Preserved fractal character of structural brain networks is associated with covert consciousness after severe brain injury.

Self-similarity is ubiquitous throughout natural phenomena, including the human brain. Recent evidence indicates that fractal dimension of functional brain networks, a measure of self-similarity, is diminished in patients diagnosed with disorders of consciousness arising from severe brain injury. Here, we set out to investigate whether loss of self-similarity is observed in the structural connectome of patients with disorders of consciousness. Using diffusion MRI tractography from N = 11 patients in a minimally conscious state (MCS), N = 10 patients diagnosed with unresponsive wakefulness syndrome (UWS), and N = 20 healthy controls, we show that fractal dimension of structural brain networks is diminished in DOC patients. Remarkably, we also show that fractal dimension of structural brain networks is preserved in patients who exhibit evidence of covert consciousness by performing mental imagery tasks during functional MRI scanning. These results demonstrate that differences in fractal dimension of structural brain networks are quantitatively associated with chronic loss of consciousness induced by severe brain injury, highlighting the close connection between structural organisation of the human brain and its ability to support cognitive function

Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics

Acknowledgements: This work was supported by the Gates Cambridge Trust (OPP 1144) [A.I.L.]; the Canadian Institute for Advanced Research (CIFAR; grant RCZB/072 RG93193) [to D.K.M. and E.A.S.]; The National Institute for Health Research (NIHR, UK), Cambridge Biomedical Research Centre and NIHR Senior Investigator Awards [D.K.M.]; The British Oxygen Professorship of the Royal College of Anaesthetists [D.K.M.]; The Stephen Erskine Fellowship, Queens’ College, University of Cambridge [E.A.S.]; the Wellcome Trust Research Training Fellowship (grant no. 083660/Z/07/Z), Raymond and Beverly Sackler Studentship, and the Cambridge Commonwealth Trust [to R.A.]; the Medical Research Council Doctoral Training Grant (#RG86932) [H.M.G.]; Pinsent Darwin Award [H.M.G.]; Joachim Herz Foundation Add-on Fellowship in Interdisciplinary Life Sciences [H.M.G.]; MRC grant MR/K004360/1 [S.I.D.], a Marie Sklodowska-Curie COFUND EU-UK Research Fellowship [S.I.D.], a Beatriu de Pinós fellowship (2020 BP 00116) [S.I.D.]; AMO acknowledges support by the Canada Excellence Research Chairs program (215063); LN acknowledges support by the L’Oreal-Unesco for Women in Science Excellence Research Fellowship; ZQL is supported by the Fonds de Recherche du Quebec - Nature et Technologies (FRQNT). Acquisition of the NYU test–retest dataset was funded by Stavros S. Niarchos Foundation, the Leon Lowenstein Foundation, NARSAD (The Mental Health Research Association) grants to F.Xavier Castellanos; and Linda and Richard Schaps, Jill and Bob Smith, and the Taubman Foundation gifts to F. Xavier Castellanos. This work was performed using resources provided by the Cambridge Service for Data Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/T022159/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk). For the purpose of open access, the authors have applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising from this submission.Funder: Fonds de Recherche du Québec - Nature et Technologies (Quebec Fund for Research in Nature and Technology); doi: https://doi.org/10.13039/501100003151Funder: L’Oreal-Unesco for Women in Science Excellence Research FellowshipFunder: EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 Marie Skłodowska-Curie Actions (H2020 Excellent Science - Marie Skłodowska-Curie Actions); doi: https://doi.org/10.13039/100010665Funder: Beatriu de Pinós fellowship (2020 BP 00116)Funder: Canadian Institute for Advanced Research (L'Institut Canadien de Recherches Avancées)Funder: Stephen Erskine Fellowship, Queens’ College, University of CambridgeAbstractFunctional interactions between brain regions can be viewed as a network, enabling neuroscientists to investigate brain function through network science. Here, we systematically evaluate 768 data-processing pipelines for network reconstruction from resting-state functional MRI, evaluating the effect of brain parcellation, connectivity definition, and global signal regression. Our criteria seek pipelines that minimise motion confounds and spurious test-retest discrepancies of network topology, while being sensitive to both inter-subject differences and experimental effects of interest. We reveal vast and systematic variability across pipelines’ suitability for functional connectomics. Inappropriate choice of data-processing pipeline can produce results that are not only misleading, but systematically so, with the majority of pipelines failing at least one criterion. However, a set of optimal pipelines consistently satisfy all criteria across different datasets, spanning minutes, weeks, and months. We provide a full breakdown of each pipeline’s performance across criteria and datasets, to inform future best practices in functional connectomics.</jats:p

Systematic evaluation of fMRI data-processing pipelines for consistent functional connectomics.

Functional interactions between brain regions can be viewed as a network, enabling neuroscientists to investigate brain function through network science. Here, we systematically evaluate 768 data-processing pipelines for network reconstruction from resting-state functional MRI, evaluating the effect of brain parcellation, connectivity definition, and global signal regression. Our criteria seek pipelines that minimise motion confounds and spurious test-retest discrepancies of network topology, while being sensitive to both inter-subject differences and experimental effects of interest. We reveal vast and systematic variability across pipelines' suitability for functional connectomics. Inappropriate choice of data-processing pipeline can produce results that are not only misleading, but systematically so, with the majority of pipelines failing at least one criterion. However, a set of optimal pipelines consistently satisfy all criteria across different datasets, spanning minutes, weeks, and months. We provide a full breakdown of each pipeline's performance across criteria and datasets, to inform future best practices in functional connectomics.This work was supported by the Gates Cambridge Trust (OPP 1144) [AIL]; the Canadian Institute for Advanced Research (CIFAR; grant RCZB/072 RG93193) [to DKM and EAS]; The National Institute for Health Research (NIHR, UK), Cambridge Biomedical Research Centre and NIHR Senior Investigator Awards [DKM]; The British Oxygen Professorship of the Royal College of Anaesthetists [DKM]; The Stephen Erskine Fellowship, Queens’ College, University of Cambridge [EAS]; the Wellcome Trust Research Training Fellowship (grant no. 083660/Z/07/Z), Raymond and Beverly Sackler Studentship, and the Cambridge Commonwealth Trust [to RA]; the Medical Research Council Doctoral Training Grant (#RG86932) [HMG]; Pinsent Darwin Award [HMG]; Joachim Herz Foundation Add-on Fellowship in Interdisciplinary Life Sciences [HMG]; MRC grant MR/K004360/1 [SID], a Marie Sklodowska-Curie COFUND EU-UK Research Fellowship [SID], a Beatriu de Pinós fellowship (2020 BP 00116) [SID]; AMO acknowledges support by the Canada Excellence Research Chairs program (215063); LN acknowledges support by the L’Oreal-Unesco for Women in Science Excellence Research Fellowship; ZQL is supported by the Fonds de Recherche du Quebec - Nature et Technologies (FRQNT). Acquisition of the NYU Test-Retest dataset was funded by Stavros S. Niarchos Foundation, the Leon Lowenstein Foundation, NARSAD (The Mental Health Research Association) grants to F.Xavier Castellanos; and Linda and Richard Schaps, Jill and Bob Smith, and the Taubman Foundation gifts to F. Xavier Castellanos. This work was performed using resources provided by the Cambridge Service for Data Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/T022159/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk)

Paths to Oblivion: Common Neural Mechanisms of Anaesthesia and Disorders of Consciousness

The human brain generates a rich repertoire of spatiotemporal dynamics during normal wakefulness, supporting a wide variety of conscious experiences and cognitive functions. However, neural dynamics are reconfigured, in comparable ways, when consciousness is lost either due to anaesthesia or disorders of consciousness (DOC). Here, leveraging a neurobiologically realistic whole-brain computational model informed by functional MRI, diffusion MRI, and PET, we sought to identify the neurobiological mechanisms that explain the common reconfiguration of neural dynamics observed both for transient pharmacological intervention and chronic neuroanatomical injury. Our results show that, by incorporating local inhibitory action through a PET-based GABA receptor density map, our model can reproduce the brain dynamics of subjects undergoing propofol anaesthesia, and that this effect depends specifically on the spatial distribution of GABA receptors across cortical regions. Additionally, using a structural connectome obtained from DOC patients, we demonstrate how the dynamics that characterise loss of consciousness can emerge from changes in neuroanatomical connectivity. Crucially, we find that each of these two interventions generalises across datasets: a model with increased GABA-mediated inhibition can reproduce the dynamics of DOC patients’ brains, and a model with a DOC connectome is also compatible with brain dynamics observed during propofol anaesthesia. These results demonstrate how increased inhibition and connectome randomisation represent different neurobiological paths towards the characteristic dynamics of the unconscious brain. Overall, the present findings begin to disentangle the neurobiological mechanisms by which highly dissimilar perturbations of the brain’s neurodynamics can lead to unconsciousness

Reduced emergent character of neural dynamics in patients with a disrupted connectome.

High-level brain functions are widely believed to emerge from the orchestrated activity of multiple neural systems. However, lacking a formal definition and practical quantification of emergence for experimental data, neuroscientists have been unable to empirically test this long-standing conjecture. Here we investigate this fundamental question by leveraging a recently proposed framework known as "Integrated Information Decomposition," which establishes a principled information-theoretic approach to operationalise and quantify emergence in dynamical systems - including the human brain. By analysing functional MRI data, our results show that the emergent and hierarchical character of neural dynamics is significantly diminished in chronically unresponsive patients suffering from severe brain injury. At a functional level, we demonstrate that emergence capacity is positively correlated with the extent of hierarchical organisation in brain activity. Furthermore, by combining computational approaches from network control theory and whole-brain biophysical modelling, we show that the reduced capacity for emergent and hierarchical dynamics in severely brain-injured patients can be mechanistically explained by disruptions in the patients' structural connectome. Overall, our results suggest that chronic unresponsiveness resulting from severe brain injury may be related to structural impairment of the fundamental neural infrastructures required for brain dynamics to support emergence

Whole-brain modelling identifies distinct but convergent paths to unconsciousness in anaesthesia and disorders of consciousness.

The human brain entertains rich spatiotemporal dynamics, which are drastically reconfigured when consciousness is lost due to anaesthesia or disorders of consciousness (DOC). Here, we sought to identify the neurobiological mechanisms that explain how transient pharmacological intervention and chronic neuroanatomical injury can lead to common reconfigurations of neural activity. We developed and systematically perturbed a neurobiologically realistic model of whole-brain haemodynamic signals. By incorporating PET data about the cortical distribution of GABA receptors, our computational model reveals a key role of spatially-specific local inhibition for reproducing the functional MRI activity observed during anaesthesia with the GABA-ergic agent propofol. Additionally, incorporating diffusion MRI data obtained from DOC patients reveals that the dynamics that characterise loss of consciousness can also emerge from randomised neuroanatomical connectivity. Our results generalise between anaesthesia and DOC datasets, demonstrating how increased inhibition and connectome perturbation represent distinct neurobiological paths towards the characteristic activity of the unconscious brain.The authors would like to thank all the participants for their contribution to this study. This work was supported by grants from the UK Medical Research Council [U.1055.01.002.00001.01 to AMO and JDP]; The James S. McDonnell Foundation [to AMO and JDP]; and the Canada Excellence Research Chairs program (215063 to AMO); the National Institute for Health Research (NIHR, UK), Cambridge Biomedical Research Centre and NIHR Senior Investigator Awards [to DKM], the Stephen Erskine Fellowship (Queens’ College, Cambridge, to EAS), the Canadian Institute for Advanced Research (CIFAR; grant RCZB/072 RG93193) (to DKM and EAS); the L’Oreal-Unesco for Women in Science Excellence Research Fellowship to LN; the British Oxygen Professorship of the Royal College of Anaesthetists [to DKM]; The Evelyn Trust, Cambridge and the EoE CLAHRC fellowship [JA]; the Gates Cambridge Trust (to AIL); the Cambridge International Trust and the Howard Sidney Sussex Studentship (to MMC); and the Vice-Chancellor Award (to PC). AMO and DKM are Fellows of the CIFAR Brain, Mind, and Consciousness Programme. PAM and DB are funded by the Wellcome Trust (grant no. 210920/Z/18/Z). FR is funded by the Ad Astra Chandaria foundation. Computing infrastructure at the Wolfson Brain Imaging Centre (WBIC-HPHI) was funded by the MRC research infrastructure award (MR/M009041/1). The research was also supported by the NIHR Brain Injury Healthcare Technology Co-operative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge

Selective Thalamic Neuronal Loss in Chronic Traumatic Brain Injury: Outcome Associations and Mechanisms

Importance: The chronic neuronal burden of traumatic brain injury (TBI) is not fully characterised by routine imaging, limiting our understanding of the neuronal substrates underlying adverse outcome. Objective: To determine whether otherwise ‘healthy’ tissue on routine imaging can be investigated for selective neuronal loss using 11C-flumazenil positron emission tomography (FMZ PET), with relevance to long-term outcome. Design: Cross-sectional study with data collected between September 2004 - May 2021, analysed in 2023. Setting: Multicentre data collected prospectively from two centres – Cambridge (UK) and Weill Cornell Medicine (USA). Participants: TBI patients (>6 months post-injury) were compared to healthy volunteers. All were >18 years of age and exclusion criteria were neurological disease, benzodiazepines, or MRI contraindication. Data were retrospectively collated with non-consecutive recruitment, driven by convenience, and scanner/PET ligand availability. Exposure: Flumazenil voxel-wise binding potential relative to non-displaceable distribution volume (BPND). Main Outcome(s) and Measure(s): Selective neuronal loss identified with FMZ PET was compared between groups on voxelwise and regional scales, and related to functional, cognitive, and psychological outcomes. Diffusion-tensor imaging further related regions of cortical damage to regions of thalamic selective neuronal loss. Results: Twenty-four patients with chronic TBI (mean[SD] age: 39.2[12.3] years, 18 male (75.0%), median[range] months post-injury: 29[7 – 95]) compared to 33 healthy controls (47.6[20.5] years, 23 male (69.7%)) underwent FMZ PET. TBI patients displayed selective neuronal loss in thalamic nuclei, over and above gross volume loss, across a wide range of injury severities. Neuronal loss associated with worse functional outcome using the Glasgow Outcome Scale, worse cognitive outcome on measures of sustained executive attention, and worse emotional outcome using the 36-Item Short Form Health Survey. Chronic thalamic neuronal loss partially mirrored the location of primary cortical contusions, which may indicate secondary injury mechanisms of transneuronal degeneration. Conclusions and Relevance: We propose that selective thalamic vulnerability perpetuates into chronic neuronal consequences with relevance to long-term outcome, substantiating the evolving and potentially lifelong thalamic neuronal consequences of TBI. Flumazenil PET is a more sensitive marker of the burden of neuronal injury than routine imaging, could inform outcome prognostication, and lead to the development of individualised precision medicine approaches.Medical Research Council (MRC) Doctoral Training Programme Grant MR N013433-1 (REW) NIHR Cambridge Biomedical Research Centre BRC-1215-20014 (JPC) Academy of Medical Sciences/Health Foundation Clinician Scientist Fellowship (JPC) NIH 1R01NS102646-01A1 (SAS, NDS) National Center for Advancing Translational Sciences UL1TR002384 (SAS) Stephen Erskine Fellowship at Queens’ College, Cambridge (EAS) Canadian Institute for Advanced Research (EAS, DKM) British Oxygen Professorship of the Royal College of Anaesthetists (DKM) NIHR Senior Investigator Awards (DKM) Medical Research Council UK (DKM, JPC, TDF) Société Française d'Anesthésie et de Réanimation (TG

Dopaminergic brainstem disconnection is common to pharmacological and pathological consciousness perturbation.

Clinical research into consciousness has long focused on cortical macroscopic networks and their disruption in pathological or pharmacological consciousness perturbation. Despite demonstrating diagnostic utility in disorders of consciousness (DoC) and monitoring anesthetic depth, these cortico-centric approaches have been unable to characterize which neurochemical systems may underpin consciousness alterations. Instead, preclinical experiments have long implicated the dopaminergic ventral tegmental area (VTA) in the brainstem. Despite dopaminergic agonist efficacy in DoC patients equally pointing to dopamine, the VTA has not been studied in human perturbed consciousness. To bridge this translational gap between preclinical subcortical and clinical cortico-centric perspectives, we assessed functional connectivity changes of a histologically characterized VTA using functional MRI recordings of pharmacologically (propofol sedation) and pathologically perturbed consciousness (DoC patients). Both cohorts demonstrated VTA disconnection from the precuneus and posterior cingulate (PCu/PCC), a main default mode network node widely implicated in consciousness. Strikingly, the stronger VTA-PCu/PCC connectivity was, the more the PCu/PCC functional connectome resembled its awake configuration, suggesting a possible neuromodulatory relationship. VTA-PCu/PCC connectivity increased toward healthy control levels only in DoC patients who behaviorally improved at follow-up assessment. To test whether VTA-PCu/PCC connectivity can be affected by a dopaminergic agonist, we demonstrated in a separate set of traumatic brain injury patients without DoC that methylphenidate significantly increased this connectivity. Together, our results characterize an in vivo dopaminergic connectivity deficit common to reversible and chronic consciousness perturbation. This noninvasive assessment of the dopaminergic system bridges preclinical and clinical work, associating dopaminergic VTA function with macroscopic network alterations, thereby elucidating a critical aspect of brainstem-cortical interplay for consciousness.This work was supported by a grant from the Wellcome Trust: Clinical Research Training Fellowship [to R.A.] (Contract grant number: 083660/Z/07/Z). The work was also supported by grants from the UK Medical Research Council (U.1055.01.002.00001.01) [to J.D.P.]; The James S. McDonnell Foundation [to J.D.P.]; The Canadian Institute for Advanced Research (CIFAR) [to D.K.M. and E.A.S.]; The National Institute for Health Research (NIHR, UK), Cambridge Biomedical Research Centre and NIHR Senior Investigator Awards [to J.D.P. and D.K.M.]; The British Oxygen Professorship of the Royal College of Anaesthetists [to D.K.M.]; The Cambridge International Trust and the Cambridge European Scholarship [to LRBS.]; The Evelyn Trust, Cambridge and the EoE CLAHRC fellowship [to J.A.]; The Stephen Erskine Fellowship, Queens’ College, University of Cambridge [to E.A.S.] and the Gates Cambridge Trust [to A.I.L.]. The research was also supported by the NIHR Brain Injury Healthcare Technology Cooperative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge. Computing infrastructure at the Wolfson Brain Imaging Centre. (WBIC-HPHI) was funded by MRC research infrastructure award (MR/M009041/1)

Distributed harmonic patterns of structure-function dependence orchestrate human consciousness

A central question in neuroscience is how consciousness arises from the dynamic interplay of brain structure and function. Here we decompose functional MRI signals from pathological and pharmacologically-induced perturbations of consciousness into distributed patterns of structure-function dependence across scales: the harmonic modes of the human structural connectome. `We show that structure-function coupling is a generalisable indicator of consciousness that is under bi-directional neuromodulatory control. We find increased structure-function coupling across scales during loss of consciousness, whether due to anaesthesia or brain injury, capable of discriminating between behaviourally indistinguishable sub-categories of brain-injured patients, tracking the presence of covert consciousness. The opposite harmonic signature characterises the altered state induced by LSD or ketamine, reflecting psychedelic-induced decoupling of brain function from structure and correlating with physiological and subjective scores. Overall, connectome harmonic decomposition reveals how neuromodulation and the network architecture of the human connectome jointly shape consciousness and distributed functional activation across scales.AIL, JV and PAMM would like to thank Lena Dorfschmidt for co-organising OxBridge BrainHack 2019, where this work began. We also thank all volunteers and patients who provided data. This work was supported by grants from The Wellcome Trust Research Training Fellowship (grant no. 083660/Z/07/Z), Raymond and Beverly Sackler Studentship, and the Cambridge Commonwealth Trust [RA]; the UK Medical Research Council (U.1055.01.002.00001.01) [JDP]; The James S. McDonnell Foundation [JDP]; the Canadian Institute for Advanced Research (CIFAR; grant RCZB/072 RG93193) [to DKM and EAS]; The National Institute for Health Research (NIHR, UK), Cambridge Biomedical Research Centre and NIHR Senior Investigator Awards [JDP and DKM]; The British Oxygen Professorship of the Royal College of Anaesthetists [DKM]; The Stephen Erskine Fellowship, Queens’ College, University of Cambridge [EAS]; The Evelyn Trust, Cambridge and the EoE CLAHRC fellowship [JA]; The Gates Cambridge Trust [AIL]; The Cambridge International Trust and the Howard Sidney Sussex Studentship [MMC]; The Oon Khye Beng Ch'Hia Tsio Studentship for Research in Preventive Medicine, Downing College, University of Cambridge [IP]; The Wellcome Trust (grant no. 210920/Z/18/Z) [PAMM]; The European Research Council Consolidator Grant CAREGIVING (615539) [MLK and SA]; The Center for Music in the Brain, funded by the Danish National Research Foundation (DNRF117) [MLK, SA and JV]; The Centre for Eudaimonia and Human Flourishing, funded by the Pettit and Carlsberg Foundations [MLK]; The Imperial College President’s Scholarship [LR]; The Alex Mosley Charitable Trust [RLCH]; The ketamine study was funded by the Bernard Wolfe Health Neuroscience Fund and the Wellcome Trust. The original LSD study received support from a Crowd Funding Campaign and the Beckley Foundation, as part of the Beckley-Imperial Research Programme. The research was also supported by the NIHR Brain Injury Healthcare Technology Co-operative based at Cambridge University Hospitals NHS Foundation Trust and University of Cambridge. Data used to obtain the human connectome were provided by the Human Connectome Project, WU-Minn Consortium (Principal Investigators: David Van Essen and Kamil Ugurbil; 1U54MH091657) funded by the 16 NIH Institutes and Centers that support the NIH Blueprint for Neuroscience Research; and by the McDonnell Center for Systems Neuroscience at Washington University. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

In vivo mapping of pharmacologically induced functional reorganization onto the human brain's neurotransmitter landscape.

To understand how pharmacological interventions can exert their powerful effects on brain function, we need to understand how they engage the brain's rich neurotransmitter landscape. Here, we bridge microscale molecular chemoarchitecture and pharmacologically induced macroscale functional reorganization, by relating the regional distribution of 19 neurotransmitter receptors and transporters obtained from positron emission tomography, and the regional changes in functional magnetic resonance imaging connectivity induced by 10 different mind-altering drugs: propofol, sevoflurane, ketamine, lysergic acid diethylamide (LSD), psilocybin, N,N-Dimethyltryptamine (DMT), ayahuasca, 3,4-methylenedioxymethamphetamine (MDMA), modafinil, and methylphenidate. Our results reveal a many-to-many mapping between psychoactive drugs' effects on brain function and multiple neurotransmitter systems. The effects of both anesthetics and psychedelics on brain function are organized along hierarchical gradients of brain structure and function. Last, we show that regional co-susceptibility to pharmacological interventions recapitulates co-susceptibility to disorder-induced structural alterations. Collectively, these results highlight rich statistical patterns relating molecular chemoarchitecture and drug-induced reorganization of the brain's functional architecture.Gates Cambridge Trust (OPP 1144) [to AIL]; Wellcome Trust Research Training Fellowship (grant no. 083660/Z/07/Z), Raymond and Beverly Sackler Studentship, and the Cambridge Commonwealth Trust [to RA]; Canadian Institute for Advanced Research (CIFAR; grant RCZB/072 RG93193) [to DKM and EAS]; Cambridge Biomedical Research Centre and NIHR Senior Investigator Awards and the British Oxygen Professorship of the Royal College of Anaesthetists [to DKM]; Stephen Erskine Fellowship at Queens’ College, Cambridge [to EAS]; Natural Sciences and Engineering Research Council of Canada (NSERC Discovery Grant RGPIN #017-04265) and Canada Research Chairs Program [to BM]; Helmholtz International BigBrain Analytics & Learning Laboratory, the Natural Sciences 1435 and Engineering Research Council of Canada, and Fonds de reserches de Québec [to JYH]; Canada Excellence Research Chairs program (215063) [to AMO]; L’Oreal-Unesco for Women in Science Excellence Research Fellowship to LN]; Imperial College President’s Scholarship [to LR]; Belgian National Funds for Scientific Research (F.R.S-FNRS) [to PC and NLNA]; GIGA-Doctoral School for Health Sciences (University of Liège) [to PC]; Human Brain Project [to NLNA]; Italian Department of Education [Fondo per gli Investimenti della Ricerca di Base (FIRB) 2003; Programmi di Ricerca di Rilevante Interesse nazionale (PRIN) 2008 [to SLS]; Alex Mosley Charitable Trust and supporters of the Centre for Psychedelic Research, Ralph Metzner Distinguished Professorship at UCSF [to RLC-H]