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Sebenius I, Dorfschmidt L, Seidlitz J, Alexander-Bloch A, Morgan SE, Bullmore E. Structural MRI of brain similarity networks. Nat Rev Neurosci 2025; 26:42-59. [PMID: 39609622 DOI: 10.1038/s41583-024-00882-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/31/2024] [Indexed: 11/30/2024]
Abstract
Recent advances in structural MRI analytics now allow the network organization of individual brains to be comprehensively mapped through the use of the biologically principled metric of anatomical similarity. In this Review, we offer an overview of the measurement and meaning of structural MRI similarity, especially in relation to two key assumptions that often underlie its interpretation: (i) that MRI similarity can be representative of architectonic similarity between cortical areas and (ii) that similar areas are more likely to be axonally connected, as predicted by the homophily principle. We first introduce the historical roots and technical foundations of MRI similarity analysis and compare it with the distinct MRI techniques of structural covariance and tractography analysis. We contextualize this empirical work with two generative models of homophilic networks: an economic model of cost-constrained connectional homophily and a heterochronic model of ontogenetically phased cortical maturation. We then review (i) studies of the genetic and transcriptional architecture of MRI similarity in population-averaged and disorder-specific contexts and (ii) developmental studies of normative cohorts and clinical studies of neurodevelopmental and neurodegenerative disorders. Finally, we prioritize knowledge gaps that must be addressed to consolidate structural MRI similarity as an accessible, valid marker of the architecture and connectivity of an individual brain network.
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Affiliation(s)
- Isaac Sebenius
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK.
| | - Lena Dorfschmidt
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
| | - Jakob Seidlitz
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Aaron Alexander-Bloch
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Sarah E Morgan
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Edward Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire & Peterborough NHS Foundation Trust, Cambridge, UK
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2
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Pathak A, Menon SN, Sinha S. A hierarchy index for networks in the brain reveals a complex entangled organizational structure. Proc Natl Acad Sci U S A 2024; 121:e2314291121. [PMID: 38923990 PMCID: PMC11228506 DOI: 10.1073/pnas.2314291121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 05/23/2024] [Indexed: 06/28/2024] Open
Abstract
Networks involved in information processing often have their nodes arranged hierarchically, with the majority of connections occurring in adjacent levels. However, despite being an intuitively appealing concept, the hierarchical organization of large networks, such as those in the brain, is difficult to identify, especially in absence of additional information beyond that provided by the connectome. In this paper, we propose a framework to uncover the hierarchical structure of a given network, that identifies the nodes occupying each level as well as the sequential order of the levels. It involves optimizing a metric that we use to quantify the extent of hierarchy present in a network. Applying this measure to various brain networks, ranging from the nervous system of the nematode Caenorhabditis elegans to the human connectome, we unexpectedly find that they exhibit a common network architectural motif intertwining hierarchy and modularity. This suggests that brain networks may have evolved to simultaneously exploit the functional advantages of these two types of organizations, viz., relatively independent modules performing distributed processing in parallel and a hierarchical structure that allows sequential pooling of these multiple processing streams. An intriguing possibility is that this property we report may be common to information processing networks in general.
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Affiliation(s)
- Anand Pathak
- The Institute of Mathematical Sciences, CIT Campus, Taramani, Chennai600113, India
- Homi Bhabha National Institute, Mumbai400 094, India
| | - Shakti N. Menon
- The Institute of Mathematical Sciences, CIT Campus, Taramani, Chennai600113, India
| | - Sitabhra Sinha
- The Institute of Mathematical Sciences, CIT Campus, Taramani, Chennai600113, India
- Homi Bhabha National Institute, Mumbai400 094, India
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3
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Dichio V, De Vico Fallani F. Exploration-Exploitation Paradigm for Networked Biological Systems. PHYSICAL REVIEW LETTERS 2024; 132:098402. [PMID: 38489647 DOI: 10.1103/physrevlett.132.098402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 01/24/2024] [Indexed: 03/17/2024]
Abstract
The stochastic exploration of the configuration space and the exploitation of functional states underlie many biological processes. The evolutionary dynamics stands out as a remarkable example. Here, we introduce a novel formalism that mimics evolution and encodes a general exploration-exploitation dynamics for biological networks. We apply it to the brain wiring problem, focusing on the maturation of that of the nematode Caenorhabditis elegans. We demonstrate that a parsimonious maxent description of the adult brain combined with our framework is able to track down the entire developmental trajectory.
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Affiliation(s)
- Vito Dichio
- Sorbonne Universite, Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hopital de la Pitie Salpêtriere, F-75013, Paris, France
| | - Fabrizio De Vico Fallani
- Sorbonne Universite, Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hopital de la Pitie Salpêtriere, F-75013, Paris, France
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4
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Ripoll-Sánchez L, Watteyne J, Sun H, Fernandez R, Taylor SR, Weinreb A, Bentley BL, Hammarlund M, Miller DM, Hobert O, Beets I, Vértes PE, Schafer WR. The neuropeptidergic connectome of C. elegans. Neuron 2023; 111:3570-3589.e5. [PMID: 37935195 PMCID: PMC7615469 DOI: 10.1016/j.neuron.2023.09.043] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 08/02/2023] [Accepted: 09/29/2023] [Indexed: 11/09/2023]
Abstract
Efforts are ongoing to map synaptic wiring diagrams, or connectomes, to understand the neural basis of brain function. However, chemical synapses represent only one type of functionally important neuronal connection; in particular, extrasynaptic, "wireless" signaling by neuropeptides is widespread and plays essential roles in all nervous systems. By integrating single-cell anatomical and gene-expression datasets with biochemical analysis of receptor-ligand interactions, we have generated a draft connectome of neuropeptide signaling in the C. elegans nervous system. This network is characterized by high connection density, extended signaling cascades, autocrine foci, and a decentralized topology, with a large, highly interconnected core containing three constituent communities sharing similar patterns of input connectivity. Intriguingly, several key network hubs are little-studied neurons that appear specialized for peptidergic neuromodulation. We anticipate that the C. elegans neuropeptidergic connectome will serve as a prototype to understand how networks of neuromodulatory signaling are organized.
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Affiliation(s)
- Lidia Ripoll-Sánchez
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Department of Psychiatry, Cambridge University, Cambridge, UK
| | - Jan Watteyne
- Department of Biology, KU Leuven, Leuven, Belgium
| | - HaoSheng Sun
- Department of Biological Sciences/HHMI, Columbia University, New York, NY, USA; Department of Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Robert Fernandez
- Department of Biological Sciences/HHMI, Columbia University, New York, NY, USA
| | - Seth R Taylor
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Alexis Weinreb
- Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Barry L Bentley
- Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, UK
| | - Marc Hammarlund
- Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - David M Miller
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Oliver Hobert
- Department of Biological Sciences/HHMI, Columbia University, New York, NY, USA
| | - Isabel Beets
- Department of Biology, KU Leuven, Leuven, Belgium
| | - Petra E Vértes
- Department of Psychiatry, Cambridge University, Cambridge, UK
| | - William R Schafer
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Department of Biology, KU Leuven, Leuven, Belgium.
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5
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Carozza S, Holmes J, Vértes PE, Bullmore E, Arefin TM, Pugliese A, Zhang J, Kaffman A, Akarca D, Astle DE. Early adversity changes the economic conditions of mouse structural brain network organization. Dev Psychobiol 2023; 65:e22405. [PMID: 37607894 PMCID: PMC10505050 DOI: 10.1002/dev.22405] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Revised: 05/09/2023] [Accepted: 05/31/2023] [Indexed: 08/24/2023]
Abstract
Early adversity can change educational, cognitive, and mental health outcomes. However, the neural processes through which early adversity exerts these effects remain largely unknown. We used generative network modeling of the mouse connectome to test whether unpredictable postnatal stress shifts the constraints that govern the organization of the structural connectome. A model that trades off the wiring cost of long-distance connections with topological homophily (i.e., links between regions with shared neighbors) generated simulations that successfully replicate the rodent connectome. The imposition of early life adversity shifted the best-performing parameter combinations toward zero, heightening the stochastic nature of the generative process. Put simply, unpredictable postnatal stress changes the economic constraints that reproduce rodent connectome organization, introducing greater randomness into the development of the simulations. While this change may constrain the development of cognitive abilities, it could also reflect an adaptive mechanism that facilitates effective responses to future challenges.
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Affiliation(s)
- Sofia Carozza
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Joni Holmes
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- School of PsychologyUniversity of East AngliaNorwichUK
| | | | - Ed Bullmore
- Department of PsychiatryUniversity of CambridgeCambridgeUK
- Department of Clinical Neurosciences, Wolfson Brain Imaging CentreUniversity of CambridgeCambridgeUK
| | - Tanzil M. Arefin
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of RadiologyNew York University School of MedicineNew YorkNew YorkUSA
| | - Alexa Pugliese
- Department of PsychiatryYale University School of MedicineNew HavenConnecticutUSA
| | - Jiangyang Zhang
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of RadiologyNew York University School of MedicineNew YorkNew YorkUSA
| | - Arie Kaffman
- Department of PsychiatryYale University School of MedicineNew HavenConnecticutUSA
| | - Danyal Akarca
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Duncan E. Astle
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- Department of PsychiatryUniversity of CambridgeCambridgeUK
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6
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Sarparast M, Pourmand E, Hinman J, Vonarx D, Reason T, Zhang F, Paithankar S, Chen B, Borhan B, Watts JL, Alan J, Lee KSS. Dihydroxy-Metabolites of Dihomo-γ-linolenic Acid Drive Ferroptosis-Mediated Neurodegeneration. ACS CENTRAL SCIENCE 2023; 9:870-882. [PMID: 37252355 PMCID: PMC10214511 DOI: 10.1021/acscentsci.3c00052] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Indexed: 05/31/2023]
Abstract
Even after decades of research, the mechanism of neurodegeneration remains understudied, hindering the discovery of effective treatments for neurodegenerative diseases. Recent reports suggest that ferroptosis could be a novel therapeutic target for neurodegenerative diseases. While polyunsaturated fatty acid (PUFA) plays an important role in neurodegeneration and ferroptosis, how PUFAs may trigger these processes remains largely unknown. PUFA metabolites from cytochrome P450 and epoxide hydrolase metabolic pathways may modulate neurodegeneration. Here, we test the hypothesis that specific PUFAs regulate neurodegeneration through the action of their downstream metabolites by affecting ferroptosis. We find that the PUFA dihomo-γ-linolenic acid (DGLA) specifically induces ferroptosis-mediated neurodegeneration in dopaminergic neurons. Using synthetic chemical probes, targeted metabolomics, and genetic mutants, we show that DGLA triggers neurodegeneration upon conversion to dihydroxyeicosadienoic acid through the action of CYP-EH (CYP, cytochrome P450; EH, epoxide hydrolase), representing a new class of lipid metabolites that induce neurodegeneration via ferroptosis.
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Affiliation(s)
- Morteza Sarparast
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Elham Pourmand
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Jennifer Hinman
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Derek Vonarx
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Tommy Reason
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Fan Zhang
- Department
of Pharmacology and Toxicology, Michigan
State University, East Lansing, Michigan 48824, United States
| | - Shreya Paithankar
- Department
of Pediatrics and Human Development, Michigan
State University, Grand Rapids, Michigan 49503, United States
| | - Bin Chen
- Department
of Pharmacology and Toxicology, Michigan
State University, East Lansing, Michigan 48824, United States
- Department
of Pediatrics and Human Development, Michigan
State University, Grand Rapids, Michigan 49503, United States
| | - Babak Borhan
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Jennifer L. Watts
- School
of Molecular Biosciences, Washington State
University, Pullman, Washington 99164, United States
| | - Jamie Alan
- Department
of Pharmacology and Toxicology, Michigan
State University, East Lansing, Michigan 48824, United States
| | - Kin Sing Stephen Lee
- Department
of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
- Department
of Pharmacology and Toxicology, Michigan
State University, East Lansing, Michigan 48824, United States
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7
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Sarparast M, Pourmand E, Hinman J, Vonarx D, Reason T, Zhang F, Paithankar S, Chen B, Borhan B, Watts JL, Alan J, Lee KSS. Dihydroxy-Metabolites of Dihomo-gamma-linolenic Acid Drive Ferroptosis-Mediated Neurodegeneration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.05.522933. [PMID: 36711920 PMCID: PMC9881903 DOI: 10.1101/2023.01.05.522933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Even after decades of research, the mechanism of neurodegeneration remains understudied, hindering the discovery of effective treatments for neurodegenerative diseases. Recent reports suggest that ferroptosis could be a novel therapeutic target for neurodegenerative diseases. While polyunsaturated fatty acid (PUFA) plays an important role in neurodegeneration and ferroptosis, how PUFAs may trigger these processes remains largely unknown. PUFA metabolites from cytochrome P450 and epoxide hydrolase metabolic pathways may modulate neurodegeneration. Here, we test the hypothesis that specific PUFAs regulate neurodegeneration through the action of their downstream metabolites by affecting ferroptosis. We find that the PUFA, dihomo gamma linolenic acid (DGLA), specifically induces ferroptosis-mediated neurodegeneration in dopaminergic neurons. Using synthetic chemical probes, targeted metabolomics, and genetic mutants, we show that DGLA triggers neurodegeneration upon conversion to dihydroxyeicosadienoic acid through the action of CYP-EH, representing a new class of lipid metabolite that induces neurodegeneration via ferroptosis.
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Affiliation(s)
- Morteza Sarparast
- Department of Chemistry, Michigan State University, East Lansing, MI, USA
| | - Elham Pourmand
- Department of Chemistry, Michigan State University, East Lansing, MI, USA
| | - Jennifer Hinman
- Department of Chemistry, Michigan State University, East Lansing, MI, USA
| | - Derek Vonarx
- Department of Chemistry, Michigan State University, East Lansing, MI, USA
| | - Tommy Reason
- Department of Chemistry, Michigan State University, East Lansing, MI, USA
| | - Fan Zhang
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI, USA
| | - Shreya Paithankar
- Department of Pediatrics and Human Development, Michigan State University, Grand Rapids, MI, USA
| | - Bin Chen
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI, USA,Department of Pediatrics and Human Development, Michigan State University, Grand Rapids, MI, USA
| | - Babak Borhan
- Department of Chemistry, Michigan State University, East Lansing, MI, USA
| | - Jennifer L. Watts
- School of Molecular Biosciences, Washington State University, Pullman, WA, USA
| | - Jamie Alan
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI, USA,Corresponding Authors
| | - Kin Sing Stephen Lee
- Department of Chemistry, Michigan State University, East Lansing, MI, USA,Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI, USA,Corresponding Authors
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8
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Pathak A, Menon SN, Sinha S. Mesoscopic architecture enhances communication across the macaque connectome revealing structure-function correspondence in the brain. Phys Rev E 2022; 106:054304. [PMID: 36559437 DOI: 10.1103/physreve.106.054304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 09/13/2022] [Indexed: 06/17/2023]
Abstract
Analyzing the brain in terms of organizational structures at intermediate scales provides an approach to unravel the complexity arising from interactions between its large number of components. Focusing on a wiring diagram that spans the cortex, basal ganglia, and thalamus of the macaque brain, we identify robust modules in the network that provide a mesoscopic-level description of its topological architecture. Surprisingly, we find that the modular architecture facilitates rapid communication across the network, instead of localizing activity as is typically expected in networks having community organization. By considering processes of diffusive spreading and coordination, we demonstrate that the specific pattern of inter- and intramodular connectivity in the network allows propagation to be even faster than equivalent randomized networks with or without modular structure. This pattern of connectivity is seen at different scales and is conserved across principal cortical divisions, as well as subcortical structures. Furthermore, we find that the physical proximity between areas is insufficient to explain the modular organization, as similar mesoscopic structures can be obtained even after factoring out the effect of distance constraints on the connectivity. By supplementing the topological information about the macaque connectome with physical locations, volumes, and functions of the constituent areas and analyzing this augmented dataset, we reveal a counterintuitive role played by the modular architecture of the brain in promoting global coordination of its activity. It suggests a possible explanation for the ubiquity of modularity in brain networks.
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Affiliation(s)
- Anand Pathak
- The Institute of Mathematical Sciences, CIT Campus, Taramani, Chennai 600113, India
- Homi Bhabha National Institute, Anushaktinagar, Mumbai 400 094, India
| | - Shakti N Menon
- The Institute of Mathematical Sciences, CIT Campus, Taramani, Chennai 600113, India
| | - Sitabhra Sinha
- The Institute of Mathematical Sciences, CIT Campus, Taramani, Chennai 600113, India
- Homi Bhabha National Institute, Anushaktinagar, Mumbai 400 094, India
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9
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Alicea B. Raising the Connectome: The Emergence of Neuronal Activity and Behavior in Caenorhabditis elegans. Front Cell Neurosci 2020; 14:524791. [PMID: 33100971 PMCID: PMC7522492 DOI: 10.3389/fncel.2020.524791] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 08/24/2020] [Indexed: 11/15/2022] Open
Abstract
The differentiation of neurons and formation of connections between cells is the basis of both the adult phenotype and behaviors tied to cognition, perception, reproduction, and survival. Such behaviors are associated with local (circuits) and global (connectome) brain networks. A solid understanding of how these networks emerge is critical. This opinion piece features a guided tour of early developmental events in the emerging connectome, which is crucial to a new view on the connectogenetic process. Connectogenesis includes associating cell identities with broader functional and developmental relationships. During this process, the transition from developmental cells to terminally differentiated cells is defined by an accumulation of traits that ultimately results in neuronal-driven behavior. The well-characterized developmental and cell biology of Caenorhabditis elegans will be used to build a synthesis of developmental events that result in a functioning connectome. Specifically, our view of connectogenesis enables a first-mover model of synaptic connectivity to be demonstrated using data representing larval synaptogenesis. In a first-mover model of Stackelberg competition, potential pre- and postsynaptic relationships are shown to yield various strategies for establishing various types of synaptic connections. By comparing these results to what is known regarding principles for establishing complex network connectivity, these strategies are generalizable to other species and developmental systems. In conclusion, we will discuss the broader implications of this approach, as what is presented here informs an understanding of behavioral emergence and the ability to simulate related biological phenomena.
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Affiliation(s)
- Bradly Alicea
- Orthogonal Research and Education Laboratory, Champaign, IL, United States
- OpenWorm Foundation, Boston, MA, United States
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