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Dipasquale, O.

Publications and source records attributed to Dipasquale, O..

At least 19 recordsLinked to original sources

Linking human brain functional connectivity to underlying neurotransmission

The human brain is organized into interacting functional systems. Their underlying neurobiological mechanisms remain difficult to study in vivo. Here, we adopt a topological framework to quantify the association between neurobiology and brain functional connectivity derived from both resting-state fMRI and MEG. Across six healthy adult cohorts (n = 19-112), regional variation in fMRI connectivity robustly aligns with the distribution of neurotransmitter receptors and transporters. These patterns are present in every single subject, replicate across all cohorts, and are mirrored in MEG. Most prominently, noradrenergic modulation of connectivity in a sensorimotor-insular network is consistently detected across individuals and linked to autonomic arousal. In pharmacological and clinical samples, associations are sensitive to neurotransmitter system manipulation and are altered in early psychosis, aligning with clinical symptomatology. These findings provide biological insight into typical and atypical functional organization of the human brain using a framework linking underlying neurobiology to the functional connectome (NEOFC).

neuroscience↗

Brain dynamics of attentional, default-mode and limbic networks are disrupted at rest in Post-COVID-19 Syndrome

BackgroundPost-COVID-19 Syndrome (PCS) is characterised by persistent fatigue, cognitive impairments, and affective symptoms, yet its underlying neural mechanisms remain poorly understood. While static neuroimaging studies have identified resting-state connectivity abnormalities in PCS, such approaches fail to capture the brains dynamic functional organisation. This represents a missed opportunity to understand how alterations at the dynamic macroscale interactions give rise to the complex and fluctuating symptom profile of PCS. Cognitive and emotional processes rely on the brains capacity to flexibly reconfigure large-scale networks over time; disruptions in the exploration and transition between brain states may therefore play a central role in PCS pathophysiology. MethodsResting-state fMRI data were acquired from 20 individuals with PCS (mean age = 41.8 years, SD = 9.4) and 20 age- and sex-matched healthy controls (mean age = 40.6 years, SD = 8.1) using a multi-echo sequence. Following denoising with multi-echo independent component analysis, we applied Leading Eigenvector Dynamics Analysis (LEiDA) to identify recurrent patterns of whole-brain phase synchrony. The optimal number of dynamic brain states was determined using the Dunn index. For each state, we quantified probability of occurrence, lifetime, and transition probabilities, and mapped spatial topographies onto canonical functional networks. Group differences were assessed using ANCOVAs controlling for age, sex, and handedness. Exploratory associations with clinical symptoms, cognitive performance, and inflammatory markers were examined using both frequentist and Bayesian approaches. ResultsFive recurrent dynamic brain states were identified. Compared with controls, PCS participants showed reduced probability of occurrence and shorter lifetime of a visual/dorsal attention state, alongside increased probability of a limbic/default mode network (DMN) state. PCS was also characterised by reduced transitions between visual/dorsal attention and frontoparietal-DMN states, and increased transitions from somatomotor/visual states toward the limbic-DMN configuration. Exploratory analyses revealed that greater expression of the limbic-DMN state was negatively associated with global cognitive performance (MoCA) and positively associated with serum IL-1{beta} levels. ConclusionsPCS is associated with a reorganisation of intrinsic brain dynamics, marked by a shift from externally oriented attentional states toward limbic-DMN configurations. This imbalance may reflect reduced cognitive flexibility and increased sensitivity to interoceptive or affective signals. The observed links between dynamic brain-state expression, cognitive impairment, and peripheral inflammation support a systems-level mechanism through which immune signalling may influence neural function in PCS. Dynamic functional connectivity offers a sensitive framework for capturing these alterations and may inform future mechanistic models of post-viral dysfunction and therapeutic targeting. HighlightsO_LIPost-COVID-19 Syndrome (PCS) is linked to altered intrinsic brain dynamics at rest. C_LIO_LIPatients show reduced engagement of visual and attentional brain states. C_LIO_LIIncreased recruitment of limbic-DMN states suggests a shift toward more internally, emotionally charged focussed brain activity. C_LIO_LIBrain-state dynamics are putatively associated with global cognition and IL-1{beta}. C_LIO_LIReduced brain-state flexibility may underlie cognitive and emotional symptoms in PCS. C_LI

neuroscience↗

The Role of the Dorsolateral Prefrontal Cortex in Ego Dissolution and Emotional Arousal During the Psychedelic State

Lysergic acid diethylamide (LSD) is a classic serotonergic psychedelic that induces a profoundly altered conscious state. In conjunction with psychological support, it is currently being explored as a treatment for generalized anxiety disorder and depression. The dorsolateral prefrontal cortex (DLPFC) is a brain region that is known to be involved in mood regulation and disorders; hypofunction in the left DLPFC is associated with depression. This study investigated the role of the DLPFC in the psycho-emotional effects of LSD with functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) data of healthy human participants during the acute LSD experience. In the fMRI data, we measured the correlation between changes in resting-state functional connectivity (RSFC) of the DLPFC and post-scan subjective ratings of positive mood, emotional arousal, and ego dissolution. We found significant, positive correlations between ego dissolution and functional connectivity between the left & right DLPFC, thalamus, and a higher-order visual area, the fusiform face area (FFA). Additionally, emotional arousal was significantly associated with increased connectivity between the right DLPFC, intraparietal sulcus (IPS), and the salience network (SN). A confirmational "reverse" analysis, in which the outputs of the original RSFC analysis were used as input seeds, substantiated the role of the right DLPFC and the aforementioned regions in both ego dissolution and emotional arousal. Subsequently, we measured the effects of LSD on directed functional connectivity in MEG data that was source-localized to the input and output regions of both the original and reverse analyses. The Granger causality (GC) analysis revealed that LSD increased information flow between two nodes of the ego dissolution network, the thalamus and the DLPFC, in the theta band, substantiating the hypothesis that disruptions in thalamic gating underlie the experience of ego dissolution. Overall, this multimodal study elucidates a role for the DLPFC in LSD-induced states of consciousness and sheds more light on the brain basis of ego dissolution.

neuroscience↗

Transcriptional and neurochemical signatures of cerebral blood flow alterations in schizophrenia and the clinical high-risk state for psychosis

The brain integrates multiple scales of description, from the level of cells and molecules to large-scale networks and behaviour, and understanding the relationships between these layers may be fundamental to advancing our understanding of how the brain works in health and disease. Recent neuroimaging research has shown that alterations in brain function that are associated with schizophrenia spectrum disorders (SSD) are already present in young adults at clinical high-risk for psychosis (CHR-P), yet the cellular and molecular determinants of these alterations are not well understood. Here, combining regional cerebral blood flow (rCBF) data with existing transcriptomic and neurotransmitter data, we show that cell-types involved in stress response and inflammation, as well as the dopamine, acetylcholine, GABAA and NMDA receptor systems, align as shared and distinct cellular and neurochemical signatures of rCBF phenotypes in people with SSD and those at CHR-P. Decoding the biological pathways involved in neuroimaging-based psychosis phenotypes may provide a basis for the development of novel interventions.

neuroscience↗

Normative Modelling of Molecular-based Functional Neurocircuits Captures Clinical Heterogeneity Transdiagnostically in Neuropsychiatric Patients

Clinical neuroscience principally aims to delineate the neurobiology underpinning the symptoms of various disorders, with the ultimate goal of developing mechanistically informed treatments for these conditions. This has been hindered by the complex hierarchical organisation of the brain and extreme heterogeneity of neuropsychiatric disorders. However, recent advances in multimodal analytic techniques - such as Receptor Enriched Analysis of Connectivity by Targets (REACT) - have allowed to integrate the functional dynamics seen in fMRI with the brains receptor landscape, providing novel trans-hierarchical insights. Similarly, normative modelling of brain features has allowed translational neuroscience to move beyond group average differences between patients and controls and characterise deviations from health at an individual level. Here, we bring these novel methods together for the first time in order to address these two longstanding translational barriers in clinical neuroscience. REACT was used create functional networks enriched with the main modulatory (noradrenaline, dopamine, serotonin, acetylcholine), inhibitory (GABA), and excitatory (glutamate) neurotransmitter systems in a large group of healthy participants [N=607]. Next, we generated normative models of these networks across the spectrum of healthy ageing and demonstrated that these capture deviations within and across patients with Schizophrenia, Bipolar-disorder, and ADHD [N=119]. Our results align with prior accounts of excitatory-inhibitory imbalance in schizophrenia and bipolar disorder, with the former also related to deviations within the cholinergic system. Our transdiagnostic analyses also emphasised the substantial overlap in symptoms and deviations across these disorders. Altogether, this work provides impetus for the development of novel biomarkers that characterise both molecular- and systems-level dysfunction at the individual level, helping facilitate the transition towards mechanistically targeted treatments. Significance statementHuman beings show enormous variability, with inter-individual differences spanning from neurotransmitters to networks. Understanding how these mechanisms interact across scales and produce heterogenous symptomatology within psychiatric disorders presents an enormous challenge. Here, we provide a novel analytic framework to overcome these barriers, combining molecular-enriched neuroimaging with normative modelling to examine neuropathology across scales at the individual level. Our results converge on prior neurobiological accounts of schizophrenia and bipolar disorder as well as the heterogeneity of ADHD. Moreover, we map symptomatology to molecular-enriched functional networks transdiagnostically across these disorders. By bridging the gap between dysfunctional brain networks and underlying neurotransmitter systems, these methods can facilitate the transition from one-size-fits-all approaches to personalized pharmacological interventions at the individual level.

neuroscience↗

Two differentiated brain systems micro-structurally associated with obesity

The relationship between obesity and 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 x 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.

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The functional circuits related to serotonin transporter and serotonin 1A receptor are differentially associated to serotonin transporter availability after an acute citalopram challenge

BackgroundSelective 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 serotonin 1A receptors (5-HT1AR). AimWe investigated the association between 5-HTT availability and 5-HTT- and 5-HT1AR-enriched functional connectivity (FC) after an acute citalopram challenge. MethodsWe 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. Results5-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 task. ConclusionsTaken 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.

neuroscience↗

The Effects of Propofol Anaesthesia on Molecular-enriched Networks During Resting-state and Naturalistic Stimulation

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 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 alters 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 vesicular acetylcholine transporter showed reduced FC within the right superior temporal gyrus, regardless of level of anaesthesia, and a spatial configuration correlating with a broad range of meta-analytic measures of audition- and emotion-related cognition. In bringing together these micro- and macro-scale systems, we provide support for both direct GABAergic and indirect noradrenergic-related network changes under anaesthesia and describe a cognition-related reconfiguration of the cholinergic network, highlighting the utility of REACT to explore the molecular substrates consciousness and cognition.

neuroscience↗

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 novel analytical strategy that enriches functional connectivity (FC) information from functional MRI (fMRI) with molecular information on the neurotransmitter distribution density in the human brain, providing a biological basis to the FC analysis. So far, this integrative approach has been used in blood oxygen level-dependent (BOLD) fMRI studies only, providing new insights into the brain mechanisms underlying specific disorders and its response to pharmacological challenges. In this study, we demonstrate that the application of REACT can be further extended to arterial spin labelling (ASL) fMRI. Some of the advantages of this extension include the combination of neurotransmitter specific information provided by molecular imaging with a quantitative marker of neuronal activity, the suitability of ASL for pharmacological MRI (phMRI) studies assessing drug effects on baseline brain function, and the possibility to acquire images that are not affected by susceptibility artifacts in the regions linked to major neurotransmitter systems. In this work, we tested the feasibility of applying REACT to resting state ASL fMRI and compared the molecular-enriched FC maps derived from ASL data with those derived from BOLD data. We applied REACT to high-resolution, whole-brain simultaneous ASL/BOLD resting-state fMRI data of 29 healthy subjects and estimated the ASL- and BOLD-based FC maps related to six molecular systems, including the transporters of dopamine, noradrenaline, serotonin and vesicular acetylcholine, and the GABA-A and mGlu5 receptors. We then compared the ASL and BOLD FC maps in terms of spatial similarity, using the Dice Similarity Index and the voxel-wise spatial correlation. On a data subsample (N=19) we also evaluated the test-retest reproducibility of each modality using the regional intraclass correlation coefficient, and compared the two modalities. Our results showed robust spatial patterns of molecular-enriched functional connectivity for both modalities, moderate to high similarity between BOLD- and ASL-derived FC maps and mixed results in terms of reproducibility (i.e., none of the modalities outperformed the other). Overall, our findings show that the ASL signal 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. Considering the more direct link of ASL imaging with neuronal acrivity compared to BOLD and its suitability for phMRI studies, this new integrative approach could become a valuable asset in clinical studies investigating functional alterations in patients with brain disorders, or in pharmacological studies investigating the effects of new or existing compounds on the brain.

neuroscience↗

Digital data repository and automatic analysis framework for FDOPA PET neuroimaging

IntroductionFDOPA PET has been used extensively to image the human brain in many clinical disorders and has the potential to be used for patient stratification and individualized treatment. However, to reach its full and effective clinical translation, FDOPA PET requires both a robust data infrastructure and analytical protocol that are capable of ensuring high quality data and metadata, accurate biological quantification, and replicable results. In this study we evaluate a digital data repository and automated analytical framework for FDOPA PET neuroimaging that can produce an individualised quantification of dopamine synthesis capacity in the living human brain. MethodsThe imaging platform XNAT was used to store the Kings College London institutional brain FDOPA PET imaging archive, alongside individual demographics and clinical information. A fully automated analysis pipeline for imaging processing and data quantification was developed in Python and integrated in XNAT using the Docker technology. Reproducibility was assessed in test-retest datasets both in controls and patients with psychosis. The agreement between the automated analysis estimates and the results derived by the manual analysis were compared. Finally, using a sample of healthy controls (N=115), a sensitivity analysis was performed to explore the impact of experimental and demographic variables on the FDOPA PET measures. ResultsThe final data repository includes 892 FDOPA PET scans organized from 23 different studies, collected at five different imaging sites. After removing commercials studies, the infrastructure consisted of 792 FDOPA PET scans from 666 individuals (female 33.9%, healthy controls 29.1%) collected from four different imaging sites between 2004-2021. The automated analysis pipeline provided results that were in agreement with the results from the manual analysis, with a Pearsons correlation that ranged from 0.64 to 0.99 for Kicer, and from 0.79 to 1.00 for SUVR. The mean absolute difference between the two pipelines ranges from 3.4% to 9.4% for Kicer, and from 2.5% to 12.4% for SUVR. Moreover, we found good reproducibility of the data analysis by the automated pipeline (in the whole striatum for the Kicer: ICC for the controls = 0.71, ICC for the psychotic patients = 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, while the effects of weight, age, injected radioactivity, and scanner, varied by brain region and parameter of interest. ConclusionsCombining information from different neuroimaging studies has allowed us to test comprehensively the automated pipeline for quantification of dopamine synthesis capacity using FDOPA PET data and to validate its replicability and reproducibility performances on a large sample size. This validation process is a necessary methodological step for the development of the clinical application of FDOPA PET as precision medicine biomarker. The proposed infrastructure is generalisable behind the FDOPA radiotracer.

bioengineering↗

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 originated 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. HighlightsO_LISpatiotemporal patterns of phase-locking tend to be time-invariant C_LIO_LIGlobal metastability is representative and stable in a cohort of heathy young adults C_LIO_LIdFC characteristics are in general unique to any fMRI acquisition C_LIO_LIDynamical- and informational-complexity are interrelated C_LIO_LIComplexity science contributes to a coherent description of brain dynamics C_LI

neuroscience↗

Imaging transcriptomics: Convergent cellular, transcriptomic, and molecular neuroimaging signatures in the healthy adult human brain

The expansion of neuroimaging techniques over the last decades has opened a wide range of new possibilities to characterize brain dysfunction in several neurological and psychiatric disorders. However, the lack of specificity of most of these techniques, such as magnetic resonance imaging (MRI)-derived measures, to the underlying molecular and cellular properties of the brain tissue poses limitations to the amount of information one can extract to inform precise models of brain disease. The integration of transcriptomic and neuroimaging data, known as imaging transcriptomics, has recently emerged as an indirect way forward to test and/or generate hypotheses about potential cellular and transcriptomic pathways that might underly specific changes in neuroimaging MRI biomarkers. However, the validity of this approach is yet to be examined in-depth. Here, we sought to bridge this gap by performing imaging transcriptomic analyses of the regional distribution of well-known molecular markers, assessed by positron emission tomography (PET), in the healthy human brain. We focused on tracers spanning different elements of the biology of the brain, including neuroreceptors, synaptic proteins, metabolism, and glia. Using transcriptome-wide data from the Allen Brain Atlas, we applied partial least square regression to rank genes according to their level of spatial alignment with the regional distribution of these neuroimaging markers in the brain. Then, we performed gene set enrichment analyses to explore the enrichment for specific biological and cell-type pathways among the genes most strongly associated with each neuroimaging marker. Overall, our findings show that imaging transcriptomics can recover plausible transcriptomic and cellular correlates of the regional distribution of benchmark molecular imaging markers, independently of the type of parcellation used to map gene expression and neuroimaging data. Our data support the plausibility and robustness of imaging transcriptomics as an indirect approach for bridging gene expression, cells and macroscopical neuroimaging and improving our understanding of the biological pathways underlying regional variability in neuroimaging features.

neuroscience↗

Differences in social brain function in autism spectrum disorder are linked to the serotonin transporter

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 fMRI brain networks based on a priori information about the spatial distribution of neurochemical systems from available PET templates. Here, we used REACT to estimate the dominant fMRI signal related to the serotonin transporter (5-HTT) distribution during processing of aversive facial expressions of emotion processing 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, i.e. a serotonin reuptake inhibitor, to test the hypothesis that network activity in people with and without ASD would respond differently to inhibition of 5-HTT. To confirm the specificity of our findings, we also repeated the analysis with 5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4 receptor maps. We found a baseline group difference in the 5-HTT-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. Our findings suggest that the 5HTT-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.

neuroscience↗

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

Chronic pain is a highly debilitating and poorly understood condition. Here, we attempt to advance our understanding of the brain mechanisms driving chronic pain by investigating alterations in morphometric similarity (MS) and corresponding transcriptomic and cellular signatures, in three cohorts of patients with distinct chronic pain syndromes (knee osteoarthritis, low back pain and fibromyalgia). We uncover a novel pattern of cortical MS remodelling involving mostly MS increases in the insula and limbic cortex, which cuts across the boundaries of specific pain syndromes. We show that cortical MS remodelling in chronic pain spatially correlates with the brain-wide expression of genes involved in the glial immune response and neuronal plasticity. Cortical remodelling in chronic pain might involve a disruption of multiple elements of the cellular architecture of the brain. Therefore, multi-target therapeutic approaches tackling both glial activation and neuronal hyperexcitability might better encompass the full neurobiology of chronic pain.

neuroscience↗

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

BackgroundChronic pain is a world-wide clinical challenge. Response to analgesic treatment is limited and difficult to predict. Functional MRI (fMRI) has been suggested as a potential solution. However, while most analgesics target specific neurotransmission pathways, fMRI-based biomarkers are not specific for any neurotransmitter system, limiting our understanding of how they might contribute to predict treatment response. MethodsHere, we sought to bridge this gap by applying Receptor-Enriched Analysis of Functional Connectivity by Targets (REACT) to investigate whether neurotransmission-enriched functional connectivity (FC) mapping can provide insights into the brain mechanisms underlying chronic pain and inter-individual differences in analgesic response after a placebo or duloxetine. Chronic knee osteoarthritis (OA) pain patients (n=56) 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. ResultsAcross two independent studies, we found that chronic pain OA patients present FC alterations in the FC related to the serotonin (SERT) and noradrenaline (NET) transporters, when compared to age-matched healthy controls. Placebo responders presented with higher pre-treatment dopamine transporter (DAT)-enriched FC than non-responders. Duloxetine responders presented with higher pre-treatment SERT and NET-enriched FC than non-responders. Pre-treatment SERT and NET-enriched FC achieved predictive positive values of duloxetine response up to 85.71%. ConclusionNeurotransmission-enriched FC mapping might hold promise as a new mechanistic-informed biomarker for functional brain alterations and prediction of response to pharmacological analgesia in chronic pain.

neuroscience↗

Less is more: a dose-response mechanistic account of intranasal oxytocin pharmacodynamics in the human brain

Intranasal oxytocin is receiving increasing research attention as a potential treatment for several brain disorders due to promising preclinical results. However, translating these 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) and a novel administration device, we demonstrate that oxytocin-induced physiological changes in the amygdala at rest, a key-hub of the brain oxytocin system, follow a dose-response curve with maximal effects for lower doses. Yet, the effects of oxytocin 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; the absence of major vascular confounds corroborates the validity of haemodynamic neuroimaging to probe the effects of intranasal oxytocin in the human brain.

neuroscience↗

The association between pain-induced autonomic reactivity and descending pain control is mediated by the periaqueductal grey

There is a strict interaction between the autonomic nervous system (ANS) and pain, which might involve descending pain modulatory mechanisms. The periaqueductal grey (PAG) is involved both in descending pain modulation and ANS, but its role in mediating this relationship has not yet been explored. Here, we sought to determine brain regions mediating ANS and descending pain control associations. 30 participants underwent Conditioned Pain Modulation (CPM) assessments, in which they rated painful pressure stimuli applied to their thumbnail, either alone or with a painful cold contralateral stimulation. Differences in pain ratings between pressure-only and pressure+cold stimuli provided a measure of descending pain control. In 18 of the 30 participants, structural scans and two functional MRI assessments, one pain-free and one during cold-pain, were acquired. Heart Rate Variability (HRV) was simultaneously recorded. Low frequency HRV (LF-HRV) and the CPM score were negatively correlated; individuals with higher LF-HRV during pain reported reductions in pain during CPM. PAG-frontal medial cortex (FMC) and PAG-rostral ventro-medial medulla (RVM) functional connectivity correlated negatively with the CPM. Importantly, PAG-FMC functional connectivity mediated the strength of HRV-CPM association. CPM response magnitude was also negatively associated with PAG and positively associated with FMC grey matter volumes. Our multi-modal approach, using behavioral, physiological and MRI measures, provides important new evidence of interactions between ANS and descending pain mechanisms. ANS dysregulation and dysfunctional descending pain modulation are characteristics of chronic pain. We suggest that further investigation of body-brain interactions in chronic pain patients may catalyse the development of new treatments.

neuroscience↗

Unravelling the effects of methylphenidate on the dopaminergic and noradrenergic functional circuits

Functional magnetic resonance imaging (fMRI) can be combined with drugs to investigate the system-level functional responses in the brain to such challenges. However, most psychoactive agents act on multiple neurotransmitters, limiting the ability of fMRI to identify functional effects related to actions on discrete pharmacological targets. We recently introduced a multimodal approach, REACT (Receptor-Enriched Analysis of functional Connectivity by Targets), which offers the opportunity to disentangle effects of drugs on different neurotransmitters and clarify the biological mechanisms driving clinical efficacy and side effects of a compound. Here, we focus on methylphenidate (MPH), which binds to the dopamine transporter (DAT) and the norepinephrine transporter (NET), to unravel its effects on dopaminergic and noradrenergic functional circuits in the healthy brain at rest. We then explored the relationship between these target-enriched resting state functional connectivity (FC) maps and inter-individual variability in behavioural responses to a reinforcement-learning task encompassing a novelty manipulation to disentangle the molecular systems underlying specific cognitive/behavioural effects. Results showed a significant MPH-induced FC increase in sensorimotor areas in the functional circuit associated with DAT. We also found that MPH-induced variations in DAT-and NET-enriched FC were significantly correlated with inter-individual differences in effects of MPH on key behavioural responses associated with the reinforcement-learning task. Our findings show that MPH-related FC changes are specifically associated with DAT and provide evidence that when compounds have mixed pharmacological profiles, REACT may be able to capture regional functional effects that are underpinned by the same cognitive mechanism but are related to distinct molecular targets.

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