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Orwig W, Diez I, Bueichekú E, Pedale T, Parente F, Campolongo P, Schacter DL, Sepulcre J, Santangelo V. Cortical hubs of highly superior autobiographical memory. Cortex 2024; 179:14-24. [PMID: 39094240 DOI: 10.1016/j.cortex.2024.06.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 05/10/2024] [Accepted: 06/19/2024] [Indexed: 08/04/2024]
Abstract
Highly Superior Autobiographical Memory (HSAM) is a rare form of enhanced memory in which individuals demonstrate an extraordinary ability to remember details of their personal lives with high levels of accuracy and vividness. Neuroimaging studies have identified brain regions - specifically, midline areas within the default network - associated with remembering events from one's past. Extending this research on the neural underpinnings of autobiographical memory, the present study utilizes graph theory analyses to compare functional brain connectivity in a cohort of HSAM (n = 12) and control participants (n = 29). We perform seed-based analysis in resting-state fMRI data to assess how specific cortical regions within the autobiographical memory network are differentially connected in HSAM individuals. Additionally, we apply a whole-brain connectivity analysis to identify differences in brain hub-network topology associated with enhanced autobiographical memory. Seed-based results show converging patterns of increased connectivity in HSAM across midline areas. Whole-brain analysis also reveals enhanced connectivity across medial prefrontal and posterior cingulate cortex in HSAM individuals. Together, these results extend prior research, highlighting cortical hubs within the default network associated with enhanced autobiographical memory.
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Affiliation(s)
- William Orwig
- Department of Psychology, Harvard University, Cambridge, MA, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ibai Diez
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Elisenda Bueichekú
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Tiziana Pedale
- Functional Neuroimaging Laboratory, Fondazione Santa Lucia IRCCS, Via Ardeatina 306, 00179 Rome, Italy
| | - Fabrizio Parente
- Functional Neuroimaging Laboratory, Fondazione Santa Lucia IRCCS, Via Ardeatina 306, 00179 Rome, Italy
| | - Patrizia Campolongo
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy; CERC, Fondazione Santa Lucia IRCCS, Via del Fosso di Fiorano 64, 00143 Rome, Italy
| | | | - Jorge Sepulcre
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Valerio Santangelo
- Functional Neuroimaging Laboratory, Fondazione Santa Lucia IRCCS, Via Ardeatina 306, 00179 Rome, Italy; Department of Philosophy, Social Sciences & Education, University of Perugia, Piazza G. Ermini 1, 06123 Perugia, Italy.
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2
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Guan Z, Yu J, Shi Z, Liu X, Yu R, Lai T, Yang C, Dong H, Chen R, Wei L. Dynamic graph transformer network via dual-view connectivity for autism spectrum disorder identification. Comput Biol Med 2024; 174:108415. [PMID: 38599070 DOI: 10.1016/j.compbiomed.2024.108415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 03/17/2024] [Accepted: 04/03/2024] [Indexed: 04/12/2024]
Abstract
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that requires objective and accurate identification methods for effective early intervention. Previous population-based methods via functional connectivity (FC) analysis ignore the differences between positive and negative FCs, which provide the potential information complementarity. And they also require additional information to construct a pre-defined graph. Meanwhile, two challenging demand attentions are the imbalance of performance caused by the class distribution and the inherent heterogeneity of multi-site data. In this paper, we propose a novel dynamic graph Transformer network based on dual-view connectivity for ASD Identification. It is based on the Autoencoders, which regard the input feature as individual feature and without any inductive bias. First, a dual-view feature extractor is designed to extract individual and complementary information from positive and negative connectivity. Then Graph Transformer network is innovated with a hot plugging K-Nearest Neighbor (KNN) algorithm module which constructs a dynamic population graph without any additional information. Additionally, we introduce the PolyLoss function and the Vrex method to address the class imbalance and improve the model's generalizability. The evaluation experiment on 1102 subjects from the ABIDE I dataset demonstrates our method can achieve superior performance over several state-of-the-art methods and satisfying generalizability for ASD identification.
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Affiliation(s)
- Zihao Guan
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Jiaming Yu
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Zhenshan Shi
- Department of Radiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou, 350002, China
| | - Xiumei Liu
- Developmental and Behavior Pediatrics Department, Fujian Children's Hospital - Fujian Branch of Shanghai Children's Medical Center, Fuzhou, 350002, China; College of Clinical Medicine for Obstetrics Gynecology and Pediatrics, Fujian Medical University, Fuzhou, 350012, China
| | - Renping Yu
- School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, 450001, China
| | - Taotao Lai
- College of Computer and Control Engineering, Minjiang University, Fuzhou, 350108, China
| | - Changcai Yang
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Heng Dong
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Riqing Chen
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Lifang Wei
- College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou, 350002, China; Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
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3
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Filippi M, Cividini C, Basaia S, Spinelli EG, Castelnovo V, Leocadi M, Canu E, Agosta F. Age-related vulnerability of the human brain connectome. Mol Psychiatry 2023; 28:5350-5358. [PMID: 37414925 DOI: 10.1038/s41380-023-02157-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 06/05/2023] [Accepted: 06/22/2023] [Indexed: 07/08/2023]
Abstract
Multifactorial models integrating brain variables at multiple scales are warranted to investigate aging and its relationship with neurodegeneration. Our aim was to evaluate how aging affects functional connectivity of pivotal regions of the human brain connectome (i.e., hubs), which represent potential vulnerability 'stations' to aging, and whether such effects influence the functional and structural changes of the whole brain. We combined the information of the functional connectome vulnerability, studied through an innovative graph-analysis approach (stepwise functional connectivity), with brain cortical thinning in aging. Using data from 128 cognitively normal participants (aged 20-85 years), we firstly investigated the topological functional network organization in the optimal healthy condition (i.e., young adults) and observed that fronto-temporo-parietal hubs showed a highly direct functional connectivity with themselves and among each other, while occipital hubs showed a direct functional connectivity within occipital regions and sensorimotor areas. Subsequently, we modeled cortical thickness changes over lifespan, revealing that fronto-temporo-parietal hubs were among the brain regions that changed the most, whereas occipital hubs showed a quite spared cortical thickness across ages. Finally, we found that cortical regions highly functionally linked to the fronto-temporo-parietal hubs in healthy adults were characterized by the greatest cortical thinning along the lifespan, demonstrating that the topology and geometry of hub functional connectome govern the region-specific structural alterations of the brain regions.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
| | - Camilla Cividini
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Edoardo G Spinelli
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Veronica Castelnovo
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Michela Leocadi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
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Orwig W, Setton R, Diez I, Bueichekú E, Meyer ML, Tamir DI, Sepulcre J, Schacter DL. Creativity at rest: Exploring functional network connectivity of creative experts. Netw Neurosci 2023; 7:1022-1033. [PMID: 37781148 PMCID: PMC10473280 DOI: 10.1162/netn_a_00317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 03/31/2023] [Indexed: 10/03/2023] Open
Abstract
The neuroscience of creativity seeks to disentangle the complex brain processes that underpin the generation of novel ideas. Neuroimaging studies of functional connectivity, particularly functional magnetic resonance imaging (fMRI), have revealed individual differences in brain network organization associated with creative ability; however, much of the extant research is limited to laboratory-based divergent thinking measures. To overcome these limitations, we compare functional brain connectivity in a cohort of creative experts (n = 27) and controls (n = 26) and examine links with creative behavior. First, we replicate prior findings showing reduced connectivity in visual cortex related to higher creative performance. Second, we examine whether this result is driven by integrated or segregated connectivity. Third, we examine associations between functional connectivity and vivid distal simulation separately in creative experts and controls. In accordance with past work, our results show reduced connectivity to the primary visual cortex in creative experts at rest. Additionally, we observe a negative association between distal simulation vividness and connectivity to the lateral visual cortex in creative experts. Taken together, these results highlight connectivity profiles of highly creative people and suggest that creative thinking may be related to, though not fully redundant with, the ability to vividly imagine the future.
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Affiliation(s)
- William Orwig
- Department of Psychology, Harvard University, Cambridge, MA, USA
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Roni Setton
- Department of Psychology, Harvard University, Cambridge, MA, USA
| | - Ibai Diez
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Elisenda Bueichekú
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Meghan L. Meyer
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - Diana I. Tamir
- Department of Psychology, Princeton University, Princeton, NJ, USA
| | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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5
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Klimova A, Breukelaar IA, Bryant RA, Korgaonkar MS. A comparison of the functional connectome in mild traumatic brain injury and post-traumatic stress disorder. Hum Brain Mapp 2022; 44:813-824. [PMID: 36206284 PMCID: PMC9842915 DOI: 10.1002/hbm.26101] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 08/25/2022] [Accepted: 09/07/2022] [Indexed: 01/25/2023] Open
Abstract
Post-traumatic stress disorder (PTSD) and mild traumatic brain injury (mTBI) often co-occur in the context of threat to one's life. These conditions also have an overlapping symptomatology and include symptoms of anxiety, poor concentration and memory problems. A major challenge has been articulating the underlying neurobiology of these overlapping conditions. The primary aim of this study was to compare intrinsic functional connectivity between mTBI (without PTSD) and PTSD (without mTBI). The study included functional MRI data from 176 participants: 42 participants with mTBI, 67 with PTSD and a comparison group of 66 age and sex-matched healthy controls. We used network-based statistical analyses for connectome-wide comparisons of intrinsic functional connectivity between mTBI relative to PTSD and controls. Our results showed no connectivity differences between mTBI and PTSD groups. However, we did find that mTBI had significantly reduced connectivity relative to healthy controls within an extensive network of regions including default mode, executive control, visual and auditory networks. The mTBI group also displayed hyperconnectivity between dorsal and ventral attention networks and perceptual regions. The PTSD group also demonstrated abnormal connectivity within these networks relative to controls. Connectivity alterations were not associated with severity of PTSD or post-concussive symptoms in either clinical group. Taken together, the similar profiles of intrinsic connectivity alterations in these two conditions provide neural evidence that can explain, in part, the overlapping symptomatology between mTBI and PTSD.
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Affiliation(s)
- Aleksandra Klimova
- Brain Dynamics Centre, Westmead Institute for Medical ResearchThe University of SydneyWestmeadAustralia
| | - Isabella A. Breukelaar
- Brain Dynamics Centre, Westmead Institute for Medical ResearchThe University of SydneyWestmeadAustralia,School of PsychologyUniversity of New South WalesSydneyAustralia
| | - Richard A. Bryant
- Brain Dynamics Centre, Westmead Institute for Medical ResearchThe University of SydneyWestmeadAustralia,School of PsychologyUniversity of New South WalesSydneyAustralia
| | - Mayuresh S. Korgaonkar
- Brain Dynamics Centre, Westmead Institute for Medical ResearchThe University of SydneyWestmeadAustralia,Department of Psychiatry, Faculty of Medicine and HealthUniversity of SydneyWestmeadAustralia
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Orwig W, Diez I, Bueichekú E, Kelly CA, Sepulcre J, Schacter DL. Intentionality of Self-Generated Thought: Contributions of Mind Wandering to Creativity. CREATIVITY RESEARCH JOURNAL 2022; 35:471-480. [PMID: 37576950 PMCID: PMC10414778 DOI: 10.1080/10400419.2022.2120286] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Indexed: 11/03/2022]
Abstract
Studies suggest that internally oriented cognitive processes are central to creativity. Here, we distinguish between intentional and unintentional forms of mind wandering and explore their behavioral and neural correlates. We used a sample of 155 healthy adults from the mind-brain-body dataset, all of whom completed resting-state fMRI scans and trait-level measures of mind wandering. We analyzed intentional and unintentional mind wandering tendencies using self-report measures. Next, we explored the relationship between mind wandering tendencies and creativity, as measured by a divergent thinking task. Finally, we describe patterns of resting-state network connectivity associated with mind wandering, using graph theory analysis. At the behavioral level, results showed a significant positive association between creativity and both intentional and unintentional mind wandering. Neuroimaging analysis revealed higher weighted degree connectivity associated with both forms of mind wandering, implicating core regions of the default network and the left temporal pole. We observed topological connectivity differences within the default network: intentional mind wandering was associated with degree connectivity in posterior regions, whereas unintentional mind wandering showed greater involvement of prefrontal areas. Overall, the findings highlight patterns of resting-state network connectivity associated with intentional and unintentional mind wandering, and provide novel evidence of a link between mind wandering and creativity.
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Affiliation(s)
- William Orwig
- Harvard University, Department of Psychology, Cambridge, Massachusetts
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts
| | - Ibai Diez
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts
| | - Elisenda Bueichekú
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts
| | - Christopher A. Kelly
- Department of Experimental Psychology, University College London, London
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, London
| | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts
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7
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Basaia S, Agosta F, Francia A, Cividini C, Balestrino R, Stojkovic T, Stankovic I, Markovic V, Sarasso E, Gardoni A, De Micco R, Albano L, Stefanova E, Kostic VS, Filippi M. Cerebro-cerebellar motor networks in clinical subtypes of Parkinson's disease. NPJ Parkinsons Dis 2022; 8:113. [PMID: 36068246 PMCID: PMC9448730 DOI: 10.1038/s41531-022-00377-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 08/12/2022] [Indexed: 11/30/2022] Open
Abstract
Parkinson's disease (PD) patients can be classified in tremor-dominant (TD) and postural-instability-and-gait-disorder (PIGD) motor subtypes. PIGD represents a more aggressive form of the disease that TD patients have a potentiality of converting into. This study investigated functional alterations within the cerebro-cerebellar system in PD-TD and PD-PIGD patients using stepwise functional connectivity (SFC) analysis and identified neuroimaging features that predict TD to PIGD conversion. Thirty-two PD-TD, 26 PD-PIGD patients and 60 healthy controls performed clinical/cognitive evaluations and resting-state functional MRI (fMRI). Four-year clinical follow-up data were available for 28 PD-TD patients, who were classified in 10 converters (cTD-PD) and 18 non-converters (ncTD-PD) to PIGD. The cerebellar seed-region was identified using a fMRI motor task. SFC analysis, characterizing regions that connect brain areas to the cerebellar seed at different levels of link-step distances, evaluated similar and divergent alterations in PD-TD and PD-PIGD. The discriminatory power of clinical data and/or SFC in distinguishing cPD-TD from ncPD-TD patients was assessed using ROC curve analysis. Compared to PD-TD, PD-PIGD patients showed decreased SFC in temporal lobe and occipital lobes and increased SFC in cerebellar cortex and ponto-medullary junction. Considering the subtype-conversion analysis, cPD-TD patients were characterized by increased SFC in temporal and occipital lobes and in cerebellum and ponto-medullary junction relative to ncPD-TD group. Combining clinical and SFC data, ROC curves provided the highest classification power to identify conversion to PIGD. These findings provide novel insights into the pathophysiology underlying different PD motor phenotypes and a potential tool for early characterization of PD-TD patients at risk of conversion to PIGD.
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Affiliation(s)
- Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Alessandro Francia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Camilla Cividini
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Roberta Balestrino
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Tanja Stojkovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Iva Stankovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Vladana Markovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Elisabetta Sarasso
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Laboratory of Movement Analysis, San Raffaele Scientific Institute, Milan, Italy
| | - Andrea Gardoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Laboratory of Movement Analysis, San Raffaele Scientific Institute, Milan, Italy
| | - Rosita De Micco
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Napoli, Italy
| | - Luigi Albano
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Elka Stefanova
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Vladimir S Kostic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Vita-Salute San Raffaele University, Milan, Italy.
- Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
- Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
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8
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MVS-GCN: A prior brain structure learning-guided multi-view graph convolution network for autism spectrum disorder diagnosis. Comput Biol Med 2022; 142:105239. [DOI: 10.1016/j.compbiomed.2022.105239] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 01/13/2022] [Accepted: 01/16/2022] [Indexed: 11/22/2022]
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Basaia S, Agosta F, Diez I, Bueichekú E, d'Oleire Uquillas F, Delgado-Alvarado M, Caballero-Gaudes C, Rodriguez-Oroz M, Stojkovic T, Kostic VS, Filippi M, Sepulcre J. Neurogenetic traits outline vulnerability to cortical disruption in Parkinson's disease. Neuroimage Clin 2022; 33:102941. [PMID: 35091253 PMCID: PMC8800137 DOI: 10.1016/j.nicl.2022.102941] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 12/03/2021] [Accepted: 01/10/2022] [Indexed: 01/18/2023]
Abstract
The genetic traits that underlie vulnerability to neuronal damage across specific brain circuits in Parkinson's disease (PD) remain to be elucidated. In this study, we characterized the brain topological intersection between propagating connectivity networks in controls and PD participants and gene expression patterns across the human cortex - such as the SNCA gene. We observed that brain connectivity originated from PD-related pathology epicenters in the brainstem recapitulated the anatomical distribution of alpha-synuclein histopathology in postmortem data. We also discovered that the gene set most related to cortical propagation patterns of PD-related pathology was primarily involved in microtubule cellular components. Thus, this study sheds light on new avenues for enhancing detection of PD neuronal vulnerability via an evaluation of in vivo connectivity trajectories across the human brain and successful integration of neuroimaging-genetic strategies.
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Affiliation(s)
- Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Ibai Diez
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Elisenda Bueichekú
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Federico d'Oleire Uquillas
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Manuel Delgado-Alvarado
- Neurology Department, Sierrallana Hospital, Torrelavega, Spain; IDIVAL, Valdecilla Biomedical Research Institute, Santander, Spain; Biomedical Research Networking Center for Mental Health (CIBERSAM), Madrid, Spain
| | | | - MariCruz Rodriguez-Oroz
- Neurology Department, Clínica Universidad de Navarra, Neuroscience Unit, CIMA Universidad de Navarra, Spain
| | - Tanja Stojkovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Vladimir S Kostic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute and Vita-Salute San Raffaele University, Milan, Italy
| | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
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Neurogenetics of dynamic connectivity patterns associated with obsessive-compulsive symptoms in healthy children. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2021; 2:411-420. [DOI: 10.1016/j.bpsgos.2021.11.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 10/28/2021] [Accepted: 11/14/2021] [Indexed: 01/31/2023] Open
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11
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Costumero V, Rosell Negre P, Bustamante JC, Fuentes‐Claramonte P, Adrián‐Ventura J, Palomar‐García M, Miró‐Padilla A, Llopis JJ, Sepulcre J, Barrós‐Loscertales A. Distance disintegration characterizes node-level topological dysfunctions in cocaine addiction. Addict Biol 2021; 26:e13072. [PMID: 34137121 DOI: 10.1111/adb.13072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 05/07/2021] [Accepted: 06/08/2021] [Indexed: 11/30/2022]
Abstract
Previous investigations have used global graph theory measures in order to disentangle the complexity of the neural reorganizations occurring in cocaine use disorder (CUD). However, how these global topological alterations map into individual brain network areas remains unknown. In this study, we used resting state functional magnetic resonance imaging (fMRI) data to investigate node-level topological dysfunctions in CUD. The sample was composed of 32 individuals with CUD and 32 healthy controls, matched in age, years of education and intellectual functioning. Graph theory measures of optimal connectivity distance, node strength, nodal efficiency and clustering coefficient were estimated in each participant using voxel-wise functional connectivity connectomes. CUD individuals as compared with healthy controls showed higher optimal connectivity distances in ventral striatum, insula, cerebellum, temporal cortex, lateral orbitofrontal cortex, middle frontal cortex and left hippocampus. Furthermore, clinical measures quantifying severity of dependence were positively related with optimal connectivity distances in the right rolandic operculum and the right lateral orbitofrontal cortex, whereas length of abstinence was negatively associated with optimal connectivity distances in the right temporal pole and the left insula. Our results reveal a topological distancing of cognitive and affective related areas in addiction, suggesting an overall reduction in the communication capacity of these regions.
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Affiliation(s)
- Víctor Costumero
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology University Jaume I Castellón de la Plana Spain
| | - Patricia Rosell Negre
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology University Jaume I Castellón de la Plana Spain
| | | | | | - Jesús Adrián‐Ventura
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology University Jaume I Castellón de la Plana Spain
| | - María‐Ángeles Palomar‐García
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology University Jaume I Castellón de la Plana Spain
| | - Anna Miró‐Padilla
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology University Jaume I Castellón de la Plana Spain
| | - Juan José Llopis
- Addictive Behaviors Unit San Agustín Hospital General Universitario de Castellón Castellón de la Plana Spain
| | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Department of Radiology Massachusetts General Hospital and Harvard Medical School Boston Massachusetts USA
| | - Alfonso Barrós‐Loscertales
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology University Jaume I Castellón de la Plana Spain
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12
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Braund TA, Breukelaar IA, Griffiths K, Tillman G, Palmer DM, Bryant R, Phillips ML, Harris AWF, Korgaonkar MS. Intrinsic Functional Connectomes Characterize Neuroticism in Major Depressive Disorder and Predict Antidepressant Treatment Outcomes. BIOLOGICAL PSYCHIATRY: COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2021; 7:276-284. [PMID: 34363999 DOI: 10.1016/j.bpsc.2021.07.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 06/18/2021] [Accepted: 07/20/2021] [Indexed: 12/28/2022]
Abstract
BACKGROUND Antidepressant efficacy in people with major depressive disorder (MDD) remains modest, yet identifying treatment predictive neurobiological markers may improve outcomes. While disruptions in functional connectivity within and between large-scale brain networks predict poorer treatment outcome, it is unclear whether higher trait neuroticism - which has been associated with generally poorer outcome - contributes to these disruptions and to antidepressant-specific treatment outcomes. Here, we used whole-brain functional connectivity analysis to identify a neural connectomic signature of neuroticism and tested whether this signature predicted antidepressant treatment outcome. METHOD Participants were 229 adults with MDD and 68 healthy controls who underwent functional MRI and were assessed on clinical features at baseline. MDD participants were then randomized to one of three commonly prescribed antidepressants and after 8 weeks completed a second functional MRI and were reassessed for depressive symptom remission/response. Baseline intrinsic functional connectivity between each pair of 436 brain regions were analysed using network-based statistics to identify connectomic features associated with neuroticism. Features were then assessed on their ability to predict treatment outcome and whether they changed after 8 weeks of treatment. RESULTS Higher baseline neuroticism was associated with greater connectivity within and between the salience, executive control, and somatomotor brain networks. Greater connectivity across these networks predicted poorer treatment outcome that was not mediated by baseline neuroticism, and connectivity strength decreased after antidepressant treatment. CONCLUSIONS Our findings demonstrate that neuroticism is associated with organization of intrinsic neural networks that predict treatment outcome, elucidating its biological underpinnings and opportunity for better treatment personalization.
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Affiliation(s)
- Taylor A Braund
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Sydney, NSW, Australia; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia; Total Brain, Sydney, NSW, Australia.
| | - Isabella A Breukelaar
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Sydney, NSW, Australia; School of Psychology, University of New South Wales, Sydney, Australia
| | - Kristi Griffiths
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Sydney, NSW, Australia
| | - Gabriel Tillman
- School of Science, Psychology and Sport, Federation University, Australia
| | - Donna M Palmer
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Sydney, NSW, Australia; Total Brain, Sydney, NSW, Australia
| | - Richard Bryant
- School of Psychology, University of New South Wales, Sydney, Australia
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Anthony W F Harris
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Sydney, NSW, Australia; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Mayuresh S Korgaonkar
- Brain Dynamics Centre, The Westmead Institute for Medical Research, Sydney, NSW, Australia; Sydney Medical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia; School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
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13
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Early-life trauma endophenotypes and brain circuit-gene expression relationships in functional neurological (conversion) disorder. Mol Psychiatry 2021; 26:3817-3828. [PMID: 32051548 PMCID: PMC7423688 DOI: 10.1038/s41380-020-0665-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Revised: 01/02/2020] [Accepted: 01/28/2020] [Indexed: 12/14/2022]
Abstract
Functional neurological (conversion) disorder (FND) is a neuropsychiatric condition whereby individuals present with sensorimotor symptoms incompatible with other neurological disorders. Early-life maltreatment (ELM) is a risk factor for developing FND, yet few studies have investigated brain network-trauma relationships in this population. In this neuroimaging-gene expression study, we used two graph theory approaches to elucidate ELM subtype effects on resting-state functional connectivity architecture in 30 patients with motor FND. Twenty-one individuals with comparable depression, anxiety, and ELM scores were used as psychiatric controls. Thereafter, we compared trauma endophenotypes in FND with regional differences in transcriptional gene expression as measured by the Allen Human Brain Atlas (AHBA). In FND patients only, we found that early-life physical abuse severity, and to a lesser extent physical neglect, correlated with corticolimbic weighted-degree functional connectivity. Connectivity profiles influenced by physical abuse occurred in limbic (amygdalar-hippocampal), paralimbic (cingulo-insular and ventromedial prefrontal), and cognitive control (ventrolateral prefrontal) areas, as well as in sensorimotor and visual cortices. These findings held adjusting for individual differences in depression/anxiety, PTSD, and motor phenotypes. In FND, physical abuse also correlated with amygdala and insula coupling to motor cortices. In exploratory analyses, physical abuse correlated connectivity maps overlapped with the AHBA spatial expression of three gene clusters: (i) neuronal morphogenesis and synaptic transmission genes in limbic/paralimbic areas; (ii) locomotory behavior and neuronal generation genes in left-lateralized structures; and (iii) nervous system development and cell motility genes in right-lateralized structures. These circuit-specific architectural profiles related to individual differences in childhood physical abuse burden advance our understanding of the pathophysiology of FND.
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14
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Orwig W, Diez I, Bueichekú E, Vannini P, Beaty R, Sepulcre J. Cortical Networks of Creative Ability Trace Gene Expression Profiles of Synaptic Plasticity in the Human Brain. Front Hum Neurosci 2021; 15:694274. [PMID: 34381343 PMCID: PMC8350487 DOI: 10.3389/fnhum.2021.694274] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 06/30/2021] [Indexed: 01/18/2023] Open
Abstract
The ability to produce novel ideas is central to societal progress and innovation; however, little is known about the biological basis of creativity. Here, we investigate the organization of brain networks that support creativity by combining functional neuroimaging data with gene expression information. Given the multifaceted nature of creative thinking, we hypothesized that distributed connectivity would not only be related to individual differences in creative ability, but also delineate the cortical distributions of genes involved in synaptic plasticity. We defined neuroimaging phenotypes using a graph theory approach that detects local and distributed network circuits, then characterized the spatial associations between functional connectivity and cortical gene expression distributions. Our findings reveal strong spatial correlations between connectivity maps and sets of genes devoted to synaptic assembly and signaling. This connectomic-transcriptome approach thus identifies gene expression profiles associated with high creative ability, linking cognitive flexibility to neural plasticity in the human brain.
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Affiliation(s)
- William Orwig
- Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Ibai Diez
- Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Elisenda Bueichekú
- Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
| | - Patrizia Vannini
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, United States
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Roger Beaty
- Department of Psychology, The Pennsylvania State University, University Park, PA, United States
| | - Jorge Sepulcre
- Department of Radiology, Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
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15
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Zacharopoulos G, Emir U, Cohen Kadosh R. The cross-sectional interplay between neurochemical profile and brain connectivity. Hum Brain Mapp 2021; 42:2722-2733. [PMID: 33835605 PMCID: PMC8127145 DOI: 10.1002/hbm.25396] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 02/11/2021] [Accepted: 02/21/2021] [Indexed: 01/05/2023] Open
Abstract
Neurochemical profile and brain connectivity are both critical aspects of brain function. However, our knowledge of their interplay across development is currently poor. We combined single-voxel magnetic resonance spectroscopy and resting functional magnetic resonance imaging in a cross-sectional sample spanning from childhood to adulthood which was reassessed in ~1.5 years (N = 293). We revealed the developmental trajectories of 20 neurochemicals in two key developmental brain regions (the intraparietal sulcus, IPS, and the middle frontal gyrus, MFG). We found that certain neurochemicals exhibited similar developmental trajectories across the two regions, while other trajectories were region-specific. Crucially, we mapped the connectivity of the brain regions IPS and MFG to the rest of the brain across development as a function of regional glutamate and GABA concentration. We demonstrated that glutamate concentration within the IPS is modulated by age in explaining IPS connectivity with frontal, temporal and parietal regions. In mature participants, higher glutamate within the IPS was related to more negative connectivity while the opposite pattern was found for younger participants. Our findings offer specific developmental insights on the interplay between the brain's resting activity and the glutamatergic system both of which are crucial for regulating normal functioning and are dysregulated in several clinical conditions.
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Affiliation(s)
- George Zacharopoulos
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental PsychologyUniversity of OxfordOxfordUK
| | - Uzay Emir
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental PsychologyUniversity of OxfordOxfordUK
- School of Health Sciences, College of Health and Human SciencesPurdue UniversityWest LafayetteIndianaUSA
| | - Roi Cohen Kadosh
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental PsychologyUniversity of OxfordOxfordUK
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16
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Breukelaar IA, Bryant RA, Korgaonkar MS. The functional connectome in posttraumatic stress disorder. Neurobiol Stress 2021; 14:100321. [PMID: 33912628 PMCID: PMC8065342 DOI: 10.1016/j.ynstr.2021.100321] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 02/15/2021] [Accepted: 03/18/2021] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Previous fMRI studies of posttraumatic stress disorder (PTSD) have investigated region-specific alterations in intrinsic connectivity but connectome-wide changes in connectivity are yet to be characterized. Understanding the neurobiology of this is important to develop novel treatment interventions for PTSD. This study aims to identify connectome-wide disruptions in PTSD to provide a more comprehensive analysis of nseural networks in this disorder. METHODS A functional MRI scan was completed by 138 individuals (67 PTSD and 71 non-trauma-exposed healthy controls [HC]). For every individual, inter-regional intrinsic functional connectivity was estimated between 436 brain regions, comprising intra and inter-network connectivity of eight large-scale brain networks. Group-wise differences between PTSD and HC were investigated using network-based statistics at a family-wise error rate of p < 0.05. Significant network differences were then further investigated in 27 individuals with trauma exposure but no PTSD [TC]). RESULTS Compared to HC, PTSD displayed lower intrinsic functional connectivity in a network of 203 connections between 420 regions within and between mid-posterior default mode, central executive, limbic, visual and somatomotor regions. Additionally, PTSD displayed higher connectivity across a network of 50 connections from thalamic and limbic to sensory and default-mode regions. Connectivity in TC in both these networks was intermediate and significantly different to PTSD and HC. CONCLUSION A large-scale imbalance between hypoconnectivity of higher-order cortical networks and hyperconnectivity of emotional and arousal response systems seems to occur on a sliding scale from trauma exposure to clinical manifestation as PTSD. Novel interventions that target this systemic functional imbalance could provide potential mitigation of PTSD.
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Affiliation(s)
- Isabella A. Breukelaar
- Brain Dynamics Centre, Westmead Institute for Medical Research, University of Sydney, Westmead, NSW, Australia
- School of Psychology, University of New South Wales, Sydney, Australia
| | - Richard A. Bryant
- Brain Dynamics Centre, Westmead Institute for Medical Research, University of Sydney, Westmead, NSW, Australia
- School of Psychology, University of New South Wales, Sydney, Australia
| | - Mayuresh S. Korgaonkar
- Brain Dynamics Centre, Westmead Institute for Medical Research, University of Sydney, Westmead, NSW, Australia
- Discipline of Psychiatry, Sydney Medical School, Westmead, NSW, Australia
- School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
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17
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Ofoghi Z, Rohr CS, Dewey D, Bray S, Yeates KO, Noel M, Barlow KM. Functional connectivity of the anterior cingulate cortex with pain-related regions in children with post-traumatic headache. CEPHALALGIA REPORTS 2021. [DOI: 10.1177/25158163211009477] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Introduction: Post-traumatic headaches (PTH) are common following mild traumatic brain injury (mTBI). There is evidence of altered central pain processing in adult PTH; however, little is known about how children with PTH process pain. The anterior cingulate cortex (ACC) plays a critical role in descending central pain modulation. In this study, we explored whether the functional connectivity (FC) of the ACC is altered in children with PTH. Methods: In this case-control study, we investigated resting-state FC of 5 ACC seeds (caudal, dorsal, rostral, perigenual, and subgenual) in children with PTH ( n = 73) and without PTH ( n = 29) following mTBI, and healthy controls ( n = 27). Post-concussion symptoms were assessed using the Post-Concussion Symptom Inventory and the Child Health Questionnaire. Resting-state functional Magnetic Resonance Imaging (fMRI) data were used to generate maps of ACC FC. Group-level comparisons were performed within a target mask comprised of pain-related regions using FSL Randomise. Results: We found decreased FC between the right perigenual ACC and the left cerebellum, and increased FC between the right subgenual ACC and the left dorsolateral prefrontal cortex in children with PTH compared to healthy controls. The ACC FC in children without PTH following mTBI did not differ from the group with PTH or healthy controls. FC between rostral and perigenual ACC seeds and the cerebellum was increased in children with PTH with pre-injury headaches compared to those with PTH without pre-injury headaches. There was a positive relationship between PTH severity and rostral ACC FC with the bilateral thalamus, right hippocampus and periaqueductal gray. Conclusions: Central pain processing is altered in children with PTH. Pre-existing headaches help to drive this process. Trial registration: The PlayGame Trial was registered in ClinicalTrials.gov database ( ClinicalTrials.gov Identifier: NCT01874847).
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Affiliation(s)
- Zahra Ofoghi
- Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Christiane S Rohr
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada
| | - Deborah Dewey
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Paediatrics, Cumming School of Medicine University of Calgary, Calgary, Alberta, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Owerko Centre at the Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Signe Bray
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Alberta, Canada
| | - Keith Owen Yeates
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
| | - Melanie Noel
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
| | - Karen M Barlow
- Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Paediatrics, Cumming School of Medicine University of Calgary, Calgary, Alberta, Canada
- Paediatric Neurology Child Health Research Centre, Faculty of Medicine, The University of Queensland, Brisbane, Queensland, Australia
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18
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Maallo AMS, Granovetter MC, Freud E, Kastner S, Pinsk MA, Glen D, Patterson C, Behrmann M. Large-scale resculpting of cortical circuits in children after surgical resection. Sci Rep 2020; 10:21589. [PMID: 33299002 PMCID: PMC7725819 DOI: 10.1038/s41598-020-78394-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 11/24/2020] [Indexed: 11/09/2022] Open
Abstract
Despite the relative successes in the surgical treatment of pharmacoresistant epilepsy, there is rather little research on the neural (re)organization that potentially subserves behavioral compensation. Here, we examined the post-surgical functional connectivity (FC) in children and adolescents who have undergone unilateral cortical resection and, yet, display remarkably normal behavior. Conventionally, FC has been investigated in terms of the mean correlation of the BOLD time courses extracted from different brain regions. Here, we demonstrated the value of segregating the voxel-wise relationships into mutually exclusive populations that were either positively or negatively correlated. While, relative to controls, the positive correlations were largely normal, negative correlations among networks were increased. Together, our results point to reorganization in the contralesional hemisphere, possibly suggesting competition for cortical territory due to the demand for representation of function. Conceivably, the ubiquitous negative correlations enable the differentiation of function in the reduced cortical volume following a unilateral resection.
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Affiliation(s)
- Anne Margarette S Maallo
- Department of Psychology and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, USA
| | - Michael C Granovetter
- Department of Psychology and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, USA.,School of Medicine, University of Pittsburgh, Pittsburgh, USA
| | - Erez Freud
- Department of Psychology, The Centre for Vision Research, York University, Toronto, Canada
| | - Sabine Kastner
- Princeton Neuroscience Institute, Princeton University, Princeton, USA.,Department of Psychology, Princeton University, Princeton, USA
| | - Mark A Pinsk
- Princeton Neuroscience Institute, Princeton University, Princeton, USA
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, USA
| | | | - Marlene Behrmann
- Department of Psychology and Neuroscience Institute, Carnegie Mellon University, Pittsburgh, USA.
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19
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Costumero V, d'Oleire Uquillas F, Diez I, Andorrà M, Basaia S, Bueichekú E, Ortiz-Terán L, Belloch V, Escudero J, Ávila C, Sepulcre J. Distance disintegration delineates the brain connectivity failure of Alzheimer's disease. Neurobiol Aging 2020; 88:51-60. [PMID: 31941578 PMCID: PMC7085436 DOI: 10.1016/j.neurobiolaging.2019.12.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 12/04/2019] [Accepted: 12/06/2019] [Indexed: 01/03/2023]
Abstract
Alzheimer's disease (AD) is associated with brain network dysfunction. Network-based investigations of brain connectivity have mainly focused on alterations in the strength of connectivity; however, the network breakdown in AD spectrum is a complex scenario in which multiple pathways of connectivity are affected. To integrate connectivity changes that occur under AD-related conditions, here we developed a novel metric that computes the connectivity distance between cortical regions at the voxel level (or nodes). We studied 114 individuals with mild cognitive impairment, 24 with AD, and 27 healthy controls. Results showed that areas of the default mode network, salience network, and frontoparietal network display a remarkable network separation, or greater connectivity distances, from the rest of the brain. Furthermore, this greater connectivity distance was associated with lower global cognition. Overall, the investigation of AD-related changes in paths and distances of connectivity provides a novel framework for characterizing subjects with cognitive impairment; a framework that integrates the overall network topology changes of the brain and avoids biases toward unreferenced connectivity effects.
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Affiliation(s)
- Víctor Costumero
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center for Brain and Cognition, University Pompeu Fabra, Barcelona, Catalonia, Spain; Neuropsychology and Functional Neuroimaging Group, Department of basic Psychology, University Jaume I, Castellón, Valencian Community, Spain
| | | | - Ibai Diez
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Neurotechnology Laboratory, Tecnalia Health Department, Basque Country, Spain
| | - Magi Andorrà
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Center of Neuroimmunology, Department of Neurology, Hospital Clinic of Barcelona, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), University of Barcelona, Barcelona, Catalonia, Spain
| | - Silvia Basaia
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Neuroimaging Research Unit Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Elisenda Bueichekú
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Neuropsychology and Functional Neuroimaging Group, Department of basic Psychology, University Jaume I, Castellón, Valencian Community, Spain
| | - Laura Ortiz-Terán
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Joaquin Escudero
- Department of Neurology, General Hospital of Valencia, Valencia, Valencian Community, Spain
| | - César Ávila
- Neuropsychology and Functional Neuroimaging Group, Department of basic Psychology, University Jaume I, Castellón, Valencian Community, Spain
| | - Jorge Sepulcre
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
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