Here, we built up a 3D digital cortical energy atlas based on the energetic costs of all neuropil activities into a high-resolution stereological map of the human cortex with cellular and synaptic densities derived, respectively, from ex vivo histological staining and in vivo PET imaging. The atlas was validated with PET-measured glucose oxidation at the voxel level. A 3D cortical activity map was calculated to predict the heterogeneous activity rates across all cortical regions, which revealed that resting brain is indeed active with heterogeneous neuronal activity rates averaging around 1.2 Hz, comprising around 70% of the glucose oxidation of the cortex. Additionally, synaptic density dominates spatial patterns of energetics, suggesting that the cortical energetics rely heavily on the distribution of synaptic connections. Recent evidence from functional imaging studies suggests that some cortical areas act as hubs (i.e., interconnecting distinct and functionally active regions). An inverse allometric relationship was observed between hub metabolic rates versus hub volumes. Hubs with smaller volumes have higher synapse density, metabolic rate, and activity rates compared to nonhubs. The open-source BrainEnergyAtlas provides a granular framework for exploring revealing design principles in energy-constrained human cortical circuits across multiple spatial scales.

Is the tendency to maximise energy distribution an optimal collective activity for biological purposes? A proposal for a global principle of biological organization

Our purpose is to address the biological problem of finding foundations of the organization in the collective activity among cell networks in the nervous system, at the meso/macroscale, giving rise to cognition and consciousness. But in doing so, we encounter another problem related to the interpretation of methods to assess the neural interactions and organization of the neurodynamics, because thermodynamic notions, which have precise meaning only under specific conditions, have been widely employed in these studies. The consequence is that apparently contradictory results appear in the literature, but these contradictions diminish upon the considerations of the specific circumstances of each experiment. After clarifying some of these controversial points and surveying some experimental results, we propose that a necessary condition for cognition/consciousness to emerge is to have available enough energy, or cellular activity; and a sufficient condition is the multiplicity of configurations in which cell networks can communicate, resulting in non-uniform energy distribution, the generation and dissipation of energy gradients due to the constant activity. The diversity of sensorimotor processing of higher animals needs a flexible, fluctuating web on neuronal connections, and we review results supporting such multiplicity of configurations among brain regions associated with conscious awareness and healthy brain states. These ideas may reveal possible fundamental principles of brain organization that could be extended to other natural phenomena and how healthy activity may derive to pathological states.

The energetic cost of allostasis and allostatic load

Chronic psychosocial stress increases disease risk and mortality, but the underlying mechanisms remain largely unclear. Here we outline an energy-based model for the transduction of chronic stress into disease over time. The energetic model of allostatic load (EMAL) emphasizes the energetic cost of allostasis and allostatic load, where the "load" is the additional energetic burden required to support allostasis and stress-induced energy needs. Living organisms have a limited capacity to consume energy. Overconsumption of energy by allostatic brain-body processes leads to hypermetabolism, defined as excess energy expenditure above the organism's optimum. In turn, hypermetabolism accelerates physiological decline in cells, laboratory animals, and humans, and may drive biological aging. Therefore, we propose that the transition from adaptive allostasis to maladaptive allostatic states, allostatic load, and allostatic overload arises when the added energetic cost of stress competes with longevity-promoting growth, maintenance, and repair. Mechanistically, the energetic restriction of growth, maintenance and repair processes leads to the progressive wear-and-tear of molecular and organ systems. The proposed model makes testable predictions around the physiological, cellular, and sub-cellular energetic mechanisms that transduce chronic stress into disease risk and mortality. We also highlight new avenues to quantify allostatic load and its link to health across the lifespan, via the integration of systemic and cellular energy expenditure measurements together with classic allostatic load biomarkers.

Differential Alterations to the Metabolic Connectivity of the Cortical and Subcortical Regions in Rat Brain During Ketamine-Induced Unconsciousness

BACKGROUND

Ketamine anesthesia increased glucose metabolism in most brain regions compared to another intravenous anesthetic propofol. However, whether the changes in cerebral metabolic networks induced by ketamine share the same mechanism with propofol remains to be explored. The purpose of the present study was to identify specific features of metabolic network in rat brains during ketamine-induced subanesthesia state and anesthesia state compared to awake state.

METHODS

We acquired fluorodeoxyglucose positron emission tomography (FDG-PET) images in 20 healthy adult Sprague-Dawley rats that were intravenously administrated saline and ketamine to achieve different conscious states: awake (normal saline), subanesthesia (30 mg kg -1 h -1 ), and anesthesia (160 mg kg -1 h -1 ). Based on the FDG-PET data, the alterations in cerebral glucose metabolism and metabolic topography were investigated by graph-theory analysis.

RESULTS

The baseline metabolism in rat brains was found significantly increased during ketamine-induced subanesthesia and anesthesia. The graph-theory analysis manifested a reduction in metabolism connectivity and network global/local efficiency across cortical regions and an increase across subcortical regions during ketamine-induced anesthesia (nonparametric permutation test: global efficiency between awake and anesthesia, cortex: P = .016, subcortex: P = .015; global efficiency between subanesthesia and anesthesia, subcortex: P = .012).

CONCLUSIONS

Ketamine broadly increased brain metabolism alongside decreased metabolic connectivity and network efficiency of cortex network. Modulation of these cortical metabolic networks may be a candidate mechanism underlying general anesthesia-induced loss of consciousness.

The why of the phenomenal aspect of consciousness: Its main functions and the mechanisms underpinning it

What distinguishes conscious information processing from other kinds of information processing is its phenomenal aspect (PAC), the-what-it-is-like for an agent to experience something. The PAC supplies the agent with a sense of self, and informs the agent on how its self is affected by the agent’s own operations. The PAC originates from the activity that attention performs to detect the state of what I define “the self” (S). S is centered and develops on a hierarchy of innate and acquired values, and is primarily expressed via the central and peripheral nervous systems; it maps the agent’s body and cognitive capacities, and its interactions with the environment. The detection of the state of S by attention modulates the energy level of the organ of attention (OA), i.e., the neural substrate that underpins attention. This modulation generates the PAC. The PAC can be qualified according to five dimensions: qualitative, quantitative, hedonic, temporal and spatial. Each dimension can be traced back to a specific feature of the modulation of the energy level of the OA.

Awareness and consciousness in humans and animals – neural and behavioral correlates in an evolutionary perspective

Awareness or consciousness in the context of stimulus perception can directly be assessed in well controlled test situations with humans via the persons’ reports about their subjective experiences with the stimuli. Since we have no direct access to subjective experiences in animals, their possible awareness or consciousness in stimulus perception tasks has often been inferred from behavior and cognitive abilities previously observed in aware and conscious humans. Here, we analyze published human data primarily on event-related potentials and brain-wave generation during perception and responding to sensory stimuli and extract neural markers (mainly latencies of evoked-potential peaks and of gamma-wave occurrence) indicating that a person became aware or conscious of the perceived stimulus. These neural correlates of consciousness were then applied to sets of corresponding data from various animals including several species of mammals, and one species each of birds, fish, cephalopods, and insects. We found that the neural markers from studies in humans could also successfully be applied to the mammal and bird data suggesting that species in these animal groups can become subjectively aware of and conscious about perceived stimuli. Fish, cephalopod and insect data remained inconclusive. In an evolutionary perspective we have to consider that both awareness of and consciousness about perceived stimuli appear as evolved, attention-dependent options added to the ongoing neural activities of stimulus processing and action generation. Since gamma-wave generation for functional coupling of brain areas in aware/conscious states is energetically highly cost-intensive, it remains to be shown which animal species under which conditions of lifestyle and ecological niche may achieve significant advantages in reproductive fitness by drawing upon these options. Hence, we started our discussion about awareness and consciousness in animals with the question in how far these expressions of brain activity are necessary attributes for perceiving stimuli and responding in an adaptive way.

Why Do We Care More About Disease than Health?

Modern Western biomedical research and clinical practice are primarily focused on disease. This disease-centric approach has yielded an impressive amount of knowledge around what goes wrong in illness. However, in comparison, researchers and physicians know little about health. What is health? How do we quantify it? And how do we improve it? We currently do not have good answers to these questions. Our lack of fundamental knowledge about health is partly driven by three main factors: (i) a lack of understanding of the dynamic processes that cause variations in health/disease states over time, (ii) an excessive focus on genes, and (iii) a pervasive psychological bias towards additive solutions. Here I briefly discuss potential reasons why scientists and funders have generally adopted a gene- and disease-centric framework, how medicine has ended up practicing "diseasecare" rather than healthcare, and present cursory evidence that points towards an alternative energetic view of health. Understanding the basis of human health with a similar degree of precision that has been deployed towards mapping disease processes could bring us to a point where we can actively support and promote human health across the lifespan, before disease shows up on a scan or in bloodwork.

Synapses: The Brain's Energy-Demanding Sites

The brain is one of the most energy-consuming organs in the mammalian body, and synaptic transmission is one of the major contributors. To meet these energetic requirements, the brain primarily uses glucose, which can be metabolized through glycolysis and/or mitochondrial oxidative phosphorylation. The relevance of these two energy production pathways in fulfilling energy at presynaptic terminals has been the subject of recent studies. In this review, we dissect the balance of glycolysis and oxidative phosphorylation to meet synaptic energy demands in both resting and stimulation conditions. Besides ATP output needs, mitochondria at synapse are also important for calcium buffering and regulation of reactive oxygen species. These two mitochondrial-associated pathways, once hampered, impact negatively on neuronal homeostasis and synaptic activity. Therefore, as mitochondria assume a critical role in synaptic homeostasis, it is becoming evident that the synaptic mitochondria population possesses a distinct functional fingerprint compared to other brain mitochondria. Ultimately, dysregulation of synaptic bioenergetics through glycolytic and mitochondrial dysfunctions is increasingly implicated in neurodegenerative disorders, as one of the first hallmarks in several of these diseases are synaptic energy deficits, followed by synapse degeneration.

The Mental Maxwell Relations: A Thermodynamic Allegory for Higher Brain Functions

The theoretical framework of classical thermodynamics unifies vastly diverse natural phenomena and captures once-elusive effects in concrete terms. Neuroscience confronts equally varied, equally ineffable phenomena in the mental realm, but has yet to unite or to apprehend them rigorously, perhaps due to an insufficient theoretical framework. The terms for mental phenomena, the mental variables, typically used in neuroscience are overly numerous and imprecise. Unlike in thermodynamics or other branches of physics, in neuroscience, there are no core mental variables from which all others formally derive and it is unclear which variables are distinct and which overlap. This may be due to the nature of mental variables themselves. Unlike the variables of physics, perhaps they cannot be interpreted as composites of a small number of axioms. However, it is well worth exploring if they can, as that would allow more parsimonious theories of higher brain function. Here we offer a theoretical exercise in the spirit of the National Institutes of Health Research Domain Criteria (NIH RDoC) Initiative and the Cognitive Atlas Project, which aim to remedy this state of affairs. Imitating classical thermodynamics, we construct a formal framework for mental variables, an extended analogy - an allegory - between mental and thermodynamic quantities. Starting with mental correlates of the physical indefinables length, time, mass or force, and charge, we pursue the allegory up to mental versions of the thermodynamic Maxwell Relations. The Maxwell Relations interrelate the thermodynamic quantities volume, pressure, temperature, and entropy and were chosen since they are easy to derive, yet capable of generating nontrivial, nonobvious predictions. Our "Mental Maxwell Relations" interlink the mental variables consciousness, salience, arousal, and distraction and make nontrivial, nonobvious statements about mental phenomena. The mental system thus constructed is internally consistent, in harmony with introspection, and respects the RDoC criteria of employing only psychologically valid constructs with some evidence of a brain basis. We briefly apply these concepts to the problem of decision-making and sketch how some of them might be tested empirically.

Human Brain Organoids and Consciousness

This article proposes a methodological schema for engaging in a productive discussion of ethical issues regarding human brain organoids (HBOs), which are three-dimensional cortical neural tissues created using human pluripotent stem cells. Although moral consideration of HBOs significantly involves the possibility that they have consciousness, there is no widely accepted procedure to determine whether HBOs are conscious. Given that this is the case, it has been argued that we should adopt a precautionary principle about consciousness according to which, if we are not certain whether HBOs have consciousness—and where treating HBOs as not having consciousness may cause harm to them—we should proceed as if they do have consciousness. This article emphasizes a methodological advantage of adopting the precautionary principle: it enables us to sidestep the question of whether HBOs have consciousness (the whether-question) and, instead, directly address the question of what kinds of conscious experiences HBOs can have (the what-kind-question), where the what-kind-question is more tractable than the whether-question. By addressing the what-kind-question (and, in particular, the question of what kinds of valenced experiences HBOs can have), we will be able to examine how much moral consideration HBOs deserve. With this in mind, this article confronts the what-kind-question with the assistance of experimental studies of consciousness and suggests an ethical framework which supports restricting the creation and use of HBOs in bioscience.

Toward a coherent structuration of disorders of consciousness expertise at a country scale: A proposal for France

Probing consciousness and cognitive abilities in non-communicating patients is one of the most challenging diagnostic issues. A fast growing medical and scientific literature explores the various facets of this challenge, often coined under the generic expression of 'Disorders of Consciousness' (DoC). Crucially, a set of independent converging results demonstrated both (1) the diagnostic and prognostic importance of this expertise, and (2) the need to combine behavioural measures with brain structure and activity data to improve diagnostic and prognostication accuracy as well as potential therapeutic intervention. Thus, probing consciousness in DoC patients appears as a crucial activity rich of human, medical, economic and ethical consequences, but this activity needs to be organized in order to offer this expertise to each concerned patient. More precisely, diagnosis of consciousness differs in difficulty across patients: while a minimal set of data can be sufficient to reach a confident result, some patients need a higher level of expertise that relies on additional behavioural and brain activity and brain structure measures. In order to enable this service on a systematic mode, we present two complementary proposals in the present article. First, we sketch a structuration of DoC expertise at a country-scale, namely France. More precisely, we suggest that a 2-tiers network composed of local (Tier-1) and regional (Tier-2) centers backed by distant electronic databases and algorithmic centers could optimally enable the systematic implementation of DoC expertise in France. Second, we propose to create a national common register of DoC patients in order to better monitor this activity, to improve its performance on the basis of nation-wide collected evidence, and to promote rational decision-making.

Towards new concepts for a biological neuroscience of consciousness

In the search for a sound model of consciousness, we aim at introducing new concepts: closure, compositionality, biobranes and autobranes. This is important to overcome reductionism and to bring life back into the neuroscience of consciousness. Using these definitions, we conjecture that consciousness co-arises with the non-trivial composition of biological closure in the form of biobranes and autobranes: conscious processes generate closed activity at various levels and are, in turn, themselves, supported by biobranes and autobranes. This approach leads to a non-reductionist biological and simultaneously phenomenological theory of conscious experience, giving new perspectives for a science of consciousness. Future works will implement experimental definitions and computational simulations to characterize these dynamical biobranes interacting.

Insights of neurophysiology on unconscious state using combined transcranial magnetic stimulation and electroencephalography: A systematic review

Unconscious state has been investigated in numerous studies so far, but pathophysiology of this state is not fully understood. Recently, combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has been developed to allow for non-invasive assessment of neurophysiology in the cerebral cortex. We conducted a systematic literature search for TMS-EEG studies on human unconscious state using PubMed with cross-reference and manual searches. The initial search yielded 137 articles, and 19 of them were identified as relevant, including one article found by manual search. This review included 10 studies for unresponsive wakefulness syndrome (UWS), 9 for minimally conscious states (MCS), 5 for medication-induced unconscious states, and 6 for natural non-rapid eye movement states. These studies analyzed TMS-evoked potential to calculate perturbational complexity index (PCI) and OFF-periods. In particular, PCI was found to be a potentially useful marker to differentiate between UWS and MCS. This review demonstrated that TMS-EEG could represent a promising neuroscientific tool to investigate various unconscious states. Further TMS-EEG research may help elucidate the neural basis of unconscious state.

Deriving Mental Energy From Task Completion

Many tasks in everyday life (e.g., making an accurate decision, completing job tasks, and searching for product information) are extrinsically motivated (i.e., the task is performed to gain a benefit) and require mental effort. Prior research shows that the cognitive resources needed to perform an extrinsically motivated task are allocated pre-task. The pre-task allocation of mental resources tends to be conservative, because mental effort is costly. Consequently, there are mental energy deficits when the use of mental resources exceeds the allocated amount. This research provides evidence for post-task mental energy replenishment. The amount of resource replenishment is a function of the size of the mental energy deficit and the favorability of the cost-benefit trade-off experienced at the completion of the task (i.e., the value of the reward given the energy investment). The findings have implications for how cognitive resources management influences the availability of mental energy on a moment-to-moment basis.

Sparsely Wiring Connectivity in the Upper Beta Band Characterizes the Brains of Top Swimming Athletes

Human brains are extremely energy costly in neural connections and activities. However, it is unknown what is the difference in the brain connectivity between top athletes with long-term professional trainings and age-matched controls. Here we ask whether long-term training can lower brain-wiring cost while have better performance. Since elite swimming requires athletes to move their arms and legs at different tempos in time with high coordination skills, we selected an eye-hand-foot complex reaction (CR) task to examine the relations between the task performance and the brain connections and activities, as well as to explore the energy cost-efficiency of top athletes. Twenty-one master-level professional swimmers and 23 age-matched non-professional swimmers as controls were recruited to perform the CR task with concurrent 8-channel EEG recordings. Reaction time and accuracy of the CR task were recorded. Topological network analysis of various frequency bands was performed using the phase lag index (PLI) technique to avoid volume conduction effects. The wiring number of connections and mean frequency were calculated to reflect the wiring and activity cost, respectively. Results showed that professional athletes demonstrated better eye-hand-foot coordination than controls when performing the CR task, indexing by faster reaction time and higher accuracy. Comparing to controls, athletes' brain demonstrated significantly less connections and weaker correlations in upper beta frequency band between the frontal and parietal regions, while demonstrated stronger connectivity in the low theta frequency band between sites of F3 and Cz/C4. Additionally, athletes showed highly stable and low eye-blinking rates across different reaction performance, while controls had high blinking frequency with high variance. Elite athletes' brain may be characterized with energy efficient sparsely wiring connections in support of superior motor performance and better cognitive performance in the eye-hand-foot complex reaction task.

How Energy Supports Our Brain to Yield Consciousness: Insights From Neuroimaging Based on the Neuroenergetics Hypothesis

Consciousness is considered a result of specific neuronal processes and mechanisms in the brain. Various suggested neuronal mechanisms, including the information integration theory (IIT), global neuronal workspace theory (GNWS), and neuronal construction of time and space as in the context of the temporospatial theory of consciousness (TTC), have been laid forth. However, despite their focus on different neuronal mechanisms, these theories neglect the energetic-metabolic basis of the neuronal mechanisms that are supposed to yield consciousness. Based on the findings of physiology-induced (sleep), pharmacology-induced (general anesthesia), and pathology-induced [vegetative state/unresponsive wakeful syndrome (VS/UWS)] loss of consciousness in both human subjects and animals, we, in this study, suggest that the energetic-metabolic processes focusing on ATP, glucose, and γ-aminobutyrate/glutamate are indispensable for functional connectivity (FC) of normal brain networks that renders consciousness possible. Therefore, we describe the energetic-metabolic predispositions of consciousness (EPC) that complement the current theories focused on the neural correlates of consciousness (NCC).

Multimodal FDG-PET and EEG assessment improves diagnosis and prognostication of disorders of consciousness

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FDG-PET metabolic index of the best hemisphere is robust to diagnose MCS.

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FDG-PET slightly outperforms EEG-based automatic classification of conscious state.

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Optimal diagnostic performances are obtained by combining PET and EEG.

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PET and EEG combination identifies cortical activation suggestive of residual consciousness.

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PET and EEG combination also predict patients 6-month command-following.

Introduction

Functional brain-imaging techniques have revealed that clinical examination of disorders of consciousness (DoC) can underestimate the conscious level of patients. FDG-PET metabolic index of the best preserved hemisphere (MIBH) has been reported as a promising measure of consciousness but has never been externally validated and compared with other brain-imaging diagnostic procedures such as quantitative EEG.

Methods

FDG-PET, quantitative EEG and cognitive evoked potential using an auditory oddball paradigm were performed in minimally conscious state (MCS) and vegetative state (VS) patient. We compared out-sample diagnostic and prognostic performances of PET-MIBH and EEG-based classification of conscious state to the current behavioral gold-standard, the Coma Recovery Scale – revised (CRS-R).

Results

Between January 2016 and October 2019, 52 patients were included: 21 VS and 31 MCS. PET-MIBH had an AUC of 0.821 [0.694–0.930], sensitivity of 79% [62–91] and specificity of 78% [56–93], not significantly different from EEG (p = 0.628). Their combination accurately identified almost all MCS patients with a sensitivity of 94% [79–99%] and specificity of 67% [43–85]. Multimodal assessment also identified VS patients with neural correlate of consciousness (4/7 (57%) vs. 1/14 (7%), p = 0.025) and patients with 6-month recovery of command-following (9/24 (38%) vs. 0/16 (0%), p = 0.006), outperforming each technique taken in isolation.

Conclusion

FDG-PET MIBH is an accurate and robust procedure across sites to diagnose MCS. Its combination with EEG-based classification of conscious state not only optimizes diagnostic performances but also allows to detect covert cognition and to predict 6-month command-following recovery demonstrating the added value of multimodal assessment of DoC.

Human torpor: translating insights from nature into manned deep space expedition

During a long-duration manned spaceflight mission, such as flying to Mars and beyond, all crew members will spend a long period in an independent spacecraft with closed-loop bioregenerative life-support systems. Saving resources and reducing medical risks, particularly in mental heath, are key technology gaps hampering human expedition into deep space. In the 1960s, several scientists proposed that an induced state of suppressed metabolism in humans, which mimics 'hibernation', could be an ideal solution to cope with many issues during spaceflight. In recent years, with the introduction of specific methods, it is becoming more feasible to induce an artificial hibernation-like state (synthetic torpor) in non-hibernating species. Natural torpor is a fascinating, yet enigmatic, physiological process in which metabolic rate (MR), body core temperature (T_b ) and behavioural activity are reduced to save energy during harsh seasonal conditions. It employs a complex central neural network to orchestrate a homeostatic state of hypometabolism, hypothermia and hypoactivity in response to environmental challenges. The anatomical and functional connections within the central nervous system (CNS) lie at the heart of controlling synthetic torpor. Although progress has been made, the precise mechanisms underlying the active regulation of the torpor-arousal transition, and their profound influence on neural function and behaviour, which are critical concerns for safe and reversible human torpor, remain poorly understood. In this review, we place particular emphasis on elaborating the central nervous mechanism orchestrating the torpor-arousal transition in both non-flying hibernating mammals and non-hibernating species, and aim to provide translational insights into long-duration manned spaceflight. In addition, identifying difficulties and challenges ahead will underscore important concerns in engineering synthetic torpor in humans. We believe that synthetic torpor may not be the only option for manned long-duration spaceflight, but it is the most achievable solution in the foreseeable future. Translating the available knowledge from natural torpor research will not only benefit manned spaceflight, but also many clinical settings attempting to manipulate energy metabolism and neurobehavioural functions.

Intracellular ATP levels in mouse cortical excitatory neurons varies with sleep-wake states

Whilst the brain is assumed to exert homeostatic functions to keep the cellular energy status constant under physiological conditions, this has not been experimentally proven. Here, we conducted in vivo optical recordings of intracellular concentration of adenosine 5'-triphosphate (ATP), the major cellular energy metabolite, using a genetically encoded sensor in the mouse brain. We demonstrate that intracellular ATP levels in cortical excitatory neurons fluctuate in a cortex-wide manner depending on the sleep-wake states, correlating with arousal. Interestingly, ATP levels profoundly decreased during rapid eye movement sleep, suggesting a negative energy balance in neurons despite a simultaneous increase in cerebral hemodynamics for energy supply. The reduction in intracellular ATP was also observed in response to local electrical stimulation for neuronal activation, whereas the hemodynamics were simultaneously enhanced. These observations indicate that cerebral energy metabolism may not always meet neuronal energy demands, consequently resulting in physiological fluctuations of intracellular ATP levels in neurons.

Altered Global Brain Signal during Physiologic, Pharmacologic, and Pathologic States of Unconsciousness in Humans and Rats

BACKGROUND

Consciousness is supported by integrated brain activity across widespread functionally segregated networks. The functional magnetic resonance imaging-derived global brain signal is a candidate marker for a conscious state, and thus the authors hypothesized that unconsciousness would be accompanied by a loss of global temporal coordination, with specific patterns of decoupling between local regions and global activity differentiating among various unconscious states.

METHODS

Functional magnetic resonance imaging global signals were studied in physiologic, pharmacologic, and pathologic states of unconsciousness in human natural sleep (n = 9), propofol anesthesia (humans, n = 14; male rats, n = 12), and neuropathological patients (n = 21). The global signal amplitude as well as the correlation between global signal and signals of local voxels were quantified. The former reflects the net strength of global temporal coordination, and the latter yields global signal topography.

RESULTS

A profound reduction of global signal amplitude was seen consistently across the various unconscious states: wakefulness (median [1st, 3rd quartile], 0.46 [0.21, 0.50]) versus non-rapid eye movement stage 3 of sleep (0.30 [0.24, 0.32]; P = 0.035), wakefulness (0.36 [0.31, 0.42]) versus general anesthesia (0.25 [0.21, 0.28]; P = 0.001), healthy controls (0.30 [0.27, 0.37]) versus unresponsive wakefulness syndrome (0.22 [0.15, 0.24]; P < 0.001), and low dose (0.07 [0.06, 0.08]) versus high dose of propofol (0.04 [0.03, 0.05]; P = 0.028) in rats. Furthermore, non-rapid eye movement stage 3 of sleep was characterized by a decoupling of sensory and attention networks from the global network. General anesthesia and unresponsive wakefulness syndrome were characterized by a dissociation of the majority of functional networks from the global network. This decoupling, however, was dominated by distinct neuroanatomic foci (e.g., precuneus and anterior cingulate cortices).

CONCLUSIONS

The global temporal coordination of various modules across the brain may distinguish the coarse-grained state of consciousness versus unconsciousness, while the relationship between the global and local signals may define the particular qualities of a particular unconscious state.

Cysteine becomes conditionally essential during hypobaric hypoxia and regulates adaptive neuro-physiological responses through CBS/H2S pathway

Brain is well known for its disproportionate oxygen consumption and high energy-budget for optimal functioning. The decrease in oxygen supply to brain, thus, necessitates rapid activation of adaptive pathways - the absence of which manifest into vivid pathological conditions. Amongst these, oxygen sensing in glio-vascular milieu and H₂S-dependent compensatory increase in cerebral blood flow (CBF) is a major adaptive response. We had recently demonstrated that the levels of H₂S were significantly decreased during chronic hypobaric hypoxia (HH)-induced neuro-pathological effects. The mechanistic basis of this phenomenon, however, remained to be deciphered. We, here, describe experimental evidence for marked limitation of cysteine during HH - both in animal model as well as human volunteers ascending to high altitude. We show that the preservation of brain cysteine level, employing cysteine pro-drug (N-acetyl-_L-cysteine, NAC), markedly curtailed effects of HH - not only on endogenous H₂S levels but also, impairment of spatial reference memory in our animal model. We, further, present multiple lines of experimental evidence that the limitation of cysteine was causally governed by physiological propensity of brain to utilize cysteine, in cystathionine beta synthase (CBS)-dependent manner, past its endogenous replenishment potential. Notably, decrease in the levels of brain cysteine manifested despite positive effect (up-regulation) of HH on endogenous cysteine maintenance pathways and thus, qualifying cysteine as a conditionally essential nutrient (CEN) during HH. In brief, our data supports an adaptive, physiological role of CBS-mediated cysteine-utilization pathway - activated to increase endogenous levels of H₂S - for optimal responses of brain to hypobaric hypoxia.

On the emergence of cognition: from catalytic closure to neuroglial closure

In an analogous manner as occurred during the development of a connected metabolism that at some point reached characteristics associated with what is called "life"-due mainly to a catalytic closure phenomenon when chemicals started to autocatalyze themselves forming a closed web of chemical reactions-it is here proposed that cognition and consciousness (or features associated with them) arose as a consequence of another type of closure within the nervous system, the brain especially. Proper brain function requires an efficient web of connections and once certain complexity is attained due to the number and coordinated activities of the brain cell networks, the emergent properties of cognition and consciousness take place. Seeking to identify main features of the nervous system organization for optimal function, it is here proposed that while catalytic closure yielded life, neuroglial closure produced cognition/consciousness.

Propofol Anesthesia Alters Spatial and Topologic Organization of Rat Brain Metabolism

BACKGROUND

Loss of consciousness during anesthesia reduces local and global rate of cerebral glucose metabolism. Despite this, the influence of gradual anesthetic-induced changes on consciousness across the entire brain metabolic network has barely been studied. The purpose of the present study was to identify specific cerebral metabolic patterns characteristic of different consciousness/anesthesia states induced by intravenous anesthetic propofol.

METHODS

At various times, 20 Sprague-Dawley adult rats were intravenously administered three different dosages of propofol to induce different anesthetic states: mild sedation (20 mg · kg · h), deep sedation (40 mg · kg · h), and deep anesthesia (80 mg · kg · h). Using [F]fluorodeoxyglucose positron emission tomography brain imaging, alterations in the spatial pattern of metabolic distribution and metabolic topography were investigated by applying voxel-based spatial covariance analysis and graph-theory analysis.

RESULTS

Evident reductions were found in baseline metabolism along with altered metabolic spatial distribution during propofol-induced anesthesia. Moreover, graph-theory analysis revealed a disruption in global and local efficiency of the metabolic brain network characterized by decreases in metabolic connectivity and energy efficiency during propofol-induced deep anesthesia (mild sedation global efficiency/local efficiency = 0.6985/0.7190, deep sedation global efficiency/local efficiency = 0.7444/0.7875, deep anesthesia global efficiency/local efficiency = 0.4498/0.6481; mild sedation vs. deep sedation, global efficiency: P = 0.356, local efficiency: P = 0.079; mild sedation vs. deep anesthesia, global efficiency: P < 0.0001, local efficiency: P < 0.0001; deep sedation vs. deep anesthesia, global efficiency: P < 0.0001, local efficiency: P < 0.0001). A strong spatial correlation was also found between cerebral metabolism and metabolic connectivity strength, which decreased significantly with deepening anesthesia level (correlation coefficients: mild sedation, r = 0.55, deep sedation, r = 0.47; deep anesthesia, r = 0.23; P < 0.0001 between the sedation and deep anesthesia groups).

CONCLUSIONS

The data revealed anesthesia-related alterations in spatial and topologic organization of metabolic brain network, as well as a close relationship between metabolic connectivity and cerebral metabolism during propofol anesthesia. These findings may provide novel insights into the metabolic mechanism of anesthetic-induced loss of consciousness.

On a Simple General Principle of Brain Organization

A possible framework to characterize nervous system dynamics and its organization in conscious and unconscious states is introduced, derived from a high level perspective on the coordinated activity of brain cell ensembles. Some questions are best addressable in a global framework and here we build on past observations about the structure of configurations of brain networks in conscious and unconscious states and about neurophysiological results. Aiming to bind some results together into some sort of coherence with a central theme, the scenario that emerges underscores the crucial importance of the creation and dissipation of energy gradients in brain cellular ensembles resulting in maximization of the configurations in the functional connectivity among those networks that favor conscious awareness and healthy conditions. These considerations are then applied to indicate approaches that can be used to improve neuropathological syndromes.

Local oxygen homeostasis during various neuronal network activity states in the mouse hippocampus

Cortical information processing comprises various activity states emerging from timed synaptic excitation and inhibition. However, the underlying energy metabolism is widely unknown. We determined the cerebral metabolic rate of oxygen (CMRO2) along a tissue depth of <0.3 mm in the hippocampal CA3 region during various network activities, including gamma oscillations and sharp wave-ripples that occur during wakefulness and sleep. These physiological states associate with sensory perception and memory formation, and critically depend on perisomatic GABA inhibition. Moreover, we modelled vascular oxygen delivery based on quantitative microvasculature analysis. (1) Local CMRO2 was highest during gamma oscillations (3.4 mM/min), medium during sharp wave-ripples, asynchronous activity and isoflurane application (2.0-1.6 mM/min), and lowest during tetrodotoxin application (1.4 mM/min). (2) Energy expenditure of axonal and synaptic signaling accounted for >50% during gamma oscillations. (3) CMRO2 positively correlated with number and synchronisation of activated synapses, and neural multi-unit activity. (4) The median capillary distance was 44 µm. (5) The vascular oxygen partial pressure of 33 mmHg was needed to sustain oxidative phosphorylation during gamma oscillations. We conclude that gamma oscillations featuring high energetics require a hemodynamic response to match oxygen consumption of respiring mitochondria, and that perisomatic inhibition significantly contributes to the brain energy budget.

A Non-cognitive Behavioral Model for Interpreting Functional Neuroimaging Studies

The dominant model for interpreting brain imaging experiments, which we refer to as the Standard Cognitive Model (SCM), assumes that the brain is organized in support of mental processes that control behavior. However, functional neuroimaging experiments of cognitive tasks have not shown clear anatomic segregation between mental processes originally proposed by this model. This failing has been blamed on limitations in imaging technology and non-linearity in the brain's implementation of these processes. However, the validity of the underlying cognitive models used to describe the brain has rarely been questioned or directly tested against imaging results. We propose an alternative model of brain function, that we term the Non-cognitive Behavioral Model (NBM), which correlates observed human behavior directly with measured brain activity without making assumptions about intervening cognitive processes. Our model derives from behavioral psychology but is extended to include brain activity, in addition to behavior, as observables. A further extension is the role of neuroplasticity, as opposed to innate cognitive processes, in developing the brain's support of cognitive behavior. We present the theoretical basis with which the SCM maps cognitive processes onto functional magnetic resonance and positron emission tomography images and compare and contrast with the NBM. We also describe how the NBM can be used experimentally to study how the brain supports behavior. Two applications are presented that support the usefulness of the NBM. In one, the NBM use of the total functional imaging signal (not just the differences between states) provides a stronger correlation of neural activity with the behavioral state of consciousness than the SCM approach in both anesthesia and coma. The second example reviews studies of facial and object recognition that provide evidence for the NBM proposal that neuroplasticity and experience play key roles in the brain's support of recognition and other behaviors. The conclusions regarding neuroplasticity are then generalized to explain the incomplete functional segregation observed in the application of the SCM to neuroimaging.

State-Dependent Changes in Brain Glycogen Metabolism

A fundamental understanding of glycogen structure, concentration, polydispersity and turnover is critical to qualify the role of glycogen in the brain. These molecular and metabolic features are under the control of neuronal activity through the interdependent action of neuromodulatory tone, ionic homeostasis and availability of metabolic substrates, all variables that concur to define the state of the system. In this chapter, we briefly describe how glycogen responds to selected behavioral, nutritional, environmental, hormonal, developmental and pathological conditions. We argue that interpreting glycogen metabolism through the lens of brain state is an effective approach to establish the relevance of energetics in connecting molecular and cellular neurophysiology to behavior.

Consciousness as a Physical Process Caused by the Organization of Energy in the Brain

To explain consciousness as a physical process we must acknowledge the role of energy in the brain. Energetic activity is fundamental to all physical processes and causally drives biological behavior. Recent neuroscientific evidence can be interpreted in a way that suggests consciousness is a product of the organization of energetic activity in the brain. The nature of energy itself, though, remains largely mysterious, and we do not fully understand how it contributes to brain function or consciousness. According to the principle outlined here, energy, along with forces and work, can be described as actualized differences of motion and tension. By observing physical systems, we can infer there is something it is like to undergo actualized difference from the intrinsic perspective of the system. Consciousness occurs because there is something it is like, intrinsically, to undergo a certain organization of actualized differences in the brain.

Evaluating the gray and white matter energy budgets of human brain function

The insatiable appetite for energy to support human brain function is mainly supplied by glucose oxidation (CMR_glc(ox)). But how much energy is consumed for signaling and nonsignaling processes in gray/white matter is highly debated. We examined this issue by combining metabolic measurements of gray/white matter and a theoretical calculation of bottom-up energy budget using biophysical properties of neuronal/glial cells in conjunction with species-exclusive electrophysiological and morphological data. We calculated a CMR_glc(ox)-derived budget and confirmed it with experimental results measured by PET, autoradiography, ¹³C-MRS, and electrophysiology. Several conserved principles were observed regarding the energy costs for brain's signaling and nonsignaling components in both human and rat. The awake resting cortical signaling processes and mass-dependent nonsignaling processes, respectively, demand ∼70% and ∼30% of CMR_glc(ox). Inhibitory neurons and glia need 15-20% of CMR_glc(ox), with the rest demanded by excitatory neurons. Nonsignaling demands dominate in white matter, in near opposite contrast to gray matter demands. Comparison between ¹³C-MRS data and calculations suggests ∼1.2 Hz glutamatergic signaling rate in the awake human cortex, which is ∼4 times lower than signaling in the rat cortex. Top-down validated bottom-up budgets could allow computation of anatomy-based CMR_glc(ox) maps and accurate cellular level interpretation of brain metabolic imaging.

Cerebral Metabolic Changes During Sleep

PURPOSE OF REVIEW

The goal of the present paper is to review current literature supporting the occurrence of fundamental changes in brain energy metabolism during the transition from wakefulness to sleep.

RECENT FINDINGS

Latest research in the field indicates that glucose utilization and the concentrations of several brain metabolites consistently change across the sleep-wake cycle. Lactate, a product of glycolysis that is involved in synaptic plasticity, has emerged as a good biomarker of brain state. Sleep-induced changes in cerebral metabolite levels result from a shift in oxidative metabolism, which alters the reliance of brain metabolism upon carbohydrates. We found wide support for the notion that brain energetics is state dependent. In particular, fatty acids and ketone bodies partly replace glucose as cerebral energy source during sleep. This mechanism plausibly accounts for increases in biosynthetic pathways and functional alterations in neuronal activity associated with sleep. A better account of brain energy metabolism during sleep might help elucidate the long mysterious restorative effects of sleep for the whole organism.

Beyond static measures: A review of functional magnetic resonance spectroscopy and its potential to investigate dynamic glutamatergic abnormalities in schizophrenia

Abnormalities of the glutamate system are increasingly implicated in schizophrenia but their exact nature remains unknown. Proton magnetic resonance spectroscopy (¹H-MRS), while fundamental in revealing glutamatergic alterations in schizophrenia, has, until recently, been significantly limited and thought to only provide static measures. Functional magnetic resonance spectroscopy (fMRS), which uses sequential scans for dynamic measurement of a range of brain metabolites in activated brain areas, has lately been applied to a variety of task or stimulus conditions, producing interesting insights into neurometabolite responses to neural activation. Here, we summarise the existing ¹H-MRS studies of brain glutamate in schizophrenia. We then present a comprehensive review of research studies that have utilised fMRS, and lastly consider how fMRS methods might further the understanding of glutamatergic abnormalities in schizophrenia.

Consciousness: a unique way of processing information

In this article, I argue that consciousness is a unique way of processing information, in that: it produces information, rather than purely transmitting it; the information it produces is meaningful for us; the meaning it has is always individuated. This uniqueness allows us to process information on the basis of our personal needs and ever-changing interactions with the environment, and consequently to act autonomously. Three main basic cognitive processes contribute to realize this unique way of information processing: the self, attention and working memory. The self, which is primarily expressed via the central and peripheral nervous systems, maps our body, the environment, and our relations with the environment. It is the primary means by which the complexity inherent to our composite structure is reduced into the "single voice" of a unique individual. It provides a reference system that (albeit evolving) is sufficiently stable to define the variations that will be used as the raw material for the construction of conscious information. Attention allows for the selection of those variations in the state of the self that are most relevant in the given situation. Attention originates and is deployed from a single locus inside our body, which represents the center of the self, around which all our conscious experiences are organized. Whatever is focused by attention appears in our consciousness as possessing a spatial quality defined by this center and the direction toward which attention is focused. In addition, attention determines two other features of conscious experience: periodicity and phenomenal quality. Self and attention are necessary but not sufficient for conscious information to be produced. Complex forms of conscious experiences, such as the various modes of givenness of conscious experience and the stream of consciousness, need a working memory mechanism to assemble the basic pieces of information selected by attention.

Advances in Imaging Brain Metabolism

Metabolism is central to neuroimaging because it can reveal pathways by which neuronal and glial cells use nutrients to fuel their growth and function. We focus on advanced magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) methods used in brain metabolic studies. ¹⁷O-MRS and ³¹P-MRS, respectively, provide rates of oxygen use and ATP synthesis inside mitochondria, whereas ¹⁹F-MRS enables measurement of cytosolic glucose metabolism. Calibrated functional MRI (fMRI), an advanced form of fMRI that uses contrast generated by deoxyhemoglobin, provides maps of oxygen use that track neuronal firing across brain regions. ¹³C-MRS is the only noninvasive method of measuring both glutamatergic neurotransmission and cell-specific energetics with signaling and nonsignaling purposes. Novel MRI contrasts, arising from endogenous diamagnetic agents and exogenous paramagnetic agents, permit pH imaging of glioma. Overall, these magnetic resonance methods for imaging brain metabolism demonstrate translational potential to better understand brain disorders and guide diagnosis and treatment.

Regional knockdown of NDUFS4 implicates a thalamocortical circuit mediating anesthetic sensitivity

Knockout of the mitochondrial complex I protein, NDUFS4, profoundly increases sensitivity of mice to volatile anesthetics. In mice carrying an Ndufs4lox/lox gene, adeno-associated virus expressing Cre recombinase was injected into regions of the brain postulated to affect sensitivity to volatile anesthetics. These injections generated otherwise phenotypically wild type mice with region-specific, postnatal inactivation of Ndufs4, minimizing developmental effects of gene loss. Sensitivities to the volatile anesthetics isoflurane and halothane were measured using loss of righting reflex (LORR) and movement in response to tail clamp (TC) as endpoints. Knockdown (KD) of Ndufs4 in the vestibular nucleus produced resistance to both anesthetics for movement in response to TC. Ndufs4 loss in the central and dorsal medial thalami and in the parietal association cortex increased anesthetic sensitivity to both TC and LORR. Knockdown of Ndufs4 only in the parietal association cortex produced striking hypersensitivity for both endpoints, and accounted for half the total change seen in the global KO (Ndufs4(KO)). Excitatory synaptic transmission in the parietal association cortex in slices from Ndufs4(KO) animals was hypersensitive to isoflurane compared to control slices. We identified a direct neural circuit between the parietal association cortex and the central thalamus, consistent with a model in which isoflurane sensitivity is mediated by a thalamic signal relayed through excitatory synapses to the parietal association cortex. We postulate that the thalamocortical circuit is crucial for maintenance of consciousness and is disrupted by the inhibitory effects of isoflurane/halothane on mitochondria.

Consciousness Level and Recovery Outcome Prediction Using High-Order Brain Functional Connectivity Network

Based on the neuroimaging data from a large set of acquired brain injury patients, we investigate the feasibility of using machine learning for automatic prediction of individual consciousness level. Rather than using the traditional Pearson's correlation-based brain functional network, which measures only the simple temporal synchronization of the BOLD signals from each pair of brain regions, we construct a high-order brain functional network that is capable of characterizing topographical information-based high-level functional associations among brain regions. In such a high-order brain network, each node represents the community of a brain region, described by a set of this region's low-order functional associations with other brain regions, and each edge characterizes topographical similarity between a pair of such communities. Experimental results show that the high-order brain functional network enables a significant better classification for consciousness level and recovery outcome prediction.

How spontaneous brain activity and narcissistic features shape social interaction

There is an increasing interest in how ongoing spontaneous brain activity and personality provide a predisposition for the processing of environmental demands. It further has been suggested that the brain has an inherent sensitivity to the social environment. Here we tested in healthy volunteers if spontaneous brain activity contributes to a predisposition for social behavior and how this is modulated by narcissistic personality features associated with poor interpersonal functioning. Functional magnetic resonance imaging included a resting state and an experimental paradigm focusing on the anticipation of actively touching an animate (human hand) versus an inanimate target (mannequin hand). The experimental task induced a significant modulation of neural activity in left postcentral gyrus (PostCG), right culmen and, co-varying with narcissistic features, in right anterior insula (AI). Neural activity in anticipation of the animate target significantly correlated with spontaneous activity during the resting state indexed by the Power Law Exponent (PLE) in PostCG and AI. Finally, the correlation between spontaneous and task-induced activity in AI was mediated by narcissistic features. These findings provide novel evidence for a relationship between intrinsic brain activity and social behavior and show how personality could contribute to individual differences in our predisposition to approach the animate world.

How do the brain's time and space mediate consciousness and its different dimensions? Temporo-spatial theory of consciousness (TTC)

Time and space are the basic building blocks of nature. As a unique existent in nature, our brain exists in time and takes up space. The brain's activity itself also constitutes and spreads in its own (intrinsic) time and space that is crucial for consciousness. Consciousness is a complex phenomenon including different dimensions: level/state, content/form, phenomenal aspects, and cognitive features. We propose a Temporo-spatial Theory of Consciousness (TTC) focusing primarily on the temporal and spatial features of the brain activity. We postulate four different neuronal mechanisms accounting for the different dimensions of consciousness: (i) "temporo-spatial nestedness" of the spontaneous activity accounts for the level/state of consciousness as neural predisposition of consciousness (NPC); (ii) "temporo-spatial alignment" of the pre-stimulus activity accounts for the content/form of consciousness as neural prerequisite of consciousness (preNCC); (iii) "temporo-spatial expansion" of early stimulus-induced activity accounts for phenomenal consciousness as neural correlates of consciousness (NCC); (iv) "temporo-spatial globalization" of late stimulus-induced activity accounts for the cognitive features of consciousness as neural consequence of consciousness (NCCcon).

[18F]Fludeoxyglucose-Positron Emission Tomography Evidence for Cerebral Hypermetabolism in the Awake State in Narcolepsy and Idiopathic Hypersomnia

Background

Changes in structural and functional central nervous system have been reported in narcolepsy, with large discrepancies between studies. No study has investigated yet spontaneous brain activity at wake in idiopathic hypersomnia (IH). We compared relative changes in regional brain metabolism in two central hypersomnia conditions with different clinical features, namely narcolepsy type 1 (NT1) and IH, and in healthy controls.

Methods

Sixteen patients [12 males, median age 30 years (17–78)] with NT1, nine patients [2 males, median age 27 years (20–60)] with IH and 19 healthy controls [16 males, median age 36 years (17–78)] were included. ¹⁸F-fludeoxyglucose positron emission tomography (PET) was performed in all drug-free subjects under similar conditions and instructions to stay in a wake resting state.

Results

We found increased metabolism in the anterior and middle cingulate and the insula in the two pathological conditions as compared to healthy controls. The reverse contrast failed to evidence hypometabolism in patients vs. controls. Comparisons between patient groups were non-significant. At sub-statistical threshold, we found higher right superior occipital gyrus glucose metabolism in narcolepsy and higher middle orbital cortex and supplementary motor area metabolism in IH, findings that require further confirmation.

Conclusion

There is significant hypermetabolism in narcolepsy and IH in the wake resting state in a set of brain regions constitutive of the salience cortical network that may reflect a compensatory neurocircuitry activity secondary to sleepiness. Metabolic differences between the two disorders within the executive-control network may be a signature of abnormally functioning neural system leading to persistent drowsiness typical of IH.

Clinical Concepts Emerging from fMRI Functional Connectomics

Recent advances in connectomics have led to a synthesis of perspectives regarding the brain's functional organization that reconciles classical concepts of localized specialization with an appreciation for properties that emerge from interactions across distributed functional networks. This provides a more comprehensive framework for understanding neural mechanisms of normal cognition and disease. Although fMRI has not become a routine clinical tool, research has already had important influences on clinical concepts guiding diagnosis and patient management. Here we review illustrative examples. Studies demonstrating the network plasticity possible in adults and the global consequences of even focal brain injuries or disease both have had substantial impact on modern concepts of disease evolution and expression. Applications of functional connectomics in studies of clinical populations are challenging traditional disease classifications and helping to clarify biological relationships between clinical syndromes (and thus also ways of extending indications for, or "re-purposing," current treatments). Large datasets from prospective, longitudinal studies promise to enable the discovery and validation of functional connectomic biomarkers with the potential to identify people at high risk of disease before clinical onset, at a time when treatments may be most effective. Studies of pain and consciousness have catalyzed reconsiderations of approaches to clinical management, but also have stimulated debate about the clinical meaningfulness of differences in internal perceptual or cognitive states inferred from functional connectomics or other physiological correlates. By way of a closing summary, we offer a personal view of immediate challenges and potential opportunities for clinically relevant applications of fMRI-based functional connectomics.

High-resolution functional MRI identified distinct global intrinsic functional networks of nociceptive posterior insula and S2 regions in squirrel monkey brain

Numerous functional imaging and electrophysiological studies in humans and animals indicate that the two contiguous areas of secondary somatosensory cortex (S2) and posterior insula (pIns) are core regions in nociceptive processing and pain perception. In this study, we tested the hypothesis that the S2-pIns connection serves as a hub for connecting distinct sensory and affective nociceptive processing networks in the squirrel monkey brain. At 9.4T, we first mapped the brain regions that respond to nociceptive heat stimuli with high-resolution fMRI, and then used seed-based resting-state fMRI (rsfMRI) analysis to delineate and refine the global intrinsic functional connectivity circuits of the proximal S2 and pIns regions. In each subject, nociceptive (47.5°C) heat-evoked fMRI activations were detected in many brain regions, including primary somatosensory (S1), S2, pIns, area 7b, anterior cingulate cortex (ACC), primary motor cortex, prefrontal cortex, supplementary motor area, thalamus, and caudate. Using the heat-evoked fMRI activation foci in S2 and pIns as the seeds, voxel-wise whole-brain resting-state functional connectivity (rsFC) analysis revealed strong functional connections between contralateral S2 and pIns, as well as their corresponding regions in the ipsilateral hemisphere. Spatial similarity and overlap analysis identified each region as part of two distinct intrinsic functional networks with 7% overlap: sensory S2-S1-area 7b and affective pIns-ACC-PCC networks. Moreover, a high degree of overlap was observed between the combined rsFC maps of nociceptive S2 and pIns regions and the nociceptive heat-evoked activation map. In summary, our study provides evidence for the existence of two distinct intrinsic functional networks for S2 and pIns nociceptive regions, and these two networks are joined via the S2-pIns connection. Brain regions that are involved in processing nociceptive inputs are also highly interconnected at rest. The presence of robust and distinct S1-S2-area 7b and pIns-ACC-PCC rsFC networks under anesthesia underscores their fundamental roles in processing nociceptive information.

Multi-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks

Anesthesia-induced changes in functional connectivity and cerebral blow flow (CBF) in large-scale brain networks have emerged as key markers of reduced consciousness. However, studies of functional connectivity disagree on which large-scale networks are altered or preserved during anesthesia, making it difficult to find a consensus amount studies. Additionally, pharmacological alterations in CBF could amplify or occlude changes in connectivity due to the shared variance between CBF and connectivity. Here, we used data-driven connectivity methods and multi-modal imaging to investigate shared and unique neural correlates of reduced consciousness for connectivity in large-scale brain networks. Rs-fMRI and CBF data were collected from the same subjects during an awake and deep sedation condition induced by propofol. We measured whole-brain connectivity using the intrinsic connectivity distribution (ICD), a method not reliant on pre-defined seed regions, networks of interest, or connectivity thresholds. The shared and unique variance between connectivity and CBF were investigated. Finally, to account for shared variance, we present a novel extension to ICD that incorporates cerebral blood flow (CBF) as a scaling factor in the calculation of global connectivity, labeled CBF-adjusted ICD). We observed altered connectivity in multiple large-scale brain networks including the default mode (DMN), salience, visual, and motor networks and reduced CBF in the DMN, frontoparietal network, and thalamus. Regional connectivity and CBF were significantly correlated during both the awake and propofol condition. Nevertheless changes in connectivity and CBF between the awake and deep sedation condition were only significantly correlated in a subsystem of the DMN, suggesting that, while there is significant shared variance between the modalities, changes due to propofol are relatively unique. Similar, but less significant, results were observed in the CBF-adjusted ICD analysis, providing additional evidence that connectivity differences were not fully explained by CBF. In conclusion, these results provide further evidence of alterations in large-scale brain networks are associated with reduced consciousness and suggest that different modalities capture unique aspects of these large scale changes.