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

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

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

BACKGROUND

Selective serotonin reuptake inhibitors (SSRIs) potentiate serotonergic neurotransmission by blocking the serotonin transporter (5-HTT), but the functional brain response to SSRIs involves neural circuits beyond regions with high 5-HTT expression. Currently, it is unclear whether and how changes in 5-HTT availability after SSRI administration modulate brain function of key serotoninergic circuits, including those characterized by high availability of the serotonin 1A receptor (5-HT1AR).

AIM

We investigated the association between 5-HTT availability and 5-HTT- and 5-HT1AR-enriched functional connectivity (FC) after an acute citalopram challenge.

METHODS

We analyzed multimodal data from a dose-response, placebo-controlled, double-blind study, in which 45 healthy women were randomized into three groups receiving placebo, a low (4 mg), or high (16 mg) oral dose of citalopram. Receptor-Enhanced Analysis of functional Connectivity by Targets was used to estimate 5-HTT- and 5-HT1AR-enriched FC from resting-state and task-based fMRI. 5-HTT availability was determined using [123I]FP-CIT single-photon emission computerized tomography.

RESULTS

5-HTT availability was negatively correlated with resting-state 5-HTT-enriched FC, and with task-dependent 5-HT1AR-enriched FC. Our exploratory analyses revealed lower 5-HT1AR-enriched FC in the low-dose group compared to the high-dose group at rest and the placebo group during the emotional face-matching task.

CONCLUSIONS

Taken together, our findings provide evidence for differential links between 5-HTT availability and brain function within 5-HTT and 5-HT1AR pathways and in context- and dose-dependent manner. As such, they support a potential pivotal role of the 5-HT1AR in the effects of citalopram on the brain and add to its potential as a therapeutic avenue for mood and anxiety disturbances.

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

OBJECTIVE

Neuropharmacological changes in visual snow syndrome (VSS) are poorly understood. We aimed to use receptor target maps combined with resting functional magnetic resonance imaging (fMRI) data to identify which neurotransmitters might modulate brain circuits involved in VSS.

METHODS

We used Receptor-Enriched Analysis of Functional Connectivity by Targets (REACT) to estimate and compare the molecular-enriched functional networks related to 5 neurotransmitter systems of patients with VSS (n = 24), healthy controls (HCs; n = 24), and migraine patients ([MIG], n = 25, 15 of whom had migraine with aura [MwA]). For REACT we used receptor density templates for the transporters of noradrenaline, dopamine, and serotonin, GABA-A and NMDA receptors, as well as 5HT1B and 5HT2A receptors, and estimated the subject-specific voxel-wise maps of functional connectivity (FC). We then performed voxel-wise comparisons of these maps among HCs, MIG, and VSS.

RESULTS

Patients with VSS had reduced FC in glutamatergic networks localized in the anterior cingulate cortex (ACC) compared to HCs and patients with migraine, and reduced FC in serotoninergic networks localized in the insula, temporal pole, and orbitofrontal cortex compared to controls, similar to patients with migraine with aura. Patients with VSS also showed reduced FC in 5HT2A -enriched networks, largely localized in occipito-temporo-parietal association cortices. As revealed by subgroup analyses, these changes were independent of, and analogous to, those found in patients with migraine with aura.

INTERPRETATION

Our results show that glutamate and serotonin are involved in brain connectivity alterations in areas of the visual, salience, and limbic systems in VSS. Importantly, altered serotonergic connectivity is independent of migraine in VSS, and simultaneously comparable to that of migraine with aura, highlighting a shared biology between the disorders. ANN NEUROL 2023;94:873-884.

Two human brain systems micro-structurally associated with obesity

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

An automatic analysis framework for FDOPA PET neuroimaging

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

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

BACKGROUND

Resting state connectivity studies link ketamine's antidepressant effects with normalisation of the brain connectivity changes that are observed in depression. These changes, however, usually co-occur with improvement in depressive symptoms, making it difficult to attribute these changes to ketamine's effects per se.

AIMS

Our aim is to examine the effects of ketamine in brain connectivity, 2 h after its administration in a cohort of volunteers with remitted depression. Any significant changes observed in this study could provide insight of ketamine's antidepressant mechanism as they are not accompanied by symptom changes.

METHODS

In total, 35 participants with remitted depression (21 females, mean age = 28.5 years) participated in a double-blind, placebo-controlled study of ketamine (0.5 mg/kg) or saline. Resting state scans were acquired approximately 2 h after the ketamine infusion. Brain connectivity was examined using a seed-based approach (ventral striatum, amygdala, hippocampus, posterior cingulate cortex and subgenual anterior cingulate cortex (sgACC)) and a brain network analysis (independent component analysis).

RESULTS

Decreased connectivity between the sgACC and the amygdala was observed approximately 2 h after the ketamine infusion, compared to placebo (pFWE < 0.05). The executive network presented with altered connectivity with different cortical and subcortical regions. Within the network, the left hippocampus and right amygdala had decreased connectivity (pFWE < 0.05).

CONCLUSIONS

Our findings support a model whereby ketamine would change the connectivity of brain areas and networks that are important for cognitive processing and emotional regulation. These changes could also be an indirect indicator of the plasticity changes induced by the drug.

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

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

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

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

From Neurotransmitters to Networks: Transcending Organisational Hierarchies with Molecular-informed Functional Imaging

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

Metastability as a candidate neuromechanistic biomarker of schizophrenia pathology

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

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

•

Spatiotemporal patterns of phase-locking tend to be time-invariant.

•

Global metastability is representative and stable in a cohort of heathy young adults.

•

dFC characteristics are in general unique to any fMRI acquisition.

•

Dynamical and informational complexity are interrelated.

•

Complexity science contributes to a coherent description of brain dynamics.

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

Integrating neuroimaging and gene expression data using the imaging transcriptomics toolbox

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

For complete details on the use and execution of this protocol, please refer to Martins et al. (2021).

•

Protocol for using the Imaging Transcriptomics toolbox

•

Identifies transcriptomic correlates of neuroimaging data

•

Performs gene enrichment analysis to contextualize findings

•

Standardized and user-friendly pipeline using robust statistics

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

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

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

BACKGROUND

Alterations in the serotonergic control of brain pathways responsible for facial emotion processing in people with autism spectrum disorder (ASD) may be a target for intervention. However, the molecular underpinnings of autistic-neurotypical serotonergic differences are challenging to access in vivo. Receptor-Enriched Analysis of functional Connectivity by Targets (REACT) has helped define molecular-enriched functional magnetic resonance imaging (fMRI) brain networks based on a priori information about the spatial distribution of neurochemical systems from available PET templates.

METHODS

We used REACT to estimate the dominant fMRI signal related to the serotonin (5-HT) transporter (SERT) distribution during processing of aversive facial emotion in adults with and without ASD. We first predicted a group difference in baseline (placebo) functioning of this system. We next used a single 20 mg oral dose of citalopram, a serotonin reuptake inhibitor, to test the hypothesis that network activity in people with and without ASD would respond differently to inhibition of SERT. To confirm the specificity of our findings, we also repeated the analysis with 5-HT1A, 5-HT1B, 5-HT2A and 5-HT4 receptor maps.

RESULTS

Using REACT with the SERT map, we found a baseline group difference in the SERT-enriched response to faces in the ventromedial prefrontal cortex. A single oral dose of citalopram 'shifted' the response in the ASD group towards the neurotypical baseline but did not alter response in the control group. Similar differences in SERT-enriched response were observed after controlling for other 5-HT maps.

CONCLUSIONS

Our findings suggest that the SERT-enriched functional network is dynamically different in ASD during processing of socially relevant stimuli. Whether this acute neurobiological response to citalopram in ASD translates to a clinical target will be an important next step.

Transcriptional and cellular signatures of cortical morphometric remodelling in chronic pain

ABSTRACT

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

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

RATIONALE

LSD is the prototypical psychedelic. Despite a clear central role of the 5HT2a receptor in its mechanism of action, the contributions of additional receptors for which it shows affinity and agonist activity remain unclear.

OBJECTIVES

We employed receptor-enriched analysis of functional connectivity by targets (REACT) to explore differences in functional connectivity (FC) associated with the distributions of the primary targets of LSD-the 5HT1a, 5HT1b, 5HT2a, D1 and D2 receptors.

METHODS

We performed secondary analyses of an openly available dataset (N = 15) to estimate the LSD-induced alterations in receptor-enriched FC maps associated with these systems. Principal component analysis (PCA) was employed as a dimension reduction strategy for subjective experiences associated with LSD captured by the Altered States of Consciousness (ASC) questionnaire. Correlations between these principal components as well as VAS ratings of subjective effects with receptor-enriched FC were explored.

RESULTS

Compared to placebo, LSD produced differences in FC when the analysis was enriched with each of the primary serotonergic and dopaminergic receptors. Altered receptor-enriched FC showed relationships with the subjective effects of LSD on conscious experience, with serotonergic and dopaminergic systems being predominantly associated with perceptual effects and perceived selfhood as well as cognition respectively. These relationships were dissociable, with different receptors showing the same relationships within, but not between, the serotonergic and dopaminergic systems.

CONCLUSIONS

These exploratory findings provide new insights into the pharmacology of LSD and highlight the need for additional investigation of non-5HT2a-mediated mechanisms.

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

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

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

The integration of transcriptomic and neuroimaging data, "imaging transcriptomics," has recently emerged to generate hypotheses about potential biological pathways underlying regional variability in neuroimaging features. However, the validity of this approach is yet to be examined in depth. Here, we sought to bridge this gap by performing transcriptomic decoding of the regional distribution of well-known molecular markers spanning different elements of the biology of the healthy human brain. Imaging transcriptomics identifies biological and cell pathways that are consistent with the known biology of a wide range of molecular neuroimaging markers. The extent to which it can capture patterns of gene expression that align well with elements of the biology of the neuroinflammatory axis, at least in healthy controls without a proinflammatory challenge, is inconclusive. Imaging transcriptomics might constitute an interesting approach to improve our understanding of the biological pathways underlying regional variability in a wide range of neuroimaging phenotypes.

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

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

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. 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. KEY POINTS: Heart rate variability (HRV) is associated with descending pain modulation as measured by the conditioned pain modulation protocol (CPM). There is an association between CPM scores and the functional connectivity between the periaqueductal grey (PAG) and ventro-medial prefrontal cortex (vmPFC). CPM scores are also associated with vmPFC grey matter volume. The strength of functional connectivity between the PAG and vmPFC mediates the association between HRV and CPM. Our data provide new evidence of interactions between the autonomic nervous system and descending pain mechanisms.

Cognitive fatigue in multiple sclerosis is associated with alterations in the functional connectivity of monoamine circuits

Fatigue is a highly prevalent and debilitating symptom in multiple sclerosis, but currently the available treatment options have limited efficacy. The development of innovative and efficacious targeted treatments for fatigue in multiple sclerosis has been marred by the limited knowledge of the underlying mechanisms. One of the hypotheses postulates that multiple sclerosis 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 method to investigate whether patients with high and low fatigue differ in the functional connectivity (FC) of the monoamine circuits in the brain. We recruited 55 patients with multiple sclerosis, 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 (NAT)-enriched connectivity in several frontal and prefrontal areas when compared to those with lower fatigue. The NAT-enriched FC predicted negatively individual cognitive fatigue scores. Our findings support the idea that alterations in the catecholaminergic functional circuits underlie fatigue in multiple sclerosis and identify the NAT as a putative therapeutic target directed to pathophysiology.

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

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

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

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.

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. 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.

Sustained perturbation in functional connectivity induced by cold pain

BACKGROUND

Functional connectivity (FC) perturbations have been reported in multiple chronic pain phenotypes, but the nature of reported changes varies between cohorts and may relate to the consequences of living with chronic-pain related comorbidities, such as anxiety and depression. Healthy volunteer studies provide opportunities to study the effects of tonic noxious stimulation independently of these sequelae. Connectivity changes in task negative and positive networks, for example, the default mode and salience networks (DMN/SN), respectively, have been described, but how these and other connectivity networks, for example, those governing descending pain control are affected by the presence of tonic, noxious stimulation in healthy, pain-free individuals, remains unknown.

METHOD

In 20 healthy volunteers, we assessed FC prior to, during, and following tonic cold painful stimulation in the ventromedial prefrontal cortex (vmPFC), rostral anterior insula (rAI), subgenual anterior cingulate cortex (ACC) and periaqueductal grey (PAG). We also recorded subjectively reported pain using a computerised visual analogue scale.

RESULTS

We saw DMN FC changes during painful stimulation and that inter-network connectivity between the rAI with the vmPFC increased during pain, whereas PAG-precuneus FC decreased. Pain-induced FC alterations persisted following noxious stimulation. FC changes related to the magnitude of individuals' subjectively reported pain.

CONCLUSIONS

We demonstrate FC changes during and following tonic cold-pain in healthy participants. Similarities between our findings and reports of patients with chronic pain suggest that some FC changes observed in these patients may relate to the presence of an ongoing afferent nociceptive drive.

SIGNIFICANCE

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.

Linking Pain Sensation to the Autonomic Nervous System: The Role of the Anterior Cingulate and Periaqueductal Gray Resting-State Networks

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.

Topological gene expression networks recapitulate brain anatomy and function

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.

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

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

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-HT_1A, 5-HT_1B, 5-HT_2A, 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-HT_1A distribution density maps, which are the main targets of this compound. Changes in the 5-HT_1A-enriched functional maps were also associated with the pharmacokinetic levels of MDMA and MDMA-induced FC changes in the 5-HT_2A-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.

•

MDMA connectivity effects understood through the distribution of 5-HT_1A and 5-HTT.

•

Direct link between PK levels of MDMA and 5-HT_1A-enriched functional connectivity maps.

•

Ability to link receptor targets to functional mechanisms underlying behaviour.

•

Mapping pharmacodynamic effects onto the drug's molecular targets.

Covariance statistics and network analysis of brain PET imaging studies

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.

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

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.

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

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.

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

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.

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

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 4h 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.

Theory of Mind and the Whole Brain Functional Connectivity: Behavioral and Neural Evidences with the Amsterdam Resting State Questionnaire

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

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

High-dimensional independent component analysis (ICA), compared to low-dimensional ICA, allows to conduct 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 data of 20 healthy controls and 21 patients with AD, focusing on the primarily altered default-mode network (DMN) and exploring the sensory-motor network. 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 subnetworks. Due to the higher sensitivity of the high-dimensional ICA analysis, our results suggest that high-dimensional decomposition in subnetworks is very promising to better localize FC alterations in AD and that FC damage is not confined to the DMN.