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Modelling brain dysconnectivity in rodents

  • Alessandro Gozzi
    Correspondence
    Correspondence: Dr. Alessandro Gozzi, Functional Neuroimaging Laboratory, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems @ UNITN , Corso Bettini 31, 38068 Rovereto, Italy, Phone: +39 0464 808 701
    Affiliations
    Functional Neuroimaging Lab, Istituto Italiano di Tecnologia, Center for Neuroscience and Cognitive Systems, Rovereto, Italy
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  • Valerio Zerbi
    Correspondence
    Correspondence: Dr. Valerio Zerbi, Brain Network Physiology Lab, School of Engineering (STI), Neuro-X institute (INX), EPFL, Lausanne, Switzerland, Center for Biomedical Imaging (CIBM), Lausanne, Switzerland, CH F0 582 (Bâtiment CH), Station 6 CH-1015 LausanneCH-1015 Lausanne Phone: +41 2169 30810
    Affiliations
    Brain Network Physiology Lab, School of Engineering (STI), Neuro-X institute (INX), EPFL, Lausanne, Switzerland

    CIBM Center for Biomedical Imaging, Lausanne, Switzerland
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Open AccessPublished:September 15, 2022DOI:https://doi.org/10.1016/j.biopsych.2022.09.008

      Abstract

      Altered or atypical functional connectivity as measured with fMRI is a hallmark feature of brain connectopathy in psychiatric, developmental, and neurological disorders. However, the biological underpinnings and etiopathological significance of this phenomenon remain unclear. The recent development of MRI-based techniques for mapping brain function in rodents provides a powerful platform to uncover the determinants of functional (dys)connectivity, whether they are genetic mutations, environmental risk factors or specific cellular and circuit dysfunctions. Here, we summarize the recent contribution of rodent functional MRI towards to a deeper understanding of network dysconnectivity in developmental and psychiatric disorders. We highlight substantial correspondences in the spatio-temporal organization of rodent and human fMRI networks, supporting the translational relevance of this approach. We then show how this research platform might help us comprehend the importance of connectional heterogeneity in complex brain disorders and causally relate multi-scale pathogenic contributors to functional dysconnectivity patterns. Finally, we explore how perturbational techniques can be used to dissect the fundamental aspects of fMRI coupling and reveal the causal contribution of neuromodulatory systems to macroscale network activity, as well as its altered dynamics in brain diseases. These examples outline how rodent functional imaging is poised to advance our understanding of the bases and determinants of human functional dysconnectivity.

      Keywords

      Studying the dysconnected brain

      Over the past three decades, progress in functional neuroimaging methods such as fMRI has been instrumental in assessing the landscape of brain network dysfunction in psychiatric disorders. The recent deployment of computational tools and resources for sharing and processing large datasets has further accelerated the transition from small-scale proof-of-concept studies in selected patient cohorts to initiatives aimed at assessing the extent and manifestation of network dysfunction in larger patient populations. The Autism Brain Imaging Data Exchange(
      • Di Martino A.
      • Yan C.G.
      • Li Q.
      • Denio E.
      • Castellanos F.X.
      • Alaerts K.
      • et al.
      The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.
      ), the Attention-Deficit Hyperactivity Disorder (ADHD)-200 consortium(
      • Milham P.M.
      • Damien F.
      • Maarten M.
      • Stewart H.M.
      The ADHD-200 Consortium: A model to advance the translational potential of neuroimaging in clinical neuroscience.
      ), ENIGMA(3) and the UK Biobank(
      • Miller K.L.
      • Alfaro-Almagro F.
      • Bangerter N.K.
      • Thomas D.L.
      • Yacoub E.
      • Xu J.
      • et al.
      Multimodal population brain imaging in the UK Biobank prospective epidemiological study.
      ) are examples of such large-scale endeavors. There is now great hope that these initiatives will help better pinpoint and categorize disruption of brain networks in psychiatric conditions(
      • Deco G.
      • Kringelbach M.L.
      Great expectations: using whole-brain computational connectomics for understanding neuropsychiatric disorders.
      ), possibly providing objective imaging markers that can distinguish a diseased state from a normal one - a long-term quest of neuropsychiatric imaging(
      • Turner J.A.
      The rise of large-scale imaging studies in psychiatry.
      ).
      However, understanding the biological and etiopathological significance of aberrant connectivity in mental illnesses is a non-trivial problem that is unlikely to be solved simply by aggregating more and more data. While it has been possible to demonstrate the presence of altered or atypical connectivity in most of these disorders at the population level, albeit with great variability at the individual level, the biological determinants and mechanistic significance of these deficits remain largely unknown. Moreover, human neuroimaging methods provide a snapshot of functional activity at the macroscale, but do not allow to probe pathophysiological mechanisms occurring at a finer investigational scale. This results in a wide explanatory gap between models of brain (dys)function at the cellular mesoscopic scale (i.e., receptor or neuronal dysfunction, excitatory/inhibitory imbalance, miswiring or circuit alterations) and the corresponding system-level measurement of brain function and connectivity. For these reasons, it is not yet clear what it means when specific brain functional connections in a psychiatric condition are weakened, altered, or deviate from the corresponding measure in control “healthy” populations. The consequence is that imaging techniques in psychiatric and developmental disorders are still widely regarded as general imaging markers of endophenotypes, often devoid of true diagnostic, etiopathological or mechanistic significance.
      In this review, we argue that investigational approaches that allow for causally testing mechanistic hypotheses and bridging investigational scales beyond what is currently possible in human research can clarify the significance and multifactorial origin of brain dysconnectivity in mental disorders. Preclinical application of functional MRI in animal models, such as rodents, gives a chance to fill this gap. By incorporating targeted and causally explainable perturbations into the same fMRI paradigms used in human investigations, rodent connectivity mapping is rapidly becoming a key tool for modeling, examining, and comparing network signatures found in human brain disorders(
      • Mandino F.
      • Cerri D.H.
      • Garin C.M.
      • Straathof M.
      • van Tilborg G.A.F.
      • Chakravarty M.M.
      • et al.
      Animal Functional Magnetic Resonance Imaging: Trends and Path Toward Standardization.
      ,
      • Pais-Roldán P.
      • Mateo C.
      • Pan W.-J.
      • Acland B.
      • Kleinfeld D.
      • Snyder L.H.
      • et al.
      Contribution of animal models toward understanding resting state functional connectivity.
      ). Furthermore, compared to humans, there is an abundance of high-resolution whole brain physiological data(
      • Fulcher B.D.
      • Murray J.D.
      • Zerbi V.
      • Wang X.-J.
      Multimodal gradients across mouse cortex.
      ), including direct tract tracing axonal connectivity data(
      • Oh S.W.
      • Harris J.A.
      • Ng L.
      • Winslow B.
      • Cain N.
      • Mihalas S.
      • et al.
      A mesoscale connectome of the mouse brain.
      ,
      • Harris J.A.
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      • Hirokawa K.E.
      • Whitesell J.D.
      • Choi H.
      • Bernard A.
      • et al.
      Hierarchical organization of cortical and thalamic connectivity.
      ,
      • Hintiryan H.
      • Foster N.N.
      • Bowman I.
      • Bay M.
      • Song M.Y.
      • Gou L.
      • et al.
      The mouse cortico-striatal projectome.
      ,
      • Coletta L.
      • Pagani M.
      • Whitesell J.D.
      • Harris J.A.
      • Bernhardt B.
      • Gozzi A.
      Network structure of the mouse brain connectome with voxel resolution.
      ) high-resolution gene expression maps(
      • Lein E.S.
      • Hawrylycz M.J.
      • Ao N.
      • Ayres M.
      • Bensinger A.
      • Bernard A.
      • et al.
      Genome-wide atlas of gene expression in the adult mouse brain.
      ) and cell density atlases(
      • Kim Y.
      • Yang G.R.
      • Pradhan K.
      • Venkataraju K.U.
      • Bota M.
      • García del Molino L.C.
      • et al.
      Brain-wide Maps Reveal Stereotyped Cell-Type-Based Cortical Architecture and Subcortical Sexual Dimorphism.
      ,
      • Erö C.
      • Gewaltig M.-O.
      • Keller D.
      • Markram H.
      A Cell Atlas for the Mouse Brain.
      ). This allows to examine and compare macroscopic network metrics with fundamental biological aspects of the brain, addressing the need to reconcile data on brain cellular mechanisms in rodent models with theories of brain network function from human imaging.
      This review is organized as follows. To begin, we briefly go over the technical considerations for acquiring resting-state connectivity fMRI signals in rodents, as well as current initiatives aimed at creating common platforms for data acquisition, processing, and sharing. We discuss strategies for building rodent-to-human translation based on encouraging correspondences in network organization across species. Next, we illustrate how rodent fMRI can be used to generate and test mechanistic hypothesis concerning the origin and significance of functional brain dysconnectivity in psychiatric illnesses. Finally, we review (pre)clinical fMRI research that has looked at ascending neuromodulatory systems and their impact on brain connectivity by offering the reader insight into how these mechanisms are relevant to the interpretation of connectivity aberrations in mental disorders. Our review is intended for both specialists and non-experts in the fields of psychiatry, neuroscience, and neuroimaging who want to learn about the outstanding topics that rodent fMRI aims to investigate (Table1).
      Table 1Technical/methodological challenges in the field of rodent fMRI
      Key Technical and Methodological ChallengesTranslational ImplicationsCurrent or future workarounds / mitigation strategiesSelected References
      Consensus atlas and naming convention of functional networks in the rodent brainUnclear referencing poses significant limits to study the physiology of cortical and subcortical networks and extrapolate findings across species.- Large data sharing initiatives towards consensus papers.

      - Cross-species investigations into the phylogenetic trajectory of cortical and subcortical areas across evolution.
      (
      • Lu H.
      • Zou Q.
      • Gu H.
      • Raichle M.E.
      • Stein E.A.
      • Yang Y.
      Rat brains also have a default mode network.
      ,
      • Gozzi A.
      • Schwarz A.J.
      Large-scale functional connectivity networks in the rodent brain.
      ,
      • Grandjean J.
      • Canella C.
      • Anckaerts C.
      • Ayrancı G.
      • Bougacha S.
      • Bienert T.
      • et al.
      Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.
      ,
      • Mars R.B.
      • Verhagen L.
      • Gladwin T.E.
      • Neubert F.-X.
      • Sallet J.
      • Rushworth M.F.S.
      Comparing brains by matching connectivity profiles.
      ,
      • Milham M.
      • Petkov C.I.
      • Margulies D.S.
      • Schroeder C.E.
      • Basso M.A.
      • Belin P.
      • et al.
      Accelerating the Evolution of Nonhuman Primate Neuroimaging.
      ,
      • Whitesell J.D.
      • Liska A.
      • Coletta L.
      • Hirokawa K.E.
      • Bohn P.
      • Williford A.
      • et al.
      Regional, Layer, and Cell-Type-Specific Connectivity of the Mouse Default Mode Network.
      )
      Unclear rodent-human homology across functional networks- Lack of direct correspondence between networks limits application of cross-species fMRI

      - Caution in extrapolating results to clinical populations is required
      - Standardized analyses tools across species

      - Analogous stimulation paradigms in rodents and humans

      - Testing homologous fMRI results with biologically measurable parameters (e.g. gene expression data)

      - Cross-species investigations into the phylogenetic trajectory of cortical and subcortical areas across evolution.
      (
      • Fulcher B.D.
      • Murray J.D.
      • Zerbi V.
      • Wang X.-J.
      Multimodal gradients across mouse cortex.
      ,
      • Balsters J.H.
      • Zerbi V.
      • Sallet J.
      • Wenderoth N.
      • Mars R.B.
      Primate homologs of mouse cortico-striatal circuits.
      ,
      • Xu N.
      • LaGrow T.J.
      • Anumba N.
      • Lee A.
      • Zhang X.
      • Yousefi B.
      • et al.
      Functional Connectivity of the Brain Across Rodents and Humans.
      ,

      Mars RB, Sotiropoulos SN, Passingham RE, Sallet J, Verhagen L, Khrapitchev AA, et al. (2018): Whole brain comparative anatomy using connectivity blueprints. eLife. https://doi.org/10.7554/eLife.35237

      )
      Use of light anesthesia in rodent imaging- Potential confounding effects on neurovascular coupling

      - Para-physiological states can affect brain connectivity

      - Interaction with genetic-background or stimulation protocols

      - Impossibility of doing task-based fMRI

      - Unknown state-dependent effect of neural or genetic manipulations

      - Difficulties in conducting longitudinal studies because recurrent anesthesia is required
      - Online monitoring physiological parameters

      - Use of mechanical ventilation and measures to control for hypercapnia/hyperoxia combined with continuous infusion of low-dose anesthetics

      - Standardization of fMRI protocols

      - Offline probing of genotype-dependent sensitivity to anesthesia

      - Combination of fMRI with multielectrode neural recordings to establish neural rhythms underlying coupling

      - Replication of findings across multiple anesthetic regimes or awake conditions
      (
      • Grandjean J.
      • Schroeter A.
      • Batata I.
      • Rudin M.
      Optimization of anesthesia protocol for resting-state fMRI in mice based on differential effects of anesthetics on functional connectivity patterns.
      ,
      • Grandjean J.
      • Canella C.
      • Anckaerts C.
      • Ayrancı G.
      • Bougacha S.
      • Bienert T.
      • et al.
      Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.
      ,
      • Reimann H.M.
      • Niendorf T.
      The (Un)Conscious Mouse as a Model for Human Brain Functions: Key Principles of Anesthesia and Their Impact on Translational Neuroimaging.
      ,
      • Bertero A.
      • Liska A.
      • Pagani M.
      • Parolisi R.
      • Masferrer M.E.
      • Gritti M.
      • et al.
      Autism-associated 16p11.2 microdeletion impairs prefrontal functional connectivity in mouse and human.
      ,
      • Rocchi F.
      • Canella C.
      • Noei S.
      • Gutierrez-Barragan D.
      • Coletta L.
      • Galbusera A.
      • et al.
      Increased fMRI connectivity upon chemogenetic inhibition of the mouse prefrontal cortex.
      ,
      • Paasonen J.
      • Stenroos P.
      • Salo R.A.
      • Kiviniemi V.
      • Gröhn O.
      Functional connectivity under six anesthesia protocols and the awake condition in rat brain.
      )
      Stress associated with awake proceduresState-dependent connectivity bias between animals and humans- Reliable habituation protocols on multiple days (weeks)

      - Control for stress levels (e.g. corticosterone)
      (
      • Ferris C.F.
      Applications in Awake Animal Magnetic Resonance Imaging.
      ,
      • Gutierrez-Barragan D.
      • Singh N.A.
      • Alvino F.G.
      • Coletta L.
      • Rocchi F.
      • De Guzman E.
      • et al.
      Unique spatiotemporal fMRI dynamics in the awake mouse brain.
      ,
      • King J.A.
      • Garelick T.S.
      • Brevard M.E.
      • Chen W.
      • Messenger T.L.
      • Duong T.Q.
      • Ferris C.F.
      Procedure for minimizing stress for fMRI studies in conscious rats.
      ,
      • Madularu D.
      • Mathieu A.P.
      • Kumaragamage C.
      • Reynolds L.M.
      • Near J.
      • Flores C.
      • Rajah M.N.
      A non-invasive restraining system for awake mouse imaging.
      ,
      • Chang P.-C.
      • Procissi D.
      • Bao Q.
      • Centeno M.V.
      • Baria A.
      • Apkarian A.V.
      Novel method for functional brain imaging in awake minimally restrained rats.
      ,
      • Russo G.
      • Helluy X.
      • Behroozi M.
      • Manahan-Vaughan D.
      Gradual Restraint Habituation for Awake Functional Magnetic Resonance Imaging Combined With a Sparse Imaging Paradigm Reduces Motion Artifacts and Stress Levels in Rodents.
      ,
      • Stenroos P.
      • Paasonen J.
      • Salo R.A.
      • Jokivarsi K.
      • Shatillo A.
      • Tanila H.
      • Gröhn O.
      Awake rat brain functional magnetic resonance imaging using standard radio frequency coils and a 3D printed restraint kit.
      )
      Lack of consensus on rodent and human common data acquisition, preprocessing and analyses pipelinesUnclear effects of data (pre)processing and acquisition on fMRI connectivity and connectivity changesLarge data sharing initiatives will engage towards standardization of the best practice for acquisition.(
      • Mandino F.
      • Cerri D.H.
      • Garin C.M.
      • Straathof M.
      • van Tilborg G.A.F.
      • Chakravarty M.M.
      • et al.
      Animal Functional Magnetic Resonance Imaging: Trends and Path Toward Standardization.
      ,
      • Zerbi V.
      • Grandjean J.
      • Rudin M.
      • Wenderoth N.
      Mapping the mouse brain with rs-fMRI: An optimized pipeline for functional network identification.
      ,
      • Grandjean J.
      • Canella C.
      • Anckaerts C.
      • Ayrancı G.
      • Bougacha S.
      • Bienert T.
      • et al.
      Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.
      ,
      • Grandjean J.
      StandardRat: A multi-center consensus protocol to enhance functional connectivity specificity in the rat brain.
      ,
      • Ioanas H.-I.
      • Marks M.
      • Zerbi V.
      • Yanik M.F.
      • Rudin M.
      An optimized registration workflow and standard geometric space for small animal brain imaging.
      )
      Rodent imaging studies tend to be minimally powered due to strict ethics requirements (3Rs)May limited reproducibility of rodent research

      Limited brain-behavior inference.
      - Multi-center data sharing initiatives

      - Larger emphasis for independent replication of rodent fMRI studies

      - Apply strict protocols to control for variables of no interest (standardization)
      (
      • Grandjean J.
      • Canella C.
      • Anckaerts C.
      • Ayrancı G.
      • Bougacha S.
      • Bienert T.
      • et al.
      Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.
      ,
      • Grandjean J.
      StandardRat: A multi-center consensus protocol to enhance functional connectivity specificity in the rat brain.
      ,
      • Zerbi V.
      • Pagani M.
      • Markicevic M.
      • Matteoli M.
      • Pozzi D.
      • Fagiolini M.
      • et al.
      Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes.
      )
      Unclear physiological meaning of fMRI connectivity changes in animal modelsfMRI connectivity changes often relegated as “endophenotype” of unknown biological origin in animal studies- Stronger focus on multimodal recordings and manipulations in rodents(
      • Keilholz S.D.
      • Pan W.-J.
      • Billings J.
      • Nezafati M.
      • Shakil S.
      Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies.
      ,
      • Zerbi V.
      • Pagani M.
      • Markicevic M.
      • Matteoli M.
      • Pozzi D.
      • Fagiolini M.
      • et al.
      Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes.
      ,
      • Rocchi F.
      • Canella C.
      • Noei S.
      • Gutierrez-Barragan D.
      • Coletta L.
      • Galbusera A.
      • et al.
      Increased fMRI connectivity upon chemogenetic inhibition of the mouse prefrontal cortex.
      ,
      • Grimm C.
      • Frässle S.
      • Steger C.
      • von Ziegler L.
      • Sturman O.
      • Shemesh N.
      • et al.
      Optogenetic activation of striatal D1R and D2R cells differentially engages downstream connected areas beyond the basal ganglia.
      ,
      • Oyarzabal E.A.
      • Hsu L.-M.
      • Das M.
      • Chao T.-H.H.
      • Zhou J.
      • Song S.
      • et al.
      Chemogenetic stimulation of tonic locus coeruleus activity strengthens the default mode network.
      ,
      • Lake E.M.R.
      • Ge X.
      • Shen X.
      • Herman P.
      • Hyder F.
      • Cardin J.A.
      • et al.
      Simultaneous cortex-wide fluorescence Ca2+ imaging and whole-brain fMRI.
      )
      MRI is an expensive and technically challenging method inaccessible to many groupsLimited scope of application of the technique for technical or economic reasons- Increased access to large-scale facilities

      - Inter-lab training groups and rotation

      - Data and code-sharing sharing
      (
      • Grandjean J.
      • Canella C.
      • Anckaerts C.
      • Ayrancı G.
      • Bougacha S.
      • Bienert T.
      • et al.
      Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.
      ,
      • Grandjean J.
      StandardRat: A multi-center consensus protocol to enhance functional connectivity specificity in the rat brain.
      )

      Functional connectivity MRI in rodents: technical considerations and perspectives

      Recent reviews have summarized the history and development of rodent fMRI, which are an excellent resource for the interested reader(
      • Mandino F.
      • Cerri D.H.
      • Garin C.M.
      • Straathof M.
      • van Tilborg G.A.F.
      • Chakravarty M.M.
      • et al.
      Animal Functional Magnetic Resonance Imaging: Trends and Path Toward Standardization.
      ,
      • Markicevic M.
      • Savvateev I.
      • Grimm C.
      • Zerbi V.
      Emerging imaging methods to study whole-brain function in rodent models.
      ,
      • Gorges M.
      • Roselli F.
      • Müller H.-P.
      • Ludolph A.C.
      • Rasche V.
      • Kassubek J.
      Functional Connectivity Mapping in the Animal Model: Principles and Applications of Resting-State fMRI.
      ). The first attempts to map fMRI connectivity in rodents date back to over 15 years, and they were met with mixed and often contradictory results(
      • Jonckers E.
      • Van Audekerke J.
      • De Visscher G.
      • Van der Linden A.
      • Verhoye M.
      Functional Connectivity fMRI of the Rodent Brain: Comparison of Functional Connectivity Networks in Rat and Mouse ((I. Sugihara, editor)).
      ,
      • Hutchison R.M.
      • Mirsattari S.M.
      • Jones C.K.
      • Gati J.S.
      • Leung L.S.
      Functional Networks in the Anesthetized Rat Brain Revealed by Independent Component Analysis of Resting-State fMRI.
      ,
      • Zhang N.
      • Rane P.
      • Huang W.
      • Liang Z.
      • Kennedy D.
      • Frazier J.A.
      • King J.
      Mapping resting-state brain networks in conscious animals.
      ,
      • Pawela C.P.
      • Biswal B.B.
      • Cho Y.R.
      • Kao D.S.
      • Li R.
      • Jones S.R.
      • et al.
      Resting-state functional connectivity of the rat brain.
      ). Leveraging advancements in MR hardware, optimized control of motion artefacts and physiological parameters(
      • Ferrari L.
      • Turrini G.
      • Crestan V.
      • Bertani S.
      • Cristofori P.
      • Bifone A.
      • Gozzi A.
      A robust experimental protocol for pharmacological fMRI in rats and mice.
      ), as well as improved image analyses pipeline, a second wave of investigations revealed the possibility of reliably mapping networks in rats(
      • Lu H.
      • Zou Q.
      • Gu H.
      • Raichle M.E.
      • Stein E.A.
      • Yang Y.
      Rat brains also have a default mode network.
      ,
      • Pawela C.P.
      • Biswal B.B.
      • Hudetz A.G.
      • Schulte M.L.
      • Li R.
      • Jones S.R.
      • et al.
      A protocol for use of medetomidine anesthesia in rats for extended studies using task-induced BOLD contrast and resting-state functional connectivity.
      ,
      • van Meer M.P.A.
      • Otte W.M.
      • van der Marel K.
      • Nijboer C.H.
      • Kavelaars A.
      • van der Sprenkel J.W.B.
      • et al.
      Extent of Bilateral Neuronal Network Reorganization and Functional Recovery in Relation to Stroke Severity.
      ) and mice(
      • Zerbi V.
      • Grandjean J.
      • Rudin M.
      • Wenderoth N.
      Mapping the mouse brain with rs-fMRI: An optimized pipeline for functional network identification.
      ,
      • Sforazzini F.
      • Schwarz A.J.
      • Galbusera A.
      • Bifone A.
      • Gozzi A.
      Distributed BOLD and CBV-weighted resting-state networks in the mouse brain.
      ,
      • Grandjean J.
      • Schroeter A.
      • Batata I.
      • Rudin M.
      Optimization of anesthesia protocol for resting-state fMRI in mice based on differential effects of anesthetics on functional connectivity patterns.
      ,
      • Zhan Y.
      • Paolicelli R.C.
      • Sforazzini F.
      • Weinhard L.
      • Bolasco G.
      • Pagani F.
      • et al.
      Deficient neuron-microglia signaling results in impaired functional brain connectivity and social behavior.
      ).
      Fast-forwarding to 2022, the field has matured and has begun to provide answers to initial uncertainties. For example, divergences between animal preparation, anesthesia, data acquisition, and processing were found to underlie a number of disagreements within the animal functional neuroimaging community, such as the nature of rest unilateral versus bilateral resting-state networks (RSN) in mice(
      • Jonckers E.
      • Van Audekerke J.
      • De Visscher G.
      • Van der Linden A.
      • Verhoye M.
      Functional Connectivity fMRI of the Rodent Brain: Comparison of Functional Connectivity Networks in Rat and Mouse ((I. Sugihara, editor)).
      ,
      • Zerbi V.
      • Grandjean J.
      • Rudin M.
      • Wenderoth N.
      Mapping the mouse brain with rs-fMRI: An optimized pipeline for functional network identification.
      ,
      • Sforazzini F.
      • Schwarz A.J.
      • Galbusera A.
      • Bifone A.
      • Gozzi A.
      Distributed BOLD and CBV-weighted resting-state networks in the mouse brain.
      ,
      • Mechling A.E.
      • Hübner N.S.
      • Lee H.-L.
      • Hennig J.
      • von Elverfeldt D.
      • Harsan L.-A.
      Fine-grained mapping of mouse brain functional connectivity with resting-state fMRI.
      ), or the existence of RSNs of translational relevance, such as plausible rodent homologues of the human "default mode network" (DMN) and salience networks(
      • Sforazzini F.
      • Schwarz A.J.
      • Galbusera A.
      • Bifone A.
      • Gozzi A.
      Distributed BOLD and CBV-weighted resting-state networks in the mouse brain.
      ,
      • Gozzi A.
      • Schwarz A.J.
      Large-scale functional connectivity networks in the rodent brain.
      ).
      Perhaps one of the community's most interesting actions occurred two years ago, when seventeen groups around the world openly shared their data in a joint effort to define a common image processing and analysis pipeline for mouse fMRI(33). Despite differences between laboratories in imaging equipment and procedures, this study identified multiple and reproducible large-scale RSNs in mice, including a DMN, in most datasets. This work also described several parameters, animal handling procedures and equipment that can improve RSNs detection. The experimental parameters associated with an improved spatial specificity of RSN and an enhanced reproducibility of the functional connectivity parameter estimation between institutes include the use of dedicated cryoprobes, mechanical ventilation, and light sedation with medetomidine-isoflurane or intrapulmonary administered gaseous anesthetics. This and other initiatives including a similar ongoing effort in rats(
      • Grandjean J.
      StandardRat: A multi-center consensus protocol to enhance functional connectivity specificity in the rat brain.
      ) are critical to guide the design and analysis of future rodent fMRI investigations.

      Homologies and dissimilarities in RSNs between humans and rodents

      The discovery of reproducible and consistent RSNs in rodents has sparked fresh ideas about how this information may be exploited to assess commonalities and dissimilarities between animal models of humans and rodents, parallel to fMRI efforts conducted in non-human primates. Indeed, the establishment of comparable and homologous brain networks is required for direct comparison of rodent and human fMRI research. Testing this falls within the scope of a novel branch of neuroscience termed 'comparative functional neuroanatomy', which studies brain’s organization from an evolutionary perspective(
      • Grimm C.
      • Balsters J.H.
      • Zerbi V.
      Shedding Light on Social Reward Circuitry: (Un)common Blueprints in Humans and Rodents.
      ,
      • Thiebaut de Schotten M.
      • Croxson P.L.
      • Mars R.B.
      Large-scale comparative neuroimaging: Where are we and what do we need?.
      ). The initial findings of these investigations revealed that several brain networks in rodents have a homologous architecture similar to that seen in human and primates, such as the salience(
      • Mandino F.
      • Vrooman R.M.
      • Foo H.E.
      • Yeow L.Y.
      • Bolton T.A.W.
      • Salvan P.
      • et al.
      A triple-network organization for the mouse brain.
      ,
      • Tsai P.-J.
      • Keeley R.J.
      • Carmack S.A.
      • Vendruscolo J.C.M.
      • Lu H.
      • Gu H.
      • et al.
      Converging Structural and Functional Evidence for a Rat Salience Network.
      ), default-mode(
      • Gozzi A.
      • Schwarz A.J.
      Large-scale functional connectivity networks in the rodent brain.
      ,
      • Stafford J.M.
      • Jarrett B.R.
      • Miranda-Dominguez O.
      • Mills B.D.
      • Cain N.
      • Mihalas S.
      • et al.
      Large-scale topology and the default mode network in the mouse connectome.
      ), motor(
      • Sierakowiak A.
      • Monnot C.
      • Aski S.N.
      • Uppman M.
      • Li T.-Q.
      • Damberg P.
      • Brené S.
      Default Mode Network, Motor Network, Dorsal and Ventral Basal Ganglia Networks in the Rat Brain: Comparison to Human Networks Using Resting State-fMRI.
      ), and limbic networks(
      • Balsters J.H.
      • Zerbi V.
      • Sallet J.
      • Wenderoth N.
      • Mars R.B.
      Primate homologs of mouse cortico-striatal circuits.
      ). Other investigations have expanded these analogies to include hierarchical organization of cortical connectivity as mapped with fMRI connectivity gradients(
      • Fulcher B.D.
      • Murray J.D.
      • Zerbi V.
      • Wang X.-J.
      Multimodal gradients across mouse cortex.
      ,
      • Coletta L.
      • Pagani M.
      • Whitesell J.D.
      • Harris J.A.
      • Bernhardt B.
      • Gozzi A.
      Network structure of the mouse brain connectome with voxel resolution.
      ,
      • Margulies D.S.
      • Ghosh S.S.
      • Goulas A.
      • Falkiewicz M.
      • Huntenburg J.M.
      • Langs G.
      • et al.
      Situating the default-mode network along a principal gradient of macroscale cortical organization.
      ,
      • Gunnarsdóttir B.
      • Zerbi V.
      • Kelly C.
      Multimodal gradient mapping of rodent hippocampus.
      ), or the coactivation dynamics of BOLD fMRI signal(
      • Gutierrez-Barragan D.
      • Basson M.A.
      • Panzeri S.
      • Gozzi A.
      Infraslow State Fluctuations Govern Spontaneous fMRI Network Dynamics.
      ,
      • Yousefi B.
      • Shin J.
      • Schumacher E.H.
      • Keilholz S.D.
      Quasi-periodic patterns of intrinsic brain activity in individuals and their relationship to global signal.
      ,
      • Ma Y.
      • Hamilton C.
      • Zhang N.
      Dynamic Connectivity Patterns in Conscious and Unconscious Brain.
      ).
      Indeed, cross-species variation exists in both functional and neuroanatomical network organization. Notably, rodents lack a clear neuroanatomical equivalent of the precuneus in their DMN, which serves as the most prominent hub in the human DMN, and its functional role may be transferred to the retrosplenial cortex(
      • Gozzi A.
      • Schwarz A.J.
      Large-scale functional connectivity networks in the rodent brain.
      ,
      • Liska A.
      • Galbusera A.
      • Schwarz A.J.
      • Gozzi A.
      Functional connectivity hubs of the mouse brain.
      ). It is also possible that some of these disparities are the outcome of the evolution of functional networks with particular and distinctive capabilities for humans. For example, Balsters and colleagues revealed that connectivity from the caudate nucleus and anterior putamen striatal regions in humans and macaques could not be matched to any mouse cortico-striatal circuitry(
      • Balsters J.H.
      • Zerbi V.
      • Sallet J.
      • Wenderoth N.
      • Mars R.B.
      Primate homologs of mouse cortico-striatal circuits.
      ). Interestingly, the circuits formed by these areas are related to executive and socio-linguistic function and seem to be specific to non-human and human primates.
      This information is extremely valuable and can assist the interpretation of connectivity fMRI recordings on animals, and their cautious extrapolation to corresponding investigations of network dysconnectivity in humans. We believe that upcoming results from this active field of research will be pivotal in determining the translation potential of rodent models to humans, so that the knowledge gained in animal research may be applied to understand the significance of clinical results. A review by Xu and Keilholz covers further outstanding topics and open questions about network homologies and dissimilarities between rodents and humans, both from a methodological and an evolutionary standpoint(
      • Xu N.
      • LaGrow T.J.
      • Anumba N.
      • Lee A.
      • Zhang X.
      • Yousefi B.
      • et al.
      Functional Connectivity of the Brain Across Rodents and Humans.
      ).

      Towards awake fMRI mapping in rodents

      Light anesthesia or sedation are commonly used in rodents to ensure animal immobilization and reduce stress related to image acquisition. Notwithstanding the possible confounding effects of anesthesia, this procedure comes also with a number of possible advantages. For one, optimized anesthesia protocols exist(
      • Ferrari L.
      • Turrini G.
      • Crestan V.
      • Bertani S.
      • Cristofori P.
      • Bifone A.
      • Gozzi A.
      A robust experimental protocol for pharmacological fMRI in rats and mice.
      ,
      • Pawela C.P.
      • Biswal B.B.
      • Hudetz A.G.
      • Schulte M.L.
      • Li R.
      • Jones S.R.
      • et al.
      A protocol for use of medetomidine anesthesia in rats for extended studies using task-induced BOLD contrast and resting-state functional connectivity.
      ,
      • Grandjean J.
      • Schroeter A.
      • Batata I.
      • Rudin M.
      Optimization of anesthesia protocol for resting-state fMRI in mice based on differential effects of anesthetics on functional connectivity patterns.
      ,
      • Keilholz S.D.
      • Pan W.-J.
      • Billings J.
      • Nezafati M.
      • Shakil S.
      Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies.
      ) and they enable the reliable detection of translationally-relevant RSNs, while mitigating physiological artifacts and reducing inter-subject variability(
      • Bergmann E.
      • Gofman X.
      • Kavushansky A.
      • Kahn I.
      Individual variability in functional connectivity architecture of the mouse brain.
      ). In contrast, anesthetics may under some circumstances interfere with hemodynamic coupling, as well as regionally alter cortical and sub-cortical activity (reviewed by(
      • Reimann H.M.
      • Niendorf T.
      The (Un)Conscious Mouse as a Model for Human Brain Functions: Key Principles of Anesthesia and Their Impact on Translational Neuroimaging.
      )), potentially confounding the results of manipulation or recording studies(
      • Thiebaut de Schotten M.
      • Croxson P.L.
      • Mars R.B.
      Large-scale comparative neuroimaging: Where are we and what do we need?.
      ,
      • Rungta R.L.
      • Osmanski B.-F.
      • Boido D.
      • Tanter M.
      • Charpak S.
      Light controls cerebral blood flow in naive animals.
      ,
      • Gozzi A.
      • Schwarz A.
      • Crestan V.
      • Bifone A.
      Drug–anaesthetic interaction in phMRI: the case of the psychotomimetic agent phencyclidine.
      ). These effects can be compounded by possible peripheral confounds affecting body temperature, heart rate, blood pressure, and respiratory rate, a set of parameters that can however be tightly controlled and monitored using advanced animal preparations(
      • Keilholz S.D.
      • Pan W.-J.
      • Billings J.
      • Nezafati M.
      • Shakil S.
      Noise and non-neuronal contributions to the BOLD signal: applications to and insights from animal studies.
      ,
      • Reimann H.M.
      • Niendorf T.
      The (Un)Conscious Mouse as a Model for Human Brain Functions: Key Principles of Anesthesia and Their Impact on Translational Neuroimaging.
      ).
      In response to these concerns, and in attempt to increase direct translatability of connectivity fMRI, the number of studies employing fMRI in awake rodents have grown over the last few years (
      • Ferris C.F.
      Applications in Awake Animal Magnetic Resonance Imaging.
      ,
      • Desjardins M.
      • Kılıç K.
      • Thunemann M.
      • Mateo C.
      • Holland D.
      • Ferri C.G.L.
      • et al.
      Awake Mouse Imaging: From Two-Photon Microscopy to Blood Oxygen Level–Dependent Functional Magnetic Resonance Imaging.
      ). These investigations have shown the possibility of reliably mapping networks in awake restrained(
      • Liu Y.
      • Perez P.D.
      • Ma Z.
      • Ma Z.
      • Dopfel D.
      • Cramer S.
      • et al.
      An open database of resting-state fMRI in awake rats.
      ) or head-fixed(
      • Gutierrez-Barragan D.
      • Singh N.A.
      • Alvino F.G.
      • Coletta L.
      • Rocchi F.
      • De Guzman E.
      • et al.
      Unique spatiotemporal fMRI dynamics in the awake mouse brain.
      ) animals, with minimal stress and motion-related artefacts. Notably, closely recapitulating analogous human and primate investigations(
      • Barttfeld P.
      • Uhrig L.
      • Sitt J.D.
      • Sigman M.
      • Jarraya B.
      • Dehaene S.
      Signature of consciousness in the dynamics of resting-state brain activity.
      ,
      • Demertzi A.
      • Tagliazucchi E.
      • Dehaene S.
      • Deco G.
      • Barttfeld P.
      • Raimondo F.
      • et al.
      Human consciousness is supported by dynamic complex patterns of brain signal coordination.
      ), comparisons between network organization in awake and anesthetized rodents have shown that RSN organization is overall preserved across conditions(
      • Gutierrez-Barragan D.
      • Singh N.A.
      • Alvino F.G.
      • Coletta L.
      • Rocchi F.
      • De Guzman E.
      • et al.
      Unique spatiotemporal fMRI dynamics in the awake mouse brain.
      ,
      • Liang Z.
      • Liu X.
      • Zhang N.
      Dynamic resting state functional connectivity in awake and anesthetized rodents.
      ,
      • Liang Z.
      • King J.
      • Zhang N.
      Intrinsic Organization of the Anesthetized Brain.
      ), but the underlying network dynamics is profoundly altered, exhibiting stereotypical organization as a function of state. While these encouraging results support a transition to awake preparations, this procedure also comes with a few technical caveats. Awake recordings in rodents include physical body or head restraint and exposure to loud scanner-related acoustic noise. Humans are mindful of how loud the scanner is, thus sound-proof headphones are typically provided to subjects to reduce perceived noise levels. On the other hand, if the animals are not thoroughly and repetitively habituated to this new environment, scanner noise may elicit strong stress responses. This may not only increase the likelihood of head and body movement -a nemesis of fMRI recordings- but could also distort information processing and selective attention, preventing the onset of truly “resting states” comparable to quiet wakefulness attained in human imaging. The need for longer habituation regimens for animal models known to be more sensitive to sensory input from the environment, such as En2-KO or FMR1-KO models(
      • Chelini G.
      • Zerbi V.
      • Cimino L.
      • Grigoli A.
      • Markicevic M.
      • Libera F.
      • et al.
      Aberrant Somatosensory Processing and Connectivity in Mice Lacking Engrailed-2.
      ), is another topic that is currently up for debate. This issue is still largely unexplored, and we advise carefully considering it and determining the appropriate practices on an individual basis.
      Efforts are presently underway to create protocols aimed at optimizing habituation to the MRI environment and mitigating the stressful effects of head fixation, body restraint and noise via a gradual and incremental habituation protocols(
      • King J.A.
      • Garelick T.S.
      • Brevard M.E.
      • Chen W.
      • Messenger T.L.
      • Duong T.Q.
      • Ferris C.F.
      Procedure for minimizing stress for fMRI studies in conscious rats.
      ,
      • Madularu D.
      • Mathieu A.P.
      • Kumaragamage C.
      • Reynolds L.M.
      • Near J.
      • Flores C.
      • Rajah M.N.
      A non-invasive restraining system for awake mouse imaging.
      ,
      • Yoshida K.
      • Mimura Y.
      • Ishihara R.
      • Nishida H.
      • Komaki Y.
      • Minakuchi T.
      • et al.
      Physiological effects of a habituation procedure for functional MRI in awake mice using a cryogenic radiofrequency probe.
      ,
      • Chang P.-C.
      • Procissi D.
      • Bao Q.
      • Centeno M.V.
      • Baria A.
      • Apkarian A.V.
      Novel method for functional brain imaging in awake minimally restrained rats.
      ). Some of these studies have shown that these procedure can result in stress-related corticosterone levels comparable to pre-handling levels in both mice(
      • Gutierrez-Barragan D.
      • Singh N.A.
      • Alvino F.G.
      • Coletta L.
      • Rocchi F.
      • De Guzman E.
      • et al.
      Unique spatiotemporal fMRI dynamics in the awake mouse brain.
      ) and rats(
      • Russo G.
      • Helluy X.
      • Behroozi M.
      • Manahan-Vaughan D.
      Gradual Restraint Habituation for Awake Functional Magnetic Resonance Imaging Combined With a Sparse Imaging Paradigm Reduces Motion Artifacts and Stress Levels in Rodents.
      ). In the latter species, thanks to a sparse MRI sequence tuned to reduce acoustic stress, animals could even discriminate auditory stimulation from the background scanner noise(
      • Russo G.
      • Helluy X.
      • Behroozi M.
      • Manahan-Vaughan D.
      Gradual Restraint Habituation for Awake Functional Magnetic Resonance Imaging Combined With a Sparse Imaging Paradigm Reduces Motion Artifacts and Stress Levels in Rodents.
      ).
      Overall, the body of research points to the value of both awake and anesthetized imaging procedures, provided they are carried out with great methodological rigor and (where possible) controlling for the confounders and constraints of each technique. In our opinion, the field and methods have matured to the point where awake imaging should be regarded as the gold standard for rodent fMRI investigations and used in study design wherever possible. The use of anesthesia, on the other hand, can be accepted if done consistently and with proper verifications of physiological parameters and motivated by a clear study goal, such as limitations resulting from the strain used, use of manipulations that may induce discomfort, stimulus-locked motion or physiological responses, and inability to habituate the animals (e.g. studies in pups). Consequently, the experimental choice of whether to use anesthesia – as well as the choice of the animal model – should be tailored to the research question being answered rather than the current trends.

      Modelling functional dysconnectivity in rodents

      Disrupted or atypical patterns of functional connectivity have been detected in all major psychiatric and brain disorders(
      • Di Martino A.
      • O’Connor D.
      • Chen B.
      • Alaerts K.
      • Anderson J.S.
      • Assaf M.
      • et al.
      Enhancing studies of the connectome in autism using the autism brain imaging data exchange II.
      ,
      • Wang L.
      • Alpert K.I.
      • Calhoun V.D.
      • Cobia D.J.
      • Keator D.B.
      • King M.D.
      • et al.
      SchizConnect: Mediating neuroimaging databases on schizophrenia and related disorders for large-scale integration.
      ,
      • Corbetta M.
      • Ramsey L.
      • Callejas A.
      • Baldassarre A.
      • Hacker C.D.
      • Siegel J.S.
      • et al.
      Common behavioral clusters and subcortical anatomy in stroke.
      ), supporting a conceptualization of brain pathology as the result, at least in part, of impaired brain communication(
      • Vasa R.A.
      • Mostofsky S.H.
      • Ewen J.B.
      The Disrupted Connectivity Hypothesis of Autism Spectrum Disorders: Time for the Next Phase in Research.
      ,
      • Fornito A.
      • Zalesky A.
      • Breakspear M.
      The connectomics of brain disorders.
      ,
      • Stam C.J.
      Modern network science of neurological disorders.
      ). However, recent progress in human mapping of fMRI dysconnectivity has not been paralleled by increased knowledge of the mechanistic and etiological significance of these findings. The implementation of fMRI connectivity in rodents can strategically fill this knowledge gap, shedding light on the mechanistic and etiological significance of brain functional dysconnectivity (Fig. 1).
      Figure thumbnail gr1
      Figure 1Unravelling the determinants of functional dysconnectivity with rodent fMRI. A. Transgenic models can be used to isolate genetic alterations linked to psychiatric or developmental diseases (here referred to as A, B C). Here, rodent fMRI can serve to identify large-scale disconnection patterns associated with these mutations and, if possible, to compare the changes with corresponding human populations(
      • Bertero A.
      • Liska A.
      • Pagani M.
      • Parolisi R.
      • Masferrer M.E.
      • Gritti M.
      • et al.
      Autism-associated 16p11.2 microdeletion impairs prefrontal functional connectivity in mouse and human.
      ). This process forms the basis for establishing whether disconnectivity can be further investigated in the animal model with more invasive or postmortem investigations. B. Rodents can also be used to isolate and map the effect of known molecular, cellular, developmental, or environmental factors on brain wide patterns of connectivity. These investigations have high mechanistic relevance, and they can help conceptualize human functional dysconnectivity as the complex combination of multiple and distinct patho-physiological mechanisms. C. Acute neuronal manipulation studies using optogenetics, chemogenetics, and concurring neural recordings can similarly help gain a basic understanding of the determinants of functional dysconnectivity in human disorders via a multimodal dissection of the basic cascade of events linking regional patterns of brain activity to brain wide fMRI coupling(
      • Rocchi F.
      • Canella C.
      • Noei S.
      • Gutierrez-Barragan D.
      • Coletta L.
      • Galbusera A.
      • et al.
      Increased fMRI connectivity upon chemogenetic inhibition of the mouse prefrontal cortex.
      ). When linked to appropriate physiological validations and computational modelling, this approach can potentially be employed to reverse translate (or “decode”) physiologically-relevant fMRI signal metrics from patient population into microcircuital dysfunction parameters, such as imbalances in excitatory: inhibitory ratio(
      • Markicevic M.
      • Fulcher B.D.
      • Lewis C.
      • Helmchen F.
      • Rudin M.
      • Zerbi V.
      • Wenderoth N.
      Cortical Excitation:Inhibition Imbalance Causes Abnormal Brain Network Dynamics as Observed in Neurodevelopmental Disorders.
      ,
      • Trakoshis S.
      • Martínez-Cañada P.
      • Rocchi F.
      • Canella C.
      • You W.
      • Chakrabarti B.
      • et al.
      Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women.
      ). Brain renderings from panel C replicate design used in(

      Betzel RF (2022): Network neuroscience and the connectomics revolution. Connectomic Deep Brain Stimulation. Elsevier, pp 25–58.

      ).
      Much of the added value of this field of research lies in the possibility of testing (or generating) mechanistically relevant hypotheses under tightly controlled experimental conditions that are unachievable in clinical settings. These include the control of (a) physiological and motion artefacts via sedation or head-fixation(
      • Ferrari L.
      • Turrini G.
      • Crestan V.
      • Bertani S.
      • Cristofori P.
      • Bifone A.
      • Gozzi A.
      A robust experimental protocol for pharmacological fMRI in rats and mice.
      ,
      • Grandjean J.
      • Canella C.
      • Anckaerts C.
      • Ayrancı G.
      • Bougacha S.
      • Bienert T.
      • et al.
      Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.
      ,
      • Gutierrez-Barragan D.
      • Singh N.A.
      • Alvino F.G.
      • Coletta L.
      • Rocchi F.
      • De Guzman E.
      • et al.
      Unique spatiotemporal fMRI dynamics in the awake mouse brain.
      ), (b) environmental variability, by breeding mice under controlled laboratory conditions, and (c) genetic variation, via the assessment of genetic mutations or pathological determinants with respect to well-defined control groups composed of age- or sex-matched genetically homogeneous littermate animals. The importance of these factors should not be understated, as difficulties in controlling motion-related artefacts, as well as in properly accounting for genetic and demographic heterogeneity of both control and patient populations are recognized limitations of human fMRI mapping in mental illness(
      • Airan R.D.
      • Vogelstein J.T.
      • Pillai J.J.
      • Caffo B.
      • Pekar J.J.
      • Sair H.I.
      Factors affecting characterization and localization of interindividual differences in functional connectivity using MRI: Individual Differences in Functional Connectivity.
      ,
      • Gao W.
      • Elton A.
      • Zhu H.
      • Alcauter S.
      • Smith J.K.
      • Gilmore J.H.
      • Lin W.
      Intersubject Variability of and Genetic Effects on the Brain’s Functional Connectivity during Infancy.
      ,
      • Marquand A.F.
      • Rezek I.
      • Buitelaar J.
      • Beckmann C.F.
      Understanding Heterogeneity in Clinical Cohorts Using Normative Models: Beyond Case-Control Studies.
      ).
      Two dominant translational paradigms encompassing the use of rodent fMRI to unravel functional dysconnectivity in mental disorders have emerged over the past few years. The most widely used approach, (Fig. 1A) relies on the isolation and modelling of disease-relevant genetic alterations in rodents to investigate whether and how these factors affect functional connectivity. The most advanced examples of this method have been described in the field of autism and related developmental disorders, a broad spectrum of conditions marked by high heritability and high genetic heterogeneity(
      • Satterstrom F.K.
      • Kosmicki J.A.
      • Wang J.
      • Breen M.S.
      • De Rubeis S.
      • An J.-Y.
      • et al.
      Large-Scale Exome Sequencing Study Implicates Both Developmental and Functional Changes in the Neurobiology of Autism.
      ). Using fMRI in transgenic rodents, many studies have causally linked autism-associated etiological determinants to specific patterns of fMRI hypo/hyperconnectivity. The vast majority of examined factors are genetic mutations in autism risk-genes such as Cntnap2(78,79), Shank3(80), Tsc2(81), Fmr1(82), Nf1(83), Chd8(84), and 16p11.2 microdeletion(
      • Bertero A.
      • Liska A.
      • Pagani M.
      • Parolisi R.
      • Masferrer M.E.
      • Gritti M.
      • et al.
      Autism-associated 16p11.2 microdeletion impairs prefrontal functional connectivity in mouse and human.
      ).
      The translational relevance of this paradigm is high, as it can be used to explain findings from clinical populations harboring the corresponding genetic alterations. Bertero and colleagues used this approach to characterize similar patterns of prefrontal hypoconnectivity in a mouse model and people with 16p11.2 microdeletion, revealing that this effect is linked to immature thalamo-prefrontal wiring and diminished delta band coupling(
      • Bertero A.
      • Liska A.
      • Pagani M.
      • Parolisi R.
      • Masferrer M.E.
      • Gritti M.
      • et al.
      Autism-associated 16p11.2 microdeletion impairs prefrontal functional connectivity in mouse and human.
      ). Similarly, mTOR-related synaptic surplus has been shown to produce hyperconnectivity patterns that can be decoded in patients with idiopathic autism(
      • Pagani M.
      • Barsotti N.
      • Bertero A.
      • Trakoshis S.
      • Ulysse L.
      • Locarno A.
      • et al.
      mTOR-related synaptic pathology causes autism spectrum disorder-associated functional hyperconnectivity.
      ). Encouraging cross-species correspondences in dysconnectivity have also been also reported for Nf1 deficiency(
      • Shofty B.
      • Bergmann E.
      • Zur G.
      • Asleh J.
      • Bosak N.
      • Kavushansky A.
      • et al.
      Autism-associated Nf1 deficiency disrupts corticocortical and corticostriatal functional connectivity in human and mouse.
      ). In our view, these investigations are critical because they can inform both preclinical and clinical researchers about the relevance of the mechanism studied, and the translational value of the animal models used.
      When carried out on a large scale, rodent fMRI can also help address fundamental questions related to the significance of functional dysconnectivity in brain disorders. In a recent study(
      • Zerbi V.
      • Pagani M.
      • Markicevic M.
      • Matteoli M.
      • Pozzi D.
      • Fagiolini M.
      • et al.
      Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes.
      ), we compared connectivity alterations across 16 distinct autism mouse models, with the goal of assessing whether network alterations in autism converge onto a discrete network signature of dysfunction as previously hypothesized(
      • Holiga Š.
      • Hipp J.F.
      • Chatham C.H.
      • Garces P.
      • Spooren W.
      • D’Ardhuy X.L.
      • et al.
      Patients with autism spectrum disorders display reproducible functional connectivity alterations.
      ), or if instead they differ as a result of the etiological heterogeneity of the spectrum. The mouse models chosen for this work were based on (i) genetic modifications that resembles/relates to a genetic alteration found in individuals with ASD as listed in the SFARI gene database, and (ii) other ASD-associated etiologies such as environmental models or models for “idiopathic” ASD accompanied by autistic-like behavioral phenotype. Interestingly, our mapping revealed a broad array of connectional abnormalities in which diverse, even diverging, connectivity signatures were recognizable across models. These results reconcile highly conflicting findings in clinical populations(
      • He Y.
      • Byrge L.
      • Kennedy D.P.
      Nonreplication of functional connectivity differences in autism spectrum disorder across multiple sites and denoising strategies.
      ), suggesting that etiological variability is a key determinant of heterogeneous dysconnectivity in autism. Moreover, they support a reconceptualization of autism dysconnectivity as the sum of distinct neurosubtypes, possibly reflecting common cross-etiological mechanisms(
      • Hong S.-J.
      • Vogelstein J.T.
      • Gozzi A.
      • Bernhardt B.C.
      • Yeo B.T.T.
      • Milham M.P.
      • Di Martino A.
      Toward Neurosubtypes in Autism.
      ). Future extensions of this paradigm to other complex mental disorders can be envisioned.
      A second emerging research paradigm (Fig. 1B) relies on a broader modelling of basic pathophysiological processes associated with mental illness with the aim to identify how each of these affect the organization of fMRI connectivity networks. Mechanistically-relevant studies that can be ascribed to this category include investigations of the contribution of molecular, cellular or environmental factors associated with brain disorders, such as impaired developmental pruning(
      • Zhan Y.
      • Paolicelli R.C.
      • Sforazzini F.
      • Weinhard L.
      • Bolasco G.
      • Pagani F.
      • et al.
      Deficient neuron-microglia signaling results in impaired functional brain connectivity and social behavior.
      ,
      • Filipello F.
      • Morini R.
      • Corradini I.
      • Zerbi V.
      • Canzi A.
      • Michalski B.
      • et al.
      The Microglial Innate Immune Receptor TREM2 Is Required for Synapse Elimination and Normal Brain Connectivity.
      ) and maternal immune activation(
      • Mirabella F.
      • Desiato G.
      • Mancinelli S.
      • Fossati G.
      • Rasile M.
      • Morini R.
      • et al.
      Prenatal interleukin 6 elevation increases glutamatergic synapse density and disrupts hippocampal connectivity in offspring.
      ), both of which linked synaptic dysfunction to fMRI dysconnectivity, or the role of chronic stress on brain network function(
      • Grandjean J.
      • Azzinnari D.
      • Seuwen A.
      • Sigrist H.
      • Seifritz E.
      • Pryce C.R.
      • Rudin M.
      Chronic psychosocial stress in mice leads to changes in brain functional connectivity and metabolite levels comparable to human depression.
      ). While the broad transdiagnostic nature of the mechanisms investigated with this approach prevents a direct translation to clinical populations, the benefit of this paradigm ultimately lies in the mechanistic understanding of the cascade linked to altered functional connectivity, and the possibility of conceptualizing fMRI dysconnectivity into a set of physiologically dysregulated components that may add and converge to produce clinical dysconnectivity (Fig. 1B).

      Decoding the significance of dysconnectivity via multimodal fMRI

      Importantly, recent extensions of this approach to “physiologically decode” functional dysconnectivity potentially allow for reverse-translation of human fMRI datasets (Fig. 1C). Recent examples of this line of investigation entail the use of chemogenetic manipulations to probe how regional alterations in brain activity affect corresponding brain-wide patterns of connectivity(
      • Tu W.
      • Ma Z.
      • Ma Y.
      • Dopfel D.
      • Zhang N.
      Suppressing Anterior Cingulate Cortex Modulates Default Mode Network and Behavior in Awake Rats.
      ,
      • Peeters L.M.
      • Hinz R.
      • Detrez J.R.
      • Missault S.
      • De Vos W.H.
      • Verhoye M.
      • et al.
      Chemogenetic silencing of neurons in the mouse anterior cingulate area modulates neuronal activity and functional connectivity.
      ,
      • Markicevic M.
      • Fulcher B.D.
      • Lewis C.
      • Helmchen F.
      • Rudin M.
      • Zerbi V.
      • Wenderoth N.
      Cortical Excitation:Inhibition Imbalance Causes Abnormal Brain Network Dynamics as Observed in Neurodevelopmental Disorders.
      ). Three recent studies epitomize the power of this approach. Rocchi and colleagues recently showed that chronic or acute chemogenetic inactivation of the mouse cortex can counterintuitively lead to fMRI over-connectivity and increased delta-band coupling between the inactivated regions and its terminals as a result of enhanced global oscillatory activity(
      • Rocchi F.
      • Canella C.
      • Noei S.
      • Gutierrez-Barragan D.
      • Coletta L.
      • Galbusera A.
      • et al.
      Increased fMRI connectivity upon chemogenetic inhibition of the mouse prefrontal cortex.
      ). This result suggests that the fMRI hyperconnectivity and increased delta power often observed in disorders characterized by loss of cortical function (i.e., stroke and degenerative disorders) may mechanistically reflect increased global oscillatory activity as opposed to rerouting of signals as previously hypothesized(
      • Hillary F.G.
      • Grafman J.H.
      Injured Brains and Adaptive Networks: The Benefits and Costs of Hyperconnectivity.
      ). Importantly, the same study also confirmed the prediction that inverse chemogenetic manipulations, i.e., leading to increased excitatory-inhibitory ration (E:I) in cortical areas would lead to decreased fMRI connectivity via increased gamma, and decreased delta activity. Similar results were previously described in another rodent study in which chemogenetically-augmented E:I in somatosensory areas was found to reduce cortical fMRI connectivity(
      • Markicevic M.
      • Fulcher B.D.
      • Lewis C.
      • Helmchen F.
      • Rudin M.
      • Zerbi V.
      • Wenderoth N.
      Cortical Excitation:Inhibition Imbalance Causes Abnormal Brain Network Dynamics as Observed in Neurodevelopmental Disorders.
      ). Notably, in the same study the authors next trained a classifier on the recorded fMRI signals in mice, and showed its ability to accurately classify cortical areas exhibiting increased E:I in a mouse model of autism. These important investigations link E:I imbalance (a postulated physiological correlate of cortical dysfunction in multiple brain disorders(
      • Sohal V.S.
      • Rubenstein J.L.R.
      Excitation-inhibition balance as a framework for investigating mechanisms in neuropsychiatric disorders.
      )) to a characteristic signature of fMRI dysconnectivity, further offering opportunities to infer and possibly decode microcircuit abnormalities from macroscopic fMRI measurements. A compelling demonstration of the translational power of this approach has been recently described by Trakoshis and colleagues(
      • Trakoshis S.
      • Martínez-Cañada P.
      • Rocchi F.
      • Canella C.
      • You W.
      • Chakrabarti B.
      • et al.
      Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women.
      ). Using chemogenetics to increase or decrease E:I in mouse cortical areas during fMRI recordings, the authors identified a timeseries metric called Hurst index, corresponding to 1/f relationship of BOLD fMRI signal, that changes significantly in relation to the experimental manipulation. Interestingly, the same parameter could be used to decode regions with imbalanced E:I in a clinical population and revealed impairments in specific ‘social brain' regions including the medial prefrontal cortex. This research reveals the possibility, under certain circumstances, to use the fMRI signal to infer microcircuit properties of high pathophysiological significance.
      Additional important rodent studies have employed chemogenetic or optogenetic manipulations to probe the contribution of subcortical neuromodulatory systems (e.g., noradrenergic, cholinergic, serotonergic or dopaminergic neurotransmission) to brain wide patterns of connectivity. These investigations may help disambiguate the physiological or maladaptive contribution of specific neurotransmitter system to brain-wide networks dynamics with a precision unattainable in pharmacological studies and are a key component of research on brain dysconnectivity that we cover in greater details in the next section.

      Neuromodulatory system dysfunction and brain states in mental illnesses

      Ascending neuromodulatory systems (NMS) form the basis of many cognitive functions and endow the brain’s relatively static structural architecture with flexibility, making it possible to support malleable neural dynamics required for adaptive behavior(
      • Avery M.C.
      • Krichmar J.L.
      Neuromodulatory Systems and Their Interactions: A Review of Models, Theories, and Experiments.
      ). It is therefore not surprising that NMS dysfunction is related to many psychiatric disorders characterized by a persistent discomfort in adapting to new environmental, sensory, or social stimuli(
      • Coplan J.D.
      Treating comorbid anxiety and depression: Psychosocial and pharmacological approaches.
      ).
      Until now, much of the experimental and theoretical work has been devoted to determining how neuromodulatory activity is encoded in the firing patterns of target neurons(
      • Marder E.
      Neuromodulation of Neuronal Circuits: Back to the Future.
      ,
      • Lee S.-H.
      • Dan Y.
      Neuromodulation of Brain States.
      ). However, how changes in single neuron firing pattern characteristics driven by NMS propagate into large-scale phenomena, such as large-scale fMRI network activity, is far less known. Recent studies have produced initial evidence that sustained neuromodulatory release exerts a powerful modulatory effect on coordinated neural activity and fMRI connectivity(
      • Breakspear M.
      Dynamic models of large-scale brain activity.
      ,
      • Shine J.M.
      • Breakspear M.
      • Bell P.T.
      • Ehgoetz Martens K.
      • Shine R.
      • Koyejo O.
      • et al.
      Human cognition involves the dynamic integration of neural activity and neuromodulatory systems.
      ,
      • Shine J.M.
      • van den Brink R.L.
      • Hernaus D.
      • Nieuwenhuis S.
      • Poldrack R.A.
      Catecholaminergic manipulation alters dynamic network topology across cognitive states.
      ,
      • Bradley C.
      • Nydam A.S.
      • Dux P.E.
      • Mattingley J.B.
      State-dependent effects of neural stimulation on brain function and cognition.
      ). In humans, Shine and colleagues have shown that brain-wide fMRI responses across a range of cognitive tasks aligns with regional differences in the density of neuromodulatory receptors(
      • Shine J.M.
      • Breakspear M.
      • Bell P.T.
      • Ehgoetz Martens K.
      • Shine R.
      • Koyejo O.
      • et al.
      Human cognition involves the dynamic integration of neural activity and neuromodulatory systems.
      ). Based on these findings, they theorized that a key function of NMS is to coordinate the fluctuations between integration and segregation of functional networks with the aim to optimize cognitive functioning as a response to continuously evolving environment(
      • Munn B.
      • Müller E.J.
      • Wainstein G.
      • Shine J.M.
      The Ascending Arousal System Shapes Low-Dimensional Neural Dynamics to Mediate Awareness of Intrinsic Cognitive States.
      ,
      • Shine J.M.
      • Aburn M.J.
      • Breakspear M.
      • Poldrack R.A.
      The modulation of neural gain facilitates a transition between functional segregation and integration in the brain.
      ) . Accordingly, alterations in NMS could lead to inability to flexibly switch between states of connectivity, contributing to symptomatology or the emergence of neurological and psychiatric conditions.
      Given the high interest in these processes but the inability of dissecting them in humans, research platforms that allow for controlled manipulation of NMS are crucial for understanding their contribution to brain (dis)connectivity in brain disorders.
      To date, preclinical neuroimaging research have combined fMRI and pharmacological NMS manipulations to examine the effects of various receptor agonists and antagonists on the brain’s neuronal activity(
      • Schwarz A.J.
      • Gozzi A.
      • Reese T.
      • Bifone A.
      In vivo mapping of functional connectivity in neurotransmitter systems using pharmacological MRI.
      ). The approach, termed pharmacological fMRI (phMRI) has first been used to map the brain’s broad substrates that are directly activated by drugs of abuse like nicotine(
      • Gozzi A.
      • Schwarz A.
      • Reese T.
      • Bertani S.
      • Crestan V.
      • Bifone A.
      Region-Specific Effects of Nicotine on Brain Activity: A Pharmacological MRI Study in the Drug-Naïve Rat.
      ), cocaine(
      • Choi J.-K.
      • Chen Y.I.
      • Hamel E.
      • Jenkins B.G.
      Brain hemodynamic changes mediated by dopamine receptors: Role of the cerebral microvasculature in dopamine-mediated neurovascular coupling.
      ,
      • Gozzi A.
      • Tessari M.
      • Dacome L.
      • Agosta F.
      • Lepore S.
      • Lanzoni A.
      • et al.
      Neuroimaging Evidence of Altered Fronto-Cortical and Striatal Function after Prolonged Cocaine Self-Administration in the Rat.
      ), amphetamine(
      • Schwarz A.
      • Gozzi A.
      • Reese T.
      • Bertani S.
      • Crestan V.
      • Hagan J.
      • et al.
      Selective dopamine D3 receptor antagonist SB-277011-A potentiates phMRI response to acute amphetamine challenge in the rat brain.
      ), ketamine(
      • Montani C.
      • Canella C.
      • Schwarz A.J.
      • Li J.
      • Gilmour G.
      • Galbusera A.
      • et al.
      The M1/M4 preferring muscarinic agonist xanomeline modulates functional connectivity and NMDAR antagonist-induced changes in the mouse brain.
      ) and psylocibine(
      • Grandjean J.
      • Buehlmann D.
      • Buerge M.
      • Sigrist H.
      • Seifritz E.
      • Vollenweider F.X.
      • et al.
      Psilocybin exerts distinct effects on resting state networks associated with serotonin and dopamine in mice.
      ). These studies have been later expanded to probe the receptor basis of these responses(
      • Choi J.-K.
      • Chen Y.I.
      • Hamel E.
      • Jenkins B.G.
      Brain hemodynamic changes mediated by dopamine receptors: Role of the cerebral microvasculature in dopamine-mediated neurovascular coupling.
      ,
      • Gozzi A.
      • Herdon H.
      • Schwarz A.
      • Bertani S.
      • Crestan V.
      • Turrini G.
      • Bifone A.
      Pharmacological stimulation of NMDA receptors via co-agonist site suppresses fMRI response to phencyclidine in the rat.
      ), laying the foundation for a fertile area of translational research(
      • De Simoni S.
      • Schwarz A.J.
      • O’Daly O.G.
      • Marquand A.F.
      • Brittain C.
      • Gonzales C.
      • et al.
      Test–retest reliability of the BOLD pharmacological MRI response to ketamine in healthy volunteers.
      ,
      • Doyle O.M.
      • De Simoni S.
      • Schwarz A.J.
      • Brittain C.
      • O’Daly O.G.
      • Williams S.C.R.
      • Mehta M.A.
      Quantifying the Attenuation of the Ketamine Pharmacological Magnetic Resonance Imaging Response in Humans: A Validation Using Antipsychotic and Glutamatergic Agents.
      ,
      • Javitt D.C.
      • Carter C.S.
      • Krystal J.H.
      • Kantrowitz J.T.
      • Girgis R.R.
      • Kegeles L.S.
      • et al.
      Utility of Imaging-Based Biomarkers for Glutamate-Targeted Drug Development in Psychotic Disorders: A Randomized Clinical Trial.
      ). Leveraging the sensitivity of this approach, phMRI has been recently expanded to study the functional connectivity profiles and the substrates engaged by exogenously administered modulatory compounds and neuropeptides such as oxytocin(
      • Ferris C.F.
      • Yee J.R.
      • Kenkel W.M.
      • Dumais K.M.
      • Moore K.
      • Veenema A.H.
      • et al.
      Distinct BOLD Activation Profiles Following Central and Peripheral Oxytocin Administration in Awake Rats.
      ,
      • Pagani M.
      • De Felice A.
      • Montani C.
      • Galbusera A.
      • Papaleo F.
      • Gozzi A.
      Acute and Repeated Intranasal Oxytocin Differentially Modulate Brain-wide Functional Connectivity.
      ), ghrelin(
      • Wellman P.J.
      • Clifford P.S.
      • Rodriguez J.A.
      • Hughes S.
      • Di Francesco C.
      • Melotto S.
      • et al.
      Brain reinforcement system function is ghrelin dependent: studies in the rat using pharmacological fMRI and intracranial self-stimulation: Brain reward and ghrelin.
      ) or orexin(
      • Gozzi A.
      • Turrini G.
      • Piccoli L.
      • Massagrande M.
      • Amantini D.
      • Antolini M.
      • et al.
      Functional Magnetic Resonance Imaging Reveals Different Neural Substrates for the Effects of Orexin-1 and Orexin-2 Receptor Antagonists ((S. Gaetani, editor)).
      ). Investigations of how drugs affect rsfMRI connectivity in rodent models have also been described(
      • Montani C.
      • Canella C.
      • Schwarz A.J.
      • Li J.
      • Gilmour G.
      • Galbusera A.
      • et al.
      The M1/M4 preferring muscarinic agonist xanomeline modulates functional connectivity and NMDAR antagonist-induced changes in the mouse brain.
      ,
      • Gass N.
      • Schwarz A.J.
      • Sartorius A.
      • Schenker E.
      • Risterucci C.
      • Spedding M.
      • et al.
      Sub-Anesthetic Ketamine Modulates Intrinsic BOLD Connectivity Within the Hippocampal-Prefrontal Circuit in the Rat.
      ). While useful in probing central engagement of drugs of interest in a fashion amenable to clinical translation, the mechanistic specificity of phMRI to investigate modulatory transmission is inevitably limited by off-target pharmacological effects and possible direct vasoactive contributions of multiple drug agents(
      • Giorgi A.
      • Migliarini S.
      • Galbusera A.
      • Maddaloni G.
      • Mereu M.
      • Margiani G.
      • et al.
      Brain-wide Mapping of Endogenous Serotonergic Transmission via Chemogenetic fMRI.
      ,
      • Martin C.
      • Sibson N.R.
      Pharmacological MRI in animal models: A useful tool for 5-HT research?.
      ). As a result, the central substrates engaged by pharmacological agents can differ from those modulated by endogenous transmitter release.
      Optogenetic and chemogenetic tools, combined with advances in rodent imaging capabilities, now enable us to map the functional substrates of endogenous modulatory activity without the inconvenient contribution of vasoactive or peripheral pharmacological effects(Fig. 2)(
      • Shah D.
      • Blockx I.
      • Keliris G.A.
      • Kara F.
      • Jonckers E.
      • Verhoye M.
      • Van der Linden A.
      Cholinergic and serotonergic modulations differentially affect large-scale functional networks in the mouse brain.
      ). As an example, Giorgi and colleagues showed that cell-type specific chemogenetic activation of 5-HT cells led to a specific pattern of fMRI activation of cortico-hippocampal, ventrostriatal and cerebellar areas. In contrast, pharmacologically increasing serotonin levels resulted in widespread fMRI deactivation, reflecting a combination of central and peripheral vasoconstrictive effects (
      • Giorgi A.
      • Migliarini S.
      • Galbusera A.
      • Maddaloni G.
      • Mereu M.
      • Margiani G.
      • et al.
      Brain-wide Mapping of Endogenous Serotonergic Transmission via Chemogenetic fMRI.
      ). Other studies have used similar approaches in animal models to show that manipulation of dopaminergic neurons in ventral tegmental area and substantia nigra(
      • Ioanas H.-I.
      • Saab B.J.
      • Rudin M.
      Whole-brain opto-fMRI map of mouse VTA dopaminergic activation reflects structural projections with small but significant deviations.
      ,
      • Roelofs T.J.M.
      • Verharen J.P.H.
      • van Tilborg G.A.F.
      • Boekhoudt L.
      • van der Toorn A.
      • de Jong J.W.
      • et al.
      A novel approach to map induced activation of neuronal networks using chemogenetics and functional neuroimaging in rats: A proof-of-concept study on the mesocorticolimbic system.
      ,
      • Ferenczi E.A.
      • Zalocusky K.A.
      • Liston C.
      • Grosenick L.
      • Warden M.R.
      • Amatya D.
      • et al.
      Prefrontal cortical regulation of brainwide circuit dynamics and reward-related behavior.
      ,
      • Lohani S.
      • Poplawsky A.J.
      • Kim S.-G.
      • Moghaddam B.
      Unexpected global impact of VTA dopamine neuron activation as measured by opto-fMRI.
      ) and their targets in the striatum(
      • Grimm C.
      • Frässle S.
      • Steger C.
      • von Ziegler L.
      • Sturman O.
      • Shemesh N.
      • et al.
      Optogenetic activation of striatal D1R and D2R cells differentially engages downstream connected areas beyond the basal ganglia.
      ,
      • Lee H.J.
      • Weitz A.J.
      • Bernal-Casas D.
      • Duffy B.A.
      • Choy M.
      • Kravitz A.V.
      • et al.
      Activation of Direct and Indirect Pathway Medium Spiny Neurons Drives Distinct Brain-wide Responses.
      ), serotonin neurons in the dorsal raphe nucleus (DRN)(
      • Grandjean J.
      • Corcoba A.
      • Kahn M.C.
      • Upton A.L.
      • Deneris E.S.
      • Seifritz E.
      • et al.
      A brain-wide functional map of the serotonergic responses toacute stress and fluoxetine.
      ), cholinergic neurons in the basal forebrain(
      • Shah D.
      • Blockx I.
      • Keliris G.A.
      • Kara F.
      • Jonckers E.
      • Verhoye M.
      • Van der Linden A.
      Cholinergic and serotonergic modulations differentially affect large-scale functional networks in the mouse brain.
      ,
      • Nair J.
      • Klaassen A.-L.
      • Arato J.
      • Vyssotski A.L.
      • Harvey M.
      • Rainer G.
      Basal forebrain contributes to default mode network regulation.
      ,
      • Turchi J.
      • Chang C.
      • Ye F.Q.
      • Russ B.E.
      • Yu D.K.
      • Cortes C.R.
      • et al.
      The Basal Forebrain Regulates Global Resting-State fMRI Fluctuations.
      ) and noradrenergic neurons in the locus coeruleus (LC)(
      • Zerbi V.
      • Floriou-Servou A.
      • Markicevic M.
      • Vermeiren Y.
      • Sturman O.
      • Privitera M.
      • et al.
      Rapid Reconfiguration of the Functional Connectome after Chemogenetic Locus Coeruleus Activation.
      ,
      • Oyarzabal E.A.
      • Hsu L.-M.
      • Das M.
      • Chao T.-H.H.
      • Zhou J.
      • Song S.
      • et al.
      Chemogenetic stimulation of tonic locus coeruleus activity strengthens the default mode network.
      ) can lead to brain-wide activity changes measured by cerebral blood volume or BOLD-fMRI, which in turn could alter functional connectivity within specific networks and regions of interest.
      Figure thumbnail gr2
      Figure 2Multimodal rodent fMRI to study the contribution of neuromodulations to (dys)connectivity. One important process attributed to neuromodulatory systems (NMS) is to promote dynamic adjustments in behavioral states. For example, switching from a quiet, inattentive state to an aroused, vigilant state is attributed to a sustained increase in Locus Coeruleus (LC) - NE firing(
      • Hermans E.J.
      • Henckens M.J.A.G.
      • Joëls M.
      • Fernández G.
      Dynamic adaptation of large-scale brain networks in response to acute stressors.
      ), while changes in motivational vigor have been recently correlated with tonic firing of DA neurons in the Ventral Tegmental Area (VTA)(
      • Mohebi A.
      • Pettibone J.R.
      • Hamid A.A.
      • Wong J.-M.T.
      • Vinson L.T.
      • Patriarchi T.
      • et al.
      Dissociable dopamine dynamics for learning and motivation.
      ). Evidence from both human and rodents suggest that these behavioral states are paired with internal ‘brain connectivity states’, a term used to describe brain-wide and time-varying patterns of global neural activity that can be captured by whole-brain functional imaging modalities, such as fMRI. Dynamic and flexible changes in connectivity states - under direct control of NMSs - allows anatomically defined circuits to give rise to many different patterns of (co)activity, which is crucial for adaptability of neural processing in different behavioral contexts but often impaired in psychiatric or neurological disorders. One of the key advantages of rodent fMRI is the ability to perform direct manipulations of NMS using tools like chemo- and optogenetics. Compared to behavioral or drug challenges in humans, this has the advantage of minimizing the influence of internal beliefs and perception biases that are present in traditional human fMRI studies and cause heterogeneity in the observed responses. In addition, it is possible to study the mechanisms that form network states changes using more invasive recordings. This gives to rodent fMRI the unique ability to dissect the contribution and the role of NMS to whole brain (dys)connectivity patterns.
      One highly-relevant mechanism through which NMS could dynamically shape brain-wide functional connectivity is via alterations of spontaneous neuronal ensemble dynamics from a synchronous to an asynchronous state, and vice versa. High asynchronous dynamics would lead to lower connectivity but at the same time to stronger brain responses to incoming stimuli, as background noise is reduced, thus increasing signal-to-noise ratio (SNR). Conversely, a state of high global synchronicity would elevate functional connectivity but at the cost of reducing the selective response to external stimuli. Evidence for this modulatory role has been shown by Lottem and colleagues who demonstrated that optogenetic activation of the serotonin DRN can rapidly inhibit spontaneous fluctuation in the olfactory cortex in mice, effectively increasing activity related to incoming sensory responses(
      • Lottem E.
      • Lorincz M.L.
      • Mainen Z.F.
      Optogenetic Activation of Dorsal Raphe Serotonin Neurons Rapidly Inhibits Spontaneous But Not Odor-Evoked Activity in Olfactory Cortex.
      ). This mechanism would be consistent with the data from Grandjean and colleagues, in which stimulation of DRN evoked a reduction in cortical blood volume mirrored by suppression of intrinsic delta oscillations (
      • Grandjean J.
      • Corcoba A.
      • Kahn M.C.
      • Upton A.L.
      • Deneris E.S.
      • Seifritz E.
      • et al.
      A brain-wide functional map of the serotonergic responses toacute stress and fluoxetine.
      ). Other neurotransmitters may act in a similar way. For example, Meir and colleagues showed that electrical or optogenetic activation of the cholinergic system is able to shift cortical activity to an asynchronous state, which improved sensory responses (
      • Meir I.
      • Katz Y.
      • Lampl I.
      Membrane Potential Correlates of Network Decorrelation and Improved SNR by Cholinergic Activation in the Somatosensory Cortex.
      ). These effects of NMS could at least partly explain the results of a systematic meta‐analysis on working memory tasks in patients with schizophrenia or with major depressive disorder which found common stronger fMRI responses in prefrontal and anterior cingulate cortices, two regions belonging to the DMN (
      • Wang X.
      • Cheng B.
      • Roberts N.
      • Wang S.
      • Luo Y.
      • Tian F.
      • Yue S.
      Shared and distinct brain fMRI response during performance of working memory tasks in adult patients with schizophrenia and major depressive disorder.
      ). In contrast, two independent studies showed that activation of the LC-norepinephrine system increases low-frequency synchronous fMRI connectivity within multiple cortical networks, including the DMN(138,139). The strength of this reconfiguration was found to be spatially correlated with α1-2 and β1 adrenergic receptor transcript levels and norepinephrine turnover levels, corroborating the hypothesis from human stress research that LC activity and norepinephrine release is causally linked to fMRI network integration(
      • van Oort J.
      • Tendolkar I.
      • Hermans E.J.
      • Mulders P.C.
      • Beckmann C.F.
      • Schene A.H.
      • et al.
      How the brain connects in response to acute stress: A review at the human brain systems level.
      ,
      • Hermans E.J.
      • Van Marle H.J.F.
      • Ossewaarde L.
      • Henckens M.J.A.G.
      • Qin S.
      • Van Kesteren M.T.R.
      • et al.
      Stress-related noradrenergic activity prompts large-scale neural network reconfiguration.
      ,
      • Zhang W.
      • Llera A.
      • Hashemi M.M.
      • Kaldewaij R.
      • Koch S.B.J.
      • Beckmann C.F.
      • et al.
      Discriminating stress from rest based on resting‐state connectivity of the human brain: A supervised machine learning study.
      ). Overall, these studies show that fMRI connectivity is strongly constrained by underlying neuromodulatory tone. Studying these links is an opportunity to shed light on the elusive contribution of maladaptive NMS function to brain dysconnectivity in psychiatric and neurological disorders.

      Conclusion

      fMRI applied to rodents offers a privileged angle of investigation to explore the origin and significance of brain dysconnectivity at different levels of inquiry. We urgently need to break down fMRI disconnectivity into a number of physiological processes that can be mechanically explained, such as the function of neuromodulatory systems in mental illness. Multimodal imaging must be strongly promoted in this case. We further advise that the field moves towards longitudinal and awake imaging studies to look into the relationships between etiological factors and their chronobiological effects on brain connectivity. Additionally, we must keep fostering research domains whereby animal and human networks can be comparable. Understanding which circuits and networks exist in both species is essential for choosing the research questions and hypotheses that arise from clinical research on patients. Leveraging emerging correspondences in the organization of fMRI networks across the phylogenetic tree, the impact of this versatile research platform towards a better understanding of human brain function is substantial, and it is expected to rapidly grow in the coming years. We believe that the current research marks the beginning of a new chapter for functional rodent imaging, and that new routes for integrating preclinical and clinical data through direct comparisons or computational models will lead to a better understanding of the mechanism underlying dysconnectivity in mental illness.

      Conflicts of interest

      The authors have no biomedical financial interests or potential conflicts of interest to disclose

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      .

      Acknowledgment

      We thank Christina Grimm for critically reading this manuscript. V.Z. is supported by grants from the Swiss National Science Foundation (SNSF) Ambizione (PZ00P3_173984/1) and ECCELLENZA (PCEFP3_203005). This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (#DISCONN; no. 802371 to A.G) and the Brain and Behavior Foundation (NARSAD; Independent Investigator Grant; no. 25861, to A.G.). A.G is also supported by grants from the Simons Foundation (SFARI 400101), the NIH (1R21MH116473-01A1), the Telethon foundation (GGP19177) and the Uytengsu-Hamilton 22q11 Neuropsychiatry program at Stanford University.

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