Default-mode network functional connectivity is closely related to metabolic activity

Metabolic Brain PET Connectivity

This review examines the role of metabolic connectivity based on fluorodeoxyglucose-PET in understanding brain network organization across neurologic disorders, with a focus on neurodegenerative diseases. The article explores key methodologies for metabolic connectivity study and highlights altered connectivity patterns in Alzheimer's, Parkinson's, frontotemporal dementia, and other conditions. It also discusses emerging applications, including single-subject analyses and brain-organ interactions.

Altered neurovascular coupling and structure-function coupling in Moyamoya disease affect postoperative collateral formation

Chronic ischemia in moyamoya disease (MMD) impaired white matter microstructure and neural functional network. However, the coupling between cerebral blood flow (CBF) and functional connectivity and the association between structural and functional network are largely unknown. 38 MMD patients and 20 sex/age-matched healthy controls (HC) were included for T1-weighted imaging, arterial spin labeling imaging, resting-state functional MRI and diffusion tensor imaging. All patients had preoperative and postoperative digital subtraction angiography. Upon constructing the structural connectivity (SC) and functional connectivity (FC) networks, the SC-FC coupling was calculated. After obtaining the graph theoretical parameters, neurovascular coupling represented the spatial correlation between node degree centrality (DC) of functional networks and CBF. The CBF-DC coupling and SC-FC coupling were compared between MMD and HC groups. We further analyzed the correlation between coupling indexes and cognitive scores, as well as postoperative collateral formation. Compared with HC, CBF-DC coupling was decreased in MMD (p = 0.021), especially in the parietal lobe (p = 0.047). SC-FC coupling in MMD decreased in frontal, occipital, and subcortical regions. Cognitive scores were correlated with the CBF-DC coupling in frontal lobes (r = 0.394, p = 0.029) and SC-FC coupling (r = 0.397, p = 0.027). The CBF-DC coupling of patients with good postoperative collateral formation was higher (p = 0.041). Overall, neurovascular decoupling and structure-functional decoupling at the cortical level may be the underlying neuropathological mechanisms of MMD.

Effects of four-week intranasal oxytocin administration on large-scale brain networks in older adults

Oxytocin (OT) is a crucial modulator of social cognition and behavior. Previous work primarily examined effects of acute intranasal oxytocin administration (IN-OT) in younger males on isolated brain regions. Not well understood are (i) chronic IN-OT effects, (ii) in older adults, (iii) on large-scale brain networks, representative of OT's wider-ranging brain mechanisms. To address these research gaps, 60 generally healthy older adults (mean age = 70.12 years, range = 55-83) were randomly assigned to self-administer either IN-OT or placebo twice daily via nasal spray over four weeks. Chronic IN-OT reduced resting-state functional connectivity (rs-FC) of both the right insula and the left middle cingulate cortex with the salience network but enhanced rs-FC of the left medial prefrontal cortex with the default mode network as well as the left thalamus with the basal ganglia-thalamus network. No significant chronic IN-OT effects were observed for between-network rs-FC. However, chronic IN-OT increased selective rs-FC of the basal ganglia-thalamus network with the salience network and the default mode network, indicative of more specialized, efficient communication between these networks. Directly comparing chronic vs. acute IN-OT, reduced rs-FC of the right insula with the salience network and between the default mode network and the basal ganglia-thalamus network, and greater selective rs-FC of the salience network with the default mode network and the basal ganglia-thalamus network, were more pronounced after chronic than acute IN-OT. Our results delineate the modulatory role of IN-OT on large-scale brain networks among older adults.

Relation Between Abnormal Spontaneous Brain Activity and Altered Neuromuscular Activation of Lumbar Paraspinal Muscles in Chronic Low Back Pain

OBJECTIVE

To investigate the neural mechanism underlying functional reorganization and motor coordination strategies in patients with chronic low back pain (cLBP).

DESIGN

A case-control study based on data collected during routine clinical practice.

SETTING

This study was conducted at a university hospital.

PARTICIPANTS

Fifteen patients with cLBP and 15 healthy controls.

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Whole brain blood oxygen level-dependent signals were measured using functional magnetic resonance imaging and amplitude of low-frequency fluctuation (ALFF) method to identify pain-induced changes in regional spontaneous brain activity. A novel approach based on the surface electromyogram (EMG) system and fine-wire electrodes was used to record EMG signals in the deep multifidus, superficial multifidus, and erector spinae.

RESULTS

In cLBP, compared with healthy groups, ALFF was higher in the medial prefrontal, primary somatosensory, primary motor, and inferior temporal cortices, whereas it was lower in the cerebellum and anterior cingulate and posterior cingulate cortices. Furthermore, the decrease in the average EMG activity of the 3 lumbar muscles in the cLBP group was positively correlated with the ALFF values of the primary somatosensory cortex, motor cortex, precuneus, and middle temporal cortex but significantly negatively correlated with the ALFF values of the medial prefrontal and inferior temporal cortices. Interestingly, the correlation between the functional activity in the cerebellum and the EMG activity varied in the lumbar muscles.

CONCLUSIONS

These findings suggest a functional association between changes in spontaneous brain activity and altered voluntary neuromuscular activation patterns of the lumbar paraspinal muscles, providing new insights into the mechanisms underlying pain chronicity as well as important implications for developing novel therapeutic targets of cLBP.

ℛSCZ: A Riemannian schizophrenia diagnosis framework based on the multiplexity of EEG-based dynamic functional connectivity patterns

Abnormal electrophysiological (EEG) activity has been largely reported in schizophrenia (SCZ). In the last decade, research has focused to the automatic diagnosis of SCZ via the investigation of an EEG aberrant activity and connectivity linked to this mental disorder. These studies followed various preprocessing steps of EEG activity focusing on frequency-dependent functional connectivity brain network (FCBN) construction disregarding the topological dependency among edges. FCBN belongs to a family of symmetric positive definite (SPD) matrices forming the Riemannian manifold. Due to its unique geometric properties, the whole analysis of FCBN can be performed on the Riemannian geometry of the SPD space. The advantage of the analysis of FCBN on the SPD space is that it takes into account all the pairwise interdependencies as a whole. However, only a few studies have adopted a FCBN analysis on the SPD manifold, while no study exists on the analysis of dynamic FCBN (dFCBN) tailored to SCZ. In the present study, I analyzed two open EEG-SCZ datasets under a Riemannian geometry of SPD matrices for the dFCBN analysis proposing also a multiplexity index that quantifies the associations of multi-frequency brainwave patterns. I adopted a machine learning procedure employing a leave-one-subject-out cross-validation (LOSO-CV) using snapshots of dFCBN from (N-1) subjects to train a battery of classifiers. Each classifier operated in the inter-subject dFCBN distances of sample covariance matrices (SCMs) following a rhythm-dependent decision and a multiplex-dependent one. The proposed ℛSCZ decoder supported both the Riemannian geometry of SPD and the multiplexity index DC reaching an absolute accuracy (100 %) in both datasets in the virtual default mode network (DMN) source space.

PET-based brain molecular connectivity in neurodegenerative disease

PURPOSE OF REVIEW

Molecular imaging has traditionally been used and interpreted primarily in the context of localized and relatively static neurochemical processes. New understanding of brain function and development of novel molecular imaging protocols and analysis methods highlights the relevance of molecular networks that co-exist and interact with functional and structural networks. Although the concept and evidence of disease-specific metabolic brain patterns has existed for some time, only recently has such an approach been applied in the neurotransmitter domain and in the context of multitracer and multimodal studies. This review briefly summarizes initial findings and highlights emerging applications enabled by this new approach.

RECENT FINDINGS

Connectivity based approaches applied to molecular and multimodal imaging have uncovered molecular networks with neurodegeneration-related alterations to metabolism and neurotransmission that uniquely relate to clinical findings; better disease stratification paradigms; an improved understanding of the relationships between neurochemical and functional networks and their related alterations, although the directionality of these relationships are still unresolved; and a new understanding of the molecular underpinning of disease-related alteration in resting-state brain activity.

SUMMARY

Connectivity approaches are poised to greatly enhance the information that can be extracted from molecular imaging. While currently mostly contributing to enhancing understanding of brain function, they are highly likely to contribute to the identification of specific biomarkers that will improve disease management and clinical care.

A Multimodal Meta-Analytical Evidence of Functional and Structural Brain Abnormalities Across Alzheimer's Disease Spectrum

BACKGROUND

Numerous neuroimaging studies have reported that Alzheimer's disease (AD) spectrum have been linked to alterations in intrinsic functional activity and cortical thickness (CT) of some brain areas. However, the findings have been inconsistent and the correlation with the transcriptional profile and neurotransmitter systems remain largely unknown.

METHODS

We conducted a meta-analysis to identify multimodal differences in the amplitude of low-frequency fluctuation (ALFF)/fractional ALFF (fALFF) and CT in patients with AD and preclinical AD compared to healthy controls (HCs), using the Seed-based d Mapping with Permutation of Subject Images software. Transcriptional data were retrieved from the Allen Human Brain Atlas. The atlas-based nuclear imaging-derived neurotransmitter maps were investigated by JuSpace toolbox.

RESULTS

We included 26 ALFF/fALFF studies comprising 884 patients with AD and 1,020 controls, along with 52 studies comprising 2,046 patients with preclinical AD and 2,336 controls. For CT, we included 11 studies comprising 353 patients with AD and 330 controls. Overall, compared to HCs, patients with AD showed decreased ALFF/fALFF in the bilateral posterior cingulate gyrus (PCC)/precuneus and right angular gyrus, as well as increased ALFF/fALFF in the bilateral parahippocampal gyrus (PHG). Patients with peclinical AD showed decreased ALFF/fALFF in the left precuneus. Additionally, patients with AD displayed decreased CT in the bilateral PHG, left PCC, bilateral orbitofrontal cortex, sensorimotor areas and temporal lobe. Furthermore, gene sets related to brain structural and functional changes in AD and preclincal AD were enriched for G protein-coupled receptor signaling pathway, ion gated channel activity, and components of biological membrane. Functional and structural alterations in AD and preclinical AD were spatially associated with dopaminergic, serotonergic, and GABAergic neurotransmitter systems.

CONCLUSIONS

The multimodal meta-analysis demonstrated that patients with AD exhibited convergent functional and structural alterations in the PCC/precuneus and PHG, as well as cortical thinning in the primary sensory and motor areas. Furthermore, patients with preclinical AD showed reduced functional activity in the precuneus. AD and preclinical AD showed genetic modulations/neurotransmitter deficits of brain functional and structural impairments. These findings may provide new insights into the pathophysiology of the AD spectrum.

Increased Resting-State Functional Connectivity in Patients With Autoimmune Addison Disease

CONTEXT

Individuals with autoimmune Addison disease (AAD) take replacement medication for the lack of adrenal-derived glucocorticoid (GC) and mineralocorticoid hormones from diagnosis. The brain is highly sensitive to these hormones, but the consequence of having AAD for brain health has not been widely addressed.

OBJECTIVE

The present study compared resting-state functional connectivity (rs-fc) of the brain between individuals with AAD and healthy controls.

METHODS

Fifty-seven patients with AAD (33 female) and 69 healthy controls (39 female), aged 19 to 43 years were scanned with 3-T magnetic resonance imaging (MRI).

RESULTS

Independent component and subsequent dual regression analyses revealed that individuals with AAD had stronger rs-fc compared to controls in 3 networks: the bilateral orbitofrontal cortex (OFC), the left medial visual and left posterior default mode network. A higher GC replacement dose was associated with stronger rs-fc in a small part of the left OFC in patients. We did not find any clear associations between rs-fc and executive functions or mental fatigue.

CONCLUSION

Our results suggest that having AAD affects the baseline functional organization of the brain and that current treatment strategies of AAD may be one risk factor.

Alteration of functional connectivity network in population of objectively-defined subtle cognitive decline

The objectively-defined subtle cognitive decline individuals had higher progression rates of cognitive decline and pathological deposition than healthy elderly, indicating a higher risk of progressing to Alzheimer's disease. However, little is known about the brain functional alterations during this stage. Thus, we aimed to investigate the functional network patterns in objectively-defined subtle cognitive decline cohort. Forty-two cognitive normal, 29 objectively-defined subtle cognitive decline and 55 mild cognitive impairment subjects were included based on neuropsychological measures from the Alzheimer's disease Neuroimaging Initiative dataset. Thirty cognitive normal, 22 objectively-defined subtle cognitive declines and 48 mild cognitive impairment had longitudinal MRI data. The degree centrality and eigenvector centrality for each participant were calculated by using resting-state functional MRI. For cross-sectional data, analysis of covariance was performed to detect between-group differences in degree centrality and eigenvector centrality after controlling age, sex and education. For longitudinal data, repeated measurement analysis of covariance was used for comparing the alterations during follow-up period among three groups. In order to classify the clinical significance, we correlated degree centrality and eigenvector centrality values to Alzheimer's disease biomarkers and cognitive function. The results of analysis of covariance showed significant between-group differences in eigenvector centrality and degree centrality in left superior temporal gyrus and left precuneus, respectively. Across groups, the eigenvector centrality value of left superior temporal gyrus was positively related to recognition scores in auditory verbal learning test, whereas the degree centrality value of left precuneus was positively associated with mini-mental state examination total score. For longitudinal data, the results of repeated measurement analysis of covariance indicated objectively-defined subtle cognitive decline group had the highest declined rate of both eigenvector centrality and degree centrality values than other groups. Our study showed an increased brain functional connectivity in objectively-defined subtle cognitive decline individuals at both local and global level, which were associated with Alzheimer's disease pathology and neuropsychological assessment. Moreover, we also observed a faster declined rate of functional network matrix in objectively-defined subtle cognitive decline individuals during the follow-ups.

Fragmentation of functional resting state brain networks in a transgenic mouse model of tau pathology: A metabolic connectivity study using [18F]FDG-PET

In a previous study, regional reductions in cerebral glucose metabolism have been demonstrated in the tauopathy mouse model rTg4510 (Endepols et al., 2022). Notably, glucose hypometabolism was present in some brain regions without co-localized synaptic degeneration measured with [18F]UCB-H. We hypothesized that in those regions hypometabolism may reflect reduced functional connectivity rather than synaptic damage. To test this hypothesis, we performed seed-based metabolic connectivity analyses using [18F]FDG-PET data in this mouse model. Eight rTg4510 mice at the age of seven months and 8 non-transgenic littermates were injected intraperitoneally with 11.1 ± 0.8 MBq [18F]FDG and spent a 35-min uptake period awake in single cages. Subsequently, they were anesthetized and measured in a small animal PET scanner for 30 min. Three seed-based connectivity analyses were performed per group. Seeds were selected for apparent mismatch between [18F]FDG and [18F]UCB-H. A seed was placed either in the medial orbitofrontal cortex, dorsal hippocampus or dorsal thalamus, and correlated with all other voxels of the brain across animals. In the control group, the emerging correlative pattern was strongly overlapping for all three seed locations, indicating a uniform fronto-thalamo-hippocampal resting state network. In contrast, rTg4510 mice showed three distinct networks with minimal overlap. Frontal and thalamic networks were greatly diminished. The hippocampus, however, formed a new network with the whole parietal cortex. We conclude that resting-state functional networks are fragmented in the brain of rTg4510 mice. Thus, hypometabolism can be explained by reduced functional connectivity of brain areas devoid of tau-related pathology, such as the thalamus.

Topographic metabolism-function relationships in Alzheimer's disease: A simultaneous PET/MRI study

Disruptions of neural metabolism and function occur in parallel during Alzheimer's disease (AD). While many studies have shown diverse metabolic-functional relationships in specific brain regions, much less is known about how large-scale network-level functional activity is associated with the topology of metabolism in AD. In this study, we took the advantages of simultaneous PET/MRI and multivariate analyses to investigate the associations between AD-related stereotypical spatial patterns (topographies) of glucose metabolism, measured by fluorodeoxyglucose PET, and functional connectivity, measured by resting-state functional MRI. A total of 101 participants, including 37 patients with AD, 25 patients with mild cognitive impairment (MCI), and 39 cognitively normal controls, underwent PET/MRI scans and cognitive assessments. Three pairs of distinct but optimally correlated metabolic and functional topographies were identified, encompassing large-scale networks including the default-mode, executive and control, salience, attention, and subcortical networks. Importantly, the metabolic-functional associations were not only limited to one-to-one-corresponding regions, but also occur in remote and non-overlapping regions. Furthermore, both glucose metabolism and functional connectivity, as well as their linkages, exhibited various degrees of disruptions in patients with MCI and AD, and were correlated with cognitive decline. In conclusion, our results support distributed and heterogeneous topographic associations between metabolism and function, which are jeopardized by AD. Findings of this study may deepen our understanding of the pathological mechanism of AD through the perspectives of both local energy efficiency and long-term interactions between synaptic disruption and functional disconnection contributing to the clinical symptomatology in AD.

Regional cerebral metabolism alterations and functional connectivity in individuals with opioid use disorder: An integrated resting-state PET/fMRI study

Individuals with opioid use disorder (OUD) have been reported to show abnormal brain metabolism and impaired coupling among brain networks such as the default mode network (DMN), salience network (SN), and executive control network (ECN). However, the characteristics of brain glucose metabolism and its related functions in the brain networks in individuals with OUD remain unknown. Thirty-six individuals with OUD and thirty matched healthy controls (HCs) were recruited in this integrated positron emission tomography/magnetic resonance imaging (PET/MRI) study. Differences in glucose metabolism were analyzed by using 18F-fluorodeoxyglucose (18F-FDG), and the corresponding coupling characteristics of the individuals with OUD were also analyzed. The individuals with OUD showed widespread bilateral hypometabolism in the middle temporal gyrus (MTG), superior temporal gyrus, angular gyrus, supramarginal gyrus, inferior parietal lobe, Rolandic operculum, and left insula, but obvious hypermetabolism in the brainstem and left cerebellum. Meanwhile, in individuals with OUD, the hypometabolism of right MTG which is included in the DMN was accompanied by decreased coupling with the left superior frontal gyrus and right superior parietal gyrus which are included in the ECN. Furthermore, individuals with OUD showed a positive correlation between the duration of heroin use and glucose metabolism of the left MTG. The individuals with OUD were characterized by widespread bilateral hypometabolism in the temporal and parietal regions but obvious hypermetabolism in the brainstem and left cerebellum. The results suggest that the hypometabolism in the temporal and parietal regions might be related to DMN dysfunction and the hypermetabolism in the brainstem and left cerebellum may be compensate for other brain regions showing hypometabolism. In particular, hypometabolism in the self-referential-related DMN regions in OUD might attenuate their relationships with the inhibitory-control-related ECN regions. These findings highlight the importance of evaluating the metabolic and functional profiles of the right MTG in future studies on the treatment of OUD.

Plasma Neurofilament Light Relates to Divergent Default and Salience Network Connectivity in Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia

Background

Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) show differential vulnerability to large-scale brain functional networks. Plasma neurofilament light (NfL), a promising biomarker of neurodegeneration, has been linked in AD patients to glucose metabolism changes in AD-related regions. However, it is unknown whether plasma NfL would be similarly associated with disease-specific functional connectivity changes in AD and bvFTD.

Objective

Our study examined the associations between plasma NfL and functional connectivity of the default mode and salience networks in patients with AD and bvFTD.

Methods

Plasma NfL and neuroimaging data from patients with bvFTD (n = 16) and AD or mild cognitive impairment (n = 38; AD + MCI) were analyzed. Seed-based functional connectivity maps of key regions within the default mode and salience networks were obtained and associated with plasma NfL in these patients.

RESULTS

We demonstrated divergent associations between NfL and functional connectivity in AD + MCI and bvFTD patients. Specifically, AD + MCI patients showed lower default mode network functional connectivity with higher plasma NfL, while bvFTD patients showed lower salience network functional connectivity with higher plasma NfL. Further, lower NfL-related default mode network connectivity in AD + MCI patients was associated with lower Montreal Cognitive Assessment scores and higher Clinical Dementia Rating sum-of-boxes scores, although NfL-related salience network connectivity in bvFTD patients was not associated with Neuropsychiatric Inventory Questionnaire scores.

CONCLUSIONS

Our findings indicate that plasma NfL is differentially associated with brain functional connectivity changes in AD and bvFTD.

White matter hyperintensity volume modifies the association between CSF vascular inflammatory biomarkers and regional FDG-PET along the Alzheimer's disease continuum

In older adults with abnormal levels of Alzheimer's disease neuropathology, lower cerebrospinal fluid (CSF) vascular endothelial growth factor (VEGF) levels are associated with lower [¹⁸F]-fluorodeoxyglucose positron emission tomography (FDG-PET) signal, but whether this association is (1) specific to VEGF or broadly driven by vascular inflammation, or (2) modified by vascular risk (e.g., white matter hyperintensities [WMHs]) remains unknown. To address this and build upon our past work, we evaluated whether 5 CSF vascular inflammation biomarkers (vascular cell adhesion molecule 1, VEGF, C-reactive protein, fibrinogen, and von Willebrand factor)-previously associated with CSF amyloid levels-were related to FDG-PET signal and whether WMH volume modified these associations in 158 Alzheimer's Disease Neuroimaging Initiative participants (55-90 years old, 39 cognitively normal, 80 mild cognitive impairment, 39 Alzheimer's disease). We defined regions both by cortical boundary and by the 3 major vascular territories: anterior, middle, and posterior cerebral arteries. We found that WMH volume had interactive effects with CSF biomarkers (VEGF and C-reactive protein) on FDG-PET throughout the cortex in both vascular territories and conventionally defined regions of interest.

Alterations in intra- and inter-network connectivity associated with cognition impairment in insulinoma patients

Objective

Cognitive dysfunction is common in insulinoma patients, but the underlying neural mechanisms are less well understood. This study aimed to explore the alterations of intra- and inter-network connectivity patterns associated with patients with insulinoma.

Methods

Resting-state fMRI were acquired from 13 insulinoma patients and 13 matched healthy controls (HCs). Group Independent component analysis (ICA) was employed to capture the resting-state networks (RSNs), then the intra- and inter-network connectivity patterns, were calculated and compared. Montreal Cognitive Assessment (MoCA) was used to assess the cognitive function. The relationship between connectivity patterns and MoCA scores was also examined.

Results

Insulinoma patients performed significantly worse on MoCA compared to HCs. The intra-network connectivity analysis revealed that patients with insulinoma showed decreased connectivity in the left medial superior frontal gyrus within anterior default mode network (aDMN), and decreased connectivity in right lingual gyrus within the visual network (VN). The intra-network connectivity analysis showed that patients with insulinoma had an increased connectivity between the inferior-posterior default mode network (ipDMN) and right frontoparietal network (rFPN) and decreased connectivity between the ipDMN and auditory network (AUN). There was a significant negative correlation between the ipDMN-rFPN connectivity and MoCA score.

Conclusion

This study demonstrated significant abnormalities in the intra- and inter-network connectivity in patients with insulinoma, which may represent the neural mechanisms underlying the cognitive impairment in insulinoma patients.

Network-specific metabolic and haemodynamic effects elicited by non-invasive brain stimulation

Repetitive transcranial magnetic stimulation (TMS), when applied to the dorsolateral prefrontal cortex (dlPFC), treats depression. Therapeutic effects are hypothesized to arise from propagation of local dlPFC stimulation effects across distributed networks; however, the mechanisms of this remain unresolved. dlPFC contains representations of different networks. As such, dlPFC TMS may exert different effects depending on the network being stimulated. Here, to test this, we applied high-frequency TMS to two nearby dlPFC targets functionally embedded in distinct anti-correlated networks-the default and salience networks- in the same individuals in separate sessions. Local and distributed TMS effects were measured with combined 18fluorodeoxyglucose positron emission tomography and functional magnetic resonance imaging. Identical TMS patterns caused opposing effects on local glucose metabolism: metabolism increased at the salience target following salience TMS but decreased at the default target following default TMS. At the distributed level, both conditions increased functional connectivity between the default and salience networks, with this effect being dramatically larger following default TMS. Metabolic and haemodynamic effects were also linked: across subjects, the magnitude of local metabolic changes correlated with the degree of functional connectivity changes. These results suggest that TMS effects upon dlPFC are network specific. They also invoke putative antidepressant mechanisms of TMS: network de-coupling.

The characteristics of glucose metabolism and functional connectivity in posterior default network during nondemented aging: relationship with executive function performance

BACKGROUND

Understanding the characteristics of intrinsic connectivity networks (ICNs) in terms of both glucose metabolism and functional connectivity (FC) is important for revealing cognitive aging and neurodegeneration, but the relationships between these two aspects during aging has not been well established in older adults.

OBJECTIVE

This study is to assess the relationship between age-related glucose metabolism and FC in key ICNs, and their direct or indirect effects on cognitive deficits in older adults.

METHODS

We estimated the individual-level standard uptake value ratio (SUVr) and FC of eleven ICNs in 59 cognitively unimpaired older adults, then analyzed the associations of SUVr and FC of each ICN and their relationships with cognitive performance.

RESULTS

The results showed both the SUVr and FC in the posterior default mode network (pDMN) had a significant decline with age, and the association between them was also significant. Moreover, both decline of metabolism and FC in the pDMN were significantly correlated with executive function decline. Finally, mediation analysis revealed the glucose metabolism mediated the FC decline with age and FC mediated the executive function deficits.

CONCLUSIONS

Our findings indicated that covariance between glucose metabolism and FC in the pDMN is one of the main routes that contributes to age-related executive function decline.

PET imaging of animal models with depressive-like phenotypes

Major depressive disorder is a growing and poorly understood pathology. Due to technical and ethical limitations, a significant proportion of the research on depressive disorders cannot be performed on patients, but needs to be investigated in animal paradigms. Over the years, animal studies have provided new insight in the mechanisms underlying depression. Several of these studies have used PET imaging for the non-invasive and longitudinal investigation of the brain physiology. This review summarises the findings of preclinical PET imaging in different experimental paradigms of depression and compares these findings with observations from human studies. Preclinical PET studies in animal models of depression can be divided into three main different approaches: (a) investigation of glucose metabolism as a biomarker for regional and network involvement, (b) evaluation of the availability of different neuroreceptor populations associated with depressive phenotypes, and (c) monitoring of the inflammatory response in phenotypes of depression. This review also assesses the relevance of the use of PET imaging techniques in animal paradigms for the understanding of specific aspects of the depressive-like phenotypes, in particular whether it might contribute to achieve a more detailed characterisation of the clinical depressive phenotypes for the development of new therapies for depression.

PET molecular imaging for pathophysiological visualization in Alzheimer's disease

Alzheimer's disease (AD) is the most common dementia worldwide. The exact etiology of AD is unclear as yet, and no effective treatments are currently available, making AD a tremendous burden posed on the whole society. As AD is a multifaceted and heterogeneous disease, and most biomarkers are dynamic in the course of AD, a range of biomarkers should be established to evaluate the severity and prognosis. Positron emission tomography (PET) offers a great opportunity to visualize AD from diverse perspectives by using radiolabeled agents involved in various pathophysiological processes; PET imaging technique helps to explore the pathomechanisms of AD comprehensively and find out the most appropriate biomarker in each AD phase, leading to a better evaluation of the disease. In this review, we discuss the application of PET in the course of AD and summarized radiolabeled compounds with favorable imaging characteristics.

Effect of aging on the cerebral metabolic mechanism of electroacupuncture treatment in rats with traumatic brain injury

Objective

Aging has great influence on the clinical treatment effect of cerebrovascular diseases, and evidence suggests that the effect may be associated with age-related brain plasticity. Electroacupuncture is an effective alternative treatment for traumatic brain injury (TBI). In the present study, we aimed to explore the effect of aging on the cerebral metabolic mechanism of electroacupuncture to provide new evidence for developing age-specific rehabilitation strategies.

Methods

Both aged (18 months) and young (8 weeks) rats with TBI were analyzed. Thirty-two aged rats were randomly divided into four groups: aged model, aged electroacupuncture, aged sham electroacupuncture, and aged control group. Similarly, 32 young rats were also divided into four groups: young model, young electroacupuncture, young sham electroacupuncture, and young control group. Electroacupuncture was applied to "Bai hui" (GV20) and "Qu chi" (LI11) for 8 weeks. CatWalk gait analysis was then performed at 3 days pre- and post-TBI, and at 1, 2, 4, and 8 weeks after intervention to observe motor function recovery. Positron emission computed tomography (PET/CT) was performed at 3 days pre- and post-TBI, and at 2, 4, and 8 weeks after intervention to detect cerebral metabolism.

Results

Gait analysis showed that electroacupuncture improved the forepaw mean intensity in aged rats after 8 weeks of intervention, but after 4 weeks of intervention in young rats. PET/CT revealed increased metabolism in the left (the injured ipsilateral hemisphere) sensorimotor brain areas of aged rats during the electroacupuncture intervention, and increased metabolism in the right (contralateral to injury hemisphere) sensorimotor brain areas of young rats.

Results

This study demonstrated that aged rats required a longer electroacupuncture intervention duration to improve motor function than that of young rats. The influence of aging on the cerebral metabolism of electroacupuncture treatment was mainly focused on a particular hemisphere.

Regional cerebral hypometabolism on 18F-FDG PET/CT scan in delirium is independent of acute illness and dementia

INTRODUCTION

Delirium is associated with new onset dementia and accelerated cognitive decline; however, its pathophysiology remains unknown. Cerebral glucose metabolism previously seen in delirium may have been attributable to acute illness and/or dementia. We aimed to statistically map cerebral glucose metabolism attributable to delirium.

METHODS

We assessed cerebral glucose metabolism using ¹⁸ F-fluorodeoxyglucose positron emission tomography (FDG-PET) in sick, older patients with and without delirium, all without clinical dementia (N = 20). Strict exclusion criteria were adopted to minimize the effect of established confounders on FDG-PET.

RESULTS

Patients with delirium demonstrated hypometabolism in the bilateral thalami and right superior frontal, right posterior cingulate, right infero-lateral anterior temporal, and left superior parietal cortices. Regional hypometabolism correlated with delirium severity and performance on neuropsychological testing.

DISCUSSION

In patients with acute illness but without clinical dementia, delirium is accompanied by regional cerebral hypometabolism. While some hypometabolic regions may represent preclinical Alzheimer's disease (AD), thalamic hypometabolism is atypical of AD and consistent with the clinical features that are unique to delirium.

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

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

Cortical excitatory and inhibitory correlates of the fronto-limbic circuit in major depression and differential effects of left frontal brain stimulation in a randomized sham-controlled trial

BACKGROUND

Major depressive disorder (MDD), particularly treatment-resistant ones, is associated with abnormal fronto-limbic glucose metabolism. 10-Hz repetitive transcranial magnetic stimulation (rTMS) over left prefrontal cortex (PFC) is believed to normalize the abnormal metabolism to treat depression. However, the exact molecular mechanisms underlying the mood circuit of depressed brains and whether brain stimulation techniques regulate the underlying molecules remain elusive.

METHODS

Whole-brain glucose metabolism and cortical excitatory and inhibitory markers including P30, N45, P60, N100, and LICI (long-interval cortical inhibition) of TMS-evoked potentials from left DLPFC were measured in 40 subjects with MDD patients. The neurophysiological markers were repeated immediately after 1st session of left PFC rTMS, intermittent theta-burst stimulation (iTBS), and sham (randomly assigned).

RESULTS

Brain glucose metabolism in the limbic structures significantly correlated with left PFC P30 (mainly GABA-A and glutamate receptor mediated) and with LICI (mainly GABA-B receptor mediated inhibition) (FWE-corrected p < 0.001). Correlations between other neurophysiological markers (left PFC N45, P60, and N100) and posterior cingulate cortex, a key region in the default mode network, were also noted. One session of rTMS significantly decreased left PFC P60 (mainly glutamate receptor mediated), while a significant group effect was found for LICI (iTBS < sham).

CONCLUSION

The first study showed that the underlying molecular mechanisms of fronto-limbic circuit of MDD brains involved glutamatergic excitation and GABAergic inhibition at specific time points. In addition, one session of rTMS mainly modulated glutamatergic neurotransmission at left PFC, while the mechanisms of iTBS might involve GABA-B receptor mediated inhibition.

CLINICAL TRIALS REGISTRY NUMBER

UMIN000044951.

Disrupted coupling between salience network segregation and glucose metabolism is associated with cognitive decline in Alzheimer's disease - A simultaneous resting-state FDG-PET/fMRI study

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Hybrid PET/MRI was used to explore network segregation and glucose metabolism in AD.

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DMN, CEN, and SN showed reduced segregation in AD.

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In salience network, segregation coupled with glucose metabolism in CN group.

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The coupled segregation and glucose metabolism in CN disappeared in MCI and AD.

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Reduced segregation and hypometabolism were associated with cognitive impairments.

The aberrant organization and functioning of three core neurocognitive networks (NCNs), i.e., default-mode network (DMN), central executive network (CEN), and salience network (SN), are among the prominent features in Alzheimer’s disease (AD). The dysregulation of both intra- and inter-network functional connectivities (FCs) of the three NCNs contributed to AD-related cognitive and behavioral abnormalities. Brain functional network segregation, integrating intra- and inter-network FCs, is essential for maintaining the energetic efficiency of brain metabolism. The association of brain functional network segregation, together with glucose metabolism, with age-related cognitive decline was recently shown. Yet how these joint functional-metabolic biomarkers relate to cognitive decline along with mild cognitive impairment (MCI) and AD remains to be elucidated. In this study, under the framework of the triple-network model, we performed a hybrid FDG-PET/fMRI study to evaluate the concurrent changes of resting-state brain intrinsic FCs and glucose metabolism of the three NCNs across cognitively normal (CN) (N = 24), MCI (N = 21), and AD (N = 21) groups. Lower network segregation and glucose metabolism were observed in all three NCNs in patients with AD. More interestingly, in the SN, the coupled relationship between network segregation and glucose metabolism existed in the CN group (r = 0.523, p = 0.013) and diminished in patients with MCI (r = 0.431, p = 0.065) and AD (r = 0.079, p = 0.748). Finally, the glucose metabolism of the DMN (r = 0.380, p = 0.017) and the network segregation of the SN (r = 0.363, p = 0.023) were significantly correlated with the general cognitive status of the patients. Our findings suggest that the impaired SN segregation and its uncoupled relationship with glucose metabolism contribute to the cognitive decline in AD.

Identifying the individual metabolic abnormities from a systemic perspective using whole-body PET imaging

Introduction

Distinct physiological states arise from complex interactions among the various organs present in the human body. PET is a non-invasive modality with numerous successful applications in oncology, neurology, and cardiology. However, while PET imaging has been applied extensively in detecting focal lesions or diseases, its potential in detecting systemic abnormalities is seldom explored, mostly because total-body imaging was not possible until recently.

Methods

In this context, the present study proposes a framework capable of constructing an individual metabolic abnormality network using a subject’s whole-body ¹⁸F-FDG SUV image and a normal control database. The developed framework was evaluated in the patients with lung cancer, the one discharged after suffering from Covid-19 disease, and the one that had gastrointestinal bleeding with the underlying cause unknown.

Results

The framework could successfully capture the deviation of these patients from healthy subjects at the level of both system and organ. The strength of the altered network edges revealed the abnormal metabolic connection between organs. The overall deviation of the network nodes was observed to be highly correlated to the organ SUV measures. Therefore, the molecular connectivity of glucose metabolism was characterized at a single subject level.

Conclusion

The proposed framework represents a significant step toward the use of PET imaging for identifying metabolic dysfunction from a systemic perspective. A better understanding of the underlying biological mechanisms and the physiological interpretation of the interregional connections identified in the present study warrant further research.

Alteration of the Individual Metabolic Network of the Brain Based on Jensen-Shannon Divergence Similarity Estimation in Elderly Patients With Type 2 Diabetes Mellitus

The aim of this study was to investigate the interactive effect between aging and type 2 diabetes mellitus (T2DM) on brain glucose metabolism, individual metabolic connectivity, and network properties. Using a 2 × 2 factorial design, 83 patients with T2DM (40 elderly and 43 middle-aged) and 69 sex-matched healthy control subjects (HCs) (34 elderly and 35 middle-aged) underwent 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance scanning. Jensen-Shannon divergence was applied to construct individual metabolic connectivity and networks. The topological properties of the networks were quantified using graph theoretical analysis. The general linear model was used to mainly estimate the interaction effect between aging and T2DM on glucose metabolism, metabolic connectivity, and network. There was an interaction effect between aging and T2DM on glucose metabolism, metabolic connectivity, and regional metabolic network properties (all P < 0.05). The post hoc analyses showed that compared with elderly HCs and middle-aged patients with T2DM, elderly patients with T2DM had decreased glucose metabolism, increased metabolic connectivity, and regional metabolic network properties in cognition-related brain regions (all P < 0.05). Age and fasting plasma glucose had negative correlations with glucose metabolism and positive correlations with metabolic connectivity. Elderly patients with T2DM had glucose hypometabolism, strengthened functional integration, and increased efficiency of information communication mainly located in cognition-related brain regions. Metabolic connectivity pattern changes might be compensatory changes for glucose hypometabolism.

Developmental coupling of cerebral blood flow and fMRI fluctuations in youth

The functions of the human brain are metabolically expensive and reliant on coupling between cerebral blood flow (CBF) and neural activity, yet how this coupling evolves over development remains unexplored. Here, we examine the relationship between CBF, measured by arterial spin labeling, and the amplitude of low-frequency fluctuations (ALFF) from resting-state magnetic resonance imaging across a sample of 831 children (478 females, aged 8-22 years) from the Philadelphia Neurodevelopmental Cohort. We first use locally weighted regressions on the cortical surface to quantify CBF-ALFF coupling. We relate coupling to age, sex, and executive functioning with generalized additive models and assess network enrichment via spin testing. We demonstrate regionally specific changes in coupling over age and show that variations in coupling are related to biological sex and executive function. Our results highlight the importance of CBF-ALFF coupling throughout development; we discuss its potential as a future target for the study of neuropsychiatric diseases.

Internetwork Connectivity Predicts Cognitive Decline in Parkinson’s and Is Altered by Genetic Variants

In Parkinson’s disease (PD) functional changes in the brain occur years before significant cognitive symptoms manifest yet core large-scale networks that maintain cognition and predict future cognitive decline are poorly understood. The present study investigated internetwork functional connectivity of visual (VN), anterior and posterior default mode (aDMN, pDMN), left/right frontoparietal (LFPN, RFPN), and salience (SN) networks in 63 cognitively normal PD (PDCN) and 43 healthy controls who underwent resting-state functional MRI. The functional relevance of internetwork coupling topologies was tested by their correlations with baseline cognitive performance in each group and with 2-year cognitive changes in a PDCN subsample. To disentangle heterogeneity in neurocognitive functioning, we also studied whether α-synuclein (SNCA) and microtubule-associated protein tau (MAPT) variants alter internetwork connectivity and/or accelerate cognitive decline. We found that internetwork connectivity was largely preserved in PDCN, except for reduced pDMN-RFPN/LFPN couplings, which correlated with poorer baseline global cognition. Preserved internetwork couplings also correlated with domain-specific cognition but differently for the two groups. In PDCN, stronger positive internetwork coupling topologies correlated with better cognition at baseline, suggesting a compensatory mechanism arising from less effective deployment of networks that supported cognition in healthy controls. However, stronger positive internetwork coupling topologies typically predicted greater longitudinal decline in most cognitive domains, suggesting that they were surrogate markers of neuronal vulnerability. In this regard, stronger aDMN-SN, LFPN-SN, and/or LFPN-VN connectivity predicted longitudinal decline in attention, working memory, executive functioning, and visual cognition, which is a risk factor for dementia. Coupling strengths of some internetwork topologies were altered by genetic variants. PDCN carriers of the SNCA risk allele showed amplified anticorrelations between the SN and the VN/pDMN, which supported cognition in healthy controls, but strengthened pDMN-RFPN connectivity, which maintained visual memory longitudinally. PDCN carriers of the MAPT risk allele showed greater longitudinal decline in working memory and increased VN-LFPN connectivity, which in turn predicted greater decline in visuospatial processing. Collectively, the results suggest that cognition is maintained by functional reconfiguration of large-scale internetwork communications, which are partly altered by genetic risk factors and predict future domain-specific cognitive progression.

Ranking of communities in multiplex spatiotemporal models of brain dynamics

As a relatively new field, network neuroscience has tended to focus on aggregate behaviours of the brain averaged over many successive experiments or over long recordings in order to construct robust brain models. These models are limited in their ability to explain dynamic state changes in the brain which occurs spontaneously as a result of normal brain function. Hidden Markov Models (HMMs) trained on neuroimaging time series data have since arisen as a method to produce dynamical models that are easy to train but can be difficult to fully parametrise or analyse. We propose an interpretation of these neural HMMs as multiplex brain state graph models we term Hidden Markov Graph Models. This interpretation allows for dynamic brain activity to be analysed using the full repertoire of network analysis techniques. Furthermore, we propose a general method for selecting HMM hyperparameters in the absence of external data, based on the principle of maximum entropy, and use this to select the number of layers in the multiplex model. We produce a new tool for determining important communities of brain regions using a spatiotemporal random walk-based procedure that takes advantage of the underlying Markov structure of the model. Our analysis of real multi-subject fMRI data provides new results that corroborate the modular processing hypothesis of the brain at rest as well as contributing new evidence of functional overlap between and within dynamic brain state communities. Our analysis pipeline provides a way to characterise dynamic network activity of the brain under novel behaviours or conditions.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s41109-022-00454-2.

Brain Intrinsic Functional Activity in Relation to Metabolic Changes in Alzheimer's Disease: A Simultaneous PET/fMRI study

Previous studies have shown that the intrinsic brain functional activity significantly reduced in a variety of regions of Alzheimer's disease (AD) patients. However, the associated underlying metabolic mechanism remains not clear. Brain activity is primarily driven by the dynamic activity of neurons and their interconnections, which are regulated by synapses and are closely related to glucose uptakes. Simultaneous FDG-PET/fMRI imaging provides a unique opportunity to measure the concurrent brain functional activity and cerebral glucose metabolism information. In this study, using simultaneous resting-state PET/fMRI imaging, we investigated the concurrent global intrinsic activity and metabolic signal changes in AD patients. Twenty-two controls and nineteen AD patients were included. We compared the whole-brain amplitude of low frequency fluctuations (ALFF) measured using fMRI imaging and glucose uptake maps acquired from PET imaging between the two groups. Both maps showed significant reductions in the precuneus and left inferior parietal lobule (IPL) in AD compared to the control groups. Moreover, the ALFF within the precuneus and left IPL were significantly correlated with the colocalized glucose metabolism. The ALFF in the left IPL was significantly correlated with patient cognitive performance evaluated using MMSE or MoCA. Our findings provide useful insights into the understanding of brain intrinsic functional-metabolic activity and its role in AD pathology.

Altered Metabolic Interrelationships in the Cortico-Limbic Circuitry in Military Service Members with Persistent Post-Traumatic Stress Disorder Symptoms Following Mild Traumatic Brain Injury

Introduction: Comorbid mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD) are common in military service members. The aim of this study is to investigate brain metabolic interrelationships in service members with and without persistent PTSD symptoms after mTBI by using ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography. Methods: Service members (n = 408) diagnosed with mTBI were studied retrospectively. Principal component analysis was applied to identify latent metabolic systems, and the associations between metabolic latent systems and self-report measures of post-concussive and PTSD symptoms were evaluated. Participants were divided into two groups based on DSM-IV-TR (Diagnostic and Statistical Manual of Mental Disorders, fourth edition-Text Revision) criteria for PTSD, and structural equation modeling was performed to test a priori hypotheses on metabolic interrelationships among the brain regions in the cortico-limbic circuitry responsible for top-down control and bottom-up emotional processing. The differences in metabolic interrelationships between age-matched PTSD-absent (n = 204) and PTSD-present (n = 204) groups were evaluated. Results: FDG uptake in the temporo-limbic system was positively correlated with post-concussive and hyperarousal symptoms. For the bottom-up emotional processing, the insula and amygdala-hippocampal complex in the PTSD-present group had stronger metabolic interrelationships with the bilateral rostral anterior cingulate, left lingual, right lateral occipital, and left superior temporal cortices, but a weaker relationship with the right precuneus cortex, compared with the PTSD-absent group. For the top-down control, the PTSD-present group had decreased metabolic engagements of the dorsolateral prefrontal cortex on the amygdala. Discussion: Our results suggest altered metabolic interrelationships in the cortico-limbic circuitry in mTBI subjects with persistent PTSD symptoms, which may underlie the pathophysiological mechanisms of comorbid mTBI and PTSD. Impact statement This is the first ¹⁸F-fluorodeoxyglucose positron emission tomography study to investigate brain metabolic interrelationships in service members with persistent post-traumatic stress disorder (PTSD) symptoms after mild traumatic brain injury (mTBI). We identified that the temporo-limbic metabolic system was associated with post-concussive and hyperarousal symptoms. Further, brain metabolic interrelationships in the cortico-limbic circuitry were altered in mTBI subjects with significant PTSD symptoms compared with those without them.

High Glycemic Diet Is Related to Brain Amyloid Accumulation Over One Year in Preclinical Alzheimer's Disease

Objective: To test the hypothesis that high glycemic diet is related to 1-year change in brain amyloid based on our prior cross-sectional evidence that high glycemic diet is associated with brain amyloid.

Methods: This longitudinal, observational study assessed the relationship between reported habitual consumption of a high glycemic diet (HGDiet) pattern and 1-year brain amyloid change measured by Florbetapir F18 PET scans in 102 cognitively normal older adults with elevated or sub-threshold amyloid status that participated in a 1-year randomized, controlled exercise trial at the University of Kansas Medical Center in Kansas City.

Results: Among all participants (n = 102), higher daily intake of the HGDiet pattern (β = 0.06, p = 0.04), sugar (β = 0.07, p = 0.01), and total carbohydrate (β = 0.06, p = 0.04) were related to more precuneal amyloid accumulation. These relationships in the precuneus were accentuated in participants with elevated amyloid at enrollment (n = 70) where higher intake of the HGDiet pattern, sugar, and carbohydrate were related to more precuneal amyloid accumulation (β = 0.11, p = 0.01 for all measures). In individuals with elevated amyloid, higher intake of the HGDiet pattern was also related to more amyloid accumulation in the lateral temporal lobe (β = 0.09, p < 0.05) and posterior cingulate gyrus (β = 0.09, p < 0.05) and higher sugar and carbohydrate intake were also related to more amyloid accumulation in the posterior cingulate gyrus (β = 0.10, p < 0.05 for both measures).

Conclusion: This longitudinal observational analysis suggests that a high glycemic diet relates to higher brain amyloid accumulation over 1 year in regions of the temporoparietal cortex in cognitively normal adults, particularly in those with elevated amyloid status. Further studies are required to assess whether there is causal link between a high glycemic diet and brain amyloid.

Clinical Trial Registration:ClinicalTrials.gov, Identifier (NCT02000583).

Changes of cerebral network activity after invasive stimulation of the mesencephalic locomotor region in a rat stroke model

Motor deficits after stroke reflect both, focal lesion and network alterations in brain regions distant from infarction. This remote network dysfunction may be caused by aberrant signals from cortical motor regions travelling via mesencephalic locomotor region (MLR) to other locomotor circuits. A method for modulating disturbed network activity is deep brain stimulation. Recently, we have shown that high frequency stimulation (HFS) of the MLR in rats has restored gait impairment after photothrombotic stroke (PTS). However, it remains elusive which cerebral regions are involved by MLR-stimulation and contribute to the improvement of locomotion. Seventeen male Wistar rats underwent photothrombotic stroke of the right sensorimotor cortex and implantation of a microelectrode into the right MLR. 2-[¹⁸F]Fluoro-2-deoxyglucose ([¹⁸F]FDG)-positron emission tomography (PET) was conducted before stroke and thereafter, on day 2 and 3 after stroke, without and with MLR-HFS, respectively. [¹⁸F]FDG-PET imaging analyses yielded a reduced glucose metabolism in the right cortico-striatal thalamic loop after PTS compared to the state before intervention. When MLR-HFS was applied after PTS, animals exhibited a significantly higher uptake of [¹⁸F]FDG in the right but not in the left cortico-striatal thalamic loop. Furthermore, MLR-HFS resulted in an elevated glucose metabolism of right-sided association cortices related to the ipsilateral sensorimotor cortex. These data support the concept of diaschisis i.e., of dysfunctional brain areas distant to a focal lesion and suggests that MLR-HFS can reverse remote network effects following PTS in rats which otherwise may result in chronic motor symptoms.

Concomitant functional impairment and reorganization in the linkage between the cerebellum and default mode network in patients with type 2 diabetes mellitus

BACKGROUND

Increasing evidence shows that the default mode network (DMN) and cerebellum are prone to structural and functional abnormalities in patients with type 2 diabetes mellitus (T2DM). However, the type of change in the functional connection between the DMN and cerebellum is still unknown.

METHODS

In this study, seed-based functional connectivity (FC) analysis was used to examine the intrinsic FC of the cerebellum-DMN between healthy controls (HCs) and T2DM patients. Pearson correlation analysis was used to explore the relationship between clinical variables and changes in FC.

RESULTS

Compared with HCs, T2DM patients showed significantly increased FC of the left crus I-left medial superior frontal gyrus, left crus I-right medial superior frontal gyrus, and right crus I-left medial orbitofrontal cortex. Compared with HCs, T2DM patients showed decreased FC of the lobule IX-the right angular gyrus. Moreover, diabetes duration was positively correlated with increased FC of the left crus I-right medial superior frontal gyrus (r=0.438, P=0.007).

CONCLUSIONS

Concomitant functional impairment and reorganization in the linkage between the cerebellum and DMN in patients with T2DM may be a biomarker of early brain damage that can help us better understand the pathogenesis of cognitive impairment in T2DM.

18 F-2-fluoro-2-deoxy-D-glucose-positron emission tomography metabolic pattern assessment in the brain of betel quid dependent individuals

The primary objective of this study was to identify the metabolic pattern in the brains of betel quid dependent (BQD) individuals using ¹⁸ F-2-fluoro-2-deoxy-D-glucose-positron emission tomography (¹⁸ F-FDG-PET). A total of 42 individuals (16 BQD individuals and 26 healthy controls, HCs) enrolled at the Department of Nuclear Medicine of Xiangya Hospital underwent brain ¹⁸ F-FDG-PET. Group comparisons using statistical parametric mapping (SPM) were performed to identify the ¹⁸ F-FDG-PET patterns. Standardized uptake value ratios of anterior cingulate, frontal, thalamus, parietal, occipital, temporal and cerebellum were calculated by SPM. The characteristics of abnormal metabolism in brain regions were quantified using the xjView toolbox, and a 3-D brain map was drawn using BrainNet Viewer. We found significant metabolic reduction in the bilateral middle prefrontal cortex (PFC) and the left orbital frontal gyrus (OFC). In contrast, hypermetabolism was observed in the inferior cerebellum, fusiform, superior cerebellum, parahippocampal, vermis, lingual and thalamus. However, we found no significant difference between the BQD and HC group in the anterior cingulate, thalamus, cerebellum and frontal, temporal, parietal and occipital lobes. In summary, we found abnormal ¹⁸ F-FDG-PET metabolic pattern in BQD individuals, and this pattern may help the treatment of BQD.

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).

Changes of Metabolic Connectivity in Dementia with Lewy Bodies with Visual Hallucinations: A 18F-Fluorodeoxyglucose Positron Emission Tomography/Magnetic Resonance Study

Background: Recurrent complex visual hallucinations (VHs) are common in dementia with Lewy bodies (DLB). Previous investigations suggest that VHs are associated with connectivity changes within and between large scale networks involved in visual processing and attention. Aim: To examine more directly whether VH in DLB reflects direct changes in neuronal activity between cortical regions assessing metabolic connectivity with ¹⁸F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/magnetic resonance and graph theory. Methods: Twenty-six patients with probable DLB (13 VHs and 13 no-VHs; mean age: 72.9 ± 6.87 years vs. 70.2 ± 7.96 years) were enrolled. T1-weighted 3T-MR images and FDG-PET data were coacquired using an integrated PET/MR scanner. MR images defined cortical parcels of the Shaefer-Yeo atlas for multiple functional networks. We computed in each parcel the regional standardized-uptake-values (SUV) corrected for partial volume and normalized to the cerebellar cortex. Strength degree, clustering coefficient, characteristic path length, and hubs were analyzed with graph analysis. Results: The mean ¹⁸F-FDG-PET SUVr of parcels belonging to the visual and dorsal attention networks (DANs) were significantly lower in the VH group (p = 0.01). Metabolism in the right temporoparietal cortex correlated with VH severity (R = -0.58; p < 0.01). VH patients showed weaker metabolic connectivity in the parietal, temporal, and occipital cortex of the default mode network, DAN, and visual networks, but more robust connectivity in the right insula and orbitofrontal cortex. A lower global efficiency characterized the VH group, except for ventral attention network and limbic network. Conclusions: VHs in DLB correlate with lower glucose metabolism and weaker metabolic connectivity in the parietal-occipital cortex, but stronger connectivity in the limbic system. Impact statement This study shows that application of the graph theory to ¹⁸F-fluorodeoxyglucose-positron emission tomography data, commonly acquired during the diagnostic workflow in neurodegenerative diseases, could be used to obtain information of functional connectivity at a group level, with results that are consistent with other data commonly used in brain functional investigation (e.g., electroencephalography or functional magnetic resonance). New network-based methods of metabolic image analyses, such as graph analysis, are a recent area of research with a potential capacity to extract information on alterations of metabolic connectivity that may become pharmacological and neuromodulation targets of the physiopathology of recurrent complex visual hallucinations.

Metabolic and Hemodynamic Resting-State Connectivity of the Human Brain: A High-Temporal Resolution Simultaneous BOLD-fMRI and FDG-fPET Multimodality Study

Simultaneous [18F]-fluorodeoxyglucose positron emission tomography functional magnetic resonance imaging (FDG-PET/fMRI) provides the capacity to image 2 sources of energetic dynamics in the brain-glucose metabolism and the hemodynamic response. fMRI connectivity has been enormously useful for characterizing interactions between distributed brain networks in humans. Metabolic connectivity based on static FDG-PET has been proposed as a biomarker for neurological disease, but FDG-sPET cannot be used to estimate subject-level measures of "connectivity," only across-subject "covariance." Here, we applied high-temporal resolution constant infusion functional positron emission tomography (fPET) to measure subject-level metabolic connectivity simultaneously with fMRI connectivity. fPET metabolic connectivity was characterized by frontoparietal connectivity within and between hemispheres. fPET metabolic connectivity showed moderate similarity with fMRI primarily in superior cortex and frontoparietal regions. Significantly, fPET metabolic connectivity showed little similarity with FDG-sPET metabolic covariance, indicating that metabolic brain connectivity is a nonergodic process whereby individual brain connectivity cannot be inferred from group-level metabolic covariance. Our results highlight the complementary strengths of fPET and fMRI in measuring the intrinsic connectivity of the brain and open up the opportunity for novel fundamental studies of human brain connectivity as well as multimodality biomarkers of neurological diseases.

Coupling of activity, metabolism and behaviour across the Drosophila brain

Coordinated activity across networks of neurons is a hallmark of both resting and active behavioural states in many species1-5. These global patterns alter energy metabolism over seconds to hours, which underpins the widespread use of oxygen consumption and glucose uptake as proxies of neural activity6,7. However, whether changes in neural activity are causally related to metabolic flux in intact circuits on the timescales associated with behaviour is unclear. Here we combine two-photon microscopy of the fly brain with sensors that enable the simultaneous measurement of neural activity and metabolic flux, across both resting and active behavioural states. We demonstrate that neural activity drives changes in metabolic flux, creating a tight coupling between these signals that can be measured across brain networks. Using local optogenetic perturbation, we demonstrate that even transient increases in neural activity result in rapid and persistent increases in cytosolic ATP, which suggests that neuronal metabolism predictively allocates resources to anticipate the energy demands of future activity. Finally, our studies reveal that the initiation of even minimal behavioural movements causes large-scale changes in the pattern of neural activity and energy metabolism, which reveals a widespread engagement of the brain. As the relationship between neural activity and energy metabolism is probably evolutionarily ancient and highly conserved, our studies provide a critical foundation for using metabolic proxies to capture changes in neural activity.

Elucidating the complementarity of resting-state networks derived from dynamic [18F]FDG and hemodynamic fluctuations using simultaneous small-animal PET/MRI

Functional connectivity (FC) and resting-state network (RSN) analyses using functional magnetic resonance imaging (fMRI) have evolved into a growing field of research and have provided useful biomarkers for the assessment of brain function in neurological disorders. However, the underlying mechanisms of the blood oxygen level-dependant (BOLD) signal are not fully resolved due to its inherent complexity. In contrast, [¹⁸F]fluorodeoxyglucose positron emission tomography ([¹⁸F]FDG-PET) has been shown to provide a more direct measure of local synaptic activity and may have additional value for the readout and interpretation of brain connectivity. We performed an RSN analysis from simultaneously acquired PET/fMRI data on a single-subject level to directly compare fMRI and [¹⁸F]FDG-PET-derived networks during the resting state. Simultaneous [¹⁸F]FDG-PET/fMRI scans were performed in 30 rats. Pairwise correlation analysis, as well as independent component analysis (ICA), were used to compare the readouts of both methods. We identified three RSNs with a high degree of similarity between PET and fMRI-derived readouts: the default-mode-like network (DMN), the basal ganglia network and the cerebellar-midbrain network. Overall, [¹⁸F]FDG connectivity indicated increased integration between different, often distant, brain areas compared to the results indicated by the more segregated fMRI-derived FC. Additionally, several networks exclusive to either modality were observed using ICA. These networks included mainly bilateral cortical networks of a limited spatial extent for fMRI and more spatially widespread networks for [¹⁸F]FDG-PET, often involving several subcortical areas.

This is the first study using simultaneous PET/fMRI to report RSNs subject-wise from dynamic [¹⁸F]FDG tracer delivery and BOLD fluctuations with both independent component analysis (ICA) and pairwise correlation analysis in small animals. Our findings support previous studies, which show a close link between local synaptic glucose consumption and BOLD-fMRI-derived FC. However, several brain regions were exclusively attributed to either [¹⁸F]FDG or BOLD-derived networks underlining the complementarity of this hybrid imaging approach, which may contribute to the understanding of brain functional organization and could be of interest for future clinical applications.

Brain Molecular Connectivity in Neurodegenerative Conditions

Positron emission tomography (PET) allows for the in vivo assessment of early brain functional and molecular changes in neurodegenerative conditions, representing a unique tool in the diagnostic workup. The increased use of multivariate PET imaging analysis approaches has provided the chance to investigate regional molecular processes and long-distance brain circuit functional interactions in the last decade. PET metabolic and neurotransmission connectome can reveal brain region interactions. This review is an overview of concepts and methods for PET molecular and metabolic covariance assessment with evidence in neurodegenerative conditions, including Alzheimer’s disease and Lewy bodies disease spectrum. We highlight the effects of environmental and biological factors on brain network organization. All of the above might contribute to innovative diagnostic tools and potential disease-modifying interventions.

The default mode network and cognition in Parkinson's disease: A multimodal resting-state network approach

Involvement of the default mode network (DMN) in cognitive symptoms of Parkinson's disease (PD) has been reported by resting-state functional MRI (rsfMRI) studies. However, the relation to metabolic measures obtained by [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) is largely unknown. We applied multimodal resting-state network analysis to clarify the association between intrinsic metabolic and functional connectivity abnormalities within the DMN and their significance for cognitive symptoms in PD. PD patients were classified into normal cognition (n = 36) and mild cognitive impairment (MCI; n = 12). The DMN was identified by applying an independent component analysis to FDG-PET and rsfMRI data of a matched subset (16 controls and 16 PD patients) of the total cohort. Besides metabolic activity, metabolic and functional connectivity within the DMN were compared between the patients' groups and healthy controls (n = 16). Glucose metabolism was significantly reduced in all DMN nodes in both patient groups compared to controls, with the lowest uptake in PD-MCI (p < .05). Increased metabolic and functional connectivity along fronto-parietal connections was identified in PD-MCI patients compared to controls and unimpaired patients. Functional connectivity negatively correlated with cognitive composite z-scores in patients (r = -.43, p = .005). The current study clarifies the commonalities of metabolic and hemodynamic measures of brain network activity and their individual significance for cognitive symptoms in PD, highlighting the added value of multimodal resting-state network approaches for identifying prospective biomarkers.

A study of regional homogeneity of resting-state Functional Magnetic Resonance Imaging in mild cognitive impairment

Mild cognitive impairment (MCI) is considered to be the early stage of Alzheimer's disease (AD), but the diagnostic predictive markers for MCI patients are still unclear. Here we have identified the brain function activity changes in MCI patients by using the resting-state functional magnetic resonance imaging (rs-fMRI). A total of 28 MCI patients and 38 age- and gender-matched healthy controls from the Wuxi Mental Health Center were recruited, and their abnormal spontaneous brain activities in the MCI were examined. The results showed that, compared with the healthy controls, MCI patients exhibited reduced regional homogeneity (ReHo) in the right superior temporal gyrus, right middle temporal gyrus, left angular gyrus and superior marginal gyrus. In addition, the correlation analysis revealed that ReHo in these regions were not correlated with the AD Assessment Scale-Cognitive score in MCI. We concluded abnormalities in the right superior temporal gyrus, right middle temporal gyrus, left angular gyrus and superior marginal gyrus with MCI, suggesting that the right language network may be impaired in MCI, which may provide a better understanding of dementia progression and potentially comprehensive treatment in MCI.

High-amplitude cofluctuations in cortical activity drive functional connectivity

Resting-state functional connectivity is used throughout neuroscience to study brain organization and to generate biomarkers of development, disease, and cognition. The processes that give rise to correlated activity are, however, poorly understood. Here we decompose resting-state functional connectivity using a temporal unwrapping procedure to assess the contributions of moment-to-moment activity cofluctuations to the overall connectivity pattern. This approach temporally resolves functional connectivity at a timescale of single frames, which enables us to make direct comparisons of cofluctuations of network organization with fluctuations in the blood oxygen level-dependent (BOLD) time series. We show that surprisingly, only a small fraction of frames exhibiting the strongest cofluctuation amplitude are required to explain a significant fraction of variance in the overall pattern of connection weights as well as the network's modular structure. These frames coincide with frames of high BOLD activity amplitude, corresponding to activity patterns that are remarkably consistent across individuals and identify fluctuations in default mode and control network activity as the primary driver of resting-state functional connectivity. Finally, we demonstrate that cofluctuation amplitude synchronizes across subjects during movie watching and that high-amplitude frames carry detailed information about individual subjects (whereas low-amplitude frames carry little). Our approach reveals fine-scale temporal structure of resting-state functional connectivity and discloses that frame-wise contributions vary across time. These observations illuminate the relation of brain activity to functional connectivity and open a number of directions for future research.

Association between the Onset of Idiopathic Normal Pressure Hydrocephalus Symptoms and Reduced Default Mode Network Connectivity

OBJECTIVE

The aim was to examine the association between connectivity changes in the default mode network (DMN) and the progression of idiopathic normal pressure hydrocephalus (iNPH).

METHODS

We retrospectively recruited cases of preclinical and clinical iNPH from 2,196 patients who had received whole-body 18F-fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT) scanning. We included 31 cases with asymptomatic ventriculomegaly with features of iNPH on MRI (AVIM; reported as preclinical iNPH) and 12 with iNPH. We performed a voxel-based analysis of the brain FDG-PET images of the AVIM and iNPH groups as well as for each background-matched normal control (NC) group, using Statistical Parametric Mapping 12. Volume of interest (VOI)-based analysis was also performed. We set the VOI as the region from the precuneus to the posterior cingulate cortices (PCC), and compared the mean regional standardized uptake value ratio (SUVR) between the AVIM and iNPH group FDG-PET/CT images and each corresponding NC group.

RESULTS

The voxel-based analysis showed a greater decreased FDG uptake in the PCC in the iNPH group than in the AVIM group. The VOI-based analysis revealed no significant difference in the mean SUVR of the AVIM group and the corresponding NC group, but that of the iNPH group was significantly lower than that of its corresponding NC group.

CONCLUSIONS

DMN connectivity was reduced in the clinical iNPH group but not in the preclinical group. These data suggest that alterations in the functional connectivity of the DMN are related to the onset of iNPH symptoms.

Impacts of FKBP5 variants on large-scale brain network connectivity in healthy adults

BACKGROUND

FK506 binding protein 5 (FKBP5) rs1360780 polymorphism has been identified as a molecular genetic marker associated with the dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis. The impact of FKBP5 rs1360780 on the large-scale brain network connectivity in healthy adults is still unknown.

METHODS

479 healthy volunteers (age: 20-80years) completed MRI scans, neuropsychological assessments and blood analysis.All subjects were divided into CC, CT and TT genotypes. Within and between network connectivities (10 sub-networks) were calculated using resting state functional MRI (rs-fMRI) data. The genetic effects and gene-gender/age interaction on large-scale network connectivity were explored.

RESULTS

Compared with CC and CT groups, TT group showed increased intra-connectivity in default mode network (DMN) and increased inter-connectivity mainly distributed among the network of DMN, salience network (SAN), dorsal attention network (DAN), ventral attention network (VAN), subcortical network (SUB), and visual network (VIS). Gene-by-gender and gene-by-age interaction were found in inter-connectivity of DAN to VIS and DMN to FPN, respectively. The altered connectivities correlated with anxiety status test score.

LIMITATIONS

Plasma adrenocorticotropic hormone (ACTH) or cortisol were not measured,or else, we could estimate the hypothalamic-pituitary-adrenal (HPA) axis activity which may strengthen our results.

CONCLUSIONS

FKBP5 rs1360780 modulates the large-scale brain network connectivity in healthy adults. TT carriers showed the increased intra- and inter-connectivities mainly distributed among the network of DMN, SAN, DAN, VAN, SUB and VIS.

Brain Network Segregation and Glucose Energy Utilization: Relevance for Age-Related Differences in Cognitive Function

The human brain is organized into segregated networks with strong within-network connections and relatively weaker between-network connections. This "small-world" organization may be essential for maintaining an energetically efficient system, crucial to the brain which consumes 20% of the body's energy. Brain network segregation and glucose energy utilization both change throughout the lifespan. However, it remains unclear whether these processes interact to contribute to differences in cognitive performance with age. To address this, we examined fluorodeoxyglucose-positron emission tomography and resting-state functional magnetic resonance imaging from 88 participants aged 18-73 years old. Consistent with prior work, brain network segregation showed a negative association with age across both sensorimotor and association networks. However, relative glucose metabolism demonstrated an interaction with age, showing a negative slope in association networks but a positive slope in sensorimotor networks. Overall, brain networks with lower segregation showed significantly steeper age-related differences in glucose metabolism, compared with highly segregated networks. Sensorimotor network segregation mediated the association between age and poorer spatial cognition performance, and sensorimotor network metabolism mediated the association between age and slower response time. These data provide evidence that sensorimotor segregation and glucose metabolism underlie some age-related changes in cognition. Interventions that stimulate somatosensory networks could be important for treatment of age-related cognitive decline.