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Klug S, Murgaš M, Godbersen GM, Hacker M, Lanzenberger R, Hahn A. Synaptic signaling modeled by functional connectivity predicts metabolic demands of the human brain. Neuroimage 2024; 295:120658. [PMID: 38810891 DOI: 10.1016/j.neuroimage.2024.120658] [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: 01/15/2024] [Revised: 04/22/2024] [Accepted: 05/27/2024] [Indexed: 05/31/2024] Open
Abstract
PURPOSE The human brain is characterized by interacting large-scale functional networks fueled by glucose metabolism. Since former studies could not sufficiently clarify how these functional connections shape glucose metabolism, we aimed to provide a neurophysiologically-based approach. METHODS 51 healthy volunteers underwent simultaneous PET/MRI to obtain BOLD functional connectivity and [18F]FDG glucose metabolism. These multimodal imaging proxies of fMRI and PET were combined in a whole-brain extension of metabolic connectivity mapping. Specifically, functional connectivity of all brain regions were used as input to explain glucose metabolism of a given target region. This enabled the modeling of postsynaptic energy demands by incoming signals from distinct brain regions. RESULTS Functional connectivity input explained a substantial part of metabolic demands but with pronounced regional variations (34 - 76%). During cognitive task performance this multimodal association revealed a shift to higher network integration compared to resting state. In healthy aging, a dedifferentiation (decreased segregated/modular structure of the brain) of brain networks during rest was observed. Furthermore, by including data from mRNA maps, [11C]UCB-J synaptic density and aerobic glycolysis (oxygen-to-glucose index from PET data), we show that whole-brain functional input reflects non-oxidative, on-demand metabolism of synaptic signaling. The metabolically-derived directionality of functional inputs further marked them as top-down predictions. In addition, the approach uncovered formerly hidden networks with superior efficiency through metabolically informed network partitioning. CONCLUSIONS Applying multimodal imaging, we decipher a crucial part of the metabolic and neurophysiological basis of functional connections in the brain as interregional on-demand synaptic signaling fueled by anaerobic metabolism. The observed task- and age-related effects indicate promising future applications to characterize human brain function and clinical alterations.
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Affiliation(s)
- Sebastian Klug
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Matej Murgaš
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Godber M Godbersen
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Marcus Hacker
- Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria
| | - Andreas Hahn
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Austria; Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria.
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Wang R, Liu X, Sun C, Hu B, Yang L, Liu Y, Geng D, Lin J, Li Y. Altered Neurovascular Coupling in Patients With Mitochondrial Myopathy, Encephalopathy, Lactic Acidosis, and Stroke-Like Episodes (MELAS): A Combined Resting-State fMRI and Arterial Spin Labeling Study. J Magn Reson Imaging 2024; 60:327-336. [PMID: 37795920 DOI: 10.1002/jmri.29035] [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: 06/21/2023] [Revised: 09/19/2023] [Accepted: 09/19/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Coupling between neuronal activity and blood perfusion is termed neurovascular coupling (NVC), and it provides a potentially new mechanistic perspective into understanding numerous brain diseases. Although abnormal brain activity and blood supply have been separately reported in mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes (MELAS), whether anomalous NVC would be present is unclear. PURPOSE To investigate NVC changes and potential neural basis in MELAS by combining resting-state functional MRI (rs-fMRI) and arterial spin labeling (ASL). STUDY TYPE Prospective. SUBJECTS Twenty-four patients with MELAS (age: 29.8 ± 7.3 years) in the acute stage and 24 healthy controls (HCs, age: 26.4 ± 8.1 years). Additionally, 12 patients in the chronic stage were followed up. FIELD STRENGTH/SEQUENCE 3.0 T, resting-state gradient-recalled echo-planar imaging and pseudo-continuous 3D ASL sequences. ASSESSMENT Amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and functional connectivity strength (FCS) were calculated from rs-fMRI, and cerebral blood flow (CBF) was computed from ASL. Global NVC was assessed by correlation coefficients of CBF-ALFF, CBF-fALFF, CBF-ReHo, and CBF-FCS. Regional NVC was also evaluated by voxel-wise and lesion-wise ratios of CBF/ALFF, CBF/fALFF, CBF/ReHo, and CBF/FCS. STATISTICAL TESTS Two-sample t-test, paired-sample t-test, Gaussian random fields correction. A P value <0.05 was considered statistically significant. RESULTS Compared with HC, MELAS patients in acute stage showed significantly reduced global CBF-ALFF, CBF-fALFF, CBF-ReHo, and CBF-FCS coupling (P < 0.001). Altered CBF/ALFF, CBF/fALFF, CBF/ReHo, and CBF/FCS ratios were found mainly distributed in the middle cerebral artery territory in MELAS patients. In addition, significantly increased NVC ratios were found in the acute stroke-like lesions in acute stage (P < 0.001), with a recovery trend in chronic stage. DATA CONCLUSIONS This study showed dynamic alterations in NVC in MELAS patients from acute to chronic stage, which may provide a novel insight for understanding the pathogenesis of MELAS. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Rong Wang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
| | - Xueling Liu
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
| | - Chong Sun
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Bin Hu
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
| | - Liqin Yang
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
| | - Yiru Liu
- Luhang High School, Shanghai, China
| | - Daoying Geng
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
| | - Jie Lin
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Yuxin Li
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai, China
- Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
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Tsai CJ, Lin HY, Gau SSF. Correlation of altered intrinsic functional connectivity with impaired self-regulation in children and adolescents with ADHD. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01787-y. [PMID: 38906983 DOI: 10.1007/s00406-024-01787-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Accepted: 02/16/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND Attention-deficit hyperactivity disorder (ADHD) has a high prevalence of co-occurring impaired self-regulation (dysregulation), exacerbating adverse outcomes. Neural correlates underlying impaired self-regulation in ADHD remain inconclusive. We aimed to investigate the impact of dysregulation on intrinsic functional connectivity (iFC) in children with ADHD and the correlation of iFC with dysregulation among children with ADHD relative to typically developing controls (TDC). METHODS Resting-state functional MRI data of 71 children with ADHD (11.38 ± 2.44 years) and 117 age-matched TDC were used in the final analysis. We restricted our analyses to resting-state networks (RSNs) of interest derived from independent component analysis. Impaired self-regulation was estimated based on the Child Behavioral Checklist-Dysregulation Profile. RESULTS Children with ADHD showed stronger iFC than TDC in the left frontoparietal network, somatomotor network (SMN), visual network (VIS), default-mode network (DMN), and dorsal attention network (DAN) (FWE-corrected alpha < 0.05). After adding dysregulation levels as an extra regressor, the ADHD group only showed stronger iFC in the VIS and SMN. ADHD children with high dysregulation had higher precuneus iFC within DMN than ADHD children with low dysregulation. Angular gyrus iFC within DMN was positively correlated with dysregulation in the ADHD group but negatively correlated with dysregulation in the TDC group. Functional network connectivity showed ADHD had a greater DMN-DAN connection than TDC, regardless of the dysregulation level. CONCLUSIONS Our findings suggest that DMN connectivity may contribute to impaired self-regulation in ADHD. Impaired self-regulation should be considered categorical and dimensional moderators for the neural correlates of altered iFC in ADHD.
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Affiliation(s)
- Chia-Jui Tsai
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Hsiang-Yuan Lin
- Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Susan Shur-Fen Gau
- Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan.
- Department of Psychiatry, National Taiwan University Hospital and College of Medicine, No. 7, Chung-Shan South Road, Taipei, 10002, Taiwan.
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University Hospital, Taipei, Taiwan.
- Department of Psychology, College of Science, National Taiwan University, Taipei, Taiwan.
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Kauf C, Kim HS, Lee EJ, Jhingan N, She JS, Taliaferro M, Gibson E, Fedorenko E. Linguistic inputs must be syntactically parsable to fully engage the language network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.21.599332. [PMID: 38948870 PMCID: PMC11212959 DOI: 10.1101/2024.06.21.599332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Human language comprehension is remarkably robust to ill-formed inputs (e.g., word transpositions). This robustness has led some to argue that syntactic parsing is largely an illusion, and that incremental comprehension is more heuristic, shallow, and semantics-based than is often assumed. However, the available data are also consistent with the possibility that humans always perform rule-like symbolic parsing and simply deploy error correction mechanisms to reconstruct ill-formed inputs when needed. We put these hypotheses to a new stringent test by examining brain responses to a) stimuli that should pose a challenge for syntactic reconstruction but allow for complex meanings to be built within local contexts through associative/shallow processing (sentences presented in a backward word order), and b) grammatically well-formed but semantically implausible sentences that should impede semantics-based heuristic processing. Using a novel behavioral syntactic reconstruction paradigm, we demonstrate that backward- presented sentences indeed impede the recovery of grammatical structure during incremental comprehension. Critically, these backward-presented stimuli elicit a relatively low response in the language areas, as measured with fMRI. In contrast, semantically implausible but grammatically well-formed sentences elicit a response in the language areas similar in magnitude to naturalistic (plausible) sentences. In other words, the ability to build syntactic structures during incremental language processing is both necessary and sufficient to fully engage the language network. Taken together, these results provide strongest to date support for a generalized reliance of human language comprehension on syntactic parsing. Significance statement Whether language comprehension relies predominantly on structural (syntactic) cues or meaning- related (semantic) cues remains debated. We shed new light on this question by examining the language brain areas' responses to stimuli where syntactic and semantic cues are pitted against each other, using fMRI. We find that the language areas respond weakly to stimuli that allow for local semantic composition but cannot be parsed syntactically-as confirmed in a novel behavioral paradigm-and they respond strongly to grammatical but semantically implausible sentences, like the famous 'Colorless green ideas sleep furiously' sentence. These findings challenge accounts of language processing that suggest that syntactic parsing can be foregone in favor of shallow semantic processing.
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Daood M, Magal N, Peled-Avron L, Nevat M, Ben-Hayun R, Aharon-Peretz J, Tomer R, Admon R. Graph analysis uncovers an opposing impact of methylphenidate on connectivity patterns within default mode network sub-divisions. BEHAVIORAL AND BRAIN FUNCTIONS : BBF 2024; 20:15. [PMID: 38902791 PMCID: PMC11191242 DOI: 10.1186/s12993-024-00242-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 06/13/2024] [Indexed: 06/22/2024]
Abstract
BACKGROUND The Default Mode Network (DMN) is a central neural network, with recent evidence indicating that it is composed of functionally distinct sub-networks. Methylphenidate (MPH) administration has been shown before to modulate impulsive behavior, though it is not yet clear whether these effects relate to MPH-induced changes in DMN connectivity. To address this gap, we assessed the impact of MPH administration on functional connectivity patterns within and between distinct DMN sub-networks and tested putative relations to variability in sub-scales of impulsivity. METHODS Fifty-five right-handed healthy adults underwent two resting-state functional MRI (rs-fMRI) scans, following acute administration of either MPH (20 mg) or placebo, via a randomized double-blind placebo-controlled design. Graph modularity analysis was implemented to fractionate the DMN into distinct sub-networks based on the impact of MPH (vs. placebo) on DMN connectivity patterns with other neural networks. RESULTS MPH administration led to an overall decreased DMN connectivity, particularly with the auditory, cinguloopercular, and somatomotor networks, and increased connectivity with the parietomedial network. Graph analysis revealed that the DMN could be fractionated into two distinct sub-networks, with one exhibiting MPH-induced increased connectivity and the other decreased connectivity. Decreased connectivity of the DMN sub-network with the cinguloopercular network following MPH administration was associated with elevated impulsivity and non-planning impulsiveness. CONCLUSION Current findings highlight the intricate effects of MPH administration on DMN rs-fMRI connectivity, uncovering its opposing impact on distinct DMN sub-divisions. MPH-induced dynamics in DMN connectivity patterns with other neural networks may account for some of the effects of MPH administration on impulsive behavior.
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Affiliation(s)
- Maryana Daood
- School of Psychological Sciences, University of Haifa, 199 Aba Khoushy Ave. Mount Carmel, Haifa, 31905, Israel
- Sakhnin College of Education, Sakhnin, Israel
| | - Noa Magal
- School of Psychological Sciences, University of Haifa, 199 Aba Khoushy Ave. Mount Carmel, Haifa, 31905, Israel
| | - Leehe Peled-Avron
- The Leslie and Susan Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel
- Department of Psychology, Bar-Ilan University, Ramat-Gan, Israel
| | - Michael Nevat
- School of Psychological Sciences, University of Haifa, 199 Aba Khoushy Ave. Mount Carmel, Haifa, 31905, Israel
| | - Rachel Ben-Hayun
- Stroke and Cognition Institute, Rambam Health Care Campus, Haifa, Israel
- Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Judith Aharon-Peretz
- Stroke and Cognition Institute, Rambam Health Care Campus, Haifa, Israel
- Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Rachel Tomer
- School of Psychological Sciences, University of Haifa, 199 Aba Khoushy Ave. Mount Carmel, Haifa, 31905, Israel
- The Integrated Brain and Behavior Research Center (IBBRC), University of Haifa, Haifa, Israel
| | - Roee Admon
- School of Psychological Sciences, University of Haifa, 199 Aba Khoushy Ave. Mount Carmel, Haifa, 31905, Israel.
- The Integrated Brain and Behavior Research Center (IBBRC), University of Haifa, Haifa, Israel.
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Irastorza-Valera L, Soria-Gómez E, Benitez JM, Montáns FJ, Saucedo-Mora L. Review of the Brain's Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM). Biomimetics (Basel) 2024; 9:362. [PMID: 38921242 PMCID: PMC11202129 DOI: 10.3390/biomimetics9060362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 05/28/2024] [Accepted: 06/05/2024] [Indexed: 06/27/2024] Open
Abstract
The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic review aims to cover mostly findings related to changes in the physical distribution of neurons and their connections-the connectome-both structural and functional, as well as their modelling approaches. It does not intend to offer an extensive description of all conditions affecting the brain; rather, it presents the most common ones. Thus, here, we highlight the need for accurate brain modelling that can subsequently be used to understand brain function and be applied to diagnose, track, and simulate treatments for the most prevalent pathologies affecting the brain.
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Affiliation(s)
- Luis Irastorza-Valera
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain; (L.I.-V.); (J.M.B.); (F.J.M.)
- PIMM Laboratory, ENSAM–Arts et Métiers ParisTech, 151 Bd de l’Hôpital, 75013 Paris, France
| | - Edgar Soria-Gómez
- Achúcarro Basque Center for Neuroscience, Barrio Sarriena, s/n, 48940 Leioa, Spain;
- Ikerbasque, Basque Foundation for Science, Plaza Euskadi, 5, 48009 Bilbao, Spain
- Department of Neurosciences, University of the Basque Country UPV/EHU, Barrio Sarriena, s/n, 48940 Leioa, Spain
| | - José María Benitez
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain; (L.I.-V.); (J.M.B.); (F.J.M.)
| | - Francisco J. Montáns
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain; (L.I.-V.); (J.M.B.); (F.J.M.)
- Department of Mechanical and Aerospace Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Luis Saucedo-Mora
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain; (L.I.-V.); (J.M.B.); (F.J.M.)
- Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PJ, UK
- Department of Nuclear Science and Engineering, Massachusetts Institute of Technology (MIT), 77 Massachusetts Ave, Cambridge, MA 02139, USA
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Liddell BJ, Das P, Malhi GS, Jobson L, Lau W, Felmingham KL, Nickerson A, Askovic M, Aroche J, Coello M, Bryant RA. Self-construal modulates default mode network connectivity in refugees with PTSD. J Affect Disord 2024; 361:268-276. [PMID: 38866252 DOI: 10.1016/j.jad.2024.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 05/28/2024] [Accepted: 06/03/2024] [Indexed: 06/14/2024]
Abstract
BACKGROUND While self-construal and posttraumatic stress disorder (PTSD) are independently associated with altered self-referential processes and underlying default mode network (DMN) functioning, no study has examined how self-construal affects DMN connectivity in PTSD. METHODS A final sample of 93 refugee participants (48 with DSM-5 PTSD or sub-syndromal PTSD and 45 matched trauma-exposed controls) completed a 5-minute resting state fMRI scan to enable the observation of connectivity in the DMN and other core networks. A self-construal index was calculated by substracting scores on the collectivistic and individualistic sub-scales of the Self Construal Scale. RESULTS Independent components analysis identified 9 active networks-of-interest, and functional network connectivity was determined. A significant interaction effect between PTSD and self-construal index was observed in the anterior ventromedial DMN, with spatial maps localizing this to the left ventromedial prefrontal cortex (vmPFC), extending to the ventral anterior cingulate cortex. This effect revealed that connectivity in the vMPFC showed greater reductions in those with PTSD with higher levels of collectivistic self-construal. LIMITATIONS This is an observational study and causality cannot be assumed. The specialized sample of refugees means that the findings may not generalize to other trauma-exposed populations. CONCLUSIONS Such a finding indicates that self-construal may shape the core neural architecture of PTSD, given that functional disruptions to the vmPFC underpin the core mechanisms of extinction learning, emotion dysregulation and self-referential processing in PTSD. Results have important implications for understanding the universality of neural disturbances in PTSD, and suggest that self-construal could be an important consideration in the assessment and treatment of post-traumatic stress reactions.
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Affiliation(s)
- Belinda J Liddell
- School of Psychological Sciences, University of Newcastle, Australia; School of Psychology, UNSW Sydney, Australia.
| | - Pritha Das
- School of Psychological Sciences, University of Newcastle, Australia; Academic Department of Psychiatry, Northern Sydney Local Health District, CADE Clinic, Royal North Shore Hospital, Northern Sydney Local Health District, St Leonards, NSW 2065, Australia
| | - Gin S Malhi
- Academic Department of Psychiatry, Northern Sydney Local Health District, CADE Clinic, Royal North Shore Hospital, Northern Sydney Local Health District, St Leonards, NSW 2065, Australia; University of Sydney, Faculty of Medicine and Health, Northern Clinical School, Department of Psychiatry, Sydney, New South Wales, Australia.; Department of Psychiatry, University of Oxford, Oxford, UK
| | | | - Winnie Lau
- Phoenix Australia, University of Melbourne, Australia
| | - Kim L Felmingham
- School of Psychological Sciences, University of Melbourne, Australia
| | | | - Mirjana Askovic
- NSW Service for the Treatment and Rehabilitation of Torture and Trauma Survivors (STARTTS), Sydney, Australia
| | - Jorge Aroche
- NSW Service for the Treatment and Rehabilitation of Torture and Trauma Survivors (STARTTS), Sydney, Australia
| | - Mariano Coello
- NSW Service for the Treatment and Rehabilitation of Torture and Trauma Survivors (STARTTS), Sydney, Australia
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Gbyl K, Labanauskas V, Lundsgaard CC, Mathiassen A, Ryszczuk A, Siebner HR, Rostrup E, Madsen K, Videbech P. Electroconvulsive therapy disrupts functional connectivity between hippocampus and posterior default mode network. Prog Neuropsychopharmacol Biol Psychiatry 2024; 132:110981. [PMID: 38373628 DOI: 10.1016/j.pnpbp.2024.110981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 02/13/2024] [Accepted: 02/16/2024] [Indexed: 02/21/2024]
Abstract
BACKGROUND The mechanisms underlying memory deficits after electroconvulsive therapy (ECT) remain unclear but altered functional interactions between hippocampus and neocortex may play a role. OBJECTIVES To test whether ECT reduces functional connectivity between hippocampus and posterior regions of the default mode network (DMN) and to examine whether altered hippocampal-neocortical functional connectivity correlates with memory impairment. A secondary aim was to explore if these connectivity changes are present 6 months after ECT. METHODS In-patients with severe depression (n = 35) received bitemporal ECT. Functional connectivity of the hippocampus was probed with resting-state fMRI before the first ECT-session, after the end of ECT, and at a six-month follow-up. Memory was assessed with the Verbal Learning Test - Delayed Recall. Seed-based connectivity analyses established connectivity of four hippocampal seeds, covering the anterior and posterior parts of the right and left hippocampus. RESULTS Compared to baseline, three of four hippocampal seeds became less connected to the core nodes of the posterior DMN in the week after ECT with Cohen's d ranging from -0.9 to -1.1. At the group level, patients showed post-ECT memory impairment, but individual changes in delayed recall were not correlated with the reduction in hippocampus-DMN connectivity. At six-month follow-up, no significant hippocampus-DMN reductions in connectivity were evident relative to pre-ECT, and memory scores had returned to baseline. CONCLUSION ECT leads to a temporary disruption of functional hippocampus-DMN connectivity in patients with severe depression, but the change in connectivity strength is not related to the individual memory impairment.
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Affiliation(s)
- Krzysztof Gbyl
- Center for Neuropsychiatric Depression Research, Mental Health Center Glostrup, Mental Health Services of the Capital Region of Denmark, Copenhagen University Hospital, Glostrup, Denmark; Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.
| | - Vytautas Labanauskas
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Denmark
| | - Christoffer Cramer Lundsgaard
- Center for Neuropsychiatric Depression Research, Mental Health Center Glostrup, Mental Health Services of the Capital Region of Denmark, Copenhagen University Hospital, Glostrup, Denmark; Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - André Mathiassen
- Center for Neuropsychiatric Depression Research, Mental Health Center Glostrup, Mental Health Services of the Capital Region of Denmark, Copenhagen University Hospital, Glostrup, Denmark; Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Adam Ryszczuk
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Denmark
| | - Hartwig Roman Siebner
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark; Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Egill Rostrup
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark; Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Glostrup, Denmark
| | - Kristoffer Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Denmark; Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Poul Videbech
- Center for Neuropsychiatric Depression Research, Mental Health Center Glostrup, Mental Health Services of the Capital Region of Denmark, Copenhagen University Hospital, Glostrup, Denmark; Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
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Fialoke S, Tripathi V, Thakral S, Dhawan A, Majahan V, Garg R. Functional connectivity changes in meditators and novices during yoga nidra practice. Sci Rep 2024; 14:12957. [PMID: 38839877 PMCID: PMC11153538 DOI: 10.1038/s41598-024-63765-7] [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: 02/02/2024] [Accepted: 05/31/2024] [Indexed: 06/07/2024] Open
Abstract
Yoga nidra (YN) practice aims to induce a deeply relaxed state akin to sleep while maintaining heightened awareness. Despite the growing interest in its clinical applications, a comprehensive understanding of the underlying neural correlates of the practice of YN remains largely unexplored. In this fMRI investigation, we aim to discover the differences between wakeful resting states and states attained during YN practice. The study included individuals experienced in meditation and/or yogic practices, referred to as 'meditators' (n = 30), and novice controls (n = 31). The GLM analysis, based on audio instructions, demonstrated activation related to auditory cues without concurrent default mode network (DMN) deactivation. DMN seed based functional connectivity (FC) analysis revealed significant reductions in connectivity among meditators during YN as compared to controls. We did not find differences between the two groups during the pre and post resting state scans. Moreover, when DMN-FC was compared between the YN state and resting state, meditators showed distinct decoupling, whereas controls showed increased DMN-FC. Finally, participants exhibit a remarkable correlation between reduced DMN connectivity during YN and self-reported hours of cumulative meditation and yoga practice. Together, these results suggest a unique neural modulation of the DMN in meditators during YN which results in being restful yet aware, aligned with their subjective experience of the practice. The study deepens our understanding of the neural mechanisms of YN, revealing distinct DMN connectivity decoupling in meditators and its relationship with meditation and yoga experience. These findings have interdisciplinary implications for neuroscience, psychology, and yogic disciplines.
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Affiliation(s)
- Suruchi Fialoke
- National Resource Center for Value Education in Engineering, Indian Institute of Technology, Delhi, India
| | - Vaibhav Tripathi
- Psychological and Brain Sciences, Boston University, Boston, USA
| | - Sonika Thakral
- Department of Computer Science, Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India
| | - Anju Dhawan
- National Drug Dependence Treatment Centre, All India Institute of Medical Sciences (AIIMS), Delhi, India
| | | | - Rahul Garg
- National Resource Center for Value Education in Engineering, Indian Institute of Technology, Delhi, India.
- Amar Nath and Shashi Khosla School of Information Technology, Indian Institute of Technology, Delhi, India.
- Department of Computer Science and Engineering, Indian Institute of Technology, Delhi, India.
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10
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Elbasheir A, Katrinli S, Kearney BE, Lanius RA, Harnett NG, Carter SE, Ely TD, Bradley B, Gillespie CF, Stevens JS, Lori A, van Rooij SJH, Powers A, Jovanovic T, Smith AK, Fani N. Racial Discrimination, Neural Connectivity, and Epigenetic Aging Among Black Women. JAMA Netw Open 2024; 7:e2416588. [PMID: 38869898 DOI: 10.1001/jamanetworkopen.2024.16588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/14/2024] Open
Abstract
Importance Racial discrimination increases the risk of adverse brain health outcomes, potentially via neuroplastic changes in emotion processing networks. The involvement of deep brain regions (brainstem and midbrain) in these responses is unknown. Potential associations of racial discrimination with alterations in deep brain functional connectivity and accelerated epigenetic aging, a process that substantially increases vulnerability to health problems, are also unknown. Objective To examine associations of racial discrimination with brainstem and midbrain resting-state functional connectivity (RSFC) and DNA methylation age acceleration (DMAA) among Black women in the US. Design, Setting, and Participants This cohort study was conducted between January 1, 2012, and February 28, 2015, and included a community-based sample of Black women (aged ≥18 years) recruited as part of the Grady Trauma Project. Self-reported racial discrimination was examined in association with seed-to-voxel brain connectivity, including the locus coeruleus (LC), periaqueductal gray (PAG), and superior colliculus (SC); an index of DMAA (Horvath clock) was also evaluated. Posttraumatic stress disorder (PTSD), trauma exposure, and age were used as covariates in statistical models to isolate racial discrimination-related variance. Data analysis was conducted between January 10 and October 30, 2023. Exposure Varying levels of racial discrimination exposure, other trauma exposure, and posttraumatic stress disorder (PTSD). Main Outcomes and Measures Racial discrimination frequency was assessed with the Experiences of Discrimination Scale, other trauma exposure was evaluated with the Traumatic Events Inventory, and current PTSD was evaluated with the PTSD Symptom Scale. Seed-to-voxel functional connectivity analyses were conducted with LC, PAG, and SC seeds. To assess DMAA, the Methylation EPIC BeadChip assay (Illumina) was conducted with whole-blood samples from a subset of 49 participants. Results This study included 90 Black women, with a mean (SD) age of 38.5 (11.3) years. Greater racial discrimination was associated with greater left LC RSFC to the bilateral precuneus (a region within the default mode network implicated in rumination and reliving of past events; cluster size k = 228; t85 = 4.78; P < .001, false discovery rate-corrected). Significant indirect effects were observed for the left LC-precuneus RSFC on the association between racial discrimination and DMAA (β [SE] = 0.45 [0.16]; 95% CI, 0.12-0.77). Conclusions and Relevance In this study, more frequent racial discrimination was associated with proportionately greater RSFC of the LC to the precuneus, and these connectivity alterations were associated with DMAA. These findings suggest that racial discrimination contributes to accelerated biological aging via altered connectivity between the LC and default mode network, increasing vulnerability for brain health problems.
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Affiliation(s)
- Aziz Elbasheir
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Seyma Katrinli
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Breanne E Kearney
- Department of Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Ruth A Lanius
- Department of Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Nathaniel G Harnett
- Division of Depression and Anxiety, McLean Hospital, Belmont, Massachusetts
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | | | - Timothy D Ely
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Bekh Bradley
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
- Atlanta Veterans Affairs Medical Center, Atlanta, Georgia
| | - Charles F Gillespie
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Jennifer S Stevens
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Adriana Lori
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Sanne J H van Rooij
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Abigail Powers
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Tanja Jovanovic
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University, Detroit, Michigan
| | - Alicia K Smith
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
- Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta, Georgia
| | - Negar Fani
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
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11
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Mahowald K, Ivanova AA, Blank IA, Kanwisher N, Tenenbaum JB, Fedorenko E. Dissociating language and thought in large language models. Trends Cogn Sci 2024; 28:517-540. [PMID: 38508911 DOI: 10.1016/j.tics.2024.01.011] [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: 11/06/2023] [Revised: 01/31/2024] [Accepted: 01/31/2024] [Indexed: 03/22/2024]
Abstract
Large language models (LLMs) have come closest among all models to date to mastering human language, yet opinions about their linguistic and cognitive capabilities remain split. Here, we evaluate LLMs using a distinction between formal linguistic competence (knowledge of linguistic rules and patterns) and functional linguistic competence (understanding and using language in the world). We ground this distinction in human neuroscience, which has shown that formal and functional competence rely on different neural mechanisms. Although LLMs are surprisingly good at formal competence, their performance on functional competence tasks remains spotty and often requires specialized fine-tuning and/or coupling with external modules. We posit that models that use language in human-like ways would need to master both of these competence types, which, in turn, could require the emergence of separate mechanisms specialized for formal versus functional linguistic competence.
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12
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Fedorenko E, Piantadosi ST, Gibson EAF. Language is primarily a tool for communication rather than thought. Nature 2024; 630:575-586. [PMID: 38898296 DOI: 10.1038/s41586-024-07522-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 05/03/2024] [Indexed: 06/21/2024]
Abstract
Language is a defining characteristic of our species, but the function, or functions, that it serves has been debated for centuries. Here we bring recent evidence from neuroscience and allied disciplines to argue that in modern humans, language is a tool for communication, contrary to a prominent view that we use language for thinking. We begin by introducing the brain network that supports linguistic ability in humans. We then review evidence for a double dissociation between language and thought, and discuss several properties of language that suggest that it is optimized for communication. We conclude that although the emergence of language has unquestionably transformed human culture, language does not appear to be a prerequisite for complex thought, including symbolic thought. Instead, language is a powerful tool for the transmission of cultural knowledge; it plausibly co-evolved with our thinking and reasoning capacities, and only reflects, rather than gives rise to, the signature sophistication of human cognition.
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Affiliation(s)
- Evelina Fedorenko
- Massachusetts Institute of Technology, Cambridge, MA, USA.
- Speech and Hearing in Bioscience and Technology Program at Harvard University, Boston, MA, USA.
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13
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Kosakowski HL, Saadon-Grosman N, Du J, Eldaief MC, Buckner RL. Human striatal association megaclusters. J Neurophysiol 2024; 131:1083-1100. [PMID: 38505898 DOI: 10.1152/jn.00387.2023] [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: 10/19/2023] [Revised: 03/13/2024] [Accepted: 03/13/2024] [Indexed: 03/21/2024] Open
Abstract
The striatum receives projections from multiple regions of the cerebral cortex consistent with the role of the basal ganglia in diverse motor, affective, and cognitive functions. Within the striatum, the caudate receives projections from association cortex, including multiple distinct regions of prefrontal cortex. Building on recent insights about the details of how juxtaposed cortical networks are specialized for distinct aspects of higher-order cognition, we revisited caudate organization using within-individual precision neuroimaging initially in two intensively scanned individuals (each scanned 31 times). Results revealed that the caudate has side-by-side regions that are coupled to at least five distinct distributed association networks, paralleling the organization observed in the cerebral cortex. We refer to these spatial groupings of regions as striatal association megaclusters. Correlation maps from closely juxtaposed seed regions placed within the megaclusters recapitulated the five distinct cortical networks, including their multiple spatially distributed regions. Striatal association megaclusters were explored in 15 additional participants (each scanned at least 8 times), finding that their presence generalizes to new participants. Analysis of the laterality of the regions within the megaclusters further revealed that they possess asymmetries paralleling their cortical counterparts. For example, caudate regions linked to the language network were left lateralized. These results extend the general notion of parallel specialized basal ganglia circuits with the additional discovery that, even within the caudate, there is fine-grained separation of multiple distinct higher-order networks that reflects the organization and lateralization found in the cerebral cortex.NEW & NOTEWORTHY An individualized precision neuroimaging approach reveals juxtaposed zones of the caudate that are coupled with five distinct networks in association cortex. The organization of these caudate zones recapitulates organization observed in the cerebral cortex and extends the notion of specialized basal ganglia circuits.
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Affiliation(s)
- Heather L Kosakowski
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, United States
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States
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14
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Du J, DiNicola LM, Angeli PA, Saadon-Grosman N, Sun W, Kaiser S, Ladopoulou J, Xue A, Yeo BTT, Eldaief MC, Buckner RL. Organization of the human cerebral cortex estimated within individuals: networks, global topography, and function. J Neurophysiol 2024; 131:1014-1082. [PMID: 38489238 DOI: 10.1152/jn.00308.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 01/18/2024] [Accepted: 02/16/2024] [Indexed: 03/17/2024] Open
Abstract
The cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks from functional MRI (fMRI) data in intensively sampled participants. The procedure was developed in two participants (scanned 31 times) and then prospectively applied to 15 participants (scanned 8-11 times). Analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that linked to distant regions. Third-order networks possessed regions distributed widely throughout association cortex. Regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated across multiple cortical zones. We refer to these as supra-areal association megaclusters (SAAMs). Within each SAAM, two candidate control regions were adjacent to three separate domain-specialized regions. Response properties were explored with task data. The somatomotor and visual networks responded to body movements and visual stimulation, respectively. Second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions dissociated across language, social, and spatial/episodic processing domains. These results suggest that progressively higher-order networks nest outward from primary sensory and motor cortices. Within the apex zones of association cortex, there is specialization that repeatedly divides domain-flexible from domain-specialized regions. We discuss implications of these findings, including how repeating organizational motifs may emerge during development.NEW & NOTEWORTHY The organization of cerebral networks was estimated within individuals with intensive, repeat sampling of fMRI data. A hierarchical organization emerged in each individual that delineated first-, second-, and third-order cortical networks. Regions of distinct third-order association networks consistently exhibited side-by-side juxtapositions that repeated across multiple cortical zones, with clear and robust functional specialization among the embedded regions.
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Affiliation(s)
- Jingnan Du
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Lauren M DiNicola
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Peter A Angeli
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Noam Saadon-Grosman
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Wendy Sun
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Stephanie Kaiser
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Joanna Ladopoulou
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
| | - Aihuiping Xue
- Centre for Sleep & Cognition and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - B T Thomas Yeo
- Centre for Sleep & Cognition and Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Mark C Eldaief
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, United States
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15
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Wang L, Qin Y, Yang S, Jin D, Zhu Y, Li X, Li W, Wang Y, Jin C. Posterior default mode network is associated with the social performance in male children with autism spectrum disorder: A dynamic causal modeling analysis based on triple-network model. Hum Brain Mapp 2024; 45:e26750. [PMID: 38853710 PMCID: PMC11163228 DOI: 10.1002/hbm.26750] [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: 01/10/2024] [Revised: 05/12/2024] [Accepted: 05/22/2024] [Indexed: 06/11/2024] Open
Abstract
The triple-network model has been widely applied in neuropsychiatric disorders including autism spectrum disorder (ASD). However, the mechanism of causal regulations within the triple-network and their relations with symptoms of ASD remains unclear. 81 male ASD and 80 well matched typically developing control (TDC) were included in this study, recruited from Autism Brain Image Data Exchange-I datasets. Spatial reference-based independent component analysis was used to identify the anterior and posterior part of default-mode network (aDMN and pDMN), salience network (SN), and bilateral executive-control network (ECN) from resting-state functional magnetic resonance imaging data. Spectral dynamic causal model and parametric empirical Bayes with Bayesian model reduction/average were adopted to explore the effective connectivity (EC) within triple-network and the relationship between EC and autism diagnostic observation schedule (ADOS) scores. After adjusting for age and site effect, ASD and TDC groups both showed inhibition patterns. Compared with TDC, ASD group showed weaker self-inhibition in aDMN and pDMN, stronger inhibition in pDMN→aDMN, weaker inhibition in aDMN→LECN, pDMN→SN, LECN→SN, and LECN→RECN. Furthermore, negative relationships between ADOS scores and pDMN self-inhibition strength, as well as with the EC of pDMN→aDMN were observed in ASD group. The present study reveals imbalanced effective connections within triple-networks in ASD children. More attentions should be focused at the pDMN, which modulates the core symptoms of ASD and may serve as an important region for ASD diagnosis and the target region for ASD treatments.
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Affiliation(s)
- Lei Wang
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Yue Qin
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Shuhan Yang
- Department of Disease Control and PreventionNinth Hospital of Xi'anXi'anChina
| | - Dayong Jin
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Yinhu Zhu
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Xin Li
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Wei Li
- Department of Radiology, Tangdu HospitalAir Force Military Medical UniversityXi'anChina
| | - Yarong Wang
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Chenwang Jin
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
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16
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Sanda P, Hlinka J, van den Berg M, Skoch A, Bazhenov M, Keliris GA, Krishnan GP. Cholinergic modulation supports dynamic switching of resting state networks through selective DMN suppression. PLoS Comput Biol 2024; 20:e1012099. [PMID: 38843298 PMCID: PMC11185486 DOI: 10.1371/journal.pcbi.1012099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 06/18/2024] [Accepted: 04/23/2024] [Indexed: 06/19/2024] Open
Abstract
Brain activity during the resting state is widely used to examine brain organization, cognition and alterations in disease states. While it is known that neuromodulation and the state of alertness impact resting-state activity, neural mechanisms behind such modulation of resting-state activity are unknown. In this work, we used a computational model to demonstrate that change in excitability and recurrent connections, due to cholinergic modulation, impacts resting-state activity. The results of such modulation in the model match closely with experimental work on direct cholinergic modulation of Default Mode Network (DMN) in rodents. We further extended our study to the human connectome derived from diffusion-weighted MRI. In human resting-state simulations, an increase in cholinergic input resulted in a brain-wide reduction of functional connectivity. Furthermore, selective cholinergic modulation of DMN closely captured experimentally observed transitions between the baseline resting state and states with suppressed DMN fluctuations associated with attention to external tasks. Our study thus provides insight into potential neural mechanisms for the effects of cholinergic neuromodulation on resting-state activity and its dynamics.
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Affiliation(s)
- Pavel Sanda
- Institute of Computer Science of the Czech Academy of Sciences, Prague, Czech Republic
| | - Jaroslav Hlinka
- Institute of Computer Science of the Czech Academy of Sciences, Prague, Czech Republic
- National Institute of Mental Health, Klecany, Czech Republic
| | - Monica van den Berg
- Bio-Imaging Lab, University of Antwerp, Antwerp, Belgium
- μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Maxim Bazhenov
- Department of Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Georgios A. Keliris
- Bio-Imaging Lab, University of Antwerp, Antwerp, Belgium
- Institute of Computer Science, Foundation for Research and Technology - Hellas, Heraklion, Crete, Greece
| | - Giri P. Krishnan
- Department of Medicine, University of California San Diego, La Jolla, California, United States of America
- Georgia Institute of Technology, Atlanta, Georgia, United States of America
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17
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Han Y, Jing Y, Shi Y, Mo H, Wan Y, Zhou H, Deng F. The role of language-related functional brain regions and white matter tracts in network plasticity of post-stroke aphasia. J Neurol 2024; 271:3095-3115. [PMID: 38607432 DOI: 10.1007/s00415-024-12358-5] [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: 01/05/2024] [Revised: 03/26/2024] [Accepted: 03/27/2024] [Indexed: 04/13/2024]
Abstract
The neural mechanisms underlying language recovery after a stroke remain controversial. This review aimed to summarize the plasticity and reorganization mechanisms of the language network through neuroimaging studies. Initially, we discussed the involvement of right language homologues, perilesional tissue, and domain-general networks. Subsequently, we summarized the white matter functional mapping and remodeling mechanisms associated with language subskills. Finally, we explored how non-invasive brain stimulation (NIBS) promoted language recovery by inducing neural network plasticity. It was observed that the recruitment of right hemisphere language area homologues played a pivotal role in the early stages of frontal post-stroke aphasia (PSA), particularly in patients with larger lesions. Perilesional plasticity correlated with improved speech performance and prognosis. The domain-general networks could respond to increased "effort" in a task-dependent manner from the top-down when the downstream language network was impaired. Fluency, repetition, comprehension, naming, and reading skills exhibited overlapping and unique dual-pathway functional mapping models. In the acute phase, the structural remodeling of white matter tracts became challenging, with recovery predominantly dependent on cortical activation. Similar to the pattern of cortical activation, during the subacute and chronic phases, improvements in language functions depended, respectively, on the remodeling of right white matter tracts and the restoration of left-lateralized language structural network patterns. Moreover, the midline superior frontal gyrus/dorsal anterior cingulate cortex emerged as a promising target for NIBS. These findings offered theoretical insights for the early personalized treatment of aphasia after stroke.
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Affiliation(s)
- Yue Han
- Department of Neurology, The First Hospital of Jilin University, Changchun, China
| | - Yuanyuan Jing
- Department of Neurology, The First Hospital of Jilin University, Changchun, China
| | - Yanmin Shi
- Health Management (Physical Examination) Center, The Second Norman Bethune Hospital of Jilin University, Changchun, China
| | - Hongbin Mo
- Department of Neurology, The First Hospital of Jilin University, Changchun, China
| | - Yafei Wan
- Department of Neurology, The First Hospital of Jilin University, Changchun, China
| | - Hongwei Zhou
- Department of Radiology, The First Hospital of Jilin University, Changchun, China.
| | - Fang Deng
- Department of Neurology, The First Hospital of Jilin University, Changchun, China.
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18
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Wang X, Krieger-Redwood K, Lyu B, Lowndes R, Wu G, Souter NE, Wang X, Kong R, Shafiei G, Bernhardt BC, Cui Z, Smallwood J, Du Y, Jefferies E. The Brain's Topographical Organization Shapes Dynamic Interaction Patterns That Support Flexible Behavior Based on Rules and Long-Term Knowledge. J Neurosci 2024; 44:e2223232024. [PMID: 38527807 PMCID: PMC11140685 DOI: 10.1523/jneurosci.2223-23.2024] [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: 11/15/2023] [Revised: 03/14/2024] [Accepted: 03/17/2024] [Indexed: 03/27/2024] Open
Abstract
Adaptive behavior relies both on specific rules that vary across situations and stable long-term knowledge gained from experience. The frontoparietal control network (FPCN) is implicated in the brain's ability to balance these different influences on action. Here, we investigate how the topographical organization of the cortex supports behavioral flexibility within the FPCN. Functional properties of this network might reflect its juxtaposition between the dorsal attention network (DAN) and the default mode network (DMN), two large-scale systems implicated in top-down attention and memory-guided cognition, respectively. Our study tests whether subnetworks of FPCN are topographically proximal to the DAN and the DMN, respectively, and how these topographical differences relate to functional differences: the proximity of each subnetwork is anticipated to play a pivotal role in generating distinct cognitive modes relevant to working memory and long-term memory. We show that FPCN subsystems share multiple anatomical and functional similarities with their neighboring systems (DAN and DMN) and that this topographical architecture supports distinct interaction patterns that give rise to different patterns of functional behavior. The FPCN acts as a unified system when long-term knowledge supports behavior but becomes segregated into discrete subsystems with different patterns of interaction when long-term memory is less relevant. In this way, our study suggests that the topographical organization of the FPCN and the connections it forms with distant regions of cortex are important influences on how this system supports flexible behavior.
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Affiliation(s)
- Xiuyi Wang
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Katya Krieger-Redwood
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Baihan Lyu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Rebecca Lowndes
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Guowei Wu
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Nicholas E Souter
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
| | - Xiaokang Wang
- Department of Biomedical Engineering, University of California, Davis, California 95616
| | - Ru Kong
- Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117549, Singapore
| | - Golia Shafiei
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Boris C Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec H3A 2B4, Canada
| | - Zaixu Cui
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Jonathan Smallwood
- Department of Psychology, Queens University, Kingston, Ontario K7L 3N6, Canada
| | - Yi Du
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
- Chinese Institute for Brain Research, Beijing 102206, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai 200031, China
| | - Elizabeth Jefferies
- Department of Psychology, University of York, Heslington, York YO10 5DD, United Kingdom
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19
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Malik MA, Weber AM, Lang D, Vanderwal T, Zwicker JG. Changes in cortical grey matter volume with Cognitive Orientation to daily Occupational Performance intervention in children with developmental coordination disorder. Front Hum Neurosci 2024; 18:1316117. [PMID: 38841123 PMCID: PMC11150831 DOI: 10.3389/fnhum.2024.1316117] [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: 10/10/2023] [Accepted: 05/03/2024] [Indexed: 06/07/2024] Open
Abstract
Introduction Cognitive Orientation to daily Occupational Performance (CO-OP) is a cognitive-based, task-specific intervention recommended for children with developmental coordination disorder (DCD). We recently showed structural and functional brain changes after CO-OP, including increased cerebellar grey matter. This study aimed to determine whether CO-OP intervention induced changes in cortical grey matter volume in children with DCD, and if these changes were associated with improvements in motor performance and movement quality. Methods This study is part of a randomized waitlist-control trial (ClinicalTrials.gov ID: NCT02597751). Children with DCD (N = 78) were randomized to either a treatment or waitlist group and underwent three MRIs over 6 months. The treatment group received intervention (once weekly for 10 weeks) between the first and second scan; the waitlist group received intervention between the second and third scan. Cortical grey matter volume was measured using voxel-based morphometry (VBM). Behavioral outcome measures included the Performance Quality Rating Scale (PQRS) and Bruininks-Oseretsky Test of Motor Proficiency-2 (BOT-2). Of the 78 children, 58 were excluded (mostly due to insufficient data quality), leaving a final N = 20 for analyses. Due to the small sample size, we combined both groups to examine treatment effects. Cortical grey matter volume differences were assessed using a repeated measures ANOVA, controlling for total intracranial volume. Regression analyses examined the relationship of grey matter volume changes to BOT-2 (motor performance) and PQRS (movement quality). Results After CO-OP, children had significantly decreased grey matter in the right superior frontal gyrus and middle/posterior cingulate gyri. We found no significant associations of grey matter volume changes with PQRS or BOT-2 scores. Conclusion Decreased cortical grey matter volume generally reflects greater brain maturity. Decreases in grey matter volume after CO-OP intervention were in regions associated with self-regulation and motor control, consistent with our other studies. Decreased grey matter volume may be due to focal increases in synaptic pruning, perhaps as a result of strengthening networks in the brain via the repeated learning and actions in therapy. Findings from this study add to the growing body of literature demonstrating positive neuroplastic changes in the brain after CO-OP intervention.
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Affiliation(s)
- Myrah Anum Malik
- Graduate Programs in Rehabilitation Science, University of British Columbia, Vancouver, BC, Canada
| | - Alexander Mark Weber
- Brain, Behaviour, and Development Theme, BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
| | - Donna Lang
- Brain, Behaviour, and Development Theme, BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Tamara Vanderwal
- Brain, Behaviour, and Development Theme, BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Jill G. Zwicker
- Brain, Behaviour, and Development Theme, BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
- Department of Occupational Science and Occupational Therapy, University of British Columbia, Vancouver, BC, Canada
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20
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Huang S, Faul L, Parikh N, LaBar KS, De Brigard F. Counterfactual thinking induces different neural patterns of memory modification in anxious individuals. Sci Rep 2024; 14:10630. [PMID: 38724623 PMCID: PMC11082200 DOI: 10.1038/s41598-024-61545-x] [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: 12/16/2023] [Accepted: 05/07/2024] [Indexed: 05/12/2024] Open
Abstract
Episodic counterfactual thinking (eCFT) is the process of mentally simulating alternate versions of experiences, which confers new phenomenological properties to the original memory and may be a useful therapeutic target for trait anxiety. However, it remains unclear how the neural representations of a memory change during eCFT. We hypothesized that eCFT-induced memory modification is associated with changes to the neural pattern of a memory primarily within the default mode network, moderated by dispositional anxiety levels. We tested this proposal by examining the representational dynamics of eCFT for 39 participants varying in trait anxiety. During eCFT, lateral parietal regions showed progressively more distinct activity patterns, whereas medial frontal neural activity patterns became more similar to those of the original memory. Neural pattern similarity in many default mode network regions was moderated by trait anxiety, where highly anxious individuals exhibited more generalized representations for upward eCFT (better counterfactual outcomes), but more distinct representations for downward eCFT (worse counterfactual outcomes). Our findings illustrate the efficacy of examining eCFT-based memory modification via neural pattern similarity, as well as the intricate interplay between trait anxiety and eCFT generation.
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Affiliation(s)
- Shenyang Huang
- Department of Psychology and Neuroscience, Duke University, Durham, NC, 27708, USA.
- Center for Cognitive Neuroscience, Duke University, Durham, NC, 27708, USA.
| | - Leonard Faul
- Department of Psychology and Neuroscience, Boston College, Chestnut Hill, MA, 02467, USA
| | - Natasha Parikh
- Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kevin S LaBar
- Department of Psychology and Neuroscience, Duke University, Durham, NC, 27708, USA
- Center for Cognitive Neuroscience, Duke University, Durham, NC, 27708, USA
| | - Felipe De Brigard
- Department of Psychology and Neuroscience, Duke University, Durham, NC, 27708, USA.
- Center for Cognitive Neuroscience, Duke University, Durham, NC, 27708, USA.
- Department of Philosophy, Duke University, Durham, NC, 27708, USA.
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21
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Ke M, Luo X, Guo Y, Zhang J, Ren X, Liu G. Alterations in spatiotemporal characteristics of dynamic networks in juvenile myoclonic epilepsy. Neurol Sci 2024:10.1007/s10072-024-07506-8. [PMID: 38704479 DOI: 10.1007/s10072-024-07506-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 03/27/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND Juvenile myoclonic epilepsy (JME) is characterized by altered patterns of brain functional connectivity (FC). However, the nature and extent of alterations in the spatiotemporal characteristics of dynamic FC in JME patients remain elusive. Dynamic networks effectively encapsulate temporal variations in brain imaging data, offering insights into brain network abnormalities and contributing to our understanding of the seizure mechanisms and origins. METHODS Resting-state functional magnetic resonance imaging (rs-fMRI) data were procured from 37 JME patients and 37 healthy counterparts. Forty-seven network nodes were identified by group-independent component analysis (ICA) to construct the dynamic network. Ultimately, patients' and controls' spatiotemporal characteristics, encompassing temporal clustering and variability, were contrasted at the whole-brain, large-scale network, and regional levels. RESULTS Our findings reveal a marked reduction in temporal clustering and an elevation in temporal variability in JME patients at the whole-brain echelon. Perturbations were notably pronounced in the default mode network (DMN) and visual network (VN) at the large-scale level. Nodes exhibiting anomalous were predominantly situated within the DMN and VN. Additionally, there was a significant correlation between the severity of JME symptoms and the temporal clustering of the VN. CONCLUSIONS Our findings suggest that excessive temporal changes in brain FC may affect the temporal structure of dynamic brain networks, leading to disturbances in brain function in patients with JME. The DMN and VN play an important role in the dynamics of brain networks in patients, and their abnormal spatiotemporal properties may underlie abnormal brain function in patients with JME in the early stages of the disease.
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Affiliation(s)
- Ming Ke
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China.
| | - Xiaofei Luo
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Yi Guo
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Juli Zhang
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Xupeng Ren
- School of Computer and Communication, Lanzhou University of Technology, Lanzhou, 730050, China
| | - Guangyao Liu
- Department of Nuclear Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, 730030, China.
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22
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Setton R, Wynn JS, Schacter DL. Peering into the future: Eye movements predict neural repetition effects during episodic simulation. Neuropsychologia 2024; 197:108852. [PMID: 38508374 PMCID: PMC11140475 DOI: 10.1016/j.neuropsychologia.2024.108852] [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: 10/29/2023] [Revised: 03/09/2024] [Accepted: 03/09/2024] [Indexed: 03/22/2024]
Abstract
Imagining future scenarios involves recombining different elements of past experiences into a coherent event, a process broadly supported by the brain's default network. Prior work suggests that distinct brain regions may contribute to the inclusion of different simulation features. Here we examine how activity in these brain regions relates to the vividness of future simulations. Thirty-four healthy young adults imagined future events with familiar people and locations in a two-part study involving a repetition suppression paradigm. First, participants imagined events while their eyes were tracked during a behavioral session. Immediately after, participants imagined events during MRI scanning. The events to be imagined were manipulated such that some were identical to those imagined in the behavioral session while others involved new locations, new people, or both. In this way, we could examine how self-report ratings and eye movements predict brain activity during simulation along with specific simulation features. Vividness ratings were negatively correlated with eye movements, in contrast to an often-observed positive relationship with past recollection. Moreover, fewer eye movements predicted greater involvement of the hippocampus during simulation, an effect specific to location features. Our findings suggest that eye movements may facilitate scene construction for future thinking, lending support to frameworks that spatial information forms the foundation of episodic simulation.
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Affiliation(s)
- Roni Setton
- Harvard University, Department of Psychology, Cambridge, MA, USA.
| | - Jordana S Wynn
- University of Victoria, Victoria, British Columbia, Canada
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23
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Magrou L, Joyce MKP, Froudist-Walsh S, Datta D, Wang XJ, Martinez-Trujillo J, Arnsten AFT. The meso-connectomes of mouse, marmoset, and macaque: network organization and the emergence of higher cognition. Cereb Cortex 2024; 34:bhae174. [PMID: 38771244 PMCID: PMC11107384 DOI: 10.1093/cercor/bhae174] [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: 01/31/2024] [Revised: 03/29/2024] [Accepted: 04/08/2024] [Indexed: 05/22/2024] Open
Abstract
The recent publications of the inter-areal connectomes for mouse, marmoset, and macaque cortex have allowed deeper comparisons across rodent vs. primate cortical organization. In general, these show that the mouse has very widespread, "all-to-all" inter-areal connectivity (i.e. a "highly dense" connectome in a graph theoretical framework), while primates have a more modular organization. In this review, we highlight the relevance of these differences to function, including the example of primary visual cortex (V1) which, in the mouse, is interconnected with all other areas, therefore including other primary sensory and frontal areas. We argue that this dense inter-areal connectivity benefits multimodal associations, at the cost of reduced functional segregation. Conversely, primates have expanded cortices with a modular connectivity structure, where V1 is almost exclusively interconnected with other visual cortices, themselves organized in relatively segregated streams, and hierarchically higher cortical areas such as prefrontal cortex provide top-down regulation for specifying precise information for working memory storage and manipulation. Increased complexity in cytoarchitecture, connectivity, dendritic spine density, and receptor expression additionally reveal a sharper hierarchical organization in primate cortex. Together, we argue that these primate specializations permit separable deconstruction and selective reconstruction of representations, which is essential to higher cognition.
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Affiliation(s)
- Loïc Magrou
- Department of Neural Science, New York University, New York, NY 10003, United States
| | - Mary Kate P Joyce
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States
| | - Sean Froudist-Walsh
- School of Engineering Mathematics and Technology, University of Bristol, Bristol, BS8 1QU, United Kingdom
| | - Dibyadeep Datta
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06510, United States
| | - Xiao-Jing Wang
- Department of Neural Science, New York University, New York, NY 10003, United States
| | - Julio Martinez-Trujillo
- Departments of Physiology and Pharmacology, and Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, N6A 3K7, Canada
| | - Amy F T Arnsten
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06510, United States
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24
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Xu Y, Liao X, Lei T, Cao M, Zhao J, Zhang J, Zhao T, Li Q, Jeon T, Ouyang M, Chalak L, Rollins N, Huang H, He Y. Development of neonatal connectome dynamics and its prediction for cognitive and language outcomes at age 2. Cereb Cortex 2024; 34:bhae204. [PMID: 38771241 DOI: 10.1093/cercor/bhae204] [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: 12/15/2023] [Revised: 04/23/2024] [Accepted: 05/01/2024] [Indexed: 05/22/2024] Open
Abstract
The functional brain connectome is highly dynamic over time. However, how brain connectome dynamics evolves during the third trimester of pregnancy and is associated with later cognitive growth remains unknown. Here, we use resting-state functional Magnetic Resonance Imaging (MRI) data from 39 newborns aged 32 to 42 postmenstrual weeks to investigate the maturation process of connectome dynamics and its role in predicting neurocognitive outcomes at 2 years of age. Neonatal brain dynamics is assessed using a multilayer network model. Network dynamics decreases globally but increases in both modularity and diversity with development. Regionally, module switching decreases with development primarily in the lateral precentral gyrus, medial temporal lobe, and subcortical areas, with a higher growth rate in primary regions than in association regions. Support vector regression reveals that neonatal connectome dynamics is predictive of individual cognitive and language abilities at 2 years of age. Our findings highlight network-level neural substrates underlying early cognitive development.
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Affiliation(s)
- Yuehua Xu
- School of Systems Science, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Xuhong Liao
- School of Systems Science, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Tianyuan Lei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Miao Cao
- Institution of Science and Technology for Brain-Inspired Intelligence, Fudan University, No. 220 Handan Road, Shanghai 200433, China
| | - Jianlong Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Jiaying Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Qiongling Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Tina Jeon
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, United States
| | - Minhui Ouyang
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, United States
- Department of Radiology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | - Lina Chalak
- Department of Pediatrics, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, United States
| | - Nancy Rollins
- Department of Radiology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, United States
| | - Hao Huang
- Department of Radiology, Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104, United States
- Department of Radiology, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, United States
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
- Chinese Institute for Brain Research, No. 26 Kexueyuan Road, Beijing 102206, China
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25
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Xie K, Royer J, Larivière S, Rodriguez-Cruces R, Frässle S, Cabalo DG, Ngo A, DeKraker J, Auer H, Tavakol S, Weng Y, Abdallah C, Arafat T, Horwood L, Frauscher B, Caciagli L, Bernasconi A, Bernasconi N, Zhang Z, Concha L, Bernhardt BC. Atypical connectome topography and signal flow in temporal lobe epilepsy. Prog Neurobiol 2024; 236:102604. [PMID: 38604584 DOI: 10.1016/j.pneurobio.2024.102604] [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: 06/26/2023] [Revised: 12/18/2023] [Accepted: 04/07/2024] [Indexed: 04/13/2024]
Abstract
Temporal lobe epilepsy (TLE) is the most common pharmaco-resistant epilepsy in adults. While primarily associated with mesiotemporal pathology, recent evidence suggests that brain alterations in TLE extend beyond the paralimbic epicenter and impact macroscale function and cognitive functions, particularly memory. Using connectome-wide manifold learning and generative models of effective connectivity, we examined functional topography and directional signal flow patterns between large-scale neural circuits in TLE at rest. Studying a multisite cohort of 95 patients with TLE and 95 healthy controls, we observed atypical functional topographies in the former group, characterized by reduced differentiation between sensory and transmodal association cortices, with most marked effects in bilateral temporo-limbic and ventromedial prefrontal cortices. These findings were consistent across all study sites, present in left and right lateralized patients, and validated in a subgroup of patients with histopathological validation of mesiotemporal sclerosis and post-surgical seizure freedom. Moreover, they were replicated in an independent cohort of 30 TLE patients and 40 healthy controls. Further analyses demonstrated that reduced differentiation related to decreased functional signal flow into and out of temporolimbic cortical systems and other brain networks. Parallel analyses of structural and diffusion-weighted MRI data revealed that topographic alterations were independent of TLE-related cortical thinning but partially mediated by white matter microstructural changes that radiated away from paralimbic circuits. Finally, we found a strong association between the degree of functional alterations and behavioral markers of memory dysfunction. Our work illustrates the complex landscape of macroscale functional imbalances in TLE, which can serve as intermediate markers bridging microstructural changes and cognitive impairment.
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Affiliation(s)
- Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Raul Rodriguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Stefan Frässle
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Donna Gift Cabalo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Alexander Ngo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Hans Auer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Chifaou Abdallah
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Thaera Arafat
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Linda Horwood
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Birgit Frauscher
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada; Department of Neurology, Duke University School of Medicine and Department of Biomedical Engineering, Duke University Pratt School of Engineering, Durham, NC 27705, USA
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Inselspital, Sleep-Wake-Epilepsy-Center, Bern University Hospital, University of Bern, Bern, Switzerland; Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3 BG, United Kingdom
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de Mexico (UNAM), Queretaro, Mexico
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada.
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26
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Edlow BL, Olchanyi M, Freeman HJ, Li J, Maffei C, Snider SB, Zöllei L, Iglesias JE, Augustinack J, Bodien YG, Haynes RL, Greve DN, Diamond BR, Stevens A, Giacino JT, Destrieux C, van der Kouwe A, Brown EN, Folkerth RD, Fischl B, Kinney HC. Multimodal MRI reveals brainstem connections that sustain wakefulness in human consciousness. Sci Transl Med 2024; 16:eadj4303. [PMID: 38691619 DOI: 10.1126/scitranslmed.adj4303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 04/10/2024] [Indexed: 05/03/2024]
Abstract
Consciousness is composed of arousal (i.e., wakefulness) and awareness. Substantial progress has been made in mapping the cortical networks that underlie awareness in the human brain, but knowledge about the subcortical networks that sustain arousal in humans is incomplete. Here, we aimed to map the connectivity of a proposed subcortical arousal network that sustains wakefulness in the human brain, analogous to the cortical default mode network (DMN) that has been shown to contribute to awareness. We integrated data from ex vivo diffusion magnetic resonance imaging (MRI) of three human brains, obtained at autopsy from neurologically normal individuals, with immunohistochemical staining of subcortical brain sections. We identified nodes of the proposed default ascending arousal network (dAAN) in the brainstem, hypothalamus, thalamus, and basal forebrain. Deterministic and probabilistic tractography analyses of the ex vivo diffusion MRI data revealed projection, association, and commissural pathways linking dAAN nodes with one another and with DMN nodes. Complementary analyses of in vivo 7-tesla resting-state functional MRI data from the Human Connectome Project identified the dopaminergic ventral tegmental area in the midbrain as a widely connected hub node at the nexus of the subcortical arousal and cortical awareness networks. Our network-based autopsy methods and connectivity data provide a putative neuroanatomic architecture for the integration of arousal and awareness in human consciousness.
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Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Mark Olchanyi
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Holly J Freeman
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Jian Li
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Chiara Maffei
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Samuel B Snider
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Lilla Zöllei
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - J Eugenio Iglesias
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Jean Augustinack
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Robin L Haynes
- Department of Pathology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Douglas N Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Bram R Diamond
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Allison Stevens
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Christophe Destrieux
- UMR 1253, iBrain, Université de Tours, Inserm, 10 Boulevard Tonnellé, 37032, Tours, France
- CHRU de Tours, 2 Boulevard Tonnellé, Tours, France
| | - Andre van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Emery N Brown
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | | | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Hannah C Kinney
- Department of Pathology, Boston Children's Hospital and Harvard Medical School, Boston, MA 02115, USA
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27
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Kemmerer D. Transmodal neural substrates of general semantic knowledge: From single words to sentences, stories, and the default mode network. BRAIN AND LANGUAGE 2024; 252:105412. [PMID: 38574556 DOI: 10.1016/j.bandl.2024.105412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Affiliation(s)
- David Kemmerer
- Department of Speech, Language, and Hearing Sciences, Department of Psychological Sciences, Purdue University, United States.
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28
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Fedorenko E, Ivanova AA, Regev TI. The language network as a natural kind within the broader landscape of the human brain. Nat Rev Neurosci 2024; 25:289-312. [PMID: 38609551 DOI: 10.1038/s41583-024-00802-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2024] [Indexed: 04/14/2024]
Abstract
Language behaviour is complex, but neuroscientific evidence disentangles it into distinct components supported by dedicated brain areas or networks. In this Review, we describe the 'core' language network, which includes left-hemisphere frontal and temporal areas, and show that it is strongly interconnected, independent of input and output modalities, causally important for language and language-selective. We discuss evidence that this language network plausibly stores language knowledge and supports core linguistic computations related to accessing words and constructions from memory and combining them to interpret (decode) or generate (encode) linguistic messages. We emphasize that the language network works closely with, but is distinct from, both lower-level - perceptual and motor - mechanisms and higher-level systems of knowledge and reasoning. The perceptual and motor mechanisms process linguistic signals, but, in contrast to the language network, are sensitive only to these signals' surface properties, not their meanings; the systems of knowledge and reasoning (such as the system that supports social reasoning) are sometimes engaged during language use but are not language-selective. This Review lays a foundation both for in-depth investigations of these different components of the language processing pipeline and for probing inter-component interactions.
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Affiliation(s)
- Evelina Fedorenko
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA.
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
- The Program in Speech and Hearing in Bioscience and Technology, Harvard University, Cambridge, MA, USA.
| | - Anna A Ivanova
- School of Psychology, Georgia Institute of Technology, Atlanta, GA, USA
| | - Tamar I Regev
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
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29
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Fromm AE, Grittner U, Brodt S, Flöel A, Antonenko D. No Object-Location Memory Improvement through Focal Transcranial Direct Current Stimulation over the Right Temporoparietal Cortex. Life (Basel) 2024; 14:539. [PMID: 38792561 PMCID: PMC11122124 DOI: 10.3390/life14050539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 04/14/2024] [Accepted: 04/17/2024] [Indexed: 05/26/2024] Open
Abstract
Remembering objects and their associated location (object-location memory; OLM), is a fundamental cognitive function, mediated by cortical and subcortical brain regions. Previously, the combination of OLM training and transcranial direct current stimulation (tDCS) suggested beneficial effects, but the evidence remains heterogeneous. Here, we applied focal tDCS over the right temporoparietal cortex in 52 participants during a two-day OLM training, with anodal tDCS (2 mA, 20 min) or sham (40 s) on the first day. The focal stimulation did not enhance OLM performance on either training day (stimulation effect: -0.09, 95%CI: [-0.19; 0.02], p = 0.08). Higher electric field magnitudes in the target region were not associated with individual performance benefits. Participants with content-related learning strategies showed slightly superior performance compared to participants with position-related strategies. Additionally, training gains were associated with individual verbal learning skills. Consequently, the lack of behavioral benefits through focal tDCS might be due to the involvement of different cognitive processes and brain regions, reflected by participant's learning strategies. Future studies should evaluate whether other brain regions or memory-relevant networks may be involved in the modulation of object-location associations, investigating other target regions, and further exploring individualized stimulation parameters.
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Affiliation(s)
- Anna Elisabeth Fromm
- Department of Neurology, Universitätsmedizin Greifswald, Ferdinand-Sauerbruch-Straße, 17475 Greifswald, Germany
| | - Ulrike Grittner
- Berlin Institute of Health (BIH), 10178 Berlin, Germany
- Institute of Biometry and Clinical Epidemiology, Charité—Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, 10117 Berlin, Germany
| | - Svenja Brodt
- Max Planck Institute for Biological Cybernetics, 72076 Tübingen, Germany
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, 72076 Tübingen, Germany
| | - Agnes Flöel
- Department of Neurology, Universitätsmedizin Greifswald, Ferdinand-Sauerbruch-Straße, 17475 Greifswald, Germany
- German Centre for Neurodegenerative Diseases (DZNE) Standort Greifswald, 17489 Greifswald, Germany
| | - Daria Antonenko
- Department of Neurology, Universitätsmedizin Greifswald, Ferdinand-Sauerbruch-Straße, 17475 Greifswald, Germany
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30
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Armstrong M, Castellanos J, Christie D. Chronic pain as an emergent property of a complex system and the potential roles of psychedelic therapies. FRONTIERS IN PAIN RESEARCH 2024; 5:1346053. [PMID: 38706873 PMCID: PMC11066302 DOI: 10.3389/fpain.2024.1346053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 04/02/2024] [Indexed: 05/07/2024] Open
Abstract
Despite research advances and urgent calls by national and global health organizations, clinical outcomes for millions of people suffering with chronic pain remain poor. We suggest bringing the lens of complexity science to this problem, conceptualizing chronic pain as an emergent property of a complex biopsychosocial system. We frame pain-related physiology, neuroscience, developmental psychology, learning, and epigenetics as components and mini-systems that interact together and with changing socioenvironmental conditions, as an overarching complex system that gives rise to the emergent phenomenon of chronic pain. We postulate that the behavior of complex systems may help to explain persistence of chronic pain despite current treatments. From this perspective, chronic pain may benefit from therapies that can be both disruptive and adaptive at higher orders within the complex system. We explore psychedelic-assisted therapies and how these may overlap with and complement mindfulness-based approaches to this end. Both mindfulness and psychedelic therapies have been shown to have transdiagnostic value, due in part to disruptive effects on rigid cognitive, emotional, and behavioral patterns as well their ability to promote neuroplasticity. Psychedelic therapies may hold unique promise for the management of chronic pain.
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Affiliation(s)
- Maya Armstrong
- Department of Family & Community Medicine, University of New Mexico, Albuquerque, NM, United States
| | - Joel Castellanos
- Division of Pain Medicine, Department of Anesthesiology, University of California, San Diego, CA, United States
| | - Devon Christie
- Department of Medicine, University of British Columbia, Vancouver, BC, Canada
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31
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Rosen D, Oh Y, Chesebrough C, Zhang FZ, Kounios J. Creative flow as optimized processing: Evidence from brain oscillations during jazz improvisations by expert and non-expert musicians. Neuropsychologia 2024; 196:108824. [PMID: 38387554 DOI: 10.1016/j.neuropsychologia.2024.108824] [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: 10/14/2023] [Revised: 02/14/2024] [Accepted: 02/15/2024] [Indexed: 02/24/2024]
Abstract
Using a creative production task, jazz improvisation, we tested alternative hypotheses about the flow experience: (A) that it is a state of domain-specific processing optimized by experience and characterized by minimal interference from task-negative default-mode network (DMN) activity versus (B) that it recruits domain-general task-positive DMN activity supervised by the fronto-parietal control network (FPCN) to support ideation. We recorded jazz guitarists' electroencephalograms (EEGs) while they improvised to provided chord sequences. Their flow-states were measured with the Core Flow State Scale. Flow-related neural sources were reconstructed using SPM12. Over all musicians, high-flow (relative to low-flow) improvisations were associated with transient hypofrontality. High-experience musicians' high-flow improvisations showed reduced activity in posterior DMN nodes. Low-experience musicians showed no flow-related DMN or FPCN modulation. High-experience musicians also showed modality-specific left-hemisphere flow-related activity while low-experience musicians showed modality-specific right-hemisphere flow-related deactivations. These results are consistent with the idea that creative flow represents optimized domain-specific processing enabled by extensive practice paired with reduced cognitive control.
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Affiliation(s)
- David Rosen
- Department of Psychological and Brain Sciences, Drexel University, United States.
| | - Yongtaek Oh
- Department of Psychological and Brain Sciences, Drexel University, United States.
| | | | - Fengqing Zoe Zhang
- Department of Psychological and Brain Sciences, Drexel University, United States.
| | - John Kounios
- Department of Psychological and Brain Sciences, Drexel University, United States.
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32
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Wheelock JR, Long NM. The persistence of memory: prior memory responses modulate behavior and brain state engagement. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.05.588245. [PMID: 38645245 PMCID: PMC11030234 DOI: 10.1101/2024.04.05.588245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Memory brain states may influence how we experience an event. Memory encoding and retrieval constitute neurally dissociable brain states that individuals can selectively engage based on top-down goals. To the extent that memory states linger in time - as suggested by prior behavioral work - memory states may influence not only the current experience, but also subsequent stimuli and judgments. Thus lingering memory states may have broad influences on cognition, yet this account has not been directly tested utilizing neural measures of memory states. Here we address this gap by testing the hypothesis that memory brain states are modulated by memory judgments, and that these brain states persist for several hundred milliseconds. We recorded scalp electroencephalography (EEG) while participants completed a recognition memory task. We used an independently validated multivariate mnemonic state classifier to assess memory state engagement. We replicate prior behavioral findings; however, our neural findings run counter to the predictions made on the basis of the behavioral data. Surprisingly, we find that prior responses modulate current memory state engagement on the basis of response congruency. That is, we find strong engagement of the retrieval state on incongruent trials - when a target is preceded by a correct rejection of a lure and when a lure is preceded by successful recognition of a target. These findings indicate that cortical brain states are influenced by prior judgments and suggest that a non-mnemonic, internal attention state may be recruited to in the face of changing demands in a dynamic environment.
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33
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Watters H, Fazili A, Daley L, Belden A, LaGrow TJ, Bolt T, Loui P, Keilholz S. Creative tempo: Spatiotemporal dynamics of the default mode network in improvisational musicians. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.07.588391. [PMID: 38645080 PMCID: PMC11030431 DOI: 10.1101/2024.04.07.588391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
The intrinsic dynamics of human brain activity display a recurring pattern of anti-correlated activity between the default mode network (DMN), associated with internal processing and mentation, and task positive regions, associated with externally directed attention. In human functional magnetic resonance imaging (fMRI) data, this anti-correlated pattern is detectable on the infraslow timescale (<0.1 Hz) as a quasi-periodic pattern (QPP). While the DMN is implicated in creativity and musicality in traditional time-averaged functional connectivity studies, no one has yet explored how creative training may alter dynamic spatiotemporal patterns involving the DMN such as QPPs. In the present study, we compare the outputs of two QPP detection approaches, sliding window algorithm and complex principal components analysis (cPCA). We apply both methods to an existing dataset of musicians captured with resting state fMRI, grouped as either classical, improvisational, or minimally trained non-musicians. The original time-averaged functional connectivity (FC) analysis of this dataset used improvisation as a proxy for creative thinking and found that the DMN and visual networks (VIS) display higher connectivity in improvisational musicians. We expand upon this dataset's original study and find that QPP analysis detects convergent results at the group level with both methods. In improvisational musicians, dynamic functional correlation in the group-averaged QPP was found to be increased between the DMN-VIS and DMN-FPN for both the QPP algorithm and complex principal components analysis (cPCA) methods. Additionally, we found an unexpected increase in FC in the group-averaged QPP between the dorsal attention network and amygdala in improvisational musicians; this result was not reported in the original seed-based study of this dataset. The current study represents a novel application of two dynamic FC detection methods with results that replicate and expand upon previous seed-based FC findings. The results show the robustness of both the QPP phenomenon and its detection methods. This study also demonstrates the value of dynamic FC methods in reproducing seed-based findings and their promise in detecting group-wise or individual differences that may be missed by traditional seed-based resting state fMRI studies.
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Affiliation(s)
| | | | - Lauren Daley
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology
| | | | - T J LaGrow
- Georgia Institute of Technology School of Electrical and Computer Engineering
| | - Taylor Bolt
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology
| | | | - Shella Keilholz
- Department of Biomedical Engineering, Emory University/Georgia Institute of Technology
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34
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Falcó-Roget J, Cacciola A, Sambataro F, Crimi A. Functional and structural reorganization in brain tumors: a machine learning approach using desynchronized functional oscillations. Commun Biol 2024; 7:419. [PMID: 38582867 PMCID: PMC10998892 DOI: 10.1038/s42003-024-06119-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/28/2024] [Indexed: 04/08/2024] Open
Abstract
Neuroimaging studies have allowed for non-invasive mapping of brain networks in brain tumors. Although tumor core and edema are easily identifiable using standard MRI acquisitions, imaging studies often neglect signals, structures, and functions within their presence. Therefore, both functional and diffusion signals, as well as their relationship with global patterns of connectivity reorganization, are poorly understood. Here, we explore the functional activity and the structure of white matter fibers considering the contribution of the whole tumor in a surgical context. First, we find intertwined alterations in the frequency domain of local and spatially distributed resting-state functional signals, potentially arising within the tumor. Second, we propose a fiber tracking pipeline capable of using anatomical information while still reconstructing bundles in tumoral and peritumoral tissue. Finally, using machine learning and healthy anatomical information, we predict structural rearrangement after surgery given the preoperative brain network. The generative model also disentangles complex patterns of connectivity reorganization for different types of tumors. Overall, we show the importance of carefully designing studies including MR signals within damaged brain tissues, as they exhibit and relate to non-trivial patterns of both structural and functional (dis-)connections or activity.
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Affiliation(s)
- Joan Falcó-Roget
- Brain and More Lab, Computer Vision, Sano Centre for Computational Medicine, Kraków, Poland.
| | - Alberto Cacciola
- Brain Mapping Lab, Department of Biomedical, Dental Sciences and Morphological and Functional Imaging, University of Messina, Messina, Italy
| | - Fabio Sambataro
- Department of Neuroscience, University of Padova, Padua, Italy
| | - Alessandro Crimi
- Brain and More Lab, Computer Vision, Sano Centre for Computational Medicine, Kraków, Poland.
- Faculty of Computer Science, AGH University of Krakow, Kraków, Poland.
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35
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Jones HM, Yoo K, Chun MM, Rosenberg MD. Edge-Based General Linear Models Capture Moment-to-Moment Fluctuations in Attention. J Neurosci 2024; 44:e1543232024. [PMID: 38316565 PMCID: PMC10993033 DOI: 10.1523/jneurosci.1543-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 12/18/2023] [Accepted: 01/15/2024] [Indexed: 02/07/2024] Open
Abstract
Although we must prioritize the processing of task-relevant information to navigate life, our ability to do so fluctuates across time. Previous work has identified fMRI functional connectivity (FC) networks that predict an individual's ability to sustain attention and vary with attentional state from 1 min to the next. However, traditional dynamic FC approaches typically lack the temporal precision to capture moment-to-moment network fluctuations. Recently, researchers have "unfurled" traditional FC matrices in "edge cofluctuation time series" which measure timepoint-by-timepoint cofluctuations between regions. Here we apply event-based and parametric fMRI analyses to edge time series to capture moment-to-moment fluctuations in networks related to attention. In two independent fMRI datasets examining young adults of both sexes in which participants performed a sustained attention task, we identified a reliable set of edges that rapidly deflects in response to rare task events. Another set of edges varies with continuous fluctuations in attention and overlaps with a previously defined set of edges associated with individual differences in sustained attention. Demonstrating that edge-based analyses are not simply redundant with traditional regions-of-interest-based approaches, up to one-third of reliably deflected edges were not predicted from univariate activity patterns alone. These results reveal the large potential in combining traditional fMRI analyses with edge time series to identify rapid reconfigurations in networks across the brain.
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Affiliation(s)
- Henry M Jones
- Department of Psychology, The University of Chicago, Chicago, Illinois 60637
- Institute for Mind and Biology, The University of Chicago, Chicago, Illinois 60637
| | - Kwangsun Yoo
- Department of Psychology, Yale University, New Haven, Connecticut 06520
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul 06355, Korea
- Data Science Research Institute, Research Institute for Future Medicine, Samsung Medical Center, Seoul 06351, Korea
| | - Marvin M Chun
- Department of Psychology, Yale University, New Haven, Connecticut 06520
- Wu Tsai Institute, Yale University, New Haven, Connecticut 06520
- Department of Neuroscience, Yale University, New Haven, Connecticut 06520
| | - Monica D Rosenberg
- Department of Psychology, The University of Chicago, Chicago, Illinois 60637
- Institute for Mind and Biology, The University of Chicago, Chicago, Illinois 60637
- Neuroscience Institute, The University of Chicago, Chicago, Illinois 60637
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36
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Hosseini EA, Schrimpf M, Zhang Y, Bowman S, Zaslavsky N, Fedorenko E. Artificial Neural Network Language Models Predict Human Brain Responses to Language Even After a Developmentally Realistic Amount of Training. NEUROBIOLOGY OF LANGUAGE (CAMBRIDGE, MASS.) 2024; 5:43-63. [PMID: 38645622 PMCID: PMC11025646 DOI: 10.1162/nol_a_00137] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 01/09/2024] [Indexed: 04/23/2024]
Abstract
Artificial neural networks have emerged as computationally plausible models of human language processing. A major criticism of these models is that the amount of training data they receive far exceeds that of humans during language learning. Here, we use two complementary approaches to ask how the models' ability to capture human fMRI responses to sentences is affected by the amount of training data. First, we evaluate GPT-2 models trained on 1 million, 10 million, 100 million, or 1 billion words against an fMRI benchmark. We consider the 100-million-word model to be developmentally plausible in terms of the amount of training data given that this amount is similar to what children are estimated to be exposed to during the first 10 years of life. Second, we test the performance of a GPT-2 model trained on a 9-billion-token dataset to reach state-of-the-art next-word prediction performance on the human benchmark at different stages during training. Across both approaches, we find that (i) the models trained on a developmentally plausible amount of data already achieve near-maximal performance in capturing fMRI responses to sentences. Further, (ii) lower perplexity-a measure of next-word prediction performance-is associated with stronger alignment with human data, suggesting that models that have received enough training to achieve sufficiently high next-word prediction performance also acquire representations of sentences that are predictive of human fMRI responses. In tandem, these findings establish that although some training is necessary for the models' predictive ability, a developmentally realistic amount of training (∼100 million words) may suffice.
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Affiliation(s)
- Eghbal A. Hosseini
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Martin Schrimpf
- The MIT Quest for Intelligence Initiative, Cambridge, MA, USA
- Swiss Federal Institute of Technology, Lausanne, Switzerland
| | - Yian Zhang
- Computer Science Department, Stanford University, Stanford, CA, USA
| | - Samuel Bowman
- Center for Data Science, New York University, New York, NY, USA
- Department of Linguistics, New York University, New York, NY, USA
- Department of Computer Science, New York University, New York, NY, USA
| | - Noga Zaslavsky
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- K. Lisa Yang Integrative Computational Neuroscience (ICoN) Center, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Language Science, University of California, Irvine, CA, USA
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- The MIT Quest for Intelligence Initiative, Cambridge, MA, USA
- Speech and Hearing Bioscience and Technology Program, Harvard University, Boston, MA, USA
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37
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Guichet C, Banjac S, Achard S, Mermillod M, Baciu M. Modeling the neurocognitive dynamics of language across the lifespan. Hum Brain Mapp 2024; 45:e26650. [PMID: 38553863 PMCID: PMC10980845 DOI: 10.1002/hbm.26650] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 02/08/2024] [Accepted: 02/26/2024] [Indexed: 04/02/2024] Open
Abstract
Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed between language comprehension and language production (LP). Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this variability. At the cognitive level, our findings suggest that LP is not an isolated function but is modulated throughout the lifespan by the extent of inter-cognitive synergy between semantic and domain-general processes. At the cerebral level, we show that default mode network (DMN) suppression coupled with fronto-parietal network (FPN) integration is the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related decline in LP. Relatedly, reduced DMN suppression in midlife could compromise the ability to manage the cost of FPN integration. This may prompt older adults to adopt a more cost-efficient compensatory strategy that maintains global homeostasis at the expense of LP performances. Taken together, we propose that midlife represents a critical neurocognitive juncture that signifies the onset of LP decline, as older adults gradually lose control over semantic representations. We summarize our findings in a novel synergistic, economical, nonlinear, emergent, cognitive aging model, integrating connectomic and cognitive dimensions within a complex system perspective.
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Affiliation(s)
| | - Sonja Banjac
- Université Grenoble Alpes, CNRS LPNC UMR 5105GrenobleFrance
| | - Sophie Achard
- LJK, UMR CNRS 5224, Université Grenoble AlpesGrenobleFrance
| | | | - Monica Baciu
- Université Grenoble Alpes, CNRS LPNC UMR 5105GrenobleFrance
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38
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Kim W, Kim MJ. Adaptive-to-maladaptive gradient of emotion regulation tendencies are embedded in the functional-structural hybrid connectome. Psychol Med 2024:1-13. [PMID: 38533787 DOI: 10.1017/s0033291724000473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/28/2024]
Abstract
BACKGROUND Emotion regulation tendencies are well-known transdiagnostic markers of psychopathology, but their neurobiological foundations have mostly been examined within the theoretical framework of cortical-subcortical interactions. METHODS We explored the connectome-wide neural correlates of emotion regulation tendencies using functional and diffusion magnetic resonance images of healthy young adults (N = 99; age 20-30; 28 females). We first tested the importance of considering both the functional and structural connectome through intersubject representational similarity analyses. Then, we employed a canonical correlation analysis between the functional-structural hybrid connectome and 23 emotion regulation strategies. Lastly, we sought to externally validate the results on a transdiagnostic adolescent sample (N = 93; age 11-19; 34 females). RESULTS First, interindividual similarity of emotion regulation profiles was significantly correlated with interindividual similarity of the functional-structural hybrid connectome, more so than either the functional or structural connectome. Canonical correlation analysis revealed that an adaptive-to-maladaptive gradient of emotion regulation tendencies mapped onto a specific configuration of covariance within the functional-structural hybrid connectome, which primarily involved functional connections in the motor network and the visual networks as well as structural connections in the default mode network and the subcortical-cerebellar network. In the transdiagnostic adolescent dataset, stronger functional signatures of the found network were associated with higher general positive affect through more frequent use of adaptive coping strategies. CONCLUSIONS Taken together, our study illustrates a gradient of emotion regulation tendencies that is best captured when simultaneously considering the functional and structural connections across the whole brain.
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Affiliation(s)
- Wonyoung Kim
- Department of Psychology, Emory University, Atlanta, GA, USA
- Department of Psychology, Sungkyunkwan University, Seoul, South Korea
| | - M Justin Kim
- Department of Psychology, Sungkyunkwan University, Seoul, South Korea
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, South Korea
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39
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Jimenez CA, Meyer ML. The dorsomedial prefrontal cortex prioritizes social learning during rest. Proc Natl Acad Sci U S A 2024; 121:e2309232121. [PMID: 38466844 PMCID: PMC10962978 DOI: 10.1073/pnas.2309232121] [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: 06/01/2023] [Accepted: 02/12/2024] [Indexed: 03/13/2024] Open
Abstract
Sociality is a defining feature of the human experience: We rely on others to ensure survival and cooperate in complex social networks to thrive. Are there brain mechanisms that help ensure we quickly learn about our social world to optimally navigate it? We tested whether portions of the brain's default network engage "by default" to quickly prioritize social learning during the memory consolidation process. To test this possibility, participants underwent functional MRI (fMRI) while viewing scenes from the documentary film, Samsara. This film shows footage of real people and places from around the world. We normed the footage to select scenes that differed along the dimension of sociality, while matched on valence, arousal, interestingness, and familiarity. During fMRI, participants watched the "social" and "nonsocial" scenes, completed a rest scan, and a surprise recognition memory test. Participants showed superior social (vs. nonsocial) memory performance, and the social memory advantage was associated with neural pattern reinstatement during rest in the dorsomedial prefrontal cortex (DMPFC), a key node of the default network. Moreover, it was during early rest that DMPFC social pattern reinstatement was greatest and predicted subsequent social memory performance most strongly, consistent with the "prioritization" account. Results simultaneously update 1) theories of memory consolidation, which have not addressed how social information may be prioritized in the learning process, and 2) understanding of default network function, which remains to be fully characterized. More broadly, the results underscore the inherent human drive to understand our vastly social world.
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Affiliation(s)
| | - Meghan L. Meyer
- Department of Psychology, Columbia University, New York, NY10027
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Kurkela K, Ritchey M. Intrinsic functional connectivity among memory networks does not predict individual differences in narrative recall. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.31.555768. [PMID: 38464053 PMCID: PMC10925185 DOI: 10.1101/2023.08.31.555768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Individuals differ greatly in their ability to remember the details of past events, yet little is known about the brain processes that explain such individual differences in a healthy young population. Previous research suggests that episodic memory relies on functional communication among ventral regions of the default mode network ("DMN-C") that are strongly interconnected with the medial temporal lobes. In this study, we investigated whether the intrinsic functional connectivity of the DMN-C subnetwork is related to individual differences in memory ability, examining this relationship across 243 individuals (ages 18-50 years) from the openly available Cambridge Center for Aging and Neuroscience (Cam-CAN) dataset. We first estimated each participant's whole-brain intrinsic functional brain connectivity by combining data from resting-state, movie-watching, and sensorimotor task scans to increase statistical power. We then examined whether intrinsic functional connectivity predicted performance on a narrative recall task. We found no evidence that functional connectivity of the DMN-C, with itself, with other related DMN subnetworks, or with the rest of the brain, was related to narrative recall. Exploratory connectome-based predictive modeling (CBPM) analyses of the entire connectome revealed a whole-brain multivariate pattern that predicted performance, although these changes were largely outside of known memory networks. These results add to emerging evidence suggesting that individual differences in memory cannot be easily explained by brain differences in areas typically associated with episodic memory function.
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Affiliation(s)
- Kyle Kurkela
- Department of Psychology and Neuroscience, Boston College
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Yi X, Wang X, Fu Y, Luo Y, Wang J, Han Z, Kuang Y, Chen X, Chen BT. Altered brain activity and cognitive impairment in patients with psoriasis. J Eur Acad Dermatol Venereol 2024; 38:557-567. [PMID: 38059666 DOI: 10.1111/jdv.19685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 10/25/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND Patients with psoriasis may have cognitive impairment. However, there is limited information regarding intrinsic brain activity and cognitive function in patients with psoriasis. OBJECTIVES This study aim to assess alterations of intrinsic brain activity and its association with cognitive function in patients with psoriasis. METHODS A total of 222 patients with psoriasis aged 18-70 years and 144 age and gender-matched healthy controls (HCs) were enrolled into this study. All subjects underwent brain resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological testing. The rs-fMRI data were analysed for both intrinsic brain activity as indicated by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC). Correlative analysis of brain activity with cognitive assessment was performed. RESULTS Compared with the HCs, patients with psoriasis had worse cognitive performance in the Trail Making Test, Digit Span Test and Stroop Color-Word Test (p < 0.05). Patients with psoriasis showed decreased ALFF in the left superior frontal gyrus, the left medial superior frontal gyrus and the right precuneus gyrus; as well as enhanced ALFF in the left paracentral lobule (pFWE < 0.05). Significant correlations were noted between the altered ALFF in the four brain regions and cognitive assessment (p < 0.05). Moreover, patients with psoriasis had increased FC between the four brain regions with altered ALFF (seeds) and the left prefrontal gyrus, the left anterior cingulate gyrus, left superior parietal lobule and default mode network (DMN) regions such as the right precuneus gyrus, left inferior parietal lobule, right angular gyrus and bilateral inferior temporal gyrus (pFWE < 0.05). CONCLUSIONS Patients with psoriasis had altered brain activity and connectivity in the key brain areas within the DMN-prefrontal circuit. These brain changes may be the underlying neural correlates for cognitive functioning in patients with psoriasis.
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Affiliation(s)
- Xiaoping Yi
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xueying Wang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, China
| | - Yan Fu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, China
| | - Yan Luo
- Department of Dermatology, People's Hospital of Jiangxi Province, Nanchang, Jiangxi, China
| | - Jing Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zaide Han
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yehong Kuang
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xiang Chen
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Bihong T Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, California, USA
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Giacomucci G, Moschini V, Piazzesi D, Padiglioni S, Caruso C, Nuti C, Munarin A, Mazzeo S, Galdo G, Polito C, Emiliani F, Frigerio D, Morinelli C, Bagnoli S, Ingannato A, Nacmias B, Sorbi S, Berti V, Bessi V. Disentangling empathy impairment along Alzheimer's disease continuum: From subjective cognitive decline to Alzheimer's dementia. Cortex 2024; 172:125-140. [PMID: 38301390 DOI: 10.1016/j.cortex.2023.12.009] [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: 09/15/2023] [Revised: 11/14/2023] [Accepted: 12/19/2023] [Indexed: 02/03/2024]
Abstract
Little is known about empathy changes from the early stages of Alzheimer's Disease (AD) continuum. The aim of this study is to investigate empathy across AD spectrum from Subjective Cognitive Decline (SCD) to Mild Cognitive Impairment (MCI) and AD dementia (AD-d). Forty-five SCD, 83 MCI and 80 AD-d patients were included. Empathy was assessed by Interpersonal Reactivity Index (IRI) (Perspective Taking - PT, Fantasy - FT, Empathic Concern - EC, and Personal Distress - PD), rated by caregivers before (T0) and after (T1) cognitive symptoms' onset. IRI was also administered to SCD patients to have a self-reported empathy evaluation. Facial emotion recognition was assessed by Ekman-60 Faces Test. Twenty-two SCD, 54 MCI and 62 AD-d patients underwent CSF biomarkers analysis and were classified as carriers of AD pathology (AP+) when they were A+/T+ (regardless of N), or non-carriers (AP-) when they were A- (regardless of T and N), or A+/T-/N-, or A+/T-/N+ according to the A/T(N) system. Cerebral FDG-PET SPM analysis was used to explore neural correlates underlying empathy deficits. PD scores significantly increased from T0 to T1 in SCD, MCI and AD-d (p < .001), while PT scores decreased in MCI and in AD-d (p < .001). SCD AP+ showed a greater increase in PD scores over time (ΔPD T0 - T1) than SCD AP- (p < .001). SCD self-reported PT scores were lower than those of general Italian population (14.94 ± 3.94, 95% C.I. [13.68-16.20] vs 17.70 ± 4.36, 95% C.I. [17.30-18.10]). In AD continuum (SCD AP+, MCI AP+, AD-d), a positive correlation was detected between PT-T1 and brain metabolism in left posterior cingulate gyrus, precuneus and right frontal gyri; a negative correlation was found between ΔPT and brain metabolism in bilateral posterior cingulate gyri. PT may be subtly involved since the preclinical phase of AD. Changes over time of PD are influenced by the underlying Alzheimer's pathology and could potentially serve as an early AD neuropsychological marker.
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Affiliation(s)
- Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Valentina Moschini
- SOD Neurologia I, Dipartimento Neuromuscolo-Scheletrico e degli Organi di Senso, AOU Careggi, Florence, Italy
| | - Diletta Piazzesi
- SOD Neurologia I, Dipartimento Neuromuscolo-Scheletrico e degli Organi di Senso, AOU Careggi, Florence, Italy
| | - Sonia Padiglioni
- Regional Referral Centre for Relational Criticalities - Tuscany Region, Italy; Research and Innovation Centre for Dementia-CRIDEM, AOU Careggi, Italy
| | | | | | | | - Salvatore Mazzeo
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Giulia Galdo
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | | | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Daniele Frigerio
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Carmen Morinelli
- SOD Neurologia I, Dipartimento Neuromuscolo-Scheletrico e degli Organi di Senso, AOU Careggi, Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy; IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy; IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Valentina Berti
- Department of Biomedical, Experimental and Clinical Sciences "Mario Serio", University of Florence, Florence, Italy; Nuclear Medicine Unit, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.
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Pagonabarraga J, Bejr-Kasem H, Martinez-Horta S, Kulisevsky J. Parkinson disease psychosis: from phenomenology to neurobiological mechanisms. Nat Rev Neurol 2024; 20:135-150. [PMID: 38225264 DOI: 10.1038/s41582-023-00918-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/13/2023] [Indexed: 01/17/2024]
Abstract
Parkinson disease (PD) psychosis (PDP) is a spectrum of illusions, hallucinations and delusions that are associated with PD throughout its disease course. Psychotic phenomena can manifest from the earliest stages of PD and might follow a continuum from minor hallucinations to structured hallucinations and delusions. Initially, PDP was considered to be a complication associated with dopaminergic drug use. However, subsequent research has provided evidence that PDP arises from the progression of brain alterations caused by PD itself, coupled with the use of dopaminergic drugs. The combined dysfunction of attentional control systems, sensory processing, limbic structures, the default mode network and thalamocortical connections provides a conceptual framework to explain how new incoming stimuli are incorrectly categorized, and how aberrant hierarchical predictive processing can produce false percepts that intrude into the stream of consciousness. The past decade has seen the publication of new data on the phenomenology and neurobiological basis of PDP from the initial stages of the disease, as well as the neurotransmitter systems involved in PDP initiation and progression. In this Review, we discuss the latest clinical, neuroimaging and neurochemical evidence that could aid early identification of psychotic phenomena in PD and inform the discovery of new therapeutic targets and strategies.
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Affiliation(s)
- Javier Pagonabarraga
- Movement Disorder Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.
- Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain.
- Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain.
- Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain.
| | - Helena Bejr-Kasem
- Movement Disorder Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain
- Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Saul Martinez-Horta
- Movement Disorder Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain
- Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Jaime Kulisevsky
- Movement Disorder Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
- Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain
- Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
- Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
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Kubera KM, Rashidi M, Schmitgen MM, Barth A, Hirjak D, Otte ML, Sambataro F, Calhoun VD, Wolf RC. Functional network interactions in patients with schizophrenia with persistent auditory verbal hallucinations: A multimodal MRI fusion approach using three-way pICA. Schizophr Res 2024; 265:20-29. [PMID: 37024417 DOI: 10.1016/j.schres.2023.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Revised: 02/18/2023] [Accepted: 03/03/2023] [Indexed: 04/08/2023]
Abstract
Over the last decade, there have been an increasing number of functional magnetic resonance imaging (fMRI) studies examining brain activity in schizophrenia (SZ) patients with persistent auditory verbal hallucinations (AVH) using either task-based or resting-state fMRI (rs-fMRI) paradigms. Such data have been conventionally collected and analyzed as distinct modalities, disregarding putative crossmodal interactions. Recently, it has become possible to incorporate two or more modalities in one comprehensive analysis to uncover hidden patterns of neural dysfunction not sufficiently captured by separate analysis. A novel multivariate fusion approach to multimodal data analysis, i.e., parallel independent component analysis (pICA), has been previously shown to be a powerful tool in this regard. We utilized three-way pICA to study covarying components among fractional amplitude of low-frequency fluctuations (fALFF) for rs-MRI and task-based activation computed from an alertness and a working memory (WM) paradigm of 15 SZ patients with AVH, 16 non-hallucinating SZ patients (nAVH), and 19 healthy controls (HC). The strongest connected triplet (false discovery rate (FDR)-corrected pairwise correlations) comprised a frontostriatal/temporal network (fALFF), a temporal/sensorimotor network (alertness task), and a frontoparietal network (WM task). Frontoparietal and frontostriatal/temporal network strength significantly differed between AVH patients and HC. Phenomenological features such as omnipotence and malevolence of AVH were associated with temporal/sensorimotor and frontoparietal network strength. The transmodal data confirm a complex interplay of neural systems subserving attentional processes and cognitive control interacting with speech and language processing networks. In addition, the data emphasize the importance of sensorimotor regions modulating specific symptom dimensions of AVH.
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Affiliation(s)
- Katharina M Kubera
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Germany
| | - Mahmoud Rashidi
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Germany
| | - Mike M Schmitgen
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Germany
| | - Anja Barth
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marie-Luise Otte
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Germany
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padua, Padua, Italy; Padua Neuroscience Center, University of Padua, Padua, Italy
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Robert C Wolf
- Center for Psychosocial Medicine, Department of General Psychiatry, Heidelberg University, Germany.
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Luo Y, Pluta D, Brodrick BB, Palka JM, McCoy J, Lohrenz T, Gu X, Vannucci M, Montague PR, McAdams CJ. Diminished Adaptation, Satisfaction, and Neural Responses to Advantageous Social Signals in Anorexia Nervosa and Bulimia Nervosa. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:305-313. [PMID: 37951540 PMCID: PMC10939989 DOI: 10.1016/j.bpsc.2023.10.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 09/22/2023] [Accepted: 10/23/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND Development and recurrence of 2 eating disorders (EDs), anorexia nervosa and bulimia nervosa, are frequently associated with environmental stressors. Neurobehavioral responses to social learning signals were evaluated in both EDs. METHODS Women with anorexia nervosa (n = 25), women with bulimia nervosa (n = 30), or healthy comparison women (n = 38) played a neuroeconomic game in which the norm shifted, generating social learning signals (norm prediction errors [NPEs]) during a functional magnetic resonance imaging scan. A Bayesian logistic regression model examined how the probability of offer acceptance depended on cohort, block, and NPEs. Rejection rates, emotion ratings, and neural responses to NPEs were compared across groups. RESULTS Relative to the comparison group, both ED cohorts showed less adaptation (p = .028, ηp2 = 0.060), and advantageous signals (positive NPEs) led to higher rejection rates (p = .014, ηp2 = 0.077) and less positive emotion ratings (p = .004, ηp2 = 0.111). Advantageous signals increased neural activations in the orbitofrontal cortex for the comparison group but not for women with anorexia nervosa (p = .018, d = 0.655) or bulimia nervosa (p = .043, d = 0.527). More severe ED symptoms were associated with decreased activation of dorsomedial prefrontal cortex for advantageous signals. CONCLUSIONS Diminished neural processing of advantageous social signals and impaired norm adaptation were observed in both anorexia nervosa and bulimia nervosa, while no differences were found for disadvantageous social signals. Development of neurocognitive interventions to increase responsivity to advantageous social signals could augment current treatments, potentially leading to improved clinical outcomes for EDs.
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Affiliation(s)
- Yi Luo
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Fralin Biomedical Research Institute, Virginia Tech, Roanoke, Virginia
| | - Dustin Pluta
- Department of Statistics, Rice University, Houston, Texas
| | - Brooks B Brodrick
- Department of Psychiatry, University of Texas at Southwestern Medical School, Dallas, Texas
| | - Jayme M Palka
- Department of Psychiatry, University of Texas at Southwestern Medical School, Dallas, Texas
| | - Jordan McCoy
- Department of Psychiatry, University of Texas at Southwestern Medical School, Dallas, Texas
| | - Terry Lohrenz
- Fralin Biomedical Research Institute, Virginia Tech, Roanoke, Virginia
| | - Xiaosi Gu
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York; Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | | | - P Read Montague
- Fralin Biomedical Research Institute, Virginia Tech, Roanoke, Virginia; Department of Physics, Virginia Tech, Blacksburg, Virginia; Virginia Tech-Wake Forest School of Biomedical Engineering and Mechanics, Blacksburg, Virginia
| | - Carrie J McAdams
- Department of Psychiatry, University of Texas at Southwestern Medical School, Dallas, Texas.
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Rabini G, Funghi G, Meli C, Pierotti E, Saviola F, Jovicich J, Dodich A, Papagno C, Turella L. Functional alterations in resting-state networks for Theory of Mind in Parkinson's disease. Eur J Neurosci 2024; 59:1213-1226. [PMID: 37670685 DOI: 10.1111/ejn.16145] [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: 05/31/2023] [Revised: 08/23/2023] [Accepted: 08/26/2023] [Indexed: 09/07/2023]
Abstract
In Parkinson's disease (PD), impairment of Theory of Mind (ToM) has recently attracted an increasing number of neuroscientific investigations. If and how functional connectivity of the ToM network is altered in PD is still an open question. First, we explored whether ToM network connectivity shows potential PD-specific functional alterations when compared to healthy controls (HC). Second, we tested the role of the duration of PD in the evolution of functional alterations in the ToM network. Between-group connectivity alterations were computed adopting resting-state functional magnetic resonance imaging (rs-fMRI) data of four groups: PD patients with short disease duration (PD-1, n = 72); PD patients with long disease duration (PD-2, n = 22); healthy controls for PD-1 (HC-1, n = 69); healthy controls for PD-2 (HC-2, n = 22). We explored connectivity differences in the ToM network within and between its three subnetworks: Affective, Cognitive and Core. PD-1 presented a global pattern of decreased functional connectivity within the ToM network, compared to HC-1. The alterations mainly involved the Cognitive and Affective ToM subnetworks and their reciprocal connections. PD-2-those with longer disease duration-showed an increased connectivity spanning the entire ToM network, albeit less consistently in the Core ToM network, compared to both the PD-1 and the HC-2 groups. Functional connectivity within the ToM network is altered in PD. The alterations follow a graded pattern, with decreased connectivity at short disease duration, which broadens to a generalized increase with longer disease duration. The alterations involve both the Cognitive and Affective subnetworks of ToM.
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Affiliation(s)
- Giuseppe Rabini
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Giulia Funghi
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Claudia Meli
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Enrica Pierotti
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Francesca Saviola
- Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy
| | - Jorge Jovicich
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | | | - Costanza Papagno
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Luca Turella
- Center for Mind/Brain Sciences, University of Trento, Trento, Italy
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Peters‐Founshtein G, Gazit L, Naveh T, Domachevsky L, Korczyn AD, Bernstine H, Shaharabani‐Gargir L, Groshar D, Marshall GA, Arzy S. Lost in space(s): Multimodal neuroimaging of disorientation along the Alzheimer's disease continuum. Hum Brain Mapp 2024; 45:e26623. [PMID: 38488454 PMCID: PMC10941506 DOI: 10.1002/hbm.26623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 01/02/2024] [Accepted: 01/27/2024] [Indexed: 03/18/2024] Open
Abstract
Orientation is a fundamental cognitive faculty and the bedrock of the neurologic examination. Orientation is defined as the alignment between an individual's internal representation and the external world in the spatial, temporal, and social domains. While spatial disorientation is a recognized hallmark of Alzheimer's disease (AD), little is known about disorientation beyond space in AD. This study aimed to explore disorientation in spatial, temporal, and social domains along the AD continuum. Fifty-one participants along the AD continuum performed an ecological orientation task in the spatial, temporal, and social domains while undergoing functional MRI. Disorientation in AD followed a three-way association between orientation domain, brain region, and disease stage. Specifically, patients with early amnestic mild cognitive impairment exhibited spatio-temporal disorientation and reduced brain activity in temporoparietal regions, while patients with AD dementia showed additional social disorientation and reduced brain activity in frontoparietal regions. Furthermore, patterns of hypoactivation overlapped different subnetworks of the default mode network, patterns of fluorodeoxyglucose hypometabolism, and cortical atrophy characteristic of AD. Our results suggest that AD may encompass a disorder of orientation, characterized by a biphasic process manifesting as early spatio-temporal and late social disorientation. As such, disorientation may offer a unique window into the clinicopathological progression of AD. SIGNIFICANCE STATEMENT: Despite extensive research into Alzheimer's disease (AD), its core cognitive deficit remains a matter of debate. In this study, we investigated whether orientation, defined as the ability to align internal representations with the external world in spatial, temporal, and social domains, constitutes a core cognitive deficit in AD. To do so, we used PET-fMRI imaging to collect behavioral, functional, and metabolic data from 51 participants along the AD continuum. Our findings suggest that AD may constitute a disorder of orientation, characterized by an early spatio-temporal disorientation and followed by late social disorientation, manifesting in task-evoked and neurodegenerative changes. We propose that a profile of disorientation across multiple domains offers a unique window into the progression of AD and as such could greatly benefit disease diagnosis, monitoring, and evaluation of treatment response.
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Affiliation(s)
- Gregory Peters‐Founshtein
- The Computational Neuropsychiatry Lab, Department of Medical Neurobiology, Faculty of MedicineHebrew University of JerusalemJerusalemIsrael
- Department of Nuclear MedicineSheba Medical CenterRamat‐GanIsrael
| | - Lidor Gazit
- The Computational Neuropsychiatry Lab, Department of Medical Neurobiology, Faculty of MedicineHebrew University of JerusalemJerusalemIsrael
- Department of NeurologyHadassah Hebrew University Medical SchoolJerusalemIsrael
| | - Tahel Naveh
- The Computational Neuropsychiatry Lab, Department of Medical Neurobiology, Faculty of MedicineHebrew University of JerusalemJerusalemIsrael
- Department of NeurologyHadassah Hebrew University Medical SchoolJerusalemIsrael
| | - Liran Domachevsky
- Department of Nuclear MedicineSheba Medical CenterRamat‐GanIsrael
- Department of Nuclear MedicineAssuta Medical CenterTel‐AvivIsrael
| | | | - Hanna Bernstine
- Department of Nuclear MedicineAssuta Medical CenterTel‐AvivIsrael
- Department of ImagingTel‐Aviv UniversityTel‐AvivIsrael
- Department of Nuclear MedicineRabin Medical CenterPetah TikvaIsrael
| | | | - David Groshar
- Department of Nuclear MedicineAssuta Medical CenterTel‐AvivIsrael
- Department of ImagingTel‐Aviv UniversityTel‐AvivIsrael
| | - Gad A. Marshall
- Department of Neurology, Center for Alzheimer Research and Treatment, Harvard Medical School, Brigham and Women's HospitalMassachusetts General HospitalBostonMassachusettsUSA
| | - Shahar Arzy
- The Computational Neuropsychiatry Lab, Department of Medical Neurobiology, Faculty of MedicineHebrew University of JerusalemJerusalemIsrael
- Department of NeurologyHadassah Hebrew University Medical SchoolJerusalemIsrael
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48
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Malik-Moraleda S, Jouravlev O, Taliaferro M, Mineroff Z, Cucu T, Mahowald K, Blank IA, Fedorenko E. Functional characterization of the language network of polyglots and hyperpolyglots with precision fMRI. Cereb Cortex 2024; 34:bhae049. [PMID: 38466812 PMCID: PMC10928488 DOI: 10.1093/cercor/bhae049] [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: 01/18/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 03/13/2024] Open
Abstract
How do polyglots-individuals who speak five or more languages-process their languages, and what can this population tell us about the language system? Using fMRI, we identified the language network in each of 34 polyglots (including 16 hyperpolyglots with knowledge of 10+ languages) and examined its response to the native language, non-native languages of varying proficiency, and unfamiliar languages. All language conditions engaged all areas of the language network relative to a control condition. Languages that participants rated as higher proficiency elicited stronger responses, except for the native language, which elicited a similar or lower response than a non-native language of similar proficiency. Furthermore, unfamiliar languages that were typologically related to the participants' high-to-moderate-proficiency languages elicited a stronger response than unfamiliar unrelated languages. The results suggest that the language network's response magnitude scales with the degree of engagement of linguistic computations (e.g. related to lexical access and syntactic-structure building). We also replicated a prior finding of weaker responses to native language in polyglots than non-polyglot bilinguals. These results contribute to our understanding of how multiple languages coexist within a single brain and provide new evidence that the language network responds more strongly to stimuli that more fully engage linguistic computations.
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Affiliation(s)
- Saima Malik-Moraleda
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Boston, MA 02114, United States
| | - Olessia Jouravlev
- Department of Cognitive Science, Carleton University, Ottawa K1S 5B6, Canada
| | - Maya Taliaferro
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
| | - Zachary Mineroff
- Eberly Center, Carnegie Mellon University, Pittsburgh, PA 15289, United States
| | - Theodore Cucu
- Department of Psychology, Carnegie Mellon University, Pittsburgh, PA 15289, United States
| | - Kyle Mahowald
- Department of Linguistics, The University of Texas at Austin, Austin, TX 78712, United States
| | - Idan A Blank
- Department of Psychology, University of California Los Angeles, Los Angeles, CA 90095, United States
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Boston, MA 02114, United States
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49
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Hu Y, Pan Y, Yue L, Gao X. Self-objectification and eating disorders: the psychopathological and neural processes from psychological distortion to psychosomatic illness. PSYCHORADIOLOGY 2024; 4:kkae003. [PMID: 38666139 PMCID: PMC10946225 DOI: 10.1093/psyrad/kkae003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 01/30/2024] [Accepted: 02/27/2024] [Indexed: 04/28/2024]
Affiliation(s)
- Yinying Hu
- Department of Applied Psychology, School of Psychology, Shanghai Normal University, Shanghai, Shanghai 200234, China
| | - Yafeng Pan
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, China
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, Zhejaing 310058, China
| | - Liming Yue
- Department of Applied Psychology, School of Psychology, Shanghai Normal University, Shanghai, Shanghai 200234, China
| | - Xiangping Gao
- Department of Applied Psychology, School of Psychology, Shanghai Normal University, Shanghai, Shanghai 200234, China
- Shanghai Institute of Early Childhood Education, Shanghai Normal University, Shanghai, Shanghai 200234, China
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50
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Yu M, Risacher SL, Nho KT, Wen Q, Oblak AL, Unverzagt FW, Apostolova LG, Farlow MR, Brosch JR, Clark DG, Wang S, Deardorff R, Wu YC, Gao S, Sporns O, Saykin AJ. Spatial transcriptomic patterns underlying amyloid-β and tau pathology are associated with cognitive dysfunction in Alzheimer's disease. Cell Rep 2024; 43:113691. [PMID: 38244198 PMCID: PMC10926093 DOI: 10.1016/j.celrep.2024.113691] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 11/29/2023] [Accepted: 01/03/2024] [Indexed: 01/22/2024] Open
Abstract
Amyloid-β (Aβ) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aβ and tau pathologies than others, gene expression may play a role. We study the association between brain-wide gene expression profiles and regional vulnerability to Aβ (gene-to-Aβ associations) and tau (gene-to-tau associations) pathologies by leveraging two large independent AD cohorts. We identify AD susceptibility genes and gene modules in a gene co-expression network with expression profiles specifically related to regional vulnerability to Aβ and tau pathologies in AD. In addition, we identify distinct biochemical pathways associated with the gene-to-Aβ and the gene-to-tau associations. These findings may explain the discordance between regional Aβ and tau pathologies. Finally, we propose an analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA.
| | - Shannon L Risacher
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kwangsik T Nho
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA
| | - Qiuting Wen
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adrian L Oblak
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Frederick W Unverzagt
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Liana G Apostolova
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Martin R Farlow
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jared R Brosch
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - David G Clark
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sophia Wang
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Rachael Deardorff
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yu-Chien Wu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Sujuan Gao
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA; Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA; Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana University Network Science Institute, Bloomington, IN, USA.
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