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

Daniel Martins, Katja Brodmann, Mattia Veronese, Ottavia Dipasquale, Ndaba Mazibuko, Uwe Schuschnig, Fernando Zelaya, Katarina Fotopoulou, Yannis Paloyelis
Progress in Neurobiology 2022

Journal article

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.

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

Daniel Martins, Mattia Veronese, Federico E Turkheimer, Matthew A Howard, Steve CR Williams, Ottavia Dipasquale
Brain Communications 2022

Journal article

Chronic 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.
Here, 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.
Across 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%.
Neurotransmission-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.

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

Daniel Martins, Alessio Giacomel, Steven CR Williams, Federico E Turkheimer, Ottavia Dipasquale, Mattia Veronese, PET templates working group
Cell Reports 2021

Journal article

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.

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

Daniel Martins, Ottavia Dipasquale, Mattia Veronese, Federico E Turkheimer, Marco Loggia, Stephen McMahon, Steven CR Williams
Pain 2021

Journal article

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.

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

Elena Makovac, Alessandra Venezia, David Hogenschurz-Schmidt, Ottavia Dipasquale, Jade B Jackson, Sonia Medina, Owen O'daly, Steven CR Williams, Stephen B McMahon, Matthew A Howard
The Journal of Physiology 2021

Journal article

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. Thirty 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. Normalised low-frequency HRV (LF-HRVnu) and the CPM score were negatively correlated; individuals with higher LF-HRVnu during pain reported reductions in pain during CPM. PAG-ventro-medial prefrontal cortex (vmPFC) and PAG-rostral ventromedial medulla (RVM) functional connectivity correlated negatively with the CPM. Importantly, PAG-vmPFC functional connectivity mediated the strength of the LF-HRVnu-CPM association. CPM response magnitude was also negatively correlated with vmPFC GM volume. Our multi-modal approach, using behavioural, 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.

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

Nichol ML Wong, Ottavia Dipasquale, Federico E Turkheimer, James L Findon, Robert H Wichers, Mihail Dimitrov, Clodagh M Murphy, Vladimira Stoencheva, Dene M Robertson, Declan G Murphy, Eileen Daly, Grainne M McAlonan
bioRxiv 2021

Journal article

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.

Cognitive fatigue in multiple sclerosis is associated with alterations in the functional connectivity of monoaminecircuits.

Mara Cercignani, Ottavia Dipasquale, Iulia Bogdan, Tiziana Carandini, James Scott, Waqar Rashid, Osama Sabri, Swen Hesse, Michael Rullmann, Leonardo Lopiano, Mattia Veronese, Daniel Martins, Marco Bozzali
Brain Communications 2021

Journal article

Fatigue is a highly prevalent and debilitating symptom in multiple sclerosis (MS), but currently the available treatment options have limited efficacy. The development of innovative and efficacious targeted treatments for fatigue in MS has been marred by the limited knowledge of the underlying mechanisms. One of the hypotheses postulates that MS pathology might cause reduced monoaminergic release in the central nervous system with consequences on motivation, mood, and attention. Here we applied the recently developed Receptor-Enriched Analysis of Functional Connectivity by Targets (REACT) method to investigate whether patients with high and low fatigue differ in the functional connectivity of the monoamine circuits in the brain. We recruited 55 MS patients, which were then classified as highly fatigued or mildly fatigued based on their scores on the cognitive sub-scale of the Modified Fatigue Impact scale. We acquired resting-state functional MRI scans and derived individual maps of connectivity associated with the distribution of the dopamine, noradrenaline and serotonin transporters as measured by positron emission tomography. We found that patients with high fatigue present decreased noradrenaline transporter-enriched connectivity in several frontal and prefrontal areas when compared to those with lower fatigue. The noradrenaline transporter- enriched functional connectivity predicted negatively individual cognitive fatigue scores. Our findings support the idea that alterations in the catecholaminergic functional circuits underlie fatigue in MS and identify the noradrenaline transporter as a putative therapeutic target directed to pathophysiology.

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

Federico E Turkheimer, Fernando E Rosas, Ottavia Dipasquale, Daniel Martins, Erik D Fagerholm, Paul Expert, Frantisek Vasa, Louis-David Lord, Robert Leech
The Neuroscientist 2021

Journal article

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.

Oxytocin modulates local topography of human functional connectome in healthy men at rest.

Daniel Martins, Ottavia Dipasquale, Yannis Paloyelis
Communications Biology 2021

Journal article

Oxytocin has recently received remarkable attention for its role as a modulator of human behaviour. Here, we aimed to expand our knowledge of the neural circuits engaged by oxytocin by investigating the effects of intranasal and intravenous oxytocin on the functional connectome at rest in 16 healthy men. Oxytocin modulates the functional connectome within discrete neural systems, but does not affect the global capacity for information transfer. These local effects encompass key hubs of the oxytocin system (e.g. amygdala) but also regions overlooked in previous hypothesis-driven research (i.e. the visual circuits, temporal lobe and cerebellum). Increases in levels of oxytocin in systemic circulation induce broad effects on the functional connectome, yet we provide indirect evidence supporting the involvement of nose-to-brain pathways in at least some of the observed changes after intranasal oxytocin. Together, our results suggest that oxytocin effects on human behaviour entail modulation of multiple levels of brain processing distributed across different systems.

Sustained perturbation in functional connectivity induced by cold pain.

Elena Makovac, Ottavia Dipasquale, Jade B Jackson, Sonia Medina, Owen O'daly, Jonathan O'muircheartaigh, Alfonso de Lara Rubio, Steven CR Williams, Stephen B McMahon, Matthew A Howard
European Journal of Pain 2020

Journal article

How pain‐related resting state networks are affected by tonic cold‐pain remains unknown. We investigated functional connectivity alterations during and following tonic cold pain in healthy volunteers. Cold pain perturbed the functional connectivity of the ventro‐medial prefrontal cortex, anterior insula, and the periacquaductal grey area. These connectivity changes were associated with the magnitude of individuals’ reported pain. We suggest that some connectivity changes described in chronic pain patients may be due to an ongoing afferent peripheral drive.

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

Ottavia Dipasquale, Daniel Martins, Arjun Sethi, Mattia Veronese, Swen Hesse, Michael Rullmann, Osama Sabri, Federico Turkheimer, Neil A Harrison, Mitul A Mehta, Mara Cercignani
Neuropsychopharmacology 2020

Journal article

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. Our main analysis showed a significant MPH-induced FC increase in sensorimotor areas in the functional circuit associated with DAT. In our exploratory analysis, we found that MPH-induced regional variations in the DAT and NET-enriched FC maps were significantly correlated with some of the inter-individual differences on key behavioural responses associated with the reinforcement-learning task. Our findings show that main MPH-related FC changes at rest can be understood through the distribution of DAT in the brain. Furthermore, they suggest 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 engagement of distinct molecular targets.

Linking pain sensation to the autonomic nervous system: the role of the anterior cingulate and periaqueductal gray resting-state networks.

David Johannes Hohenschurz-Schmidt, Giovanni Calcagnini, Ottavia Dipasquale, Jade B Jackson, Sonia Medina, Owen O’Daly, Jonathan O’Muircheartaigh, Alfonso de Lara Rubio, Steven CR Williams, Stephen B McMahon, Elena Makovac, Matthew A Howard
Frontiers in Neuroscience 2020

Journal article

There are bi-directional interactions between the autonomic nervous system (ANS) and pain. This is likely underpinned by a substantial overlap between brain areas of the central autonomic network and areas involved in pain processing and modulation. To date, however, relatively little is known about the neuronal substrates of the ANS-pain association. Here, we acquired resting state fMRI scans in 21 healthy subjects at rest and during tonic noxious cold stimulation. As indicators of autonomic function, we examined how heart rate variability (HRV) frequency measures were influenced by tonic noxious stimulation and how these variables related to participants’ pain perception and to brain functional connectivity in regions known to play a role in both ANS regulation and pain perception, namely the right dorsal anterior cingulate cortex (dACC) and periaqueductal gray (PAG). Our findings support a role of the cardiac ANS in brain connectivity during pain, linking functional connections of the dACC and PAG with measurements of low frequency (LF)-HRV. In particular, we identified a three-way relationship between the ANS, cortical brain networks known to underpin pain processing, and participants’ subjectively reported pain experiences. LF-HRV both at rest and during pain correlated with functional connectivity between the seed regions and other cortical areas including the right dorsolateral prefrontal cortex (dlPFC), left anterior insula (AI), and the precuneus. Our findings link cardiovascular autonomic parameters to brain activity changes involved in the elaboration of nociceptive information, thus beginning to elucidate underlying brain mechanisms associated with the reciprocal relationship between autonomic and pain-related systems.

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

Elena Makovac, Alessandra Venezia, David Hohenschurz-Schmidt, Ottavia Dipasquale, Jade B Jackson, Sonia Medina, Owen O'Daly, Steve CR Williams, Stephen B McMahon, Matthew A Howard
bioRxiv 2020

Journal article

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.

Comparison between a pure functional connectivity and a mixed functional-topological model in functional connectivity. An application on parahippocampal gyrus-anterior division data.

Paolo Finotelli, Monia Cabinio, Ottavia Dipasquale, Mara Cercignani, Baglio Francesca, Paolo Dulio
Biomedical Signal Processing and Control 2019

Journal article

The investigation of brain functional connectivity (FC) by means of rsfMRI techniques is on-going challenge in the neuroimaging field. In the present investigation we compare two mathematical models for the computation of Resting-State Networks: The first one is based on the pure analysis of time courses (pure Functional Connectivity, pFC), the second one, the FD model, includes both the time courses, the anatomical information between brain nodes and topological metrics of the network which models the brain. The two approaches have been evaluated by comparing the maximal weights of the links representing the neural network obtained by applying the two models to a dataset of rsfMRI images from 133 healthy subjects. FC analyses were performed using the two methods by focusing on the functional connections between the anterior part of the parahippocampal gyrus (PHGA), a core area for cognitive and emotive processes, and the rest of the brain. Based on the literature, we expect to collect evidences of the role of PHGA as connector hub between the temporal pole and the nodes of the Default Model Network. As expected, the majority of the significant links involved were highlighted by both methods. However, the FD model highlighted a greater number of links compared with pFC. These links are in line with the known neuroanatomy. Hence, our results invite to consider the FD approach as an effective approach of analysis, since due to its characteristics it could provide a more complete description of the brain network.

Dissociative identity as a continuum from healthy mind to psychiatric disorders: Epistemological and neurophenomenological implications approached through hypnosis.

Enrico Facco, Laura Mendozzi, Angelo Bona, Achille Motta, Massimo Garegnani, Isa Costantini, Ottavia Dipasquale, Pietro Cecconi, Roberta Menotti, Elisa Coscioli, Susanna Lipari
Medical Hypotheses 2019

Journal article

The topic of multiple personality, redefined as Dissociative Identity Disorders (DIDs) in the DSM-5, is an intriguing and still debated disorder with a long history and deep cultural and epistemological implications, extending up to the idea of possession.
Hypnosis is an appealing and valuable model to manipulate subjective experience and get an insight on both the physiology and the pathophysiology of the mind-brain functioning; it and has been closely connected with DIDs and possession since its origin in 18th century and as recently proved the capacity to yield a loss of sense of agency, mimicking delusions of alien control and spirit possession.
In this study we report on five very uncommon “hypnotic virtuosos” (HVs) free from any psychiatric disorder, spontaneously undergoing the emergence of multiple identities during neutral hypnosis; this allowed us to check the relationship between their experience and fMRI data.
During hypnosis the subjects underwent spontaneous non-intrusive experiences of other selves which were not recalled after the end of the session, due to post-hypnotic amnesia. The fMRI showed a significant decrease of connectivity in the Default Mode Network (DMN) especially between the posterior cingulate cortex and the medial prefrontal cortex.
Our results and their contrast with the available data on fMRI in DIDs allows to draw the hypothesis of a continuum between healthy mind – where multiple identities may coexist at unconscious level and may sometimes emerge to the consciousness – and DIDs, where multiple personalities emerge as dissociated, ostensibly autonomous components yielding impaired functioning, subject’s loss of control and suffering. If this is the case, it seems more reasonable to refrain from seeking for a clear-cut limit between normality (anyway a conventional, statistical concept) and pathology, and accept a grey area in between, where ostensibly odd but non-pathological experiences may occur (including so-called non-ordinary mental expressions) without calling for treatment but, rather, for being properly understood.

Receptor-Enriched Analysis of functional connectivity by targets (REACT): A novel, multimodal analytical approach informed by PET to study the pharmacodynamic response of the brain under MDMA.

Ottavia Dipasquale, Pierluigi Selvaggi, Mattia Veronese, Anthony S Gabay, Federico Turkheimer, Mitul A Mehta
NeuroImage 2019

Journal article

One of the main limitations of pharmacological fMRI is its inability to provide a molecular insight into the main effect of compounds, leaving an open question about the relationship between drug effects and haemodynamic response. The aim of this study is to investigate the acute effects of 3,4-methylenedioxymethamphetamine (MDMA) on functional connectivity (FC) using a novel multimodal method (Receptor-Enriched Analysis of functional Connectivity by Targets - REACT). This approach enriches the resting state (rs-)fMRI analysis with the molecular information about the distribution density of serotonin receptors in the brain, given the serotonergic action of MDMA.
Twenty healthy subjects participated in this double-blind, placebo-controlled, crossover study. A high-resolution in vivo atlas of four serotonin receptors (5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4) and its transporter (5-HTT) was used as a template in a two-step multivariate regression analysis to estimate the spatial maps reflecting the whole-brain connectivity behaviour related to each target under placebo and MDMA.
Results showed that the networks exhibiting significant changes after MDMA administration are the ones informed by the 5-HTT and 5-HT1A distribution density maps, which are the main targets of this compound. Changes in the 5-HT1A-enriched functional maps were also associated with the pharmacokinetic levels of MDMA and MDMA-induced FC changes in the 5-HT2A-enriched maps correlated with the spiritual experience subscale of the Altered States of Consciousness Questionnaire.
By enriching the rs-fMRI analysis with molecular data of voxel-wise distribution of the serotonin receptors across the brain, we showed that MDMA effects on FC can be understood through the distribution of its main targets. This result supports the ability of this method to characterise the specificity of the functional response of the brain to MDMA binding to serotonergic receptors, paving the way to the definition of a new fingerprint in the characterization of new compounds and potentially to a further understanding to the response to treatment.

Topological gene expression networks recapitulate brain anatomy and function.

Alice Patania, Pierluigi Selvaggi, Mattia Veronese, Ottavia Dipasquale, Paul Expert, Giovanni Petri
Network Neuroscience 2019

Journal article

Understanding how gene expression translates to and affects human behavior is one of the ultimate goals of neuroscience. In this paper, we present a pipeline based on Mapper, a topological simplification tool, to analyze gene co-expression data. We first validate the method by reproducing key results from the literature on the Allen Human Brain Atlas and the correlations between resting-state fMRI and gene co-expression maps. We then analyze a dopamine-related gene set and find that co-expression networks produced by Mapper return a structure that matches the well-known anatomy of the dopaminergic pathway. Our results suggest that network based descriptions can be a powerful tool to explore the relationships between genetic pathways and their association with brain function and its perturbation due to illness and/or pharmacological challenges.

Increased cerebral blood flow after single dose of antipsychotics in healthy volunteers depends on dopamine D2 receptor density profiles.

Pierluigi Selvaggi, Peter CT Hawkins, Ottavia Dipasquale, Gaia Rizzo, Alessandro Bertolino, Juergen Dukart, Fabio Sambataro, Giulio Pergola, Steven CR Williams, Federico Turkheimer, Fernando Zelaya, Mattia Veronese, Mitul A Mehta
Neuroimage 2019

Journal article

As a result of neuro-vascular coupling, the functional effects of antipsychotics in human brain have been investigated in both healthy and clinical populations using haemodynamic markers such as regional Cerebral Blood Flow (rCBF). However, the relationship between observed haemodynamic effects and the pharmacological action of these drugs has not been fully established. Here, we analysed Arterial Spin Labelling (ASL) rCBF data from a placebo-controlled study in healthy volunteers, who received a single dose of three different D2 receptor (D2R) antagonists and tested the association of the main effects of the drugs on rCBF against normative population maps of D2R protein density and gene-expression data. In particular, we correlated CBF changes after antipsychotic administration with non-displaceable binding potential (BPND) template maps of the high affinity D2-antagonist Positron Emission Tomography (PET) ligand [18F]Fallypride and with brain post-mortem microarray mRNA expression data for the DRD2 gene from the Allen Human Brain Atlas (ABA). For all antipsychotics, rCBF changes were directly proportional to brain D2R densities and DRD2 mRNA expression measures, although PET BPND spatial profiles explained more variance as compared with mRNA profiles (PET R2 range = 0.20–0.60, mRNA PET R2 range 0.04–0.20, pairwise-comparisons all pcorrected< 0.05). In addition, the spatial coupling between ΔCBF and D2R profiles varied between the different antipsychotics tested, possibly reflecting differential affinities. Overall, these results indicate that the functional effects of antipsychotics as measured with rCBF are tightly correlated with the distribution of their target receptors in striatal and extra-striatal regions. Our results further demonstrate the link between neurotransmitter targets and haemodynamic changes reinforcing rCBF as a robust in-vivo marker of drug effects. This work is important in bridging the gap between pharmacokinetic and pharmacodynamics of novel and existing compounds.

Covariance statistics and network analysis of brain PET imaging studies.

Mattia Veronese, Lucia Moro, Marco Arcolin, Ottavia Dipasquale, Gaia Rizzo, Paul Expert, Wasim Khan, Patrick M Fisher, Claus Svarer, Alessandra Bertoldo, Oliver Howes, Federico E Turkheimer
Scientific Reports 2019

Journal article

The analysis of structural and functional neuroimaging data using graph theory has increasingly become a popular approach for visualising and understanding anatomical and functional relationships between different cerebral areas. In this work we applied a network-based approach for brain PET studies using population-based covariance matrices, with the aim to explore topological tracer kinetic differences in cross-sectional investigations. Simulations, test-retest studies and applications to cross-sectional datasets from three different tracers ([18F]FDG, [18F]FDOPA and [11C]SB217045) and more than 400 PET scans were investigated to assess the applicability of the methodology in healthy controls and patients. A validation of statistics, including the assessment of false positive differences in parametric versus permutation testing, was also performed. Results showed good reproducibility and general applicability of the method within the range of experimental settings typical of PET neuroimaging studies, with permutation being the method of choice for the statistical analysis. The use of graph theory for the quantification of [18F]FDG brain PET covariance, including the definition of an entropy metric, proved to be particularly relevant for Alzheimer’s disease, showing an association with the progression of the pathology. This study shows that covariance statistics can be applied to PET neuroimaging data to investigate the topological characteristics of the tracer kinetics and its related targets, although sensitivity to experimental variables, group inhomogeneities and image resolution need to be considered when the method is applied to cross-sectional studies.

In vivo mapping of brainstem nuclei functional connectivity disruption in Alzheimer's disease.

Laura Serra, Marcello D'Amelio, Carlotta Di Domenico, Ottavia Dipasquale, Camillo Marra, Nicola Biagio Mercuri, Carlo Caltagirone, Mara Cercignani, Marco Bozzali
Neurobiology of aging 2018

Journal article

aWe assessed here functional connectivity changes in the locus coeruleus (LC) and ventral tegmental area (VTA) of patients with Alzheimer's disease (AD). We recruited 169 patients with either AD or amnestic mild cognitive impairment due to AD and 37 elderly controls who underwent cognitive and neuropsychiatric assessments and resting-state functional magnetic resonance imaging at 3T. Connectivity was assessed between LC and VTA and the rest of the brain. In amnestic mild cognitive impairment patients, VTA disconnection was predominant with parietal regions, while in AD patients, it involved the posterior nodes of the default-mode network. We also looked at the association between neuropsychiatric symptoms (assessed by the neuropsychiatric inventory) and VTA connectivity. Symptoms such as agitation, irritability, and disinhibition were associated with VTA connectivity with the parahippocampal gyrus and cerebellar vermis, while sleep and eating disorders were associated with VTA connectivity to the striatum and the insular cortex. This suggests a contribution of VTA degeneration to AD pathophysiology and to the occurrence of neuropsychiatric symptoms. We did not find evidence of LC disconnection, but this could be explained by the size of this nucleus, which makes it difficult to isolate. These results are consistent with animal findings and have potential implications for AD prognosis and therapies.

Exploring resting-state functional connectivity invariants across the lifespan in healthy people by means of a recently proposed graph theoretical model.

Paolo Finotelli, Ottavia Dipasquale, Isa Costantini, Alessia Pini, Francesca Baglio, Giuseppe Baselli, Paolo Dulio, Mara Cercignani
PLoS One 2018

Journal article

In this paper we investigate the changes in the functional connectivity intensity, and some related properties, in healthy people, across the life span and at resting state. For the explicit computation of the functional connectivity we exploit a recently proposed model, that bases not only on the correlations data provided by the acquisition equipment, but also on different parameters, such as the anatomical distances between nodes and their degrees. The leading purpose of the paper is to show that the proposed approach is able to recover the main aspects of resting state condition known from the available literature, as well as to suggest new insights, perspectives and speculations from a neurobiological point of view. Our study involves 133 subjects, both males and females of different ages, with no evidence of neurological diseases or systemic disorders. First, we show how the model applies to the sample, where the subjects are grouped into 28 different groups (14 of males and 14 of females), according to their age. This leads to the construction of two graphs (one for males and one for females), that can be realistically interpreted as representative of the neural network during the resting state. Second, following the idea that the brain network is better understood by focusing on specific nodes having a kind of centrality, we refine the two output graphs by introducing a new metric that favours the selection of nodes having higher degrees. As a third step, we extensively comment and discuss the obtained results. In particular, it is remarkable that, despite a great overlapping exists between the outcomes concerning males and females, some intriguing differences appear. This motivates a deeper local investigation, which represents the fourth part of the paper, carried out through a thorough statistical analysis. As a result, we are enabled to support that, for two special age groups, a few links contribute in differentiating the behaviour of males and females. In addition, we performed an average-based comparison between the proposed model and the traditional statistical correlation-based approach, then discussing and commenting the main outlined discrepancies.

Effects of motor rehabilitation on mobility and brain plasticity in multiple sclerosis: a structural and functional MRI study.

Eleonora Tavazzi, Niels Bergsland, Davide Cattaneo, Elisa Gervasoni, Maria Marcella Laganà, Ottavia Dipasquale, Cristina Grosso, Francesca Lea Saibene, Francesca Baglio, Marco Rovaris
Journal of neurology 2018

Journal article

Rehabilitation seems to promote brain plasticity, but objective measures of efficacy are lacking and there is a limited understanding of the mechanisms underlying functional recovery.
To study functional and structural brain changes induced by gait rehabilitation.
We enrolled MS inpatients (EDSS 4.5–6.5) undergoing a 4-week neurorehabilitation. Several clinical measures were obtained, including: 2-min walk test (2MWT), dynamic gait index (DGI), Berg balance scale (BBS). Furthermore, motor-task functional MRI (fMRI) of plantar dorsiflexion, resting state fMRI, and regional diffusion tensor imaging (DTI) metrics were obtained. All the assessments were performed at baseline (T0), after the end of the rehabilitation period (T1) and 3 months later (T2).
Twenty-nine patients were enrolled at T0, 26 at T1, and 16 completed all timepoints. At T1, there was a significant improvement of 2MWT, DGI, and BBS scores, along with a reduced extent of the widespread activation related to the motor task at the fMRI and an increased functional connectivity in the precentral and post-central gyrus, bilaterally. None of these changes were maintained at T2.
Our findings show a short-term beneficial effect of motor rehabilitation on gait performances in MS, accompanied by brain functional reorganization in the sensory-motor network.

Comparing resting state fMRI de-noising approaches using multi-and single-echo acquisitions.

Ottavia Dipasquale, Arjun Sethi, Maria Marcella Laganà, Francesca Baglio, Giuseppe Baselli, Prantik Kundu, Neil A Harrison, Mara Cercignani
PloS ONE 2017

Journal article

Artifact removal in resting state fMRI (rfMRI) data remains a serious challenge, with even subtle head motion undermining reliability and reproducibility. Here we compared some of the most popular single-echo de-noising methods—regression of Motion parameters, White matter and Cerebrospinal fluid signals (MWC method), FMRIB’s ICA-based X-noiseifier (FIX) and ICA-based Automatic Removal Of Motion Artifacts (ICA-AROMA)—with a multi-echo approach (ME-ICA) that exploits the linear dependency of BOLD on the echo time. Data were acquired using a clinical scanner and included 30 young, healthy participants (minimal head motion) and 30 Attention Deficit Hyperactivity Disorder patients (greater head motion). De-noising effectiveness was assessed in terms of data quality after each cleanup procedure, ability to uncouple BOLD signal and motion and preservation of default mode network (DMN) functional connectivity. Most cleaning methods showed a positive impact on data quality. However, based on the investigated metrics, ME-ICA was the most robust. It minimized the impact of motion on FC even for high motion participants and preserved DMN functional connectivity structure. The high-quality results obtained using ME-ICA suggest that using a multi-echo EPI sequence, reliable rfMRI data can be obtained in a clinical setting.

Interferon-α acutely impairs whole-brain functional connectivity network architecture–A preliminary study.

Ottavia Dipasquale, Ella A Cooper, Jeremy Tibble, Valerie Voon, Francesca Baglio, Giuseppe Baselli, Mara Cercignani, Neil A Harrison
Brain, Behavior, and Immunity 2016

Journal article

Interferon-alpha (IFN-α) is a key mediator of antiviral immune responses used to treat Hepatitis C infection. Though clinically effective, IFN-α rapidly impairs mood, motivation and cognition, effects that can appear indistinguishable from major depression and provide powerful empirical support for the inflammation theory of depression. Though inflammation has been shown to modulate activity within discrete brain regions, how it affects distributed information processing and the architecture of whole brain functional connectivity networks have not previously been investigated.
Here we use a graph theoretic analysis of resting state functional magnetic resonance imaging (rfMRI) to investigate acute effects of systemic interferon-alpha (IFN-α) on whole brain functional connectivity architecture and its relationship to IFN-α-induced mood change. Twenty-two patients with Hepatitis-C infection, initiating IFN-α-based therapy were scanned at baseline and 4 h after their first IFN-α dose. The whole brain network was parcellated into 110 cortical and sub-cortical nodes based on the Oxford-Harvard Atlas and effects assessed on higher-level graph metrics, including node degree, betweenness centrality, global and local efficiency.
IFN-α was associated with a significant reduction in global network connectivity (node degree) (p = 0.033) and efficiency (p = 0.013), indicating a global reduction of information transfer among the nodes forming the whole brain network. Effects were similar for highly connected (hub) and non-hub nodes, with no effect on betweenness centrality (p > 0.1). At a local level, we identified regions with reduced efficiency of information exchange and a sub-network with decreased functional connectivity after IFN-α. Changes in local and particularly global functional connectivity correlated with associated changes in mood measured on the Profile of Mood States (POMS) questionnaire.
IFN-α rapidly induced a profound shift in whole brain network structure, impairing global functional connectivity and the efficiency of parallel information exchange. Correlations with multiple indices of mood change support a role for global changes in brain functional connectivity architecture in coordinated behavioral responses to IFN-α.

Network functional connectivity and whole-brain functional connectomics to investigate cognitive decline in neurodegenerative conditions.

Ottavia Dipasquale, Mara Cercignani
Functional Neurology 2016

Journal article

Non-invasive mapping of brain functional connectivity (FC) has played a fundamental role in neuroscience, and numerous scientists have been fascinated by its ability to reveal the brain’s intricate morphology and functional properties. In recent years, two different techniques have been developed that are able to explore FC in pathophysiological conditions and to provide simple and non-invasive biomarkers for the detection of disease onset, severity and progression. These techniques are independent component analysis, which allows a network-based functional exploration of the brain, and graph theory, which provides a quantitative characterization of the whole-brain FC. In this paper we provide an overview of these two techniques and some examples of their clinical applications in the most common neurodegenerative disorders associated with cognitive decline, including mild cognitive impairment, Alzheimer’s disease, Parkinson’s disease, dementia with Lewy Bodies and behavioral variant frontotemporal dementia.

Assessment of internal jugular vein size in healthy subjects with magnetic resonance and semiautomatic processing.

MM Laganà, Laura Pelizzari, Elisa Scaccianoce, Ottavia Dipasquale, C Ricci, F Baglio, P Cecconi, Giuseppe Baselli
Behavioural Neurology 2016

Journal article

Background and Objectives. The hypothesized link between extracranial venous abnormalities and some neurological disorders awoke interest in the investigation of the internal jugular veins (IJVs). However, different IJV cross-sectional area (CSA) values are currently reported in literature. In this study, we introduced a semiautomatic method to measure and normalize the CSA and the degree of circularity (Circ) of IJVs along their whole length. Methods. Thirty-six healthy subjects (31.22 ± 9.29 years) were recruited and the 2D time-of-flight magnetic resonance venography was acquired with a 1.5 T Siemens scanner. The IJV were segmented on an axial slice, the contours were propagated in 3D. Then, IJV CSA and Circ were computed between the first and the seventh cervical levels (C1–C7) and normalized among subjects. Inter- and intrarater repeatability were assessed. Results. IJV CSA and Circ were significantly different among cervical levels (). A trend for side difference was observed for CSA (larger right IJV, ), but not for Circ (). Excellent inter- and intrarater repeatability was obtained for all the measures. Conclusion. This study proposed a reliable semiautomatic method able to measure the IJV area and shape along C1–C7, and suitable for defining the normality thresholds for future clinical studies.

Theory of mind and the whole brain functional connectivity: behavioral and neural evidences with the Amsterdam Resting State Questionnaire.

Antonella Marchetti, Francesca Baglio, Isa Costantini, Ottavia Dipasquale, Federica Savazzi, Raffaello Nemni, Francesca Sangiuliano Intra, Semira Tagliabue, Annalisa Valle, Davide Massaro, Ilaria Castelli
Frontiers in Psychology 2015

Journal article

A topic of common interest to psychologists and philosophers is the spontaneous flow of thoughts when the individual is awake but not involved in cognitive demands. This argument, classically referred to as the “stream of consciousness” of James, is now known in the psychological literature as “Mind-Wandering.” Although of great interest, this construct has been scarcely investigated so far. Diaz et al. (2013) created the Amsterdam Resting State Questionnaire (ARSQ), composed of 27 items, distributed in seven factors: discontinuity of mind, theory of mind (ToM), self, planning, sleepiness, comfort, and somatic awareness. The present study aims at: testing psychometric properties of the ARSQ in a sample of 670 Italian subjects; exploring the neural correlates of a subsample of participants (N = 28) divided into two groups on the basis of the scores obtained in the ToM factor. Results show a satisfactory reliability of the original factional structure in the Italian sample. In the subjects with a high mean in the ToM factor compared to low mean subjects, functional MRI revealed: a network (48 nodes) with higher functional connectivity (FC) with a dominance of the left hemisphere; an increased within-lobe FC in frontal and insular lobes. In both neural and behavioral terms, our results support the idea that the mind, which does not rest even when explicitly asked to do so, has various and interesting mentalistic-like contents.

Effective artifact removal in resting state fMRI data improves detection of DMN functional connectivity alteration in Alzheimer's disease.

Ludovica Griffanti, Ottavia Dipasquale, Maria Marcella Laganà, Raffaello Nemni, Mario Clerici, Stephen M Smith, Giuseppe Baselli, Francesca Baglio
Frontiers in Human Neuroscience 2015

Journal article

Artifact removal from resting state fMRI data is an essential step for a better identification of the resting state networks and the evaluation of their functional connectivity (FC), especially in pathological conditions. There is growing interest in the development of cleaning procedures, especially those not requiring external recordings (data-driven), which are able to remove multiple sources of artifacts. It is important that only inter-subject variability due to the artifacts is removed, preserving the between-subject variability of interest—crucial in clinical applications using clinical scanners to discriminate different pathologies and monitor their staging. In Alzheimer's disease (AD) patients, decreased FC is usually observed in the posterior cingulate cortex within the default mode network (DMN), and this is becoming a possible biomarker for AD. The aim of this study was to compare four different data-driven cleaning procedures (regression of motion parameters; regression of motion parameters, mean white matter and cerebrospinal fluid signal; FMRIB's ICA-based Xnoiseifier—FIX—cleanup with soft and aggressive options) on data acquired at 1.5 T. The approaches were compared using data from 20 elderly healthy subjects and 21 AD patients in a mild stage, in terms of their impact on within-group consistency in FC and ability to detect the typical FC alteration of the DMN in AD patients. Despite an increased within-group consistency across subjects after applying any of the cleaning approaches, only after cleaning with FIX the expected DMN FC alteration in AD was detectable. Our study validates the efficacy of artifact removal even in a relatively small clinical population, and supports the importance of cleaning fMRI data for sensitive detection of FC alterations in a clinical environment.

High-dimensional ICA analysis detects within-network functional connectivity damage of default-mode and sensory-motor networks in Alzheimer’s disease.

Ottavia Dipasquale, Ludovica Griffanti, Mario Clerici, Raffaello Nemni, Giuseppe Baselli, Francesca Baglio
Frontiers in Human Neuroscience 2015

Journal article

High dimensional independent component analysis (ICA), compared to low dimensional ICA, allows performing a detailed parcellation of the resting state networks. The purpose of this study was to give further insight into functional connectivity (FC) in Alzheimer’s disease (AD) using high dimensional ICA. For this reason, we performed both low and high dimensional ICA analyses of resting state fMRI (rfMRI) data of 20 healthy controls and 21 AD patients, focusing on the primarily altered default mode network (DMN) and exploring the sensory motor network (SMN). As expected, results obtained at low dimensionality were in line with previous literature. Moreover, high dimensional results allowed us to observe either the presence of within-network disconnections and FC damage confined to some of the resting state sub-networks. Due to the higher sensitivity of the high dimensional ICA analysis, our results suggest that high-dimensional decomposition in sub-networks is very promising to better localize FC alterations in AD and that FC damage is not confined to the default mode network.