A blood-free modeling approach for the quantification of the blood-to-brain tracer exchange in TSPO PET imaging.

Introduction: Recent evidence suggests the blood-to-brain influx rate (K1 ) in TSPO PET imaging as a promising biomarker of blood-brain barrier (BBB) permeability alterations commonly associated with peripheral inflammation and heightened immune activity in the brain. However, standard compartmental modeling quantification is limited by the requirement of invasive and laborious procedures for extracting an arterial blood input function. In this study, we validate a simplified blood-free methodologic framework for K1 estimation by fitting the early phase tracer dynamics using a single irreversible compartment model and an image-derived input function (1T1K-IDIF). Methods: The method is tested on a multi-site dataset containing 177 PET studies from two TSPO tracers ([11C]PBR28 and [18F]DPA714). Firstly, 1T1K-IDIF K1 estimates were compared in terms of both bias and correlation with standard kinetic methodology. Then, the method was tested on an independent sample of [11C]PBR28 scans before and after inflammatory interferon-α challenge, and on test-retest dataset of [18F]DPA714 scans. Results: Comparison with standard kinetic methodology showed good-to-excellent intra-subject correlation for regional 1T1K-IDIF-K1 (ρintra = 0.93 ± 0.08), although the bias was variable depending on IDIF ability to approximate blood input functions (0.03-0.39 mL/cm3/min). 1T1K-IDIF-K1 unveiled a significant reduction of BBB permeability after inflammatory interferon-α challenge, replicating results from standard quantification. High intra-subject correlation (ρ = 0.97 ± 0.01) was reported between K1 estimates of test and retest scans. Discussion: This evidence supports 1T1K-IDIF as blood-free alternative to assess TSPO tracers' unidirectional blood brain clearance. K1 investigation could complement more traditional measures in TSPO studies, and even allow further mechanistic insight in the interpretation of TSPO signal.

Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging.

INTRODUCTION: We propose a novel approach for the non-invasive quantification of dynamic PET imaging data, focusing on the arterial input function (AIF) without the need for invasive arterial cannulation. METHODS: Our method utilizes a combination of three-dimensional depth-wise separable convolutional layers and a physically informed deep neural network to incorporatea priori knowledge about the AIF's functional form and shape, enabling precise predictions of the concentrations of [11C]PBR28 in whole blood and the free tracer in metabolite-corrected plasma. RESULTS: We found a robust linear correlation between our model's predicted AIF curves and those obtained through traditional, invasive measurements. We achieved an average cross-validated Pearson correlation of 0.86 for whole blood and 0.89 for parent plasma curves. Moreover, our method's ability to estimate the volumes of distribution across several key brain regions - without significant differences between the use of predicted versus actual AIFs in a two-tissue compartmental model - successfully captures the intrinsic variability related to sex, the binding affinity of the translocator protein (18 kDa), and age. CONCLUSIONS: These results not only validate our method's accuracy and reliability but also establish a foundation for a streamlined, non-invasive approach to dynamic PET data quantification. By offering a precise and less invasive alternative to traditional quantification methods, our technique holds significant promise for expanding the applicability of PET imaging across a wider range of tracers, thereby enhancing its utility in both clinical research and diagnostic settings.

Synaptic changes in psychiatric and neurological disorders: state-of-the art of in vivo imaging.

Synapses are implicated in many neuropsychiatric illnesses. Here, we provide an overview of in vivo techniques to index synaptic markers in patients. Several positron emission tomography (PET) tracers for synaptic vesicle glycoprotein 2 A (SV2A) show good reliability and selectivity. We review over 50 clinical studies including over 1700 participants, and compare findings in healthy ageing and across disorders, including addiction, schizophrenia, depression, posttraumatic stress disorder, and neurodegenerative disorders, including tauopathies, Huntington's disease and α-synucleinopathies. These show lower SV2A measures in cortical brain regions across most of these disorders relative to healthy volunteers, with the most well-replicated findings in tauopathies, whilst changes in Huntington's chorea, Parkinson's disease, corticobasal degeneration and progressive supranuclear palsy are predominantly subcortical. SV2A PET measures are correlated with functional connectivity across brain networks, and a number of other measures of brain function, including glucose metabolism. However, the majority of studies found no relationship between grey matter volume measured with magnetic resonance imaging and SV2A PET measures. Cognitive dysfunction, in domains including working memory and executive function, show replicated inverse relationships with SV2A measures across diagnoses, and initial findings also suggest transdiagnostic relationships with mood and anxiety symptoms. This suggests that synaptic abnormalities could be a common pathophysiological substrate underlying cognitive and, potentially, affective symptoms. We consider limitations of evidence and future directions; highlighting the need to develop postsynaptic imaging markers and for longitudinal studies to test causal mechanisms.

Altered oxidative neurometabolic response to methylene blue in bipolar disorder revealed by quantitative neuroimaging.

BACKGROUND: Cerebral mitochondrial and hemodynamic abnormalities have been implicated in Bipolar Disorder pathophysiology, likely contributing to neurometabolic vulnerability-leading to worsen clinical outcomes and mood instability. To investigate neurometabolic vulnerability in patients with BD, we combined multi-modal quantitative MRI assessment of cerebral oxygenation with acute administration of Methylene Blue, a neurometabolic/hemodynamic modulator acting on cerebral mitochondria. METHODS: Fifteen euthymic patients with chronic BD-type 1, and fifteen age/gender-matched healthy controls underwent two separate MRI sessions in a single-blinded randomized cross-over design, each after intravenous infusion of either MB (0.5 mg/kg) or placebo. MRI-based measures of Cerebral Blood Flow and Oxygen Extraction Fraction were integrated to compute Cerebral Metabolic Rate of Oxygen in Frontal Lobe, Anterior Cingulate, and Hippocampus-implicated in BD neurometabolic pathophysiology. Inter-daily variation in mood rating was used to assess mood instability. RESULTS: A decrease in global CBF and CMRO2 was observed after acutely administrating MB to all participants. Greater regional CMRO2 reductions were observed after MB, in patients compared to controls in FL (mean = -14.2 ± 19.5 % versus 2.3 ± 14.8 %), ACC (mean = -14.8 ± 23.7 % versus 2.4 ± 15.7 %). The effects on CMRO2 in those regions were primarily driven by patients with longer disease duration and higher mood instability. LIMITATIONS: Sample size; medications potentially impacting on response to MB. CONCLUSIONS: An altered neurometabolic response to MB, a mitochondrial/hemodynamic modulator, was observed in patients, supporting the hypothesis of vulnerability to neurometabolic stress in BD. Integrating quantitative imaging of cerebral oxygen metabolism with a mitochondrial-targeting pharmacological challenge could provide a novel biomarker of neurometabolic and cerebrovascular pathophysiology in BD.

Normative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients.

Advanced methods such as REACT have allowed the integration of fMRI with the brain's receptor landscape, providing novel insights transcending the multiscale organisation of the brain. Similarly, normative modelling has allowed translational neuroscience to move beyond group-average differences and characterise deviations from health at an individual level. Here, we bring these methods together for the first time. We used REACT to create functional networks enriched with the main modulatory, inhibitory, and excitatory neurotransmitter systems and generated normative models of these networks to capture functional connectivity deviations in patients with schizophrenia, bipolar disorder (BPD), and ADHD. Substantial overlap was seen in symptomatology and deviations from normality across groups, but these could be mapped into a common space linking constellations of symptoms through to underlying neurobiology transdiagnostically. This work provides impetus for developing novel biomarkers that characterise molecular- and systems-level dysfunction at the individual level, facilitating the transition towards mechanistically targeted treatments.

Brain Fluid Clearance After Traumatic Brain Injury Measured Using Dynamic Positron Emission Tomography.

Brain fluid clearance by pathways including the recently described paravascular glymphatic system is a critical homeostatic mechanism by which metabolic products, toxins, and other wastes are removed from the brain. Brain fluid clearance may be especially important after traumatic brain injury (TBI), when blood, neuronal debris, inflammatory cells, and other substances can be released and/or deposited. Using a non-invasive dynamic positron emission tomography (PET) method that models the rate at which an intravenously injected radiolabeled molecule (in this case 11C-flumazenil) is cleared from ventricular cerebrospinal fluid (CSF), we estimated the overall efficiency of brain fluid clearance in humans who had experienced complicated-mild or moderate TBI 3-6 months before neuroimaging (n = 7) as compared to healthy controls (n = 9). While there was no significant difference in ventricular clearance between TBI subjects and controls, there was a significant group difference in dependence of ventricular clearance upon tracer delivery/blood flow to the ventricles. Specifically, in controls, ventricular clearance was highly, linearly dependent upon blood flow to the ventricle, but this relation was disrupted in TBI subjects. When accounting for blood flow and group-specific alterations in blood flow, ventricular clearance was slightly (non-significantly) increased in TBI subjects as compared to controls. Current results contrast with past studies showing reduced glymphatic function after TBI and are consistent with possible differential effects of TBI on glymphatic versus non-glymphatic clearance mechanisms. Further study using multi-modal methods capable of assessing and disentangling blood flow and different aspects of fluid clearance is needed to clarify clearance alterations after TBI.

Altered dynamical integration/segregation balance during anesthesia-induced loss of consciousness.

In recent years, brain imaging studies have begun to shed light on the neural correlates of physiologically-reversible altered states of consciousness such as deep sleep, anesthesia, and psychedelic experiences. The emerging consensus is that normal waking consciousness requires the exploration of a dynamical repertoire enabling both global integration i.e., long-distance interactions between brain regions, and segregation, i.e., local processing in functionally specialized clusters. Altered states of consciousness have notably been characterized by a tipping of the integration/segregation balance away from this equilibrium. Historically, functional MRI (fMRI) has been the modality of choice for such investigations. However, fMRI does not enable characterization of the integration/segregation balance at sub-second temporal resolution. Here, we investigated global brain spatiotemporal patterns in electrocorticography (ECoG) data of a monkey (Macaca fuscata) under either ketamine or propofol general anesthesia. We first studied the effects of these anesthetics from the perspective of band-specific synchronization across the entire ECoG array, treating individual channels as oscillators. We further aimed to determine whether synchrony within spatially localized clusters of oscillators was differently affected by the drugs in comparison to synchronization over spatially distributed subsets of ECoG channels, thereby quantifying changes in integration/segregation balance on physiologically-relevant time scales. The findings reflect global brain dynamics characterized by a loss of long-range integration in multiple frequency bands under both ketamine and propofol anesthesia, most pronounced in the beta (13-30 Hz) and low-gamma bands (30-80 Hz), and with strongly preserved local synchrony in all bands.

Microglial activation, tau and amyloid deposition in TREM2 p.R47H carriers and mild cognitive impairment patients: a multi-modal/multi-tracer PET/MRI imaging study with influenza vaccine immune challenge.

BACKGROUND: Microglia are increasingly understood to play an important role in the pathogenesis of Alzheimer's disease. The rs75932628 (p.R47H) TREM2 variant is a well-established risk factor for Alzheimer's disease. TREM2 is a microglial cell surface receptor. In this multi-modal/multi-tracer PET/MRI study we investigated the effect of TREM2 p.R47H carrier status on microglial activation, tau and amyloid deposition, brain structure and cognitive profile. METHODS: We compared TREM2 p.R47H carriers (n = 8; median age = 62.3) and participants with mild cognitive impairment (n = 8; median age = 70.7). Participants underwent two [18F]DPA-714 PET/MRI scans to assess TSPO signal, indicative of microglial activation, before and after receiving the seasonal influenza vaccination, which was used as an immune stimulant. Participants also underwent [18F]florbetapir and [18F]AV1451 PET scans to assess amyloid and tau burden, respectively. Regional tau and TSPO signal were calculated for regions of interest linked to Braak stage. An additional comparison imaging healthy control group (n = 8; median age = 45.5) had a single [18F]DPA-714 PET/MRI. An expanded group of participants underwent neuropsychological testing, to determine if TREM2 status influenced clinical phenotype. RESULTS: Compared to participants with mild cognitive impairment, TREM2 carriers had lower TSPO signal in Braak II (P = 0.04) and Braak III (P = 0.046) regions, despite having a similar burden of tau and amyloid. There were trends to suggest reduced microglial activation following influenza vaccine in TREM2 carriers. Tau deposition in the Braak VI region was higher in TREM2 carriers (P = 0.04). Furthermore, compared to healthy controls TREM2 carriers had smaller caudate (P = 0.02), total brain (P = 0.049) and white matter volumes (P = 0.02); and neuropsychological assessment revealed worse ADAS-Cog13 (P = 0.03) and Delayed Matching to Sample (P = 0.007) scores. CONCLUSIONS: TREM2 p.R47H carriers had reduced levels of microglial activation in brain regions affected early in the Alzheimer's disease course and differences in brain structure and cognition. Changes in microglial response may underlie the increased Alzheimer's disease risk in TREM2 p.R47H carriers. Future therapeutic agents in Alzheimer's disease should aim to enhance protective microglial actions.

Two human brain systems micro-structurally associated with obesity.

The relationship between obesity and human brain structure is incompletely understood. Using diffusion-weighted MRI from ∼30,000 UK Biobank participants, we test the hypothesis that obesity (waist-to-hip ratio, WHR) is associated with regional differences in two micro-structural MRI metrics: isotropic volume fraction (ISOVF), an index of free water, and intra-cellular volume fraction (ICVF), an index of neurite density. We observed significant associations with obesity in two coupled but distinct brain systems: a prefrontal/temporal/striatal system associated with ISOVF and a medial temporal/occipital/striatal system associated with ICVF. The ISOVF~WHR system colocated with expression of genes enriched for innate immune functions, decreased glial density, and high mu opioid (MOR) and other neurotransmitter receptor density. Conversely, the ICVF~WHR system co-located with expression of genes enriched for G-protein coupled receptors and decreased density of MOR and other receptors. To test whether these distinct brain phenotypes might differ in terms of their underlying shared genetics or relationship to maps of the inflammatory marker C-reactive Protein (CRP), we estimated the genetic correlations between WHR and ISOVF (rg = 0.026, P = 0.36) and ICVF (rg = 0.112, P < 9×10-4) as well as comparing correlations between WHR maps and equivalent CRP maps for ISOVF and ICVF (P<0.05). These correlational results are consistent with a two-way mechanistic model whereby genetically determined differences in neurite density in the medial temporal system may contribute to obesity, whereas water content in the prefrontal system could reflect a consequence of obesity mediated by innate immune system activation.

People with obesity are at greater risk of cardiovascular diseases and metabolic conditions such as type 2 diabetes. More recently obesity has also been linked to changes in the brain that are associated with age-related dementia and cognitive decline. This includes a thinner cortex (the brain's outer layer) and lower volume of grey matter which is where cognitive processes, such as learning, take place. However, questions remain about how obesity and grey matter are connected. For instance, it is unclear whether the change in volume is due to there being fewer cells (and thus more water between them) or fewer connections between cells in these brain areas. It is also unknown whether the reduced volume of grey matter is a cause or consequence of obesity. To address these questions, Kitzbichler et al. analysed 30,000 MRI scans of the human brain which are stored in the UK Biobank. This revealed two characteristics in grey matter that were linked to obesity: higher amounts of water between cells in some areas, and a lower density of connections between neurons in others. The areas with higher levels of free water are known to have more glial cells which provide support to neurons. They also have more receptors that bind to fatty acids (which are often raised in people with obesity) and more receptors for molecules and cells involved in the immune response. In contrast, the areas with a lower density of connections between neurons usually were more closely associated with genetic risk factors associated with obesity, and fewer receptors involved in feeding, appetite and energy use. The findings of Kitzblicher et al. suggest that differences in the density of connections between neurons may contribute to obesity. High water content in grey matter, on the other hand, may be a consequence of obesity that occurs as a result of immune receptors becoming activated. This provides new insights in to how obesity and grey matter in the brain are connected.

Establishing brain states in neuroimaging data.

The definition of a brain state remains elusive, with varying interpretations across different sub-fields of neuroscience-from the level of wakefulness in anaesthesia, to activity of individual neurons, voltage in EEG, and blood flow in fMRI. This lack of consensus presents a significant challenge to the development of accurate models of neural dynamics. However, at the foundation of dynamical systems theory lies a definition of what constitutes the 'state' of a system-i.e., a specification of the system's future. Here, we propose to adopt this definition to establish brain states in neuroimaging timeseries by applying Dynamic Causal Modelling (DCM) to low-dimensional embedding of resting and task condition fMRI data. We find that ~90% of subjects in resting conditions are better described by first-order models, whereas ~55% of subjects in task conditions are better described by second-order models. Our work calls into question the status quo of using first-order equations almost exclusively within computational neuroscience and provides a new way of establishing brain states, as well as their associated phase space representations, in neuroimaging datasets.

Mapping acute neuroinflammation in vivo with diffusion-MRI in rats given a systemic lipopolysaccharide challenge.

It is becoming increasingly apparent that neuroinflammation plays a critical role in an array of neurological and psychiatric disorders. Recent studies have demonstrated the potential of diffusion MRI (dMRI) to characterize changes in microglial density and morphology associated with neuroinflammation, but these were conducted mostly ex vivo and/or in extreme, non-physiological animal models. Here, we build upon these studies by investigating the utility of well-established dMRI methods to detect neuroinflammation in vivo in a more clinically relevant animal model of sickness behavior. We show that diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) indicate widespread increases in diffusivity in the brains of rats given a systemic lipopolysaccharide challenge (n = 20) vs. vehicle-treated controls (n = 12). These diffusivity changes correlated with histologically measured changes in microglial morphology, confirming the sensitivity of dMRI to neuroinflammatory processes. This study marks a further step towards establishing a noninvasive indicator of neuroinflammation, which would greatly facilitate early diagnosis and treatment monitoring in various neurological and psychiatric diseases.

Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI.

Receptor-enriched analysis of functional connectivity by targets (REACT) is a strategy to enrich functional MRI (fMRI) data with molecular information on the neurotransmitter distribution density in the human brain, providing a biological basis to the functional connectivity (FC) analysis. Although this approach has been used in BOLD fMRI studies only so far, extending its use to ASL imaging would provide many advantages, including the more direct link of ASL with neuronal activity compared to BOLD and its suitability for pharmacological MRI studies assessing drug effects on baseline brain function. Here, we applied REACT to simultaneous ASL/BOLD resting-state fMRI data of 29 healthy subjects and estimated the ASL and BOLD FC maps related to six molecular systems. We then compared the ASL and BOLD FC maps in terms of spatial similarity, and evaluated and compared the test-retest reproducibility of each modality. We found robust spatial patterns of molecular-enriched FC for both modalities, moderate similarity between BOLD and ASL FC maps and comparable reproducibility for all but one molecular-enriched functional networks. Our findings showed that ASL is as informative as BOLD in detecting functional circuits associated with specific molecular pathways, and that the two modalities may provide complementary information related to these circuits.

The relationship between striatal dopamine and anterior cingulate glutamate in first episode psychosis changes with antipsychotic treatment.

The neuromodulator dopamine and excitatory neurotransmitter glutamate have both been implicated in the pathogenesis of psychosis, and dopamine antagonists remain the predominant treatment for psychotic disorders. To date no study has measured the effect of antipsychotics on both of these indices together, in the same population of people with psychosis. Striatal dopamine synthesis capacity (Kicer) and anterior cingulate glutamate were measured using 18F-DOPA positron emission tomography and proton magnetic resonance spectroscopy respectively, before and after at least 5 weeks' naturalistic antipsychotic treatment in people with first episode psychosis (n = 18) and matched healthy controls (n = 20). The relationship between both measures at baseline and follow-up, and the change in this relationship was analyzed using a mixed linear model. Neither anterior cingulate glutamate concentrations (p = 0.75) nor striatal Kicer (p = 0.79) showed significant change following antipsychotic treatment. The change in relationship between whole striatal Kicer and anterior cingulate glutamate, however, was statistically significant (p = 0.017). This was reflected in a significant difference in relationship between both measures for patients and controls at baseline (t = 2.1, p = 0.04), that was not present at follow-up (t = 0.06, p = 0.96). Although we did not find any effect of antipsychotic treatment on absolute measures of dopamine synthesis capacity and anterior cingulate glutamate, the relationship between anterior cingluate glutamate and striatal dopamine synthesis capacity did change, suggesting that antipsychotic treatment affects the relationship between glutamate and dopamine.

Pharmacological modulation of TSPO in microglia/macrophages and neurons in a chronic neurodegenerative model of prion disease.

Neuroinflammation is an important component of many neurodegenerative diseases, whether as a primary cause or a secondary outcome. For that reason, either as diagnostic tools or to monitor progression and/or pharmacological interventions, there is a need for robust biomarkers of neuroinflammation in the brain. Mitochondrial TSPO (18 kDa Translocator protein) is one of few available biomarkers of neuroinflammation for which there are clinically available PET imaging agents. In this study, we further characterised neuroinflammation in a mouse model of prion-induced chronic neurodegeneration (ME7) including a pharmacological intervention via a CSF1R inhibitor. This was achieved by autoradiographic binding of the second-generation TSPO tracer, [3H]PBR28, along with a more comprehensive examination of the cellular contributors to the TSPO signal changes by immunohistochemistry. We observed regional increases of TSPO in the ME7 mouse brains, particularly in the hippocampus, cortex and thalamus. This increased TSPO signal was detected in the cells of microglia/macrophage lineage as well as in astrocytes, endothelial cells and neurons. Importantly, we show that the selective CSF1R inhibitor, JNJ-40346527 (JNJ527), attenuated the disease-dependent increase in TSPO signal, particularly in the dentate gyrus of the hippocampus, where JNJ527 attenuated the number of Iba1+ microglia and neurons, but not GFAP+ astrocytes or endothelial cells. These findings suggest that [3H]PBR28 quantitative autoradiography in combination with immunohistochemistry are important translational tools for detecting and quantifying neuroinflammation, and its treatments, in neurodegenerative disease. Furthermore, we demonstrate that although TSPO overexpression in the ME7 brains was driven by various cell types, the therapeutic effect of the CSF1R inhibitor was primarily to modulate TSPO expression in microglia and neurons, which identifies an important route of biological action of this particular CSF1R inhibitor and provides an example of a cell-specific effect of this type of therapeutic agent on the neuroinflammatory process.

Sickness behaviour and depression: An updated model of peripheral-central immunity interactions.

Current research into mood disorders indicates that circulating immune mediators participating in the pathophysiology of chronic somatic disorders have potent influences on brain function. This paradigm has brought to the fore the use of anti-inflammatory therapies as adjunctive to standard antidepressant therapy to improve treatment efficacy, particularly in subjects that do not respond to standard medication. Such new practice requires biomarkers to tailor these new therapies to those most likely to benefit but also validated mechanisms of action describing the interaction between peripheral immunity and brain function to optimize target intervention. These mechanisms are generally studied in preclinical models that try to recapitulate the human disease, MDD, through peripherally induced sickness behaviour. In this proposal paper, after an appraisal of the data in rodent models and their adherence to the data in clinical cohorts, we put forward a modified model of periphery-brain interactions that goes beyond the currently established view of microglia cells as the drivers of depression. Instead, we suggest that, for most patients with mild levels of peripheral inflammation, brain barriers are the primary actors in the pathophysiology of the disease and in treatment resistance. We then highlight data gaps in this proposal and suggest novel lines of research.

An automatic analysis framework for FDOPA PET neuroimaging.

In this study we evaluate the performance of a fully automated analytical framework for FDOPA PET neuroimaging data, and its sensitivity to demographic and experimental variables and processing parameters. An instance of XNAT imaging platform was used to store the King's College London institutional brain FDOPA PET imaging archive, alongside individual demographics and clinical information. By re-engineering the historical Matlab-based scripts for FDOPA PET analysis, a fully automated analysis pipeline for imaging processing and data quantification was implemented in Python and integrated in XNAT. The final data repository includes 892 FDOPA PET scans organized from 23 different studies. We found good reproducibility of the data analysis by the automated pipeline (in the striatum for the Kicer: for the controls ICC = 0.71, for the psychotic patients ICC = 0.88). From the demographic and experimental variables assessed, gender was found to most influence striatal dopamine synthesis capacity (F = 10.7, p < 0.001), with women showing greater dopamine synthesis capacity than men. Our automated analysis pipeline represents a valid resourse for standardised and robust quantification of dopamine synthesis capacity using FDOPA PET data. Combining information from different neuroimaging studies has allowed us to test it comprehensively and to validate its replicability and reproducibility performances on a large sample size.

From neurotransmitters to networks: Transcending organisational hierarchies with molecular-informed functional imaging.

The human brain exhibits complex interactions across micro, meso-, and macro-scale organisational principles. Recent synergistic multi-modal approaches have begun to link micro-scale information to systems level dynamics, transcending organisational hierarchies and offering novel perspectives into the brain's function and dysfunction. Specifically, the distribution of micro-scale properties (such as receptor density or gene expression) can be mapped onto macro-scale measures from functional MRI to provide novel neurobiological insights. Methodological approaches to enrich functional imaging analyses with molecular information are rapidly evolving, with several streams of research having developed relatively independently, each offering unique potential to explore the trans-hierarchical functioning of the brain. Here, we address the three principal streams of research - spatial correlation, molecular-enriched network, and in-silico whole brain modelling analyses - to provide a critical overview of the different sources of molecular information, how this information can be utilised within analyses of fMRI data, the merits and pitfalls of each methodology, and, through the use of key examples, highlight their promise to shed new light on key domains of neuroscientific inquiry.

Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology.

The disconnection hypothesis of schizophrenia proposes that symptoms of the disorder arise as a result of aberrant functional integration between segregated areas of the brain. The concept of metastability characterizes the coexistence of competing tendencies for functional integration and functional segregation in the brain, and is therefore well suited for the study of schizophrenia. In this study, we investigate metastability as a candidate neuromechanistic biomarker of schizophrenia pathology, including a demonstration of reliability and face validity. Group-level discrimination, individual-level classification, pathophysiological relevance, and explanatory power were assessed using two independent case-control studies of schizophrenia, the Human Connectome Project Early Psychosis (HCPEP) study (controls n = 53, non-affective psychosis n = 82) and the Cobre study (controls n = 71, cases n = 59). In this work we extend Leading Eigenvector Dynamic Analysis (LEiDA) to capture specific features of dynamic functional connectivity and then implement a novel approach to estimate metastability. We used non-parametric testing to evaluate group-level differences and a naïve Bayes classifier to discriminate cases from controls. Our results show that our new approach is capable of discriminating cases from controls with elevated effect sizes relative to published literature, reflected in an up to 76% area under the curve (AUC) in out-of-sample classification analyses. Additionally, our new metric showed explanatory power of between 81-92% for measures of integration and segregation. Furthermore, our analyses demonstrated that patients with early psychosis exhibit intermittent disconnectivity of subcortical regions with frontal cortex and cerebellar regions, introducing new insights about the mechanistic bases of these conditions. Overall, these findings demonstrate reliability and face validity of metastability as a candidate neuromechanistic biomarker of schizophrenia pathology.

Exploring the neuroprotective effects of montelukast on brain inflammation and metabolism in a rat model of quinolinic acid-induced striatal neurotoxicity.

BACKGROUND: One intrastriatal administration of quinolinic acid (QA) in rats induces a lesion with features resembling those observed in Huntington's disease. Our aim is to evaluate the effects of the cysteinyl leukotriene receptor antagonist montelukast (MLK), which exhibited neuroprotection in different preclinical models of neurodegeneration, on QA-induced neuroinflammation and regional metabolic functions. METHODS: The right and left striatum of Sprague Dawley and athymic nude rats were injected with QA and vehicle (VEH), respectively. Starting from the day before QA injection, animals were treated with 1 or 10 mg/kg of MLK or VEH for 14 days. At 14 and 30 days post-lesion, animals were monitored with magnetic resonance imaging (MRI) and positron emission tomography (PET) using [18F]-VC701, a translocator protein (TSPO)-specific radiotracer. Striatal neuroinflammatory response was measured post-mortem in rats treated with 1 mg/kg of MLK by immunofluorescence. Rats treated with 10 mg/kg of MLK also underwent a [18F]-FDG PET study at baseline and 4 months after lesion. [18F]-FDG PET data were then used to assess metabolic connectivity between brain regions by applying a covariance analysis method. RESULTS: MLK treatment was not able to reduce the QA-induced increase in striatal TSPO PET signal and MRI lesion volume, where we only detected a trend towards reduction in animals treated with 10 mg/kg of MLK. Post-mortem immunofluorescence analysis revealed that MLK attenuated the increase in striatal markers of astrogliosis and activated microglia in the lesioned hemisphere. We also found a significant increase in a marker of anti-inflammatory activity (MannR) and a trend towards reduction in a marker of pro-inflammatory activity (iNOS) in the lesioned striatum of MLK-compared to VEH-treated rats. [18F]-FDG uptake was significantly reduced in the striatum and ipsilesional cortical regions of VEH-treated rats at 4 months after lesion. MLK administration preserved glucose metabolism in these cortical regions, but not in the striatum. Finally, MLK was able to counteract changes in metabolic connectivity and measures of network topology induced by QA, in both lesioned and non-lesioned hemispheres. CONCLUSIONS: Overall, MLK treatment produced a significant neuroprotective effect by reducing neuroinflammation assessed by immunofluorescence and preserving regional brain metabolism and metabolic connectivity from QA-induced neurotoxicity in cortical and subcortical regions.

The effects of acute Methylene Blue administration on cerebral blood flow and metabolism in humans and rats.

Methylene Blue (MB) is a brain-penetrating drug with putative neuroprotective, antioxidant and metabolic enhancing effects. In vitro studies suggest that MB enhances mitochondrial complexes activity. However, no study has directly assessed the metabolic effects of MB in the human brain. We used in vivo neuroimaging to measure the effect of MB on cerebral blood flow (CBF) and brain metabolism in humans and in rats. Two doses of MB (0.5 and 1 mg/kg in humans; 2 and 4 mg/kg in rats; iv) induced reductions in global cerebral blood flow (CBF) in humans (F(1.74, 12.17)5.82, p = 0.02) and rats (F(1,5)26.04, p = 0.0038). Human cerebral metabolic rate of oxygen (CMRO2) was also significantly reduced (F(1.26, 8.84)8.01, p = 0.016), as was the rat cerebral metabolic rate of glucose (CMRglu) (t = 2.6(16) p = 0.018). This was contrary to our hypothesis that MB will increase CBF and energy metrics. Nevertheless, our results were reproducible across species and dose dependent. One possible explanation is that the concentrations used, although clinically relevant, reflect MB's hormetic effects, i.e., higher concentrations produce inhibitory rather than augmentation effects on metabolism. Additionally, here we used healthy volunteers and healthy rats with normal cerebral metabolism where MB's ability to enhance cerebral metabolism might be limited.