Connectome dysfunction in patients at clinical high risk for psychosis and modulation by oxytocin.

Abnormalities in functional brain networks (functional connectome) are increasingly implicated in people at Clinical High Risk for Psychosis (CHR-P). Intranasal oxytocin, a potential novel treatment for the CHR-P state, modulates network topology in healthy individuals. However, its connectomic effects in people at CHR-P remain unknown. Forty-seven men (30 CHR-P and 17 healthy controls) received acute challenges of both intranasal oxytocin 40 IU and placebo in two parallel randomised, double-blind, placebo-controlled cross-over studies which had similar but not identical designs. Multi-echo resting-state fMRI data was acquired at approximately 1 h post-dosing. Using a graph theoretical approach, the effects of group (CHR-P vs healthy control), treatment (oxytocin vs placebo) and respective interactions were tested on graph metrics describing the topology of the functional connectome. Group effects were observed in 12 regions (all pFDR < 0.05) most localised to the frontoparietal network. Treatment effects were found in 7 regions (all pFDR < 0.05) predominantly within the ventral attention network. Our major finding was that many effects of oxytocin on network topology differ across CHR-P and healthy individuals, with significant interaction effects observed in numerous subcortical regions strongly implicated in psychosis onset, such as the thalamus, pallidum and nucleus accumbens, and cortical regions which localised primarily to the default mode network (12 regions, all pFDR < 0.05). Collectively, our findings provide new insights on aberrant functional brain network organisation associated with psychosis risk and demonstrate, for the first time, that oxytocin modulates network topology in brain regions implicated in the pathophysiology of psychosis in a clinical status (CHR-P vs healthy control) specific manner.

Modulation of functional networks related to the serotonin neurotransmitter system by citalopram: Evidence from a multimodal neuroimaging study.

BACKGROUND: Selective serotonin reuptake inhibitors (SSRIs) potentiate serotonergic neurotransmission by blocking the serotonin transporter (5-HTT), but the functional brain response to SSRIs involves neural circuits beyond regions with high 5-HTT expression. Currently, it is unclear whether and how changes in 5-HTT availability after SSRI administration modulate brain function of key serotoninergic circuits, including those characterized by high availability of the serotonin 1A receptor (5-HT1AR). AIM: We investigated the association between 5-HTT availability and 5-HTT- and 5-HT1AR-enriched functional connectivity (FC) after an acute citalopram challenge. METHODS: We analyzed multimodal data from a dose-response, placebo-controlled, double-blind study, in which 45 healthy women were randomized into three groups receiving placebo, a low (4 mg), or high (16 mg) oral dose of citalopram. Receptor-Enhanced Analysis of functional Connectivity by Targets was used to estimate 5-HTT- and 5-HT1AR-enriched FC from resting-state and task-based fMRI. 5-HTT availability was determined using [123I]FP-CIT single-photon emission computerized tomography. RESULTS: 5-HTT availability was negatively correlated with resting-state 5-HTT-enriched FC, and with task-dependent 5-HT1AR-enriched FC. Our exploratory analyses revealed lower 5-HT1AR-enriched FC in the low-dose group compared to the high-dose group at rest and the placebo group during the emotional face-matching task. CONCLUSIONS: Taken together, our findings provide evidence for differential links between 5-HTT availability and brain function within 5-HTT and 5-HT1AR pathways and in context- and dose-dependent manner. As such, they support a potential pivotal role of the 5-HT1AR in the effects of citalopram on the brain and add to its potential as a therapeutic avenue for mood and anxiety disturbances.

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.

Ketamine-induced changes in resting state connectivity, 2 h after the drug administration in patients with remitted depression.

BACKGROUND: Resting state connectivity studies link ketamine's antidepressant effects with normalisation of the brain connectivity changes that are observed in depression. These changes, however, usually co-occur with improvement in depressive symptoms, making it difficult to attribute these changes to ketamine's effects per se. AIMS: Our aim is to examine the effects of ketamine in brain connectivity, 2 h after its administration in a cohort of volunteers with remitted depression. Any significant changes observed in this study could provide insight of ketamine's antidepressant mechanism as they are not accompanied by symptom changes. METHODS: In total, 35 participants with remitted depression (21 females, mean age = 28.5 years) participated in a double-blind, placebo-controlled study of ketamine (0.5 mg/kg) or saline. Resting state scans were acquired approximately 2 h after the ketamine infusion. Brain connectivity was examined using a seed-based approach (ventral striatum, amygdala, hippocampus, posterior cingulate cortex and subgenual anterior cingulate cortex (sgACC)) and a brain network analysis (independent component analysis). RESULTS: Decreased connectivity between the sgACC and the amygdala was observed approximately 2 h after the ketamine infusion, compared to placebo (pFWE < 0.05). The executive network presented with altered connectivity with different cortical and subcortical regions. Within the network, the left hippocampus and right amygdala had decreased connectivity (pFWE < 0.05). CONCLUSIONS: Our findings support a model whereby ketamine would change the connectivity of brain areas and networks that are important for cognitive processing and emotional regulation. These changes could also be an indirect indicator of the plasticity changes induced by the drug.

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.

Abnormal Glutamatergic and Serotonergic Connectivity in Visual Snow Syndrome and Migraine with Aura.

OBJECTIVE: Neuropharmacological changes in visual snow syndrome (VSS) are poorly understood. We aimed to use receptor target maps combined with resting functional magnetic resonance imaging (fMRI) data to identify which neurotransmitters might modulate brain circuits involved in VSS. METHODS: We used Receptor-Enriched Analysis of Functional Connectivity by Targets (REACT) to estimate and compare the molecular-enriched functional networks related to 5 neurotransmitter systems of patients with VSS (n = 24), healthy controls (HCs; n = 24), and migraine patients ([MIG], n = 25, 15 of whom had migraine with aura [MwA]). For REACT we used receptor density templates for the transporters of noradrenaline, dopamine, and serotonin, GABA-A and NMDA receptors, as well as 5HT1B and 5HT2A receptors, and estimated the subject-specific voxel-wise maps of functional connectivity (FC). We then performed voxel-wise comparisons of these maps among HCs, MIG, and VSS. RESULTS: Patients with VSS had reduced FC in glutamatergic networks localized in the anterior cingulate cortex (ACC) compared to HCs and patients with migraine, and reduced FC in serotoninergic networks localized in the insula, temporal pole, and orbitofrontal cortex compared to controls, similar to patients with migraine with aura. Patients with VSS also showed reduced FC in 5HT2A -enriched networks, largely localized in occipito-temporo-parietal association cortices. As revealed by subgroup analyses, these changes were independent of, and analogous to, those found in patients with migraine with aura. INTERPRETATION: Our results show that glutamate and serotonin are involved in brain connectivity alterations in areas of the visual, salience, and limbic systems in VSS. Importantly, altered serotonergic connectivity is independent of migraine in VSS, and simultaneously comparable to that of migraine with aura, highlighting a shared biology between the disorders. ANN NEUROL 2023;94:873-884.

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.

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.

The effects of propofol anaesthesia on molecular-enriched networks during resting-state and naturalistic listening.

Placing a patient in a state of anaesthesia is crucial for modern surgical practice. However, the mechanisms by which anaesthetic drugs, such as propofol, impart their effects on consciousness remain poorly understood. Propofol potentiates GABAergic transmission, which purportedly has direct actions on cortex as well as indirect actions via ascending neuromodulatory systems. Functional imaging studies to date have been limited in their ability to unravel how these effects on neurotransmission impact the system-level dynamics of the brain. Here, we leveraged advances in multi-modal imaging, Receptor-Enriched Analysis of functional Connectivity by Targets (REACT), to investigate how different levels of propofol-induced sedation alter neurotransmission-related functional connectivity (FC), both at rest and when individuals are exposed to naturalistic auditory stimulation. Propofol increased GABA-A- and noradrenaline transporter-enriched FC within occipital and somatosensory regions respectively. Additionally, during auditory stimulation, the network related to the dopamine transporter showed reduced FC within bilateral regions of temporal and mid/posterior cingulate cortices, with the right temporal cluster showing an interaction between auditory stimulation and level of consciousness. In bringing together these micro- and macro-scale systems, we provide support for both direct GABAergic and indirect noradrenergic and dopaminergic-related network changes under propofol sedation. Further, we delineate a cognition-related reconfiguration of the dopaminergic network, highlighting the utility of REACT to explore the molecular substrates of consciousness and cognition.

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.

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.

Metastability, fractal scaling, and synergistic information processing: What phase relationships reveal about intrinsic brain activity.

Dynamic functional connectivity (dFC) in resting-state fMRI holds promise to deliver candidate biomarkers for clinical applications. However, the reliability and interpretability of dFC metrics remain contested. Despite a myriad of methodologies and resulting measures, few studies have combined metrics derived from different conceptualizations of brain functioning within the same analysis - perhaps missing an opportunity for improved interpretability. Using a complexity-science approach, we assessed the reliability and interrelationships of a battery of phase-based dFC metrics including tools originating from dynamical systems, stochastic processes, and information dynamics approaches. Our analysis revealed novel relationships between these metrics, which allowed us to build a predictive model for integrated information using metrics from dynamical systems and information theory. Furthermore, global metastability - a metric reflecting simultaneous tendencies for coupling and decoupling - was found to be the most representative and stable metric in brain parcellations that included cerebellar regions. Additionally, spatiotemporal patterns of phase-locking were found to change in a slow, non-random, continuous manner over time. Taken together, our findings show that the majority of characteristics of resting-state fMRI dynamics reflect an interrelated dynamical and informational complexity profile, which is unique to each acquisition. This finding challenges the interpretation of results from cross-sectional designs for brain neuromarker discovery, suggesting that individual life-trajectories may be more informative than sample means.

May the 4C's be with you: an overview of complexity-inspired frameworks for analysing resting-state neuroimaging data.

Competing and complementary models of resting-state brain dynamics contribute to our phenomenological and mechanistic understanding of whole-brain coordination and communication, and provide potential evidence for differential brain functioning associated with normal and pathological behaviour. These neuroscientific theories stem from the perspectives of physics, engineering, mathematics and psychology and create a complicated landscape of domain-specific terminology and meaning, which, when used outside of that domain, may lead to incorrect assumptions and conclusions within the neuroscience community. Here, we review and clarify the key concepts of connectivity, computation, criticality and coherence-the 4C's-and outline a potential role for metastability as a common denominator across these propositions. We analyse and synthesize whole-brain neuroimaging research, examined through functional magnetic imaging, to demonstrate that complexity science offers a principled and integrated approach to describe, and potentially understand, macroscale spontaneous brain functioning.

Differences in social brain function in autism spectrum disorder are linked to the serotonin transporter: A randomised placebo-controlled single-dose crossover trial.

BACKGROUND: Alterations in the serotonergic control of brain pathways responsible for facial emotion processing in people with autism spectrum disorder (ASD) may be a target for intervention. However, the molecular underpinnings of autistic-neurotypical serotonergic differences are challenging to access in vivo. Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) has helped define molecular-enriched functional magnetic resonance imaging (fMRI) brain networks based on a priori information about the spatial distribution of neurochemical systems from available PET templates. METHODS: We used REACT to estimate the dominant fMRI signal related to the serotonin (5-HT) transporter (SERT) distribution during processing of aversive facial emotion in adults with and without ASD. We first predicted a group difference in baseline (placebo) functioning of this system. We next used a single 20 mg oral dose of citalopram, a serotonin reuptake inhibitor, to test the hypothesis that network activity in people with and without ASD would respond differently to inhibition of SERT. To confirm the specificity of our findings, we also repeated the analysis with 5-HT1A, 5-HT1B, 5-HT2A and 5-HT4 receptor maps. RESULTS: Using REACT with the SERT map, we found a baseline group difference in the SERT-enriched response to faces in the ventromedial prefrontal cortex. A single oral dose of citalopram 'shifted' the response in the ASD group towards the neurotypical baseline but did not alter response in the control group. Similar differences in SERT-enriched response were observed after controlling for other 5-HT maps. CONCLUSIONS: Our findings suggest that the SERT-enriched functional network is dynamically different in ASD during processing of socially relevant stimuli. Whether this acute neurobiological response to citalopram in ASD translates to a clinical target will be an important next step.

Integrating neuroimaging and gene expression data using the imaging transcriptomics toolbox.

The integration of neuroimaging and transcriptomics data, Imaging Transcriptomics, is becoming increasingly popular but standardized workflows for its implementation are still lacking. We describe the Imaging Transcriptomics toolbox, a new package that implements a full imaging transcriptomics pipeline using a user-friendly, command line interface. This toolbox allows the user to identify patterns of gene expression which correlates with a specific neuroimaging phenotype and perform gene set enrichment analyses to inform the biological interpretation of the findings using up-to-date methods. For complete details on the use and execution of this protocol, please refer to Martins et al. (2021).

Differential contributions of serotonergic and dopaminergic functional connectivity to the phenomenology of LSD.

RATIONALE: LSD is the prototypical psychedelic. Despite a clear central role of the 5HT2a receptor in its mechanism of action, the contributions of additional receptors for which it shows affinity and agonist activity remain unclear. OBJECTIVES: We employed receptor-enriched analysis of functional connectivity by targets (REACT) to explore differences in functional connectivity (FC) associated with the distributions of the primary targets of LSD-the 5HT1a, 5HT1b, 5HT2a, D1 and D2 receptors. METHODS: We performed secondary analyses of an openly available dataset (N = 15) to estimate the LSD-induced alterations in receptor-enriched FC maps associated with these systems. Principal component analysis (PCA) was employed as a dimension reduction strategy for subjective experiences associated with LSD captured by the Altered States of Consciousness (ASC) questionnaire. Correlations between these principal components as well as VAS ratings of subjective effects with receptor-enriched FC were explored. RESULTS: Compared to placebo, LSD produced differences in FC when the analysis was enriched with each of the primary serotonergic and dopaminergic receptors. Altered receptor-enriched FC showed relationships with the subjective effects of LSD on conscious experience, with serotonergic and dopaminergic systems being predominantly associated with perceptual effects and perceived selfhood as well as cognition respectively. These relationships were dissociable, with different receptors showing the same relationships within, but not between, the serotonergic and dopaminergic systems. CONCLUSIONS: These exploratory findings provide new insights into the pharmacology of LSD and highlight the need for additional investigation of non-5HT2a-mediated mechanisms.

"Less is more": A dose-response account of intranasal oxytocin pharmacodynamics in the human brain.

Intranasal oxytocin is attracting attention as a potential treatment for several brain disorders due to promising preclinical results. However, translating findings to humans has been hampered by remaining uncertainties about its pharmacodynamics and the methods used to probe its effects in the human brain. Using a dose-response design (9, 18 and 36 IU), we demonstrate that intranasal oxytocin-induced changes in local regional cerebral blood flow (rCBF) in the amygdala at rest, and in the covariance between rCBF in the amygdala and other key hubs of the brain oxytocin system, follow a dose-response curve with maximal effects for lower doses. Yet, the effects on local rCBF might vary by amygdala subdivision, highlighting the need to qualify dose-response curves within subregion. We further link physiological changes with the density of the oxytocin receptor gene mRNA across brain regions, strengthening our confidence in intranasal oxytocin as a valid approach to engage central targets. Finally, we demonstrate that intranasal oxytocin does not disrupt cerebrovascular reactivity, which corroborates the validity of haemodynamic neuroimaging to probe the effects of intranasal oxytocin in the human brain. DATA AVAILABILITY: Participants did not consent for open sharing of the data. Therefore, data can only be accessed from the corresponding author upon reasonable request.

A candidate neuroimaging biomarker for detection of neurotransmission-related functional alterations and prediction of pharmacological analgesic response in chronic pain.

Chronic pain is a world-wide clinical challenge. Response to analgesic treatment is limited and difficult to predict. Functional MRI has been suggested as a potential solution. However, while most analgesics target specific neurotransmission pathways, functional MRI-based biomarkers are not specific for any neurotransmitter system, limiting our understanding of how they might contribute to predict treatment response. Here, we sought to bridge this gap by applying Receptor-Enriched Analysis of Functional Connectivity by Targets to investigate whether neurotransmission-enriched functional connectivity mapping can provide insights into the brain mechanisms underlying chronic pain and inter-individual differences in analgesic response after a placebo or duloxetine. We performed secondary analyses of two openly available resting-state functional MRI data sets of 56 patients with chronic knee osteoarthritis pain who underwent pre-treatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-week single-blinded placebo pill trial. Study 2 (n = 39) was a 3-month double-blinded randomized trial comparing placebo to duloxetine, a dual serotonin-noradrenaline reuptake inhibitor. Across two independent studies, we found that patients with chronic pain present alterations in the functional circuit related to the serotonin transporter, when compared with age-matched healthy controls. Placebo responders in Study 1 presented with higher pre-treatment functional connectivity enriched by the dopamine transporter compared to non-responders. Duloxetine responders presented with higher pre-treatment functional connectivity enriched by the serotonin and noradrenaline transporters when compared with non-responders. Neurotransmission-enriched functional connectivity mapping might hold promise as a new mechanistic-informed biomarker for functional brain alterations and prediction of response to pharmacological analgesia in chronic pain.

Transcriptional and cellular signatures of cortical morphometric remodelling in chronic pain.

ABSTRACT: Chronic pain is a highly debilitating and difficult to treat condition, which affects the structure of the brain. Although the development of chronic pain is moderately heritable, how disease-related alterations at the microscopic genetic architecture drive macroscopic brain abnormalities is currently largely unknown. Here, we examined alterations in morphometric similarity (MS) and applied an integrative imaging transcriptomics approach to identify transcriptional and cellular correlates of these MS changes, in 3 independent small cohorts of patients with distinct chronic pain syndromes (knee osteoarthritis, low back pain, and fibromyalgia) and age-matched and sex-matched pain-free controls. We uncover a novel pattern of cortical MS remodelling involving mostly small-to-medium MS increases in the insula and limbic cortex (none of these changes survived stringent false discovery rate correction for the number of regions tested). This pattern of changes is different from that observed in patients with major depression and cuts across the boundaries of specific pain syndromes. By leveraging transcriptomic data from Allen Human Brain Atlas, we show that cortical MS remodelling in chronic pain spatially correlates with the brain-wide expression of genes related to pain and broadly involved in the glial immune response and neuronal plasticity. Our findings bridge levels to connect genes, cell classes, and biological pathways to in vivo imaging correlates of chronic pain. Although correlational, our data suggest that cortical remodelling in chronic pain might be shaped by multiple elements of the cellular architecture of the brain and identifies several pathways that could be prioritized in future genetic association or drug development studies.

A Complex Systems Perspective on Neuroimaging Studies of Behavior and Its Disorders.

The study of complex systems deals with emergent behavior that arises as a result of nonlinear spatiotemporal interactions between a large number of components both within the system, as well as between the system and its environment. There is a strong case to be made that neural systems as well as their emergent behavior and disorders can be studied within the framework of complexity science. In particular, the field of neuroimaging has begun to apply both theoretical and experimental procedures originating in complexity science-usually in parallel with traditional methodologies. Here, we illustrate the basic properties that characterize complex systems and evaluate how they relate to what we have learned about brain structure and function from neuroimaging experiments. We then argue in favor of adopting a complex systems-based methodology in the study of neuroimaging, alongside appropriate experimental paradigms, and with minimal influences from noncomplex system approaches. Our exposition includes a review of the fundamental mathematical concepts, combined with practical examples and a compilation of results from the literature.