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Parkes L, Kim JZ, Stiso J, Brynildsen JK, Cieslak M, Covitz S, Gur RE, Gur RC, Pasqualetti F, Shinohara RT, Zhou D, Satterthwaite TD, Bassett DS. A network control theory pipeline for studying the dynamics of the structural connectome. Nat Protoc 2024:10.1038/s41596-024-01023-w. [PMID: 39075309 DOI: 10.1038/s41596-024-01023-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 05/16/2024] [Indexed: 07/31/2024]
Abstract
Network control theory (NCT) is a simple and powerful tool for studying how network topology informs and constrains the dynamics of a system. Compared to other structure-function coupling approaches, the strength of NCT lies in its capacity to predict the patterns of external control signals that may alter the dynamics of a system in a desired way. An interesting development for NCT in the neuroscience field is its application to study behavior and mental health symptoms. To date, NCT has been validated to study different aspects of the human structural connectome. NCT outputs can be monitored throughout developmental stages to study the effects of connectome topology on neural dynamics and, separately, to test the coherence of empirical datasets with brain function and stimulation. Here, we provide a comprehensive pipeline for applying NCT to structural connectomes by following two procedures. The main procedure focuses on computing the control energy associated with the transitions between specific neural activity states. The second procedure focuses on computing average controllability, which indexes nodes' general capacity to control the dynamics of the system. We provide recommendations for comparing NCT outputs against null network models, and we further support this approach with a Python-based software package called 'network control theory for python'. The procedures in this protocol are appropriate for users with a background in network neuroscience and experience in dynamical systems theory.
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Affiliation(s)
- Linden Parkes
- Department of Psychiatry, Rutgers University, Piscataway, NJ, USA.
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Jason Z Kim
- Department of Physics, Cornell University, Ithaca, NY, USA
| | - Jennifer Stiso
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Julia K Brynildsen
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Cieslak
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sydney Covitz
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Raquel E Gur
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ruben C Gur
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Fabio Pasqualetti
- Department of Mechanical Engineering, University of California, Riverside, Riverside, CA, USA
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, Philadelphia, PA, USA
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA, USA
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dale Zhou
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D Satterthwaite
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA, USA
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
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2
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Al-Redouan A, Salaj M, Kubova H, Druga R. Compartmental neuronal degeneration in the ventral striatum induced by status epilepticus in young rats' brain in comparison with adults. Int J Dev Neurosci 2024; 84:328-341. [PMID: 38631684 DOI: 10.1002/jdn.10331] [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: 11/09/2023] [Revised: 03/11/2024] [Accepted: 03/26/2024] [Indexed: 04/19/2024] Open
Abstract
According to experimental and clinical studies, status epilepticus (SE) causes neurodegenerative morphological changes not only in the hippocampus and other limbic structures, it also affects the thalamus and the neocortex. In addition, several studies reported atrophy, metabolic changes, and neuronal degeneration in the dorsal striatum. The literature lacks studies investigating potential neuronal damage in the ventral component of the striatopallidal complex (ventral striatum [VS] and ventral pallidum) in SE experimentations. To better understand the development of neuronal damage in the striatopallidal complex associated with SE, the detected neuronal degeneration in the compartments of the VS, namely, the nucleus accumbens (NAc) and the olfactory tubercle (OT), was analyzed. The experiments were performed on Wistar rats at age of 25-day-old pups and 3-month-old adult animals. Lithium-pilocarpine model of SE was used. Lithium chloride (3 mmol/kg, ip) was injected 24 h before administering pilocarpine (40 mg/kg, ip). This presented study demonstrates the variability of post SE neuronal damage in 25-day-old pups in comparison with 3-month-old adult rats. The NAc exhibited small to moderate number of Fluoro-Jade B (FJB)-positive neurons detected 4 and 8 h post SE intervals. The number of degenerated neurons in the shell subdivision of the NAc significantly increased at survival interval of 12 h after the SE. FJB-positive neurons were evidently more prominent occupying the whole anteroposterior and mediolateral extent of the nucleus at longer survival intervals of 24 and 48 h after the SE. This was also the case in the bordering vicinity between the shell and the core compartments but with clusters of degenerating cells. The severity of damage of the shell subdivision of the NAc reached its peak at an interval of 24 h post SE. Isolated FJB-positive neurons were detected in the ventral peripheral part of the core compartment. Degenerated neurons persisted in the shell subdivision of the NAc 1 week after SE. However, the quantity of cell damage had significantly reduced in comparison with the aforementioned shorter intervals. The third layer of the OT exhibited more degenerated neurons than the second layer. The FJB-positive cells in the young animals were higher than in the adult animals. The morphology of those cells was identical in the two age groups except in the OT.
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Affiliation(s)
- Azzat Al-Redouan
- Department of Anatomy, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Martin Salaj
- Department of Anatomy, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Hana Kubova
- Department of developmental Epileptology, Institute of Physiology, The Czech Academy of Sciences, Prague, Czech Republic
| | - Rastislav Druga
- Department of Anatomy, Second Faculty of Medicine, Charles University, Prague, Czech Republic
- Department of developmental Epileptology, Institute of Physiology, The Czech Academy of Sciences, Prague, Czech Republic
- Institute of Anatomy, First Faculty of Medicine, Charles University, Prague, Czech Republic
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3
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Woo KA, Kim HJ, Shin JH, Cho K, Choi H, Jeon B. Symmetric and Profound Monoaminergic Degeneration in Parkinson's Disease with Premotor REM Sleep Behavior Disorder. JOURNAL OF PARKINSON'S DISEASE 2024; 14:823-831. [PMID: 38640171 PMCID: PMC11191437 DOI: 10.3233/jpd-230459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/18/2024] [Indexed: 04/21/2024]
Abstract
Background Rapid eye movement sleep behavior disorder (RBD) may precede or follow motor symptoms in Parkinson's disease (PD). While over 70% of idiopathic RBD cases phenoconvert within a decade, a small subset develops PD after a more extended period or remains nonconverted. These heterogeneous manifestations of RBD in PD prompt subtype investigations. Premotor RBD may signify "body-first" PD with bottom-up, symmetric synucleinopathy propagation. Objective Explore brainstem and nigrostriatal monoaminergic degeneration pattern differences based on premotor RBD presence and duration in de novo PD patients. Methods In a cross-sectional analysis of de novo PD patients (n = 150) undergoing FP-CIT PET and RBD Single-Question Screen, the cohort was categorized into groups with and without premotor RBD (PDRBD +/-), with further classification of PDRBD + based on a 10-year duration of premotor RBD. Analysis of FP-CIT binding in the striatum and pons, striatal asymmetry, and striatum-to-pons ratios compared patterns of nigrostriatal and brainstem monoaminergic degeneration. Results PDRBD + exhibited more severe and symmetrical striatal dopaminergic denervation compared to PDRBD-, with the difference in severity accentuated in the least-affected hemisphere. The PDRBD +<10Y subgroup displayed the most prominent striatal symmetry, supporting a more homogeneous "body-first" subtype. Pontine uptakes remained lower in PDRBD + even after adjusting for striatal uptake, suggesting early degeneration of pontine monoaminergic nuclei. Conclusions Premotor RBD in PD is associated with severe, symmetrical nigrostriatal and brainstem monoaminergic degeneration, especially in cases with PD onset within 10 years of RBD. This supports the concept of a "widespread, bottom-up" pathophysiological mechanism associated with premotor RBD in PD.
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Affiliation(s)
- Kyung Ah Woo
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Han-Joon Kim
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Jung Hwan Shin
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Kangyoung Cho
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Hongyoon Choi
- Department of Nuclear Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Beomseok Jeon
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
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Oldham S, Ball G. A phylogenetically-conserved axis of thalamocortical connectivity in the human brain. Nat Commun 2023; 14:6032. [PMID: 37758726 PMCID: PMC10533558 DOI: 10.1038/s41467-023-41722-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 09/15/2023] [Indexed: 09/29/2023] Open
Abstract
The thalamus enables key sensory, motor, emotive, and cognitive processes via connections to the cortex. These projection patterns are traditionally considered to originate from discrete thalamic nuclei, however recent work showing gradients of molecular and connectivity features in the thalamus suggests the organisation of thalamocortical connections occurs along a continuous dimension. By performing a joint decomposition of densely sampled gene expression and non-invasive diffusion tractography in the adult human thalamus, we define a principal axis of genetic and connectomic variation along a medial-lateral thalamic gradient. Projections along this axis correspond to an anterior-posterior cortical pattern and are aligned with electrophysiological properties of the cortex. The medial-lateral axis demonstrates phylogenetic conservation, reflects transitions in neuronal subtypes, and shows associations with neurodevelopment and common brain disorders. This study provides evidence for a supra-nuclear axis of thalamocortical organisation characterised by a graded transition in molecular properties and anatomical connectivity.
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Affiliation(s)
- Stuart Oldham
- Developmental Imaging, Murdoch Children's Research Institute, Parkville, VIC, Australia.
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia.
| | - Gareth Ball
- Developmental Imaging, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
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5
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Kanaan AS, Yu D, Metere R, Schäfer A, Schlumm T, Bilgic B, Anwander A, Mathews CA, Scharf JM, Müller-Vahl K, Möller HE. Convergent imaging-transcriptomic evidence for disturbed iron homeostasis in Gilles de la Tourette syndrome. Neurobiol Dis 2023; 185:106252. [PMID: 37536382 DOI: 10.1016/j.nbd.2023.106252] [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: 05/10/2023] [Revised: 07/11/2023] [Accepted: 08/01/2023] [Indexed: 08/05/2023] Open
Abstract
Gilles de la Tourette syndrome (GTS) is a neuropsychiatric movement disorder with reported abnormalities in various neurotransmitter systems. Considering the integral role of iron in neurotransmitter synthesis and transport, it is hypothesized that iron exhibits a role in GTS pathophysiology. As a surrogate measure of brain iron, quantitative susceptibility mapping (QSM) was performed in 28 patients with GTS and 26 matched controls. Significant susceptibility reductions in the patients, consistent with reduced local iron content, were obtained in subcortical regions known to be implicated in GTS. Regression analysis revealed a significant negative association of tic scores and striatal susceptibility. To interrogate genetic mechanisms that may drive these reductions, spatially specific relationships between susceptibility and gene-expression patterns from the Allen Human Brain Atlas were assessed. Correlations in the striatum were enriched for excitatory, inhibitory, and modulatory neurochemical signaling mechanisms in the motor regions, mitochondrial processes driving ATP production and iron‑sulfur cluster biogenesis in the executive subdivision, and phosphorylation-related mechanisms affecting receptor expression and long-term potentiation in the limbic subdivision. This link between susceptibility reductions and normative transcriptional profiles suggests that disruptions in iron regulatory mechanisms are involved in GTS pathophysiology and may lead to pervasive abnormalities in mechanisms regulated by iron-containing enzymes.
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Affiliation(s)
- Ahmad Seif Kanaan
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany.
| | - Dongmei Yu
- Center for Human Genetics Research, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Riccardo Metere
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Andreas Schäfer
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Siemens Healthcare GmbH, Diagnostic Imaging, Magnetic Resonance, Research and Development, Erlangen, Germany
| | - Torsten Schlumm
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Berkin Bilgic
- Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alfred Anwander
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Carol A Mathews
- Department of Psychiatry, Center for OCD, Anxiety, and Related Disorders, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Jeremiah M Scharf
- Center for Human Genetics Research, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Kirsten Müller-Vahl
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
| | - Harald E Möller
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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6
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Parkes L, Kim JZ, Stiso J, Brynildsen JK, Cieslak M, Covitz S, Gur RE, Gur RC, Pasqualetti F, Shinohara RT, Zhou D, Satterthwaite TD, Bassett DS. Using network control theory to study the dynamics of the structural connectome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.23.554519. [PMID: 37662395 PMCID: PMC10473719 DOI: 10.1101/2023.08.23.554519] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Network control theory (NCT) is a simple and powerful tool for studying how network topology informs and constrains dynamics. Compared to other structure-function coupling approaches, the strength of NCT lies in its capacity to predict the patterns of external control signals that may alter dynamics in a desired way. We have extensively developed and validated the application of NCT to the human structural connectome. Through these efforts, we have studied (i) how different aspects of connectome topology affect neural dynamics, (ii) whether NCT outputs cohere with empirical data on brain function and stimulation, and (iii) how NCT outputs vary across development and correlate with behavior and mental health symptoms. In this protocol, we introduce a framework for applying NCT to structural connectomes following two main pathways. Our primary pathway focuses on computing the control energy associated with transitioning between specific neural activity states. Our second pathway focuses on computing average controllability, which indexes nodes' general capacity to control dynamics. We also provide recommendations for comparing NCT outputs against null network models. Finally, we support this protocol with a Python-based software package called network control theory for python (nctpy).
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Affiliation(s)
- Linden Parkes
- Department of Bioengineering, University of Pennsylvania, PA 19104, USA
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, Rutgers University, Piscataway, NJ 08854, USA
| | - Jason Z Kim
- Department of Physics, Cornell University, Ithaca, NY 14853, USA
| | - Jennifer Stiso
- Department of Bioengineering, University of Pennsylvania, PA 19104, USA
| | | | - Matthew Cieslak
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sydney Covitz
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ruben C Gur
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Fabio Pasqualetti
- Department of Mechanical Engineering, University of California, Riverside, Riverside, CA 92521, USA
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dale Zhou
- Department of Bioengineering, University of Pennsylvania, PA 19104, USA
| | - Theodore D Satterthwaite
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Penn/CHOP Lifespan Brain Institute, Perelman School of Medicine, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, PA 19104, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, Philadelphia, PA 19104, USA
- Department of Electrical and Systems Engineering, University of Pennsylvania, PA 19104, USA
- Department of Physics and Astronomy, University of Pennsylvania, PA 19104, USA
- Santa Fe Institute, Santa Fe, NM 87501, USA
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7
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Gordon EM, Laumann TO, Marek S, Newbold DJ, Hampton JM, Seider NA, Montez DF, Nielsen AM, Van AN, Zheng A, Miller R, Siegel JS, Kay BP, Snyder AZ, Greene DJ, Schlaggar BL, Petersen SE, Nelson SM, Dosenbach NUF. Individualized Functional Subnetworks Connect Human Striatum and Frontal Cortex. Cereb Cortex 2022; 32:2868-2884. [PMID: 34718460 PMCID: PMC9247416 DOI: 10.1093/cercor/bhab387] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 11/14/2022] Open
Abstract
The striatum and cerebral cortex are interconnected via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate corticostriatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited in part by the practice of averaging neuroimaging data across individuals. Here we utilized highly sampled resting-state functional connectivity MRI for individual-specific precision functional mapping (PFM) of corticostriatal connections. We identified ten individual-specific subnetworks linking cortex-predominately frontal cortex-to striatum, most of which converged with nonhuman primate tract-tracing work. These included separable connections between nucleus accumbens core/shell and orbitofrontal/medial frontal gyrus; between anterior striatum and dorsomedial prefrontal cortex; between dorsal caudate and lateral prefrontal cortex; and between middle/posterior putamen and supplementary motor/primary motor cortex. Two subnetworks that did not converge with nonhuman primates were connected to cortical regions associated with human language function. Thus, precision subnetworks identify detailed, individual-specific, neurobiologically plausible corticostriatal connectivity that includes human-specific language networks.
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Affiliation(s)
- Evan M Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Timothy O Laumann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Scott Marek
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Dillan J Newbold
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jacqueline M Hampton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Nicole A Seider
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - David F Montez
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ashley M Nielsen
- Institute for Innovations in Developmental Sciences, Northwestern University, Chicago, IL 60611, USA
| | - Andrew N Van
- Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Annie Zheng
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Ryland Miller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Joshua S Siegel
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Benjamin P Kay
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Deanna J Greene
- Department of Cognitive Science, University of California San Diego, La Jolla, CA 92093, USA
| | - Bradley L Schlaggar
- Kennedy Krieger Institute, Baltimore, MD 21205, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Steven E Petersen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Psychological & Brain Sciences, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Steven M Nelson
- Department of Pediatrics, University of Minnesota, Minneapolis, MN 55454, USA
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN 55454, USA
| | - Nico U F Dosenbach
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Kennedy Krieger Institute, Baltimore, MD 21205, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA
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8
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Sabaroedin K, Razi A, Chopra S, Tran N, Pozaruk A, Chen Z, Finlay A, Nelson B, Allott K, Alvarez-Jimenez M, Graham J, Yuen HP, Harrigan S, Cropley V, Sharma S, Saluja B, Williams R, Pantelis C, Wood SJ, O’Donoghue B, Francey S, McGorry P, Aquino K, Fornito A. Frontostriatothalamic effective connectivity and dopaminergic function in the psychosis continuum. Brain 2022; 146:372-386. [PMID: 35094052 PMCID: PMC9825436 DOI: 10.1093/brain/awac018] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 12/21/2021] [Accepted: 12/22/2021] [Indexed: 01/12/2023] Open
Abstract
Dysfunction of fronto-striato-thalamic (FST) circuits is thought to contribute to dopaminergic dysfunction and symptom onset in psychosis, but it remains unclear whether this dysfunction is driven by aberrant bottom-up subcortical signalling or impaired top-down cortical regulation. We used spectral dynamic causal modelling of resting-state functional MRI to characterize the effective connectivity of dorsal and ventral FST circuits in a sample of 46 antipsychotic-naïve first-episode psychosis patients and 23 controls and an independent sample of 36 patients with established schizophrenia and 100 controls. We also investigated the association between FST effective connectivity and striatal 18F-DOPA uptake in an independent healthy cohort of 33 individuals who underwent concurrent functional MRI and PET. Using a posterior probability threshold of 0.95, we found that midbrain and thalamic connectivity were implicated as dysfunctional across both patient groups. Dysconnectivity in first-episode psychosis patients was mainly restricted to the subcortex, with positive symptom severity being associated with midbrain connectivity. Dysconnectivity between the cortex and subcortical systems was only apparent in established schizophrenia patients. In the healthy 18F-DOPA cohort, we found that striatal dopamine synthesis capacity was associated with the effective connectivity of nigrostriatal and striatothalamic pathways, implicating similar circuits to those associated with psychotic symptom severity in patients. Overall, our findings indicate that subcortical dysconnectivity is evident in the early stages of psychosis, that cortical dysfunction may emerge later in the illness, and that nigrostriatal and striatothalamic signalling are closely related to striatal dopamine synthesis capacity, which is a robust marker for psychosis.
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Affiliation(s)
- Kristina Sabaroedin
- Correspondence to: Kristina Sabaroedin Turner Institute for Brain and Mental Health 770 Blackburn Road, Clayton, Victoria 3168, Australia E-mail:
| | - Adeel Razi
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia,Monash Biomedical Imaging, Monash University, Clayton, Victoria 3800, Australia,Wellcome Centre for Human Neuroimaging, University College, London WC1N 3AR, UK
| | - Sidhant Chopra
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia
| | - Nancy Tran
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia
| | - Andrii Pozaruk
- Monash Biomedical Imaging, Monash University, Clayton, Victoria 3800, Australia
| | - Zhaolin Chen
- Monash Biomedical Imaging, Monash University, Clayton, Victoria 3800, Australia
| | - Amy Finlay
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia
| | - Barnaby Nelson
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Kelly Allott
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Mario Alvarez-Jimenez
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Jessica Graham
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Hok P Yuen
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Susy Harrigan
- Department of Social Work, Monash University, Victoria 3800, Australia,Melbourne School of Population and Global Health, The University of Melbourne, Parkville. Victoria 3010, Australia
| | - Vanessa Cropley
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, Victoria 3010, Australia
| | - Sujit Sharma
- Monash Health, Dandenong, Victoria 3175, Australia
| | | | - Rob Williams
- The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, Victoria 3010, Australia,The Florey Institute for Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Stephen J Wood
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia,School of Psychology, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK
| | - Brian O’Donoghue
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Shona Francey
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Patrick McGorry
- Orygen, Parkville, Victoria 3052, Australia,Centre for Youth Mental Health, The University of Melbourne, Parkville, Victoria 3052, Australia
| | - Kevin Aquino
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia,Monash Biomedical Imaging, Monash University, Clayton, Victoria 3800, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria 3800, Australia,Monash Biomedical Imaging, Monash University, Clayton, Victoria 3800, Australia
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9
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Where the genome meets the connectome: Understanding how genes shape human brain connectivity. Neuroimage 2021; 244:118570. [PMID: 34508898 DOI: 10.1016/j.neuroimage.2021.118570] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 08/10/2021] [Accepted: 09/07/2021] [Indexed: 02/07/2023] Open
Abstract
The integration of modern neuroimaging methods with genetically informative designs and data can shed light on the molecular mechanisms underlying the structural and functional organization of the human connectome. Here, we review studies that have investigated the genetic basis of human brain network structure and function through three complementary frameworks: (1) the quantification of phenotypic heritability through classical twin designs; (2) the identification of specific DNA variants linked to phenotypic variation through association and related studies; and (3) the analysis of correlations between spatial variations in imaging phenotypes and gene expression profiles through the integration of neuroimaging and transcriptional atlas data. We consider the basic foundations, strengths, limitations, and discoveries associated with each approach. We present converging evidence to indicate that anatomical connectivity is under stronger genetic influence than functional connectivity and that genetic influences are not uniformly distributed throughout the brain, with phenotypic variation in certain regions and connections being under stronger genetic control than others. We also consider how the combination of imaging and genetics can be used to understand the ways in which genes may drive brain dysfunction in different clinical disorders.
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10
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Robert C, Patel R, Blostein N, Steele CJ, Chakravarty MM. Analyses of microstructural variation in the human striatum using non-negative matrix factorization. Neuroimage 2021; 246:118744. [PMID: 34848302 DOI: 10.1016/j.neuroimage.2021.118744] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 11/08/2021] [Accepted: 11/18/2021] [Indexed: 12/12/2022] Open
Abstract
The striatum is a major subcortical connection hub that has been heavily implicated in a wide array of motor and cognitive functions. Here, we developed a normative multimodal, data-driven microstructural parcellation of the striatum using non-negative matrix factorization (NMF) based on multiple magnetic resonance imaging-based metrics (mean diffusivity, fractional anisotropy, and the ratio between T1- and T2-weighted structural scans) from the Human Connectome Project Young Adult dataset (n = 329 unrelated participants, age range: 22-35, F/M: 185/144). We further explored the biological and functional relationships of this parcellation by relating our findings to motor and cognitive performance in tasks known to involve the striatum as well as demographics. We identified 5 spatially distinct striatal components for each hemisphere. We also show the gain in component stability when using multimodal versus unimodal metrics. Our findings suggest distinct microstructural patterns in the human striatum that are largely symmetric and that relate mostly to age and sex. Our work also highlights the putative functional relevance of these striatal components to different designations based on a Neurosynth meta-analysis.
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Affiliation(s)
- Corinne Robert
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada.
| | - Raihaan Patel
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada; Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada
| | - Nadia Blostein
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada; Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Chrisopher J Steele
- Department of Psychology, Concordia University, Montreal, QC, Canada; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - M Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada; Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada; Department of Biological and Biomedical Engineering, McGill University, Montreal, QC, Canada; Department of Psychiatry, McGill University, Montreal, QC, Canada.
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11
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Markello RD, Arnatkeviciute A, Poline JB, Fulcher BD, Fornito A, Misic B. Standardizing workflows in imaging transcriptomics with the abagen toolbox. eLife 2021; 10:e72129. [PMID: 34783653 PMCID: PMC8660024 DOI: 10.7554/elife.72129] [Citation(s) in RCA: 128] [Impact Index Per Article: 42.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 11/15/2021] [Indexed: 12/12/2022] Open
Abstract
Gene expression fundamentally shapes the structural and functional architecture of the human brain. Open-access transcriptomic datasets like the Allen Human Brain Atlas provide an unprecedented ability to examine these mechanisms in vivo; however, a lack of standardization across research groups has given rise to myriad processing pipelines for using these data. Here, we develop the abagen toolbox, an open-access software package for working with transcriptomic data, and use it to examine how methodological variability influences the outcomes of research using the Allen Human Brain Atlas. Applying three prototypical analyses to the outputs of 750,000 unique processing pipelines, we find that choice of pipeline has a large impact on research findings, with parameters commonly varied in the literature influencing correlations between derived gene expression and other imaging phenotypes by as much as ρ ≥ 1.0. Our results further reveal an ordering of parameter importance, with processing steps that influence gene normalization yielding the greatest impact on downstream statistical inferences and conclusions. The presented work and the development of the abagen toolbox lay the foundation for more standardized and systematic research in imaging transcriptomics, and will help to advance future understanding of the influence of gene expression in the human brain.
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Affiliation(s)
- Ross D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill UniversityMontrealCanada
| | - Aurina Arnatkeviciute
- School of Psychological Sciences & Monash Biomedical Imaging, Monash UniversityClaytonAustralia
| | - Jean-Baptiste Poline
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill UniversityMontrealCanada
| | - Ben D Fulcher
- School of Physics, University of SydneySydneyAustralia
| | - Alex Fornito
- School of Psychological Sciences & Monash Biomedical Imaging, Monash UniversityClaytonAustralia
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill UniversityMontrealCanada
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12
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de Oliveira KC, Camilo C, Gastaldi VD, Sant'Anna Feltrin A, Lisboa BCG, de Jesus Rodrigues de Paula V, Moretto AC, Lafer B, Hoexter MQ, Miguel EC, Maschietto M, Brentani H. Brain areas involved with obsessive-compulsive disorder present different DNA methylation modulation. BMC Genom Data 2021; 22:45. [PMID: 34717534 PMCID: PMC8557022 DOI: 10.1186/s12863-021-00993-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2021] [Accepted: 08/29/2021] [Indexed: 12/13/2022] Open
Abstract
Background Obsessive-compulsive disorder (OCD) is characterized by intrusive thoughts and repetitive actions, that presents the involvement of the cortico-striatal areas. The contribution of environmental risk factors to OCD development suggests that epigenetic mechanisms may contribute to its pathophysiology. DNA methylation changes and gene expression were evaluated in post-mortem brain tissues of the cortical (anterior cingulate gyrus and orbitofrontal cortex) and ventral striatum (nucleus accumbens, caudate nucleus and putamen) areas from eight OCD patients and eight matched controls. Results There were no differentially methylated CpG (cytosine-phosphate-guanine) sites (DMSs) in any brain area, nevertheless gene modules generated from CpG sites and protein-protein-interaction (PPI) showed enriched gene modules for all brain areas between OCD cases and controls. All brain areas but nucleus accumbens presented a predominantly hypomethylation pattern for the differentially methylated regions (DMRs). Although there were common transcriptional factors that targeted these DMRs, their targeted differentially expressed genes were different among all brain areas. The protein-protein interaction network based on methylation and gene expression data reported that all brain areas were enriched for G-protein signaling pathway, immune response, apoptosis and synapse biological processes but each brain area also presented enrichment of specific signaling pathways. Finally, OCD patients and controls did not present significant DNA methylation age differences. Conclusions DNA methylation changes in brain areas involved with OCD, especially those involved with genes related to synaptic plasticity and the immune system could mediate the action of genetic and environmental factors associated with OCD. Supplementary Information The online version contains supplementary material available at 10.1186/s12863-021-00993-0.
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Affiliation(s)
- Kátia Cristina de Oliveira
- Departamento & Instituto de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Rua Dr. Ovídio Pires de Campos, 785 - LIM23 (Térreo), São Paulo, 05403-010, Brazil.,Center of Mathematics, Computation and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil.,Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Caroline Camilo
- Departamento & Instituto de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Rua Dr. Ovídio Pires de Campos, 785 - LIM23 (Térreo), São Paulo, 05403-010, Brazil.
| | - Vinícius Daguano Gastaldi
- Departamento & Instituto de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Rua Dr. Ovídio Pires de Campos, 785 - LIM23 (Térreo), São Paulo, 05403-010, Brazil
| | - Arthur Sant'Anna Feltrin
- Center of Mathematics, Computation and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
| | - Bianca Cristina Garcia Lisboa
- Departamento & Instituto de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Rua Dr. Ovídio Pires de Campos, 785 - LIM23 (Térreo), São Paulo, 05403-010, Brazil
| | - Vanessa de Jesus Rodrigues de Paula
- Departamento & Instituto de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Rua Dr. Ovídio Pires de Campos, 785 - LIM23 (Térreo), São Paulo, 05403-010, Brazil
| | | | - Beny Lafer
- Departamento & Instituto de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Rua Dr. Ovídio Pires de Campos, 785 - LIM23 (Térreo), São Paulo, 05403-010, Brazil
| | - Marcelo Queiroz Hoexter
- Departamento & Instituto de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Rua Dr. Ovídio Pires de Campos, 785 - LIM23 (Térreo), São Paulo, 05403-010, Brazil.,Laboratório de Psicopatologia e Terapêutica Psiquiátrica (LIM23), Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Euripedes Constantino Miguel
- Departamento & Instituto de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Rua Dr. Ovídio Pires de Campos, 785 - LIM23 (Térreo), São Paulo, 05403-010, Brazil.,Laboratório de Psicopatologia e Terapêutica Psiquiátrica (LIM23), Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | | | | | - Helena Brentani
- Departamento & Instituto de Psiquiatria, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Rua Dr. Ovídio Pires de Campos, 785 - LIM23 (Térreo), São Paulo, 05403-010, Brazil.,Laboratório de Psicopatologia e Terapêutica Psiquiátrica (LIM23), Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
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13
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Basile GA, Bertino S, Bramanti A, Ciurleo R, Anastasi GP, Milardi D, Cacciola A. Striatal topographical organization: Bridging the gap between molecules, connectivity and behavior. Eur J Histochem 2021; 65. [PMID: 34643358 PMCID: PMC8524362 DOI: 10.4081/ejh.2021.3284] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 09/07/2021] [Indexed: 12/22/2022] Open
Abstract
The striatum represents the major hub of the basal ganglia, receiving projections from the entire cerebral cortex and it is assumed to play a key role in a wide array of complex behavioral tasks. Despite being extensively investigated during the last decades, the topographical organization of the striatum is not well understood yet. Ongoing efforts in neuroscience are focused on analyzing striatal anatomy at different spatial scales, to understand how structure relates to function and how derangements of this organization are involved in various neuropsychiatric diseases. While being subdivided at the macroscale level into dorsal and ventral divisions, at a mesoscale level the striatum represents an anatomical continuum sharing the same cellular makeup. At the same time, it is now increasingly ascertained that different striatal compartments show subtle histochemical differences, and their neurons exhibit peculiar patterns of gene expression, supporting functional diversity across the whole basal ganglia circuitry. Such diversity is further supported by afferent connections which are heterogenous both anatomically, as they originate from distributed cortical areas and subcortical structures, and biochemically, as they involve a variety of neurotransmitters. Specifically, the cortico-striatal projection system is topographically organized delineating a functional organization which is maintained throughout the basal ganglia, subserving motor, cognitive and affective behavioral functions. While such functional heterogeneity has been firstly conceptualized as a tripartite organization, with sharply defined limbic, associative and sensorimotor territories within the striatum, it has been proposed that such territories are more likely to fade into one another, delineating a gradient-like organization along medio-lateral and ventro-dorsal axes. However, the molecular and cellular underpinnings of such organization are less understood, and their relations to behavior remains an open question, especially in humans. In this review we aimed at summarizing the available knowledge on striatal organization, especially focusing on how it links structure to function and its alterations in neuropsychiatric diseases. We examined studies conducted on different species, covering a wide array of different methodologies: from tract-tracing and immunohistochemistry to neuroimaging and transcriptomic experiments, aimed at bridging the gap between macroscopic and molecular levels.
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Affiliation(s)
- Gianpaolo Antonio Basile
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina.
| | - Salvatore Bertino
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina.
| | - Alessia Bramanti
- Department of Medicine, Surgery and Dentistry "Medical School of Salerno", University of Salerno.
| | | | - Giuseppe Pio Anastasi
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina.
| | - Demetrio Milardi
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina.
| | - Alberto Cacciola
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Images, University of Messina.
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14
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Bueichekú E, Gonzalez-de-Echavarri JM, Ortiz-Teran L, Montal V, d'Oleire Uquillas F, De Marcos L, Orwig W, Kim CM, Ortiz-Teran E, Basaia S, Diez I, Sepulcre J. Divergent connectomic organization delineates genetic evolutionary traits in the human brain. Sci Rep 2021; 11:19692. [PMID: 34608211 PMCID: PMC8490416 DOI: 10.1038/s41598-021-99082-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 09/07/2021] [Indexed: 02/08/2023] Open
Abstract
The relationship between human brain connectomics and genetic evolutionary traits remains elusive due to the inherent challenges in combining complex associations within cerebral tissue. In this study, insights are provided about the relationship between connectomics, gene expression and divergent evolutionary pathways from non-human primates to humans. Using in vivo human brain resting-state data, we detected two co-existing idiosyncratic functional systems: the segregation network, in charge of module specialization, and the integration network, responsible for information flow. Their topology was approximated to whole-brain genetic expression (Allen Human Brain Atlas) and the co-localization patterns yielded that neuron communication functionalities-linked to Neuron Projection-were overrepresented cell traits. Homologue-orthologue comparisons using dN/dS-ratios bridged the gap between neurogenetic outcomes and biological data, summarizing the known evolutionary divergent pathways within the Homo Sapiens lineage. Evidence suggests that a crosstalk between functional specialization and information flow reflects putative biological qualities of brain architecture, such as neurite cellular functions like axonal or dendrite processes, hypothesized to have been selectively conserved in the species through positive selection. These findings expand our understanding of human brain function and unveil aspects of our cognitive trajectory in relation to our simian ancestors previously left unexplored.
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Affiliation(s)
- Elisenda Bueichekú
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Jose M Gonzalez-de-Echavarri
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Barcelona βeta Brain Research Center, Barcelona, Spain
| | - Laura Ortiz-Teran
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Victor Montal
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain
- Centro de Investigacón Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Federico d'Oleire Uquillas
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Lola De Marcos
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- University of Navarra School of Medicine, University of Navarra, Pamplona, Navarra, Spain
| | - William Orwig
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Chan-Mi Kim
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, USA
| | - Elena Ortiz-Teran
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Facultad de Ciencias Jurídicas y Sociales, Universidad Rey Juan Carlos, Madrid, Spain
| | - Silvia Basaia
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Neuroimaging Research Unit, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Ibai Diez
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, USA
| | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, USA.
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15
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McCutcheon RA, Brown K, Nour MM, Smith SM, Veronese M, Zelaya F, Osugo M, Jauhar S, Hallett W, Mehta MM, Howes OD. Dopaminergic organization of striatum is linked to cortical activity and brain expression of genes associated with psychiatric illness. SCIENCE ADVANCES 2021; 7:7/24/eabg1512. [PMID: 34108214 PMCID: PMC8189589 DOI: 10.1126/sciadv.abg1512] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 04/15/2021] [Indexed: 05/02/2023]
Abstract
Dopamine signaling is constrained to discrete tracts yet has brain-wide effects on neural activity. The nature of this relationship between local dopamine signaling and brain-wide neuronal activity is not clearly defined and has relevance for neuropsychiatric illnesses where abnormalities of cortical activity and dopamine signaling coexist. Using simultaneous PET-MRI in healthy volunteers, we find strong evidence that patterns of striatal dopamine signaling and cortical blood flow (an index of local neural activity) contain shared information. This shared information links amphetamine-induced changes in gradients of striatal dopamine receptor availability to changes in brain-wide blood flow and is informed by spatial patterns of gene expression enriched for genes implicated in schizophrenia, bipolar disorder, and autism spectrum disorder. These results advance our knowledge of the relationship between cortical function and striatal dopamine, with relevance for understanding pathophysiology and treatment of diseases in which simultaneous aberrations of these systems exist.
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Affiliation(s)
- Robert A McCutcheon
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Kirsten Brown
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Matthew M Nour
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Stephen M Smith
- Oxford University Centre for Functional MRI of the Brain (FMRIB), Oxford, UK
| | - Mattia Veronese
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Fernando Zelaya
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Martin Osugo
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Sameer Jauhar
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - William Hallett
- Invicro Imaging Services, Burlington Danes Building, Du Cane Road, London, UK
| | - Mitul M Mehta
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK
- Psychiatric Imaging Group, MRC London Institute of Medical Sciences, Hammersmith Hospital, Imperial College London, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
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16
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Fulcher BD, Arnatkeviciute A, Fornito A. Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data. Nat Commun 2021; 12:2669. [PMID: 33976144 PMCID: PMC8113439 DOI: 10.1038/s41467-021-22862-1] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 03/31/2021] [Indexed: 02/03/2023] Open
Abstract
Transcriptomic atlases have improved our understanding of the correlations between gene-expression patterns and spatially varying properties of brain structure and function. Gene-category enrichment analysis (GCEA) is a common method to identify functional gene categories that drive these associations, using gene-to-category annotation systems like the Gene Ontology (GO). Here, we show that applying standard GCEA methodology to spatial transcriptomic data is affected by substantial false-positive bias, with GO categories displaying an over 500-fold average inflation of false-positive associations with random neural phenotypes in mouse and human. The estimated false-positive rate of a GO category is associated with its rate of being reported as significantly enriched in the literature, suggesting that published reports are affected by this false-positive bias. We show that within-category gene-gene coexpression and spatial autocorrelation are key drivers of the false-positive bias and introduce flexible ensemble-based null models that can account for these effects, made available as a software toolbox.
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Affiliation(s)
- Ben D Fulcher
- School of Physics, The University of Sydney, Camperdown, NSW, Australia.
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia.
| | - Aurina Arnatkeviciute
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences and Monash Biomedical Imaging, Monash University, Clayton, VIC, Australia
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17
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Parkes L, Satterthwaite TD, Bassett DS. Towards precise resting-state fMRI biomarkers in psychiatry: synthesizing developments in transdiagnostic research, dimensional models of psychopathology, and normative neurodevelopment. Curr Opin Neurobiol 2020; 65:120-128. [PMID: 33242721 PMCID: PMC7770086 DOI: 10.1016/j.conb.2020.10.016] [Citation(s) in RCA: 49] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 10/11/2020] [Accepted: 10/14/2020] [Indexed: 02/01/2023]
Abstract
Searching for biomarkers has been a chief pursuit of the field of psychiatry. Toward this end, studies have catalogued candidate resting-state biomarkers in nearly all forms of mental disorder. However, it is becoming increasingly clear that these biomarkers lack specificity, limiting their capacity to yield clinical impact. We discuss three avenues of research that are overcoming this limitation: (i) the adoption of transdiagnostic research designs, which involve studying and explicitly comparing multiple disorders from distinct diagnostic axes of psychiatry; (ii) dimensional models of psychopathology that map the full spectrum of symptomatology and that cut across traditional disorder boundaries; and (iii) modeling individuals' unique functional connectomes throughout development. We provide a framework for tying these subfields together that draws on tools from machine learning and network science.
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Affiliation(s)
- Linden Parkes
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute, University of Pennsylvania & Children's Hospital of Philadelphia, Philadelphia, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Danielle S Bassett
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Perelman School of Medicine, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA; Santa Fe Institute, Santa Fe, NM 87501, USA.
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18
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Fallon J, Ward PGD, Parkes L, Oldham S, Arnatkevičiūtė A, Fornito A, Fulcher BD. Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain. Netw Neurosci 2020; 4:788-806. [PMID: 33615091 PMCID: PMC7888482 DOI: 10.1162/netn_a_00151] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 06/08/2020] [Indexed: 12/21/2022] Open
Abstract
Intrinsic timescales of activity fluctuations vary hierarchically across the brain. This variation reflects a broad gradient of functional specialization in information storage and processing, with integrative association areas displaying slower timescales that are thought to reflect longer temporal processing windows. The organization of timescales is associated with cognitive function, distinctive between individuals, and disrupted in disease, but we do not yet understand how the temporal properties of activity dynamics are shaped by the brain's underlying structural connectivity network. Using resting-state fMRI and diffusion MRI data from 100 healthy individuals from the Human Connectome Project, here we show that the timescale of resting-state fMRI dynamics increases with structural connectivity strength, matching recent results in the mouse brain. Our results hold at the level of individuals, are robust to parcellation schemes, and are conserved across a range of different timescale- related statistics. We establish a comprehensive BOLD dynamical signature of structural connectivity strength by comparing over 6,000 time series features, highlighting a range of new temporal features for characterizing BOLD dynamics, including measures of stationarity and symbolic motif frequencies. Our findings indicate a conserved property of mouse and human brain organization in which a brain region's spontaneous activity fluctuations are closely related to their surrounding structural scaffold.
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Affiliation(s)
- John Fallon
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
| | - Phillip G. D. Ward
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
- Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne, Australia
| | - Linden Parkes
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104 USA
| | - Stuart Oldham
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
| | - Aurina Arnatkevičiūtė
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
| | - Alex Fornito
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
| | - Ben D. Fulcher
- Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne, Australia
- School of Physics, University of Sydney, NSW, Australia
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19
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Hierarchical dynamics as a macroscopic organizing principle of the human brain. Proc Natl Acad Sci U S A 2020; 117:20890-20897. [PMID: 32817467 DOI: 10.1073/pnas.2003383117] [Citation(s) in RCA: 97] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Multimodal evidence suggests that brain regions accumulate information over timescales that vary according to anatomical hierarchy. Thus, these experimentally defined "temporal receptive windows" are longest in cortical regions that are distant from sensory input. Interestingly, spontaneous activity in these regions also plays out over relatively slow timescales (i.e., exhibits slower temporal autocorrelation decay). These findings raise the possibility that hierarchical timescales represent an intrinsic organizing principle of brain function. Here, using resting-state functional MRI, we show that the timescale of ongoing dynamics follows hierarchical spatial gradients throughout human cerebral cortex. These intrinsic timescale gradients give rise to systematic frequency differences among large-scale cortical networks and predict individual-specific features of functional connectivity. Whole-brain coverage permitted us to further investigate the large-scale organization of subcortical dynamics. We show that cortical timescale gradients are topographically mirrored in striatum, thalamus, and cerebellum. Finally, timescales in the hippocampus followed a posterior-to-anterior gradient, corresponding to the longitudinal axis of increasing representational scale. Thus, hierarchical dynamics emerge as a global organizing principle of mammalian brains.
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20
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Hörtnagl H, Pifl C, Hörtnagl E, Reiner A, Sperk G. Distinct gradients of various neurotransmitter markers in caudate nucleus and putamen of the human brain. J Neurochem 2019; 152:650-662. [PMID: 31608979 PMCID: PMC7078952 DOI: 10.1111/jnc.14897] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 10/07/2019] [Accepted: 10/10/2019] [Indexed: 01/23/2023]
Abstract
The caudate nucleus (CN) and the putamen (PUT) as parts of the human striatum are distinguished by a marked heterogeneity in functional, anatomical, and neurochemical patterns. Our study aimed to document in detail the regional diversity in the distribution of dopamine (DA), serotonin, γ‐aminobuturic acid, and choline acetyltransferase within the CN and PUT. For this purpose we dissected the CN as well as the PUT of 12 post‐mortem brains of human subjects with no evidence of neurological and psychiatric disorders (38–81 years old) into about 80 tissue parts. We then investigated rostro‐caudal, dorso‐ventral, and medio‐lateral gradients of these neurotransmitter markers. All parameters revealed higher levels, turnover rates, or activities in the PUT than in the CN. Within the PUT, DA levels increased continuously from rostral to caudal. In contrast, the lowest molar ratio of homovanillic acid to DA, a marker of DA turnover, coincided with highest DA levels in the caudal PUT, the part of the striatum with the highest loss of DA in Parkinson’s disease (N. Engl. J. Med., 318, 1988, 876). Highest DA concentrations were found in the most central areas both in the PUT and CN. We observed an age‐dependent loss of DA in the PUT and CN that did not correspond to the loss described for Parkinson’s disease indicating different mechanisms inducing the deficit of DA. Our data demonstrate a marked heterogeneity in the anatomical distribution of neurotransmitter markers in the human dorsal striatum indicating anatomical and functional diversity within this brain structure. ![]()
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Affiliation(s)
- Heide Hörtnagl
- Department of Pharmacology, Innsbruck Medical University, Innsbruck, Austria
| | - Christian Pifl
- Centre for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Erik Hörtnagl
- ipsum, interkultureller Kunstverein, Müllerstr. 28, Innsbruck, Austria
| | | | - Günther Sperk
- Department of Pharmacology, Innsbruck Medical University, Innsbruck, Austria
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21
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Parkes L, Tiego J, Aquino K, Braganza L, Chamberlain SR, Fontenelle LF, Harrison BJ, Lorenzetti V, Paton B, Razi A, Fornito A, Yücel M. Transdiagnostic variations in impulsivity and compulsivity in obsessive-compulsive disorder and gambling disorder correlate with effective connectivity in cortical-striatal-thalamic-cortical circuits. Neuroimage 2019; 202:116070. [PMID: 31382045 DOI: 10.1016/j.neuroimage.2019.116070] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 07/24/2019] [Accepted: 08/02/2019] [Indexed: 12/15/2022] Open
Abstract
Individual differences in impulsivity and compulsivity is thought to underlie vulnerability to a broad range of disorders and are closely tied to cortical-striatal-thalamic-cortical function. However, whether impulsivity and compulsivity in clinical disorders is continuous with the healthy population and explains cortical-striatal-thalamic-cortical dysfunction across different disorders remains unclear. Here, we characterized the relationship between cortical-striatal-thalamic-cortical effective connectivity, estimated using dynamic causal modelling of resting-state functional magnetic resonance imaging data, and dimensional phenotypes of impulsivity and compulsivity in two symptomatically distinct but phenotypically related disorders, obsessive-compulsive disorder and gambling disorder. 487 online participants provided data for modelling of dimensional phenotypes. These data were combined with 34 obsessive-compulsive disorder patients, 22 gambling disorder patients, and 39 healthy controls, who underwent functional magnetic resonance imaging. Three core dimensions were identified: disinhibition, impulsivity, and compulsivity. Patients' scores on these dimensions were continuously distributed with the healthy participants, supporting a continuum model of psychopathology. Across all participants, higher disinhibition correlated with lower bottom-up connectivity in the dorsal circuit and greater bottom-up connectivity in the ventral circuit, and higher compulsivity correlated with lower bottom-up connectivity in the dorsal circuit. In patients, higher clinical severity was also linked to lower bottom-up connectivity in the dorsal circuit, but these findings were independent of phenotypic variation, demonstrating convergence towards behaviourally and clinically relevant changes in brain dynamics. Effective connectivity did not differ as a function of traditional diagnostic labels and only weak associations were observed for functional connectivity measures. Together, our results demonstrate that cortical-striatal-thalamic-cortical dysfunction across obsessive-compulsive disorder and gambling disorder may be better characterized by dimensional phenotypes than diagnostic comparisons, supporting investigation of quantitative liability phenotypes.
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Affiliation(s)
- Linden Parkes
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia.
| | - Jeggan Tiego
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
| | - Kevin Aquino
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
| | - Leah Braganza
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia; Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Victoria, Australia
| | - Samuel R Chamberlain
- Department of Psychiatry, University of Cambridge and Cambridge Peterborough NHS Foundation Trust, Cambridge, United Kingdom
| | - Leonardo F Fontenelle
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia; Obsessive, Compulsive, and Anxiety Spectrum Research Program, Institute of Psychiatry, Federal University of Rio de Janeiro & D'Or Institute for Research and Education, Rio de Janeiro, Brazil
| | - Ben J Harrison
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Victoria, Australia
| | - Valentina Lorenzetti
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia; School of Psychology, Faculty of Health, Australian Catholic University, Fitzroy, Australia
| | - Bryan Paton
- School of Psychology, Faculty of Science, University of Newcastle, Newcastle, Australia; Cognition & Philosophy Lab, Monash University, Melbourne, Australia
| | - Adeel Razi
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia; Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, United Kingdom; Department of Electronic Engineering, NED University of Engineering and Technology, Karachi, Pakistan
| | - Alex Fornito
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
| | - Murat Yücel
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, Australia
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22
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Arnatkevičiūtė A, Fulcher BD, Fornito A. Uncovering the Transcriptional Correlates of Hub Connectivity in Neural Networks. Front Neural Circuits 2019; 13:47. [PMID: 31379515 PMCID: PMC6659348 DOI: 10.3389/fncir.2019.00047] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 07/04/2019] [Indexed: 12/04/2022] Open
Abstract
Connections in nervous systems are disproportionately concentrated on a small subset of neural elements that act as network hubs. Hubs have been found across different species and scales ranging from C. elegans to mouse, rat, cat, macaque, and human, suggesting a role for genetic influences. The recent availability of brain-wide gene expression atlases provides new opportunities for mapping the transcriptional correlates of large-scale network-level phenotypes. Here we review studies that use these atlases to investigate gene expression patterns associated with hub connectivity in neural networks and present evidence that some of these patterns are conserved across species and scales.
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Affiliation(s)
- Aurina Arnatkevičiūtė
- Monash Biomedical Imaging, School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
| | - Ben D. Fulcher
- Monash Biomedical Imaging, School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
- School of Physics, The University of Sydney, Sydney, NSW, Australia
| | - Alex Fornito
- Monash Biomedical Imaging, School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
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23
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Initial findings of striatum tripartite model in OCD brain samples based on transcriptome analysis. Sci Rep 2019; 9:3086. [PMID: 30816141 PMCID: PMC6395771 DOI: 10.1038/s41598-019-38965-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Accepted: 12/17/2018] [Indexed: 11/22/2022] Open
Abstract
Obsessive-compulsive disorder (OCD) is a psychiatric disorder characterized by obsessions and/or compulsions. Different striatal subregions belonging to the cortico-striato-thalamic circuitry (CSTC) play an important role in the pathophysiology of OCD. The transcriptomes of 3 separate striatal areas (putamen (PT), caudate nucleus (CN) and accumbens nucleus (NAC)) from postmortem brain tissue were compared between 6 OCD and 8 control cases. In addition to network connectivity deregulation, different biological processes are specific to each striatum region according to the tripartite model of the striatum and contribute in various ways to OCD pathophysiology. Specifically, regulation of neurotransmitter levels and presynaptic processes involved in chemical synaptic transmission were shared between NAC and PT. The Gene Ontology terms cellular response to chemical stimulus, response to external stimulus, response to organic substance, regulation of synaptic plasticity, and modulation of synaptic transmission were shared between CN and PT. Most genes harboring common and/or rare variants previously associated with OCD that were differentially expressed or part of a least preserved coexpression module in our study also suggest striatum subregion specificity. At the transcriptional level, our study supports differences in the 3 circuit CSTC model associated with OCD.
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24
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Arnatkeviciute A, Fulcher BD, Fornito A. A practical guide to linking brain-wide gene expression and neuroimaging data. Neuroimage 2019; 189:353-367. [PMID: 30648605 DOI: 10.1016/j.neuroimage.2019.01.011] [Citation(s) in RCA: 337] [Impact Index Per Article: 67.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Revised: 01/03/2019] [Accepted: 01/05/2019] [Indexed: 12/19/2022] Open
Abstract
The recent availability of comprehensive, brain-wide gene expression atlases such as the Allen Human Brain Atlas (AHBA) has opened new opportunities for understanding how spatial variations on molecular scale relate to the macroscopic neuroimaging phenotypes. A rapidly growing body of literature is demonstrating relationships between gene expression and diverse properties of brain structure and function, but approaches for combining expression atlas data with neuroimaging are highly inconsistent, with substantial variations in how the expression data are processed. The degree to which these methodological variations affect findings is unclear. Here, we outline a seven-step analysis pipeline for relating brain-wide transcriptomic and neuroimaging data and compare how different processing choices influence the resulting data. We suggest that studies using the AHBA should work towards a unified data processing pipeline to ensure consistent and reproducible results in this burgeoning field.
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Affiliation(s)
- Aurina Arnatkeviciute
- Brain and Mental Health Research Hub, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, 770 Blackburn Rd, Clayton, 3168, VIC, Australia.
| | - Ben D Fulcher
- Brain and Mental Health Research Hub, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, 770 Blackburn Rd, Clayton, 3168, VIC, Australia; School of Physics, Sydney University, Sydney, 2006, NSW, Australia
| | - Alex Fornito
- Brain and Mental Health Research Hub, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, 770 Blackburn Rd, Clayton, 3168, VIC, Australia
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25
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Fornito A, Arnatkevičiūtė A, Fulcher BD. Bridging the Gap between Connectome and Transcriptome. Trends Cogn Sci 2019; 23:34-50. [DOI: 10.1016/j.tics.2018.10.005] [Citation(s) in RCA: 156] [Impact Index Per Article: 31.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 10/10/2018] [Accepted: 10/23/2018] [Indexed: 11/24/2022]
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26
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Morgan SE, White SR, Bullmore ET, Vértes PE. A Network Neuroscience Approach to Typical and Atypical Brain Development. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2018; 3:754-766. [PMID: 29703679 PMCID: PMC6986924 DOI: 10.1016/j.bpsc.2018.03.003] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Revised: 02/21/2018] [Accepted: 03/01/2018] [Indexed: 12/15/2022]
Abstract
Human brain networks based on neuroimaging data have already proven useful in characterizing both normal and abnormal brain structure and function. However, many brain disorders are neurodevelopmental in origin, highlighting the need to go beyond characterizing brain organization in terms of static networks. Here, we review the fast-growing literature shedding light on developmental changes in network phenotypes. We begin with an overview of recent large-scale efforts to map healthy brain development, and we describe the key role played by longitudinal data including repeated measurements over a long period of follow-up. We also discuss the subtle ways in which healthy brain network development can inform our understanding of disorders, including work bridging the gap between macroscopic neuroimaging results and the microscopic level. Finally, we turn to studies of three specific neurodevelopmental disorders that first manifest primarily in childhood and adolescence/early adulthood, namely psychotic disorders, attention-deficit/hyperactivity disorder, and autism spectrum disorder. In each case we discuss recent progress in understanding the atypical features of brain network development associated with the disorder, and we conclude the review with some suggestions for future directions.
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Affiliation(s)
- Sarah E Morgan
- Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.
| | - Simon R White
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
| | - Edward T Bullmore
- Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough NHS Foundation Trust, Huntingdon, United Kingdom; ImmunoPsychiatry, Immuno-Inflammation Therapeutic Area Unit, GlaxoSmithKline R&D, Stevenage, United Kingdom
| | - Petra E Vértes
- Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
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27
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Anderson KM, Krienen FM, Choi EY, Reinen JM, Yeo BTT, Holmes AJ. Gene expression links functional networks across cortex and striatum. Nat Commun 2018; 9:1428. [PMID: 29651138 PMCID: PMC5897339 DOI: 10.1038/s41467-018-03811-x] [Citation(s) in RCA: 80] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 03/14/2018] [Indexed: 12/12/2022] Open
Abstract
The human brain is comprised of a complex web of functional networks that link anatomically distinct regions. However, the biological mechanisms supporting network organization remain elusive, particularly across cortical and subcortical territories with vastly divergent cellular and molecular properties. Here, using human and primate brain transcriptional atlases, we demonstrate that spatial patterns of gene expression show strong correspondence with limbic and somato/motor cortico-striatal functional networks. Network-associated expression is consistent across independent human datasets and evolutionarily conserved in non-human primates. Genes preferentially expressed within the limbic network (encompassing nucleus accumbens, orbital/ventromedial prefrontal cortex, and temporal pole) relate to risk for psychiatric illness, chloride channel complexes, and markers of somatostatin neurons. Somato/motor associated genes are enriched for oligodendrocytes and markers of parvalbumin neurons. These analyses indicate that parallel cortico-striatal processing channels possess dissociable genetic signatures that recapitulate distributed functional networks, and nominate molecular mechanisms supporting cortico-striatal circuitry in health and disease. The functional connectivity of brain regions can be reflected in a shared molecular architecture. This cross-modal study demonstrates correspondence of spatial patterns of gene expression to limbic and somato/motor cortico-striatal networks in human and non-human primates.
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Affiliation(s)
- Kevin M Anderson
- Department of Psychology, Yale University, New Haven, CT, 06520, USA
| | - Fenna M Krienen
- Department of Genetics, Harvard Medical School, Boston, MA, 02114, USA
| | - Eun Young Choi
- Department of Neurosurgery, Stanford University, Stanford, CA, 94305, USA
| | - Jenna M Reinen
- Department of Psychology, Yale University, New Haven, CT, 06520, USA
| | - B T Thomas Yeo
- Department of Electrical and Computer Engineering, Clinical Imaging Research Centre, Singapore Institute for Neurotechnology and Memory Network Programme, National University of Singapore, Singapore, 117456, Singapore.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Charlestown, MA, 02129, USA
| | - Avram J Holmes
- Department of Psychology, Yale University, New Haven, CT, 06520, USA. .,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Charlestown, MA, 02129, USA. .,Department of Psychiatry, Yale University, New Haven, CT, 06520, USA. .,Department of Psychiatry, Massachusetts General Hospital, Boston, MA, 02114, USA.
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28
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Vogelsang DA, D'Esposito M. Is There Evidence for a Rostral-Caudal Gradient in Fronto-Striatal Loops and What Role Does Dopamine Play? Front Neurosci 2018; 12:242. [PMID: 29706863 PMCID: PMC5906550 DOI: 10.3389/fnins.2018.00242] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 03/27/2018] [Indexed: 11/13/2022] Open
Abstract
Research has shown that the lateral prefrontal cortex (LPFC) may be hierarchically organized along a rostral-caudal functional gradient such that control processing becomes progressively more abstract from caudal to rostral frontal regions. Here, we briefly review the most recent functional MRI, neuropsychological, and electrophysiological evidence in support of a hierarchical LPFC organization. We extend these observations by discussing how such a rostral-caudal gradient may also exist in the striatum and how the dopaminergic system may play an important role in the hierarchical organization of fronto-striatal loops. There is evidence indicating that a rostral-caudal gradient of dopamine receptor density may exist in both frontal and striatal regions. Here we formulate the hypothesis that dopamine may be an important neuromodulator in hierarchical processing, whereby frontal and striatal regions that have higher dopamine receptor density may have a larger influence over regions that exhibit lower dopamine receptor density. We conclude by highlighting directions for future research that will help elucidating the role dopamine might play in hierarchical frontal-striatal interactions.
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Affiliation(s)
- David A Vogelsang
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States.,Department of Psychology, University of California, Berkeley, Berkeley, CA, United States
| | - Mark D'Esposito
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States.,Department of Psychology, University of California, Berkeley, Berkeley, CA, United States
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29
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Arnatkevic̆iūtė A, Fulcher BD, Pocock R, Fornito A. Hub connectivity, neuronal diversity, and gene expression in the Caenorhabditis elegans connectome. PLoS Comput Biol 2018; 14:e1005989. [PMID: 29432412 PMCID: PMC5825174 DOI: 10.1371/journal.pcbi.1005989] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 02/23/2018] [Accepted: 01/19/2018] [Indexed: 11/18/2022] Open
Abstract
Studies of nervous system connectivity, in a wide variety of species and at different scales of resolution, have identified several highly conserved motifs of network organization. One such motif is a heterogeneous distribution of connectivity across neural elements, such that some elements act as highly connected and functionally important network hubs. These brain network hubs are also densely interconnected, forming a so-called rich club. Recent work in mouse has identified a distinctive transcriptional signature of neural hubs, characterized by tightly coupled expression of oxidative metabolism genes, with similar genes characterizing macroscale inter-modular hub regions of the human cortex. Here, we sought to determine whether hubs of the neuronal C. elegans connectome also show tightly coupled gene expression. Using open data on the chemical and electrical connectivity of 279 C. elegans neurons, and binary gene expression data for each neuron across 948 genes, we computed a correlated gene expression score for each pair of neurons, providing a measure of their gene expression similarity. We demonstrate that connections between hub neurons are the most similar in their gene expression while connections between nonhubs are the least similar. Genes with the greatest contribution to this effect are involved in glutamatergic and cholinergic signaling, and other communication processes. We further show that coupled expression between hub neurons cannot be explained by their neuronal subtype (i.e., sensory, motor, or interneuron), separation distance, chemically secreted neurotransmitter, birth time, pairwise lineage distance, or their topological module affiliation. Instead, this coupling is intrinsically linked to the identity of most hubs as command interneurons, a specific class of interneurons that regulates locomotion. Our results suggest that neural hubs may possess a distinctive transcriptional signature, preserved across scales and species, that is related to the involvement of hubs in regulating the higher-order behaviors of a given organism.
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Affiliation(s)
- Aurina Arnatkevic̆iūtė
- Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Ben D. Fulcher
- Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
| | - Roger Pocock
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Anatomy and Developmental Biology, Monash University, Clayton, VIC, Australia
| | - Alex Fornito
- Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
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