Dissociations between glucose metabolism and blood oxygenation in the human default mode network revealed by simultaneous PET-fMRI

Evaluation of renal oxygenation and perfusion in patients with chronic kidney disease: a preliminary prospective study based on functional magnetic resonance

BACKGROUND

Renal hypoxia and ischemia significantly contribute to chronic kidney disease (CKD) progression, underscoring the need for noninvasive quantitative assessments. This study employs blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI) and arterial spin labeling (ASL) MRI to comprehensively evaluate renal oxygenation and blood flow in CKD patients.

METHODS

Forty-two CKD patients across stages 1-5 and ten healthy volunteers underwent simultaneous BOLD-MRI and ASL-MRI. We measured oxygenation (T2* values) and renal blood flow (RBF) in both the renal cortex and medulla, assessing their correlations with estimated glomerular filtration rate (eGFR) and other renal function indicators.

RESULTS

BOLD and ASL revealed higher oxygenation and RBF in the renal cortex than in the medulla. Across CKD stages 2-5, both cortical and medullary oxygenation levels, as well as RBF, were lower than those in the control group and progressively decreased with CKD advancement. Additionally, renal oxygenation and blood flow levels positively correlated with serum creatinine (SCr), cystatin C (Cys C), and blood urea nitrogen (BUN), and negatively correlated with estimated glomerular filtration rate (eGFR) (p < 0.001). However, no significant correlation was observed with uric acid (UA) (p > 0.05). Notably, patients with CKD stages 1-3 exhibited strong correlations between renal oxygenation levels, RBF, and eGFR, while those with CKD stages 4-5 displayed weak correlations.

CONCLUSION

BOLD-MRI and ASL-MRI effectively measure renal oxygenation and perfusion noninvasively, confirming their utility in tracking CKD progression. These modalities provide accurate assessments of renal function and hypoxic-ischemic injuries across CKD stages, particularly in the early stages.

Functional PET/MRI reveals active inhibition of neuronal activity during optogenetic activation of the nigrostriatal pathway

The dopaminergic system is a central component of the brain's neurobiological framework, governing motor control and reward responses and playing an essential role in various brain disorders. Within this complex network, the nigrostriatal pathway represents a critical circuit for dopamine neurotransmission from the substantia nigra to the striatum. However, stand-alone functional magnetic resonance imaging is unable to study the intricate interplay between brain activation and its molecular underpinnings. In our study, the use of a functional [fluorine-18]2-fluor-2-deoxy-d-glucose positron emission tomography approach, simultaneously with blood oxygen level-dependent functional magnetic resonance imaging, provided an important insight that demonstrates an active suppression of the nigrostriatal activity during optogenetic stimulation. This result increases our understanding of the molecular mechanisms of brain function and provides an important perspective on how dopamine influences hemodynamic responses in the brain.

On the analysis of functional PET (fPET)-FDG: baseline mischaracterization can introduce artifactual metabolic (de)activations

Functional Positron Emission Tomography (fPET) with (bolus plus) constant infusion of [18F]-fluorodeoxyglucose FDG), known as fPET-FDG, is a recently introduced technique in human neuroimaging, enabling the detection of dynamic glucose metabolism changes within a single scan. However, the statistical analysis of fPET-FDG data remains challenging because its signal and noise characteristics differ from both classic bolus-administration FDG PET and from functional Magnetic Resonance Imaging (fMRI), which together compose the primary sources of inspiration for analytical methods used by fPET-FDG researchers. In this study, we present an investigate of how inaccuracies in modeling baseline FDG uptake can introduce artifactual patterns to detrended TAC residuals, potentially introducing spurious (de)activations to general linear model (GLM) analyses. By combining simulations and empirical data from both constant infusion and bolus-plus-constant infusion protocols, we evaluate the effects of various baseline modeling methods, including polynomial detrending, regression against the global mean time-activity curve, and two analytical methods based on tissue compartment model kinetics. Our findings indicate that improper baseline removal can introduce statistically significant artifactual effects, although these effects characterized in this study (~2-8%) are generally smaller than those reported by previous literature employing robust sensory stimulation (~10-30%). We discuss potential strategies to mitigate this issue, including informed baseline modeling, optimized tracer administration protocols, and careful experimental design. These insights aim to enhance the reliability of fPET-FDG in capturing true metabolic dynamics in neuroimaging research.

Spatiotemporal relationships between neuronal, metabolic, and hemodynamic signals in the awake and anesthetized mouse brain

Neurovascular coupling (NVC) and neurometabolic coupling (NMC) provide the basis for functional magnetic resonance imaging and positron emission tomography to map brain neurophysiology. While increases in neuronal activity are often accompanied by increases in blood oxygen delivery and oxidative metabolism, these observations are not the rule. This decoupling is important when interpreting brain network organization (e.g., resting-state functional connectivity [RSFC]) because it is unclear whether changes in NMC/NVC affect RSFC measures. We leverage wide-field optical imaging in Thy1-jRGECO1a mice to map cortical calcium activity in pyramidal neurons, flavoprotein autofluorescence (representing oxidative metabolism), and hemodynamic activity during wake and ketamine/xylazine anesthesia. Spontaneous dynamics of all contrasts exhibit patterns consistent with RSFC. NMC/NVC relative to excitatory activity varies over the cortex. Ketamine/xylazine profoundly alters NVC but not NMC. Compared to awake RSFC, ketamine/xylazine affects metabolic-based connectomes moreso than hemodynamic-based measures of RSFC. Anesthesia-related differences in NMC/NVC timing do not appreciably alter RSFC structure.

Synaptic signaling modeled by functional connectivity predicts metabolic demands of the human brain

PURPOSE

The human brain is characterized by interacting large-scale functional networks fueled by glucose metabolism. Since former studies could not sufficiently clarify how these functional connections shape glucose metabolism, we aimed to provide a neurophysiologically-based approach.

METHODS

51 healthy volunteers underwent simultaneous PET/MRI to obtain BOLD functional connectivity and [18F]FDG glucose metabolism. These multimodal imaging proxies of fMRI and PET were combined in a whole-brain extension of metabolic connectivity mapping. Specifically, functional connectivity of all brain regions were used as input to explain glucose metabolism of a given target region. This enabled the modeling of postsynaptic energy demands by incoming signals from distinct brain regions.

RESULTS

Functional connectivity input explained a substantial part of metabolic demands but with pronounced regional variations (34 - 76%). During cognitive task performance this multimodal association revealed a shift to higher network integration compared to resting state. In healthy aging, a dedifferentiation (decreased segregated/modular structure of the brain) of brain networks during rest was observed. Furthermore, by including data from mRNA maps, [11C]UCB-J synaptic density and aerobic glycolysis (oxygen-to-glucose index from PET data), we show that whole-brain functional input reflects non-oxidative, on-demand metabolism of synaptic signaling. The metabolically-derived directionality of functional inputs further marked them as top-down predictions. In addition, the approach uncovered formerly hidden networks with superior efficiency through metabolically informed network partitioning.

CONCLUSIONS

Applying multimodal imaging, we decipher a crucial part of the metabolic and neurophysiological basis of functional connections in the brain as interregional on-demand synaptic signaling fueled by anaerobic metabolism. The observed task- and age-related effects indicate promising future applications to characterize human brain function and clinical alterations.

Validation of cardiac image-derived input functions for functional PET quantification

PURPOSE

Functional PET (fPET) is a novel technique for studying dynamic changes in brain metabolism and neurotransmitter signaling. Accurate quantification of fPET relies on measuring the arterial input function (AIF), traditionally achieved through invasive arterial blood sampling. While non-invasive image-derived input functions (IDIF) offer an alternative, they suffer from limited spatial resolution and field of view. To overcome these issues, we developed and validated a scan protocol for brain fPET utilizing cardiac IDIF, aiming to mitigate known IDIF limitations.

METHODS

Twenty healthy individuals underwent fPET/MR scans using [18F]FDG or 6-[18F]FDOPA, utilizing bed motion shuttling to capture cardiac IDIF and brain task-induced changes. Arterial and venous blood sampling was used to validate IDIFs. Participants performed a monetary incentive delay task. IDIFs from various blood pools and composites estimated from a linear fit over all IDIF blood pools (3VOI) and further supplemented with venous blood samples (3VOIVB) were compared to the AIF. Quantitative task-specific images from both tracers were compared to assess the performance of each input function to the gold standard.

RESULTS

For both radiotracer cohorts, moderate to high agreement (r: 0.60-0.89) between IDIFs and AIF for both radiotracer cohorts was observed, with further improvement (r: 0.87-0.93) for composite IDIFs (3VOI and 3VOIVB). Both methods showed equivalent quantitative values and high agreement (r: 0.975-0.998) with AIF-derived measurements.

CONCLUSION

Our proposed protocol enables accurate non-invasive estimation of the input function with full quantification of task-specific changes, addressing the limitations of IDIF for brain imaging by sampling larger blood pools over the thorax. These advancements increase applicability to any PET scanner and clinical research setting by reducing experimental complexity and increasing patient comfort.

Non-invasive assessment of stimulation-specific changes in cerebral glucose metabolism with functional PET

PURPOSE

Functional positron emission tomography (fPET) with [18F]FDG allows quantification of stimulation-induced changes in glucose metabolism independent of neurovascular coupling. However, the gold standard for quantification requires invasive arterial blood sampling, limiting its widespread use. Here, we introduce a novel fPET method without the need for an input function.

METHODS

We validated the approach using two datasets (DS). For DS1, 52 volunteers (23.2 ± 3.3 years, 24 females) performed Tetris® during a [18F]FDG fPET scan (bolus + constant infusion). For DS2, 18 participants (24.2 ± 4.3 years, 8 females) performed an eyes-open/finger tapping task (constant infusion). Task-specific changes in metabolism were assessed with the general linear model (GLM) and cerebral metabolic rate of glucose (CMRGlu) was quantified with the Patlak plot as reference. We then estimated simplified outcome parameters, including GLM beta values and percent signal change (%SC), and compared them, region and whole-brain-wise.

RESULTS

We observed higher agreement with the reference for DS1 than DS2. Both DS resulted in strong correlations between regional task-specific beta estimates and CMRGlu (r = 0.763…0.912). %SC of beta values exhibited strong agreement with %SC of CMRGlu (r = 0.909…0.999). Average activation maps showed a high spatial similarity between CMRGlu and beta estimates (Dice = 0.870…0.979) as well as %SC (Dice = 0.932…0.997), respectively.

CONCLUSION

The non-invasive method reliably estimates task-specific changes in glucose metabolism without blood sampling. This streamlines fPET, albeit with the trade-off of being unable to quantify baseline metabolism. The simplification enhances its applicability in research and clinical settings.

Altered Neurovascular Coupling in Patients With Mitochondrial Myopathy, Encephalopathy, Lactic Acidosis, and Stroke-Like Episodes (MELAS): A Combined Resting-State fMRI and Arterial Spin Labeling Study

BACKGROUND

Coupling between neuronal activity and blood perfusion is termed neurovascular coupling (NVC), and it provides a potentially new mechanistic perspective into understanding numerous brain diseases. Although abnormal brain activity and blood supply have been separately reported in mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes (MELAS), whether anomalous NVC would be present is unclear.

PURPOSE

To investigate NVC changes and potential neural basis in MELAS by combining resting-state functional MRI (rs-fMRI) and arterial spin labeling (ASL).

STUDY TYPE

Prospective.

SUBJECTS

Twenty-four patients with MELAS (age: 29.8 ± 7.3 years) in the acute stage and 24 healthy controls (HCs, age: 26.4 ± 8.1 years). Additionally, 12 patients in the chronic stage were followed up.

FIELD STRENGTH/SEQUENCE

3.0 T, resting-state gradient-recalled echo-planar imaging and pseudo-continuous 3D ASL sequences.

ASSESSMENT

Amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and functional connectivity strength (FCS) were calculated from rs-fMRI, and cerebral blood flow (CBF) was computed from ASL. Global NVC was assessed by correlation coefficients of CBF-ALFF, CBF-fALFF, CBF-ReHo, and CBF-FCS. Regional NVC was also evaluated by voxel-wise and lesion-wise ratios of CBF/ALFF, CBF/fALFF, CBF/ReHo, and CBF/FCS.

STATISTICAL TESTS

Two-sample t-test, paired-sample t-test, Gaussian random fields correction. A P value <0.05 was considered statistically significant.

RESULTS

Compared with HC, MELAS patients in acute stage showed significantly reduced global CBF-ALFF, CBF-fALFF, CBF-ReHo, and CBF-FCS coupling (P < 0.001). Altered CBF/ALFF, CBF/fALFF, CBF/ReHo, and CBF/FCS ratios were found mainly distributed in the middle cerebral artery territory in MELAS patients. In addition, significantly increased NVC ratios were found in the acute stroke-like lesions in acute stage (P < 0.001), with a recovery trend in chronic stage.

DATA CONCLUSIONS

This study showed dynamic alterations in NVC in MELAS patients from acute to chronic stage, which may provide a novel insight for understanding the pathogenesis of MELAS.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

PET-MRI Applications and Future Prospects in Psychiatry

This article reviews the synergistic application of positron emission tomography-magnetic resonance imaging (PET-MRI) in neuroscience with relevance for psychiatry, particularly examining neurotransmission, epigenetics, and dynamic imaging methodologies. We begin by discussing the complementary insights that PET and MRI modalities provide into neuroreceptor systems, with a focus on dopamine, opioids, and serotonin receptors, and their implications for understanding and treating psychiatric disorders. We further highlight recent PET-MRI studies using a radioligand that enables the quantification of epigenetic enzymes, specifically histone deacetylases, in the brain in vivo. Imaging epigenetics is used to exemplify the impact the quantification of novel molecular targets may have, including new treatment approaches for psychiatric disorders. Finally, we discuss innovative designs involving functional PET using [18F]FDG (fPET-FDG), which provides detailed information regarding dynamic changes in glucose metabolism. Concurrent acquisitions of fPET-FDG and functional MRI provide a time-resolved approach to studying brain function, yielding simultaneous metabolic and hemodynamic information and thereby opening new avenues for psychiatric research. Collectively, the review underscores the potential of a multimodal PET-MRI approach to advance our understanding of brain structure and function in health and disease, which could improve clinical care based on objective neurobiological features and treatment response monitoring. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Effects of Tasks on Functional Brain Connectivity Derived from Inter-Individual Correlations: Insights from Regional Homogeneity of Functional MRI Data

Research on brain functional connectivity often relies on intra-individual moment-to-moment correlations of functional brain activity, typically using techniques like functional MRI (fMRI). Inter-individual correlations are also employed on data from fMRI and positron emission tomography (PET). Many past studies have not specified tasks for participants, keeping them in an implicit "resting" condition. This lack of task specificity raises questions about how different tasks impact inter-individual correlation estimates. In our analysis of fMRI data from 100 unrelated participants, scanned during seven task conditions and in a resting state, we calculated Regional Homogeneity (ReHo) for each task as a regional measure of brain functions. We found that changes in ReHo due to different tasks were relatively small compared with the variations across brain regions. Cross-region variations of ReHo were highly correlated between different tasks. Similarly, whole-brain inter-individual correlation patterns were remarkably consistent across the tasks, showing correlations greater than 0.78. Changes in inter-individual correlations between tasks were primarily driven by connectivity in the visual, somatomotor, default mode network, and the interactions between them. The subtle yet statistically significant differences in functional connectivity may be linked to specific brain regions associated with the studied tasks. Future studies should consider task design when exploring inter-individual connectivity in specific brain systems.

Distinctive and Complementary Roles of Default Mode Network Subsystems in Semantic Cognition

The default mode network (DMN) typically deactivates to external tasks, yet supports semantic cognition. It comprises medial temporal (MT), core, and frontotemporal (FT) subsystems, but its functional organization is unclear: the requirement for perceptual coupling versus decoupling, input modality (visual/verbal), type of information (social/spatial), and control demands all potentially affect its recruitment. We examined the effect of these factors on activation and deactivation of DMN subsystems during semantic cognition, across four task-based human functional magnetic resonance imaging (fMRI) datasets, and localized these responses in whole-brain state space defined by gradients of intrinsic connectivity. FT showed activation consistent with a central role across domains, tasks, and modalities, although it was most responsive to abstract, verbal tasks; this subsystem uniquely showed more "tuned" states characterized by increases in both activation and deactivation when semantic retrieval demands were higher. MT also activated to both perceptually coupled (scenes) and decoupled (autobiographical memory) tasks and showed stronger responses to picture associations, consistent with a role in scene construction. Core DMN consistently showed deactivation, especially to externally oriented tasks. These diverse contributions of DMN subsystems to semantic cognition were related to their location on intrinsic connectivity gradients: activation was closer to the sensory-motor cortex than deactivation, particularly for FT and MT, while activation for core DMN was distant from both visual cortex and cognitive control. These results reveal distinctive yet complementary DMN responses: MT and FT support different memory-based representations that are accessed externally and internally, while deactivation in core DMN is associated with demanding, external semantic tasks.

High-temporal resolution functional PET/MRI reveals coupling between human metabolic and hemodynamic brain response

PURPOSE

Positron emission tomography (PET) provides precise molecular information on physiological processes, but its low temporal resolution is a major obstacle. Consequently, we characterized the metabolic response of the human brain to working memory performance using an optimized functional PET (fPET) framework at a temporal resolution of 3 s.

METHODS

Thirty-five healthy volunteers underwent fPET with [18F]FDG bolus plus constant infusion, 19 of those at a hybrid PET/MRI scanner. During the scan, an n-back working memory paradigm was completed. fPET data were reconstructed to 3 s temporal resolution and processed with a novel sliding window filter to increase signal to noise ratio. BOLD fMRI signals were acquired at 2 s.

RESULTS

Consistent with simulated kinetic modeling, we observed a constant increase in the [18F]FDG signal during task execution, followed by a rapid return to baseline after stimulation ceased. These task-specific changes were robustly observed in brain regions involved in working memory processing. The simultaneous acquisition of BOLD fMRI revealed that the temporal coupling between hemodynamic and metabolic signals in the primary motor cortex was related to individual behavioral performance during working memory. Furthermore, task-induced BOLD deactivations in the posteromedial default mode network were accompanied by distinct temporal patterns in glucose metabolism, which were dependent on the metabolic demands of the corresponding task-positive networks.

CONCLUSIONS

In sum, the proposed approach enables the advancement from parallel to truly synchronized investigation of metabolic and hemodynamic responses during cognitive processing. This allows to capture unique information in the temporal domain, which is not accessible to conventional PET imaging.

Modeling the neurocognitive dynamics of language across the lifespan

Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed between language comprehension and language production (LP). Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this variability. At the cognitive level, our findings suggest that LP is not an isolated function but is modulated throughout the lifespan by the extent of inter-cognitive synergy between semantic and domain-general processes. At the cerebral level, we show that default mode network (DMN) suppression coupled with fronto-parietal network (FPN) integration is the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related decline in LP. Relatedly, reduced DMN suppression in midlife could compromise the ability to manage the cost of FPN integration. This may prompt older adults to adopt a more cost-efficient compensatory strategy that maintains global homeostasis at the expense of LP performances. Taken together, we propose that midlife represents a critical neurocognitive juncture that signifies the onset of LP decline, as older adults gradually lose control over semantic representations. We summarize our findings in a novel synergistic, economical, nonlinear, emergent, cognitive aging model, integrating connectomic and cognitive dimensions within a complex system perspective.

The significance and limited influence of cerebrovascular reactivity on age and sex effects in task- and resting-state brain activity

Functional MRI measures the blood-oxygen-level dependent signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state blood-oxygen-level dependent activity and may confound inter-individual effects, such as those related to aging and biological sex. We examined a large dataset containing breath-holding, checkerboard, and resting-state tasks. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and quantified resting-state activity with amplitude of low-frequency fluctuations and regional homogeneity. We hypothesized that cerebrovascular reactivity would be correlated with blood-oxygen-level dependent measures and that accounting for these correlations would result in better estimates of age and sex effects. We found that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with amplitude of low-frequency fluctuations and regional homogeneity in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in amplitude of low-frequency fluctuations and regional homogeneity. However, correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.

Altered task-related decoupling of the rostral anterior cingulate cortex in depression

Dysfunctional activity of the rostral anterior cingulate cortex (rACC) - an extensively connected hub region of the default mode network - has been broadly linked to cognitive and affective impairments in depression. However, the nature of aberrant task-related rACC suppression in depression is incompletely understood. In this study, we sought to characterize functional connectivity of rACC activity suppression ('deactivation') - an essential feature of rACC function - during external task engagement in depression. Specifically, we aimed to explore neural patterns of functional decoupling and coupling with the rACC during its task-driven suppression. We enrolled 81 15- to 25-year-old young people with moderate-to-severe major depressive disorder (MDD) before they commenced a 12-week clinical trial that assessed the effectiveness of cognitive behavioral therapy plus either fluoxetine or placebo. Ninety-four matched healthy controls were also recruited. Participants completed a functional magnetic resonance imaging face matching task known to elicit rACC suppression. To identify brain regions associated with the rACC during its task-driven suppression, we employed a seed-based functional connectivity analysis. We found MDD participants, compared to controls, showed significantly reduced 'decoupling' of the rACC with extended task-specific regions during task performance. Specifically, less decoupling was observed in the occipital and fusiform gyrus, dorsal ACC, medial prefrontal cortex, cuneus, amygdala, thalamus, and hippocampus. Notably, impaired decoupling was apparent in participants who did not remit to treatment, but not treatment remitters. Further, we found MDD participants showed significant increased coupling with the anterior insula cortex during task engagement. Our findings indicate that aberrant task-related rACC suppression is associated with disruptions in adaptive neural communication and dynamic switching between internal and external cognitive modes that may underpin maladaptive cognitions and biased emotional processing in depression.

Developmental coupling of brain iron and intrinsic activity in infants during the first 150 days

Brain iron is vital for core neurodevelopmental processes including myelination and neurotransmitter synthesis and, accordingly, iron accumulates in the brain with age. However, little is known about the association between brain iron and neural functioning and how they evolve with age in early infancy. This study investigated brain iron in 48 healthy infants (22 females) aged 64.00 ± 33.28 days by estimating R2 * relaxometry from multi-echo functional MRI (fMRI). Linked independent component analysis was performed to examine the association between iron deposition and spontaneous neural activity, as measured by the amplitude of low frequency fluctuations (ALFF) by interrogating shared component loadings across modalities. Further, findings were validated in an independent dataset (n = 45, 24 females, 77.93 ± 26.18 days). The analysis revealed developmental coupling between the global R2 * and ALFF within the default mode network (DMN). Furthermore, we observed that this coupling effect significantly increased with age (r = 0.78, p = 9.2e-11). Our results highlight the importance of iron-neural coupling during early development and suggest that the neural maturation of the DMN may correspond to growth in distributed brain iron.

Pathological claustrum activity drives aberrant cognitive network processing in human chronic pain

Aberrant cognitive network activity and cognitive deficits are established features of chronic pain. However, the nature of cognitive network alterations associated with chronic pain and their underlying mechanisms require elucidation. Here, we report that the claustrum, a subcortical nucleus implicated in cognitive network modulation, is activated by acute painful stimulation and pain-predictive cues in healthy participants. Moreover, we discover pathological activity of the claustrum and a lateral aspect of the right dorsolateral prefrontal cortex (latDLPFC) in migraine patients. Dynamic causal modeling suggests a directional influence of the claustrum on activity in this latDLPFC region, and diffusion weighted imaging (DWI) verifies their structural connectivity. These findings advance understanding of claustrum function during acute pain and provide evidence of a possible circuit mechanism driving cognitive impairments in chronic pain.

Functional FDG-PET: Measurement of Task Related Neural Activity in Humans-A Compartment Model Approach and Comparison to fMRI

Neuroimaging holds an essential position in global healthcare, as brain-related disorders are a substantial and growing burden. Non-degenerative disorders such as stress, depression and anxiety share common function related traits of diffuse and fluctuating changes, such as change in brain-based functions of mood, behavior and cognitive abilities, where underlying physiological mechanism remain unresolved. In this study we developed a novel application for studying intra-subject task-activated brain function by the quantitative physiological measurement of the change in glucose metabolism in a single scan setup. Data were acquired on a PET/MR-scanner. We implemented a functional [18F]-FDG PET-scan with double boli-tracer administration and finger-tapping activation, as proof-of-concept, in five healthy participants. The [18F]-FDG data were analyzed using a two-tissue compartment double boli kinetic model with an image-derived input function. For stand-alone visual reference, blood oxygenation level dependent (BOLD) functional MRI (fMRI) was acquired in the same session and analyzed separately. We were able to measure the cerebral glucose metabolic rate during baseline as well as activation. Results showed increased glucose metabolic rate during activation by 36.3-87.9% mean 62.0%, locally in the peak seed region of M1 in the brain, on an intra-subject level, as well as very good spatial accuracy on group level, and localization compared to the BOLD fMRI result at subject and group level. Our novel method successfully determined the relative increase in the cerebral metabolic rate of glucose on a voxel level with good visual association to fMRI at the subject-level, holding promise for future individual clinical application. This approach will be easily adapted in future clinical perspectives and pharmacological interventions studies.

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.

The Significance and Limited Influence of Cerebrovascular Reactivity on Age and Sex Effects in Task- and Resting-State Brain Activity

Functional MRI (fMRI) measures the blood-oxygen-level dependent (BOLD) signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state BOLD activity and may confound inter-individual effects observed in BOLD-based measures, such as those related to aging and biological sex. To investigate this, we examined a large open-access fMRI dataset containing a breath-holding task, checkerboard task, and resting-state scans. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and from the resting-state data, we quantified the resting-state amplitude of low-frequency fluctuations (ALFF), and resting-state regional homogeneity (ReHo). We hypothesized that cerebrovascular reactivity would be correlated with BOLD measures and that accounting for these correlations would result in better estimates of age and sex effects. Our analysis showed that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with ALFF and ReHo in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in ALFF and ReHo scores. Finally, we demonstrated that correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.

1H magnetic resonance spectroscopic imaging of deuterated glucose and of neurotransmitter metabolism at 7 T in the human brain

Impaired glucose metabolism in the brain has been linked to several neurological disorders. Positron emission tomography and carbon-13 magnetic resonance spectroscopic imaging (MRSI) can be used to quantify the metabolism of glucose, but these methods involve exposure to radiation, cannot quantify downstream metabolism, or have poor spatial resolution. Deuterium MRSI (2H-MRSI) is a non-invasive and safe alternative for the quantification of the metabolism of 2H-labelled substrates such as glucose and their downstream metabolic products, yet it can only measure a limited number of deuterated compounds and requires specialized hardware. Here we show that proton MRSI (1H-MRSI) at 7 T has higher sensitivity, chemical specificity and spatiotemporal resolution than 2H-MRSI. We used 1H-MRSI in five volunteers to differentiate glutamate, glutamine, γ-aminobutyric acid and glucose deuterated at specific molecular positions, and to simultaneously map deuterated and non-deuterated metabolites. 1H-MRSI, which is amenable to clinically available magnetic-resonance hardware, may facilitate the study of glucose metabolism in the brain and its potential roles in neurological disorders.

Task-evoked metabolic demands of the posteromedial default mode network are shaped by dorsal attention and frontoparietal control networks

External tasks evoke characteristic fMRI BOLD signal deactivations in the default mode network (DMN). However, for the corresponding metabolic glucose demands both decreases and increases have been reported. To resolve this discrepancy, functional PET/MRI data from 50 healthy subjects performing Tetris were combined with previously published data sets of working memory, visual and motor stimulation. We show that the glucose metabolism of the posteromedial DMN is dependent on the metabolic demands of the correspondingly engaged task-positive networks. Specifically, the dorsal attention and frontoparietal network shape the glucose metabolism of the posteromedial DMN in opposing directions. While tasks that mainly require an external focus of attention lead to a consistent downregulation of both metabolism and the BOLD signal in the posteromedial DMN, cognitive control during working memory requires a metabolically expensive BOLD suppression. This indicates that two types of BOLD deactivations with different oxygen-to-glucose index may occur in this region. We further speculate that consistent downregulation of the two signals is mediated by decreased glutamate signaling, while divergence may be subject to active GABAergic inhibition. The results demonstrate that the DMN relates to cognitive processing in a flexible manner and does not always act as a cohesive task-negative network in isolation.

Successful aging of musicians: Preservation of sensorimotor regions aids audiovisual speech-in-noise perception

Musicianship can mitigate age-related declines in audiovisual speech-in-noise perception. We tested whether this benefit originates from functional preservation or functional compensation by comparing fMRI responses of older musicians, older nonmusicians, and young nonmusicians identifying noise-masked audiovisual syllables. Older musicians outperformed older nonmusicians and showed comparable performance to young nonmusicians. Notably, older musicians retained similar neural specificity of speech representations in sensorimotor areas to young nonmusicians, while older nonmusicians showed degraded neural representations. In the same region, older musicians showed higher neural alignment to young nonmusicians than older nonmusicians, which was associated with their training intensity. In older nonmusicians, the degree of neural alignment predicted better performance. In addition, older musicians showed greater activation in frontal-parietal, speech motor, and visual motion regions and greater deactivation in the angular gyrus than older nonmusicians, which predicted higher neural alignment in sensorimotor areas. Together, these findings suggest that musicianship-related benefit in audiovisual speech-in-noise processing is rooted in preserving youth-like representations in sensorimotor regions.

Cognition is entangled with metabolism: relevance for resting-state EEG-fMRI

The brain is a living organ with distinct metabolic constraints. However, these constraints are typically considered as secondary or supportive of information processing which is primarily performed by neurons. The default operational definition of neural information processing is that (1) it is ultimately encoded as a change in individual neuronal firing rate as this correlates with the presentation of a peripheral stimulus, motor action or cognitive task. Two additional assumptions are associated with this default interpretation: (2) that the incessant background firing activity against which changes in activity are measured plays no role in assigning significance to the extrinsically evoked change in neural firing, and (3) that the metabolic energy that sustains this background activity and which correlates with differences in neuronal firing rate is merely a response to an evoked change in neuronal activity. These assumptions underlie the design, implementation, and interpretation of neuroimaging studies, particularly fMRI, which relies on changes in blood oxygen as an indirect measure of neural activity. In this article we reconsider all three of these assumptions in light of recent evidence. We suggest that by combining EEG with fMRI, new experimental work can reconcile emerging controversies in neurovascular coupling and the significance of ongoing, background activity during resting-state paradigms. A new conceptual framework for neuroimaging paradigms is developed to investigate how ongoing neural activity is "entangled" with metabolism. That is, in addition to being recruited to support locally evoked neuronal activity (the traditional hemodynamic response), changes in metabolic support may be independently "invoked" by non-local brain regions, yielding flexible neurovascular coupling dynamics that inform the cognitive context. This framework demonstrates how multimodal neuroimaging is necessary to probe the neurometabolic foundations of cognition, with implications for the study of neuropsychiatric disorders.

Widespread fMRI BOLD Signal Overactivations during Cognitive Control in Older Adults Are Not Matched by Corresponding Increases in fPET Glucose Metabolism

A common observation in fMRI studies using the BOLD signal is that older adults, compared with young adults, show overactivations, particularly during less demanding tasks. The neuronal underpinnings of such overactivations are not known, but a dominant view is that they are compensatory in nature and involve recruitment of additional neural resources. We scanned 23 young (20-37 years) and 34 older (65-86 years) healthy human adults of both sexes with hybrid positron emission tomography/MRI. The radioligand [18F]fluoro-deoxyglucose was used to assess dynamic changes in glucose metabolism as a marker of task-dependent synaptic activity, along with simultaneous fMRI BOLD imaging. Participants performed two verbal working memory (WM) tasks: one involving maintenance (easy) and one requiring manipulation (difficult) of information in WM. Converging activations to the WM tasks versus rest were observed for both imaging modalities and age groups in attentional, control, and sensorimotor networks. Upregulation of activity to WM-demand, comparing the more difficult to the easier task, also converged between both modalities and age groups. For regions in which older adults showed task-dependent BOLD overactivations compared with the young adults, no corresponding increases in glucose metabolism were found. To conclude, findings from the current study show that task-induced changes in the BOLD signal and synaptic activity as measured by glucose metabolism generally converge, but overactivations observed with fMRI in older adults are not coupled with increased synaptic activity, which suggests that these overactivations are not neuronal in origin.SIGNIFICANCE STATEMENT Findings of increased fMRI activations in older compared with younger adults have been suggested to reflect increased use of neuronal resources to cope with reduced brain function. The physiological underpinnings of such compensatory processes are poorly understood, however, and rest on the assumption that vascular signals accurately reflect neuronal activity. Comparing fMRI and simultaneously acquired functional positron emission tomography as an alternative index of synaptic activity, we show that age-related overactivations do not appear to be neuronal in origin. This result is important because mechanisms underlying compensatory processes in aging are potential targets for interventions aiming to prevent age-related cognitive decline.

A distinct intra-individual suppression subnetwork in the brain's default mode network across cognitive tasks

Suppression of the brain's default mode network (DMN) during external goal-directed cognitive tasks has been consistently observed in neuroimaging studies. However, emerging insights suggest the DMN is not a monolithic "task-negative" network but is comprised of subsystems that show functional heterogeneity. Despite considerable research interest, no study has investigated the consistency of DMN activity suppression across multiple cognitive tasks within the same individuals. In this study, 85 healthy 15- to 25-year-olds completed three functional magnetic resonance imaging tasks that were designed to reliably map DMN suppression from a resting baseline. Our findings revealed a distinct suppression subnetwork across the three tasks that comprised traditional DMN and adjacent regions. Specifically, common suppression was observed in the medial prefrontal cortex, the dorsal-to-mid posterior cingulate cortex extending to the precuneus, and the posterior insular cortex and parietal operculum. Further, we found the magnitude of suppression of these regions were significantly correlated within participants across tasks. Overall, our findings indicate that externally oriented cognitive tasks elicit common suppression of a distinct subnetwork of the broader DMN. The consistency to which the DMN is suppressed within individuals suggests a domain-general mechanism that may reflect a stable feature of cognitive function that optimizes external goal-directed behavior.

A tripartite view of the posterior cingulate cortex

The posterior cingulate cortex (PCC) is one of the least understood regions of the cerebral cortex. By contrast, the anterior cingulate cortex has been the subject of intensive investigation in humans and model animal systems, leading to detailed behavioural and computational theoretical accounts of its function. The time is right for similar progress to be made in the PCC given its unique anatomical and physiological properties and demonstrably important contributions to higher cognitive functions and brain diseases. Here, we describe recent progress in understanding the PCC, with a focus on convergent findings across species and techniques that lay a foundation for establishing a formal theoretical account of its functions. Based on this converging evidence, we propose that the broader PCC region contains three major subregions - the dorsal PCC, ventral PCC and retrosplenial cortex - that respectively support the integration of executive, mnemonic and spatial processing systems. This tripartite subregional view reconciles inconsistencies in prior unitary theories of PCC function and offers promising new avenues for progress.

Vesicular Glutamate Transporter Changes in the Cortical Default Mode Network During the Clinical and Pathological Progression of Alzheimer's Disease

BACKGROUND

Altered glutamatergic neurotransmission may contribute to impaired default mode network (DMN) function in Alzheimer's disease (AD). Among the DMN hub regions, frontal cortex (FC) was suggested to undergo a glutamatergic plasticity response in prodromal AD, while the status of glutamatergic synapses in the precuneus (PreC) during clinical-neuropathological AD progression is not known.

OBJECTIVE

To quantify vesicular glutamate transporter VGluT1- and VGluT2-containing synaptic terminals in PreC and FC across clinical stages of AD.

METHODS

Unbiased sampling and quantitative confocal immunofluorescence of cortical VGluT1- and VGluT2-immunoreactive profiles and spinophilin-labeled dendritic spines were performed in cases with no cognitive impairment (NCI), mild cognitive impairment (MCI), mild-moderate AD (mAD), or moderate-severe AD (sAD).

RESULTS

In both regions, loss of VGluT1-positive profile density was seen in sAD compared to NCI, MCI, and mAD. VGluT1-positive profile intensity in PreC did not differ across groups, while in FC it was greater in MCI, mAD, and sAD compared to NCI. VGluT2 measures were stable in PreC while FC had greater VGluT2-positive profile density in MCI compared to sAD, but not NCI or mAD. Spinophilin measures in PreC were lower in mAD and sAD compared to NCI, while in FC they were stable across groups. Lower VGluT1 and spinophilin measures in PreC, but not FC, correlated with greater neuropathology.

CONCLUSION

Frank loss of VGluT1 in advanced AD relative to NCI occurs in both DMN regions. In FC, an upregulation of VGluT1 protein content in remaining glutamatergic terminals may contribute to this region's plasticity response in AD.

Estrogen, Cognitive Performance, and Functional Imaging Studies: What Are We Missing About Neuroprotection?

Menopause transition can be interpreted as a vulnerable state characterized by estrogen deficiency with detrimental systemic effects as the low-grade chronic inflammation that appears with aging and partly explains age-related disorders as cancer, diabetes mellitus and increased risk of cognitive impairment. Over the course of a lifetime, estrogen produces several beneficial effects in healthy neurological tissues as well as cardioprotective effects, and anti-inflammatory effects. However, clinical evidence on the efficacy of hormone treatment in menopausal women has failed to confirm the benefit reported in observational studies. Unambiguously, enhanced verbal memory is the most robust finding from longitudinal and cross-sectional studies, what merits consideration for future studies aiming to determine estrogen neuroprotective efficacy. Estrogen related brain activity and functional connectivity remain, however, unexplored. In this context, the resting state paradigm may provide valuable information about reproductive aging and hormonal treatment effects, and their relationship with brain imaging of functional connectivity may be key to understand and anticipate estrogen cognitive protective effects. To go in-depth into the molecular and cellular mechanisms underlying rapid-to-long lasting protective effects of estrogen, we will provide a comprehensive review of cognitive tasks used in animal studies to evaluate the effect of hormone treatment on cognitive performance and discuss about the tasks best suited to the demonstration of clinically significant differences in cognitive performance to be applied in human studies. Eventually, we will focus on studies evaluating the DMN activity and responsiveness to pharmacological stimulation in humans.

Task-specific network interactions across key cognitive domains

Human cognition is organized in distributed networks in the brain. Although distinct specialized networks have been identified for different cognitive functions, previous work also emphasizes the overlap of key cognitive domains in higher level association areas. The majority of previous studies focused on network overlap and dissociation during resting states whereas task-related network interactions across cognitive domains remain largely unexplored. A better understanding of network overlap and dissociation during different cognitive tasks may elucidate flexible (re-)distribution of resources during human cognition. The present study addresses this issue by providing a broad characterization of large-scale network dynamics in three key cognitive domains. Combining prototypical tasks of the larger domains of attention, language, and social cognition with whole-brain multivariate activity and connectivity approaches, we provide a spatiotemporal characterization of multiple large-scale, overlapping networks that differentially interact across cognitive domains. We show that network activity and interactions increase with increased cognitive complexity across domains. Interaction patterns reveal a common core structure across domains as well as dissociable domain-specific network activity. The observed patterns of activation and deactivation of overlapping and strongly coupled networks provide insight beyond region-specific activity within a particular cognitive domain toward a network perspective approach across diverse key cognitive functions.

Functional Parcellation of the Hippocampus based on its Layer-specific Connectivity with Default Mode and Dorsal Attention Networks

Recent neuroimaging evidence suggests that there might be an anterior-posterior functional differentiation of the hippocampus along the long-axis. The HERNET (hippocampal encoding/retrieval and network) model proposed an encoding/retrieval dichotomy with the anterior hippocampus more connected to the dorsal attention network (DAN) during memory encoding, and the posterior portions more connected to the default mode network (DMN) during retrieval. Evidence both for and against the HERNET model has been reported. In this study, we test the validity of the HERNET model non-invasively in humans by computing functional connectivity (FC) in layer-specific cortico-hippocampal microcircuits. This was achieved by acquiring sub-millimeter functional magnetic resonance imaging (fMRI) data during encoding/retrieval tasks at 7T. Specifically, FC between infra-granular output layers of DAN with hippocampus during encoding and FC between supra-granular input layers of DMN with hippocampus during retrieval were computed to test the predictions of the HERNET model. Our results support some predictions of the HERNET model including anterior-posterior gradient along the long axis of the hippocampus. While preferential relationships between the entire hippocampus and DAN/DMN during encoding/retrieval, respectively, were observed as predicted, anterior-posterior specificity in these network relationships could not be confirmed. The strength and clarity of evidence for/against the HERNET model were superior with layer-specific data compared to conventional volume data.