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Silva Alves A, Rigoni I, Mégevand P, Lagarde S, Picard F, Seeck M, Vulliémoz S, Roehri N. High-density electroencephalographic functional networks in genetic generalized epilepsy: Preserved whole-brain topology hides local reorganization. Epilepsia 2024; 65:961-973. [PMID: 38306118 DOI: 10.1111/epi.17903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 01/15/2024] [Accepted: 01/16/2024] [Indexed: 02/03/2024]
Abstract
OBJECTIVE Genetic generalized epilepsy (GGE) accounts for approximately 20% of adult epilepsy cases and is considered a disorder of large brain networks, involving both hemispheres. Most studies have not shown any difference in functional whole-brain network topology when compared to healthy controls. Our objective was to examine whether this preserved global network topology could hide local reorganizations that balance out at the global network level. METHODS We recorded high-density electroencephalograms from 20 patients and 20 controls, and reconstructed the activity of 118 regions. We computed functional connectivity in windows free of interictal epileptiform discharges in broad, delta, theta, alpha, and beta frequency bands, characterized the network topology, and used the Hub Disruption Index (HDI) to quantify the topological reorganization. We examined the generalizability of our results by reproducing a 25-electrode clinical system. RESULTS Our study did not reveal any significant change in whole-brain network topology among GGE patients. However, the HDI was significantly different between patients and controls in all frequency bands except alpha (p < .01, false discovery rate [FDR] corrected, d < -1), and accompanied by an increase in connectivity in the prefrontal regions and default mode network. This reorganization suggests that regions that are important in transferring the information in controls were less so in patients. Inversely, the crucial regions in patients are less so in controls. These findings were also found in delta and theta frequency bands when using 25 electrodes (p < .001, FDR corrected, d < -1). SIGNIFICANCE In GGE patients, the overall network topology is similar to that of healthy controls but presents a balanced local topological reorganization. This reorganization causes the prefrontal areas and default mode network to be more integrated and segregated, which may explain executive impairment associated with GGE. Additionally, the reorganization distinguishes patients from controls even when using 25 electrodes, suggesting its potential use as a diagnostic tool.
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Affiliation(s)
- André Silva Alves
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Isotta Rigoni
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Pierre Mégevand
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Stanislas Lagarde
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Aix Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Fabienne Picard
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Serge Vulliémoz
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Nicolas Roehri
- EEG and Epilepsy Unit, University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
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Cardinale EM, Bezek J, Siegal O, Freitag GF, Subar A, Khosravi P, Mallidi A, Peterson O, Morales I, Haller SP, Filippi C, Lee K, Brotman MA, Leibenluft E, Pine DS, Linke JO, Kircanski K. Multivariate Assessment of Inhibitory Control in Youth: Links With Psychopathology and Brain Function. Psychol Sci 2024; 35:376-389. [PMID: 38446868 DOI: 10.1177/09567976241231574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024] Open
Abstract
Inhibitory control is central to many theories of cognitive and brain development, and impairments in inhibitory control are posited to underlie developmental psychopathology. In this study, we tested the possibility of shared versus unique associations between inhibitory control and three common symptom dimensions in youth psychopathology: attention-deficit/hyperactivity disorder (ADHD), anxiety, and irritability. We quantified inhibitory control using four different experimental tasks to estimate a latent variable in 246 youth (8-18 years old) with varying symptom types and levels. Participants were recruited from the Washington, D.C., metro region. Results of structural equation modeling integrating a bifactor model of psychopathology revealed that inhibitory control predicted a shared or general psychopathology dimension, but not ADHD-specific, anxiety-specific, or irritability-specific dimensions. Inhibitory control also showed a significant, selective association with global efficiency in a frontoparietal control network delineated during resting-state functional magnetic resonance imaging. These results support performance-based inhibitory control linked to resting-state brain function as an important predictor of comorbidity in youth psychopathology.
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Affiliation(s)
- Elise M Cardinale
- Department of Psychology, The Catholic University of America
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | | | - Olivia Siegal
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | - Gabrielle F Freitag
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | - Anni Subar
- Department of Child and Adolescent Psychiatry, New York University Grossman School of Medicine
| | - Parmis Khosravi
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | - Ajitha Mallidi
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | - Olivia Peterson
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | - Isaac Morales
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | - Simone P Haller
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | | | - Kyunghun Lee
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | - Melissa A Brotman
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | - Ellen Leibenluft
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | - Daniel S Pine
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
| | | | - Katharina Kircanski
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD
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van der Heide FCT, Steens ILM, Limmen B, Mokhtar S, van Boxtel MPJ, Schram MT, Köhler S, Kroon AA, van der Kallen CJH, Dagnelie PC, van Dongen MCJM, Eussen SJPM, Berendschot TTJM, Webers CAB, van Greevenbroek MMJ, Koster A, van Sloten TT, Jansen JFA, Backes WH, Stehouwer CDA. Thinner inner retinal layers are associated with lower cognitive performance, lower brain volume, and altered white matter network structure-The Maastricht Study. Alzheimers Dement 2024; 20:316-329. [PMID: 37611119 PMCID: PMC10917009 DOI: 10.1002/alz.13442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Revised: 07/26/2023] [Accepted: 08/01/2023] [Indexed: 08/25/2023]
Abstract
INTRODUCTION The retina may provide non-invasive, scalable biomarkers for monitoring cerebral neurodegeneration. METHODS We used cross-sectional data from The Maastricht study (n = 3436; mean age 59.3 years; 48% men; and 21% with type 2 diabetes [the latter oversampled by design]). We evaluated associations of retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses with cognitive performance and magnetic resonance imaging indices (global grey and white matter volume, hippocampal volume, whole brain node degree, global efficiency, clustering coefficient, and local efficiency). RESULTS After adjustment, lower thicknesses of most inner retinal layers were significantly associated with worse cognitive performance, lower grey and white matter volume, lower hippocampal volume, and worse brain white matter network structure assessed from lower whole brain node degree, lower global efficiency, higher clustering coefficient, and higher local efficiency. DISCUSSION The retina may provide biomarkers that are informative of cerebral neurodegenerative changes in the pathobiology of dementia.
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Grants
- 31O.041 OP-Zuid, the Province of Limburg, the Dutch Ministry of Economic Affairs
- Stichting De Weijerhorst (Maastricht, the Netherlands), the Pearl String Initiative Diabetes (Amsterdam, the Netherlands), the Cardiovascular Center (CVC, Maastricht, the Netherlands), CARIM School for Cardiovascular Diseases (Maastricht, the Netherlands), CAPHRI School for Public Health and Primary Care (Maastricht, the Netherlands), NUTRIM School for Nutrition and Translational Research in Metabolism (Maastricht, the Netherlands), Stichting Annadal (Maastricht, the Netherlands), Health Foundation Limburg (Maastricht, the Netherlands), Perimed (Järfälla, Sweden), and by unrestricted grants from Janssen-Cilag B.V. (Tilburg, the Netherlands), Novo Nordisk Farma B.V. (Alphen aan den Rijn, the Netherlands), and Sanofi-Aventis Netherlands B.V. (Gouda, the Netherlands)
- 916.19.074 VENI research
- 2018T025 Netherlands Organization for Scientific Research and the Netherlands Organization for Health Research and Development, and a Dutch Heart Foundation research
- 2021.81.004 Diabetes Fonds Fellowship
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Ding Q, Lin T, Cai G, Ou Z, Yao S, Zhu H, Lan Y. Individual differences in beta-band oscillations predict motor-inhibitory control. Front Neurosci 2023; 17:1131862. [PMID: 36937674 PMCID: PMC10014589 DOI: 10.3389/fnins.2023.1131862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Accepted: 02/14/2023] [Indexed: 03/05/2023] Open
Abstract
Objective The ability of motor-inhibitory control is critical in daily life. The physiological mechanisms underlying motor inhibitory control deficits remain to be elucidated. Beta band oscillations have been suggested to be related to motor performance, but whether they relate to motor-inhibitory control remains unclear. This study is aimed at systematically investigating the relationship between beta band oscillations and motor-inhibitory control to determine whether beta band oscillations were related to the ability of motor-inhibitory control. Methods We studied 30 healthy young adults (age: 21.6 ± 1.5 years). Stop-signal reaction time (SSRT) was derived from stop signal task, indicating the ability of motor-inhibitory control. Resting-state electroencephalography (EEG) was recorded for 12 min. Beta band power and functional connectivity (including global efficiency) were calculated. Correlations between beta band oscillations and SSRT were performed. Results Beta band EEG power in left and right motor cortex (MC), right somatosensory cortex (SC), and right inferior frontal cortex (IFC) was positively correlated with SSRT (P's = 0.031, 0.021, 0.045, and 0.015, respectively). Beta band coherence between bilateral MC, SC, and IFC was also positively correlated with SSRT (P's < 0.05). Beta band global efficiency was positively correlated with SSRT (P = 0.01). Conclusion This is the first study to investigate the relationship between resting-state cortical beta oscillations and response inhibition. Our findings revealed that individuals with better ability of motor inhibitory control tend to have less cortical beta band power and functional connectivity. This study has clinical significance on the underlying mechanisms of motor inhibitory control deficits.
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Affiliation(s)
- Qian Ding
- Department of Rehabilitation Medicine, Guangzhou First People’s Hospital, South China University of Technology, Guangzhou, Guangdong, China
- Department of Rehabilitation Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- Guangzhou Key Laboratory of Aging Frailty and Neurorehabilitation, Guangzhou, Guangdong, China
| | - Tuo Lin
- Department of Rehabilitation Medicine, Guangzhou First People’s Hospital, South China University of Technology, Guangzhou, Guangdong, China
| | - Guiyuan Cai
- Department of Rehabilitation Medicine, Guangzhou First People’s Hospital, South China University of Technology, Guangzhou, Guangdong, China
| | - Zitong Ou
- Department of Rehabilitation Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Shantong Yao
- Department of Rehabilitation Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
| | - Hongxiang Zhu
- Department of Rehabilitation Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, China
- *Correspondence: Hongxiang Zhu,
| | - Yue Lan
- Department of Rehabilitation Medicine, Guangzhou First People’s Hospital, South China University of Technology, Guangzhou, Guangdong, China
- Guangzhou Key Laboratory of Aging Frailty and Neurorehabilitation, Guangzhou, Guangdong, China
- Yue Lan,
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Song H, Ruan Z, Gao L, Lv D, Sun D, Li Z, Zhang R, Zhou X, Xu H, Zhang J. Structural network efficiency mediates the association between glymphatic function and cognition in mild VCI: a DTI-ALPS study. Front Aging Neurosci 2022; 14:974114. [PMID: 36466598 PMCID: PMC9708722 DOI: 10.3389/fnagi.2022.974114] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 10/27/2022] [Indexed: 09/03/2023] Open
Abstract
Background and objective: Vascular cognitive impairment (VCI) can be caused by multiple types of cerebrovascular pathology and is considered a network disconnection disorder. The heterogeneity hinders research progress in VCI. Glymphatic failure has been considered as a key common pathway to dementia recently. The emergence of a new method, Diffusion Tensor Image Analysis Along the Perivascular Space (DTI-ALPS), makes it possible to investigate the changes of the glymphatic function in humans non-invasively. We aimed to investigate alterations of glymphatic function in VCI and its potential impact on network connectivity. Methods: We recruited 79 patients with mild VCI, including 40 with cerebral small vessel disease cognitive impairment (SVCI) and 39 with post-stroke cognitive impairment (PSCI); and, 77 normal cognitive (NC) subjects were recruited. All subjects received neuropsychological assessments and multimodal magnetic resonance imaging scans. ALPS-index was calculated and structural networks were constructed by deterministic tractography, and then, the topological metrics of these structural connectivity were evaluated. Results: The ALPS-index of VCI patients was significantly lower than that of NC subjects (P < 0.001). Multiple linear regression analysis showed that ALPS-index affects cognitive function independently (β = 0.411, P < 0.001). The results of correlation analysis showed that the ALPS-index was correlated with overall vascular risk factor burden (r = -0.263, P = 0.001) and multiple cerebrovascular pathologies (P < 0.05). In addition, global efficiency (Eg) of network was correlated with ALPS-index in both SVCI (r = 0.348, P = 0.028) and PSCI (r = 0.732, P < 0.001) patients. Finally, the results of mediation analysis showed that Eg partially mediated in the impact of glymphatic dysfunction on cognitive impairment (indirect effect = 7.46, 95% CI 4.08-11.48). Conclusion: In both major subtypes of VCI, the ALPS-index was decreased, indicating impaired glymphatic function in VCI. Glymphatic dysfunction may affect cognitive function in VCI by disrupting network connectivity, and, may be a potential common pathological mechanism of VCI. ALPS-index is expected to become an emerging imaging marker for VCI.
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Affiliation(s)
- Hao Song
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zhao Ruan
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Lei Gao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Dongwei Lv
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Dong Sun
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zeng Li
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Ran Zhang
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xiaoli Zhou
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Haibo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Junjian Zhang
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
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Formaggio E, Rubega M, Rupil J, Antonini A, Masiero S, Toffolo GM, Del Felice A. Reduced Effective Connectivity in the Motor Cortex in Parkinson's Disease. Brain Sci 2021; 11:brainsci11091200. [PMID: 34573222 PMCID: PMC8466840 DOI: 10.3390/brainsci11091200] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 09/06/2021] [Accepted: 09/09/2021] [Indexed: 11/16/2022] Open
Abstract
Fast rhythms excess is a hallmark of Parkinson’s Disease (PD). To implement innovative, non-pharmacological, neurostimulation interventions to restore cortical-cortical interactions, we need to understand the neurophysiological mechanisms underlying these phenomena. Here, we investigated effective connectivity on source-level resting-state electroencephalography (EEG) signals in 15 PD participants and 10 healthy controls. First, we fitted multivariate auto-regressive models to the EEG source waveforms. Second, we estimated causal connections using Granger Causality, which provide information on connections’ strength and directionality. Lastly, we sought significant differences connectivity patterns between the two populations characterizing the network graph features—i.e., global efficiency and node strength. Causal brain networks in PD show overall poorer and weaker connections compared to controls quantified as a reduction of global efficiency. Motor areas appear almost isolated, with a strongly impoverished information flow particularly from parietal and occipital cortices. This striking isolation of motor areas may reflect an impaired sensory-motor integration in PD. The identification of defective nodes/edges in PD network may be a biomarker of disease and a potential target for future interventional trials.
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Affiliation(s)
- Emanuela Formaggio
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Gustiniani 3, 35128 Padova, Italy; (E.F.); (S.M.); (A.D.F.)
| | - Maria Rubega
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Gustiniani 3, 35128 Padova, Italy; (E.F.); (S.M.); (A.D.F.)
- Correspondence:
| | - Jessica Rupil
- Department of Information Engineering, University of Padova, Via Gradenigo 6/A, 35131 Padova, Italy; (J.R.); (G.M.T.)
| | - Angelo Antonini
- Parkinson and Movement Disorders Unit, Study Centre on Neurodegeneration (CESNE), Department of Neuroscience, University of Padova, Via Giustiniani 5, 35121 Padova, Italy;
- Padova Neuroscience Center, University of Padova, Via Orus, 35128 Padova, Italy
| | - Stefano Masiero
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Gustiniani 3, 35128 Padova, Italy; (E.F.); (S.M.); (A.D.F.)
- Padova Neuroscience Center, University of Padova, Via Orus, 35128 Padova, Italy
| | - Gianna Maria Toffolo
- Department of Information Engineering, University of Padova, Via Gradenigo 6/A, 35131 Padova, Italy; (J.R.); (G.M.T.)
| | - Alessandra Del Felice
- Department of Neuroscience, Section of Rehabilitation, University of Padova, Via Gustiniani 3, 35128 Padova, Italy; (E.F.); (S.M.); (A.D.F.)
- Padova Neuroscience Center, University of Padova, Via Orus, 35128 Padova, Italy
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Akın A. fNIRS-derived neurocognitive ratio as a biomarker for neuropsychiatric diseases. Neurophotonics 2021; 8:035008. [PMID: 34604439 PMCID: PMC8482313 DOI: 10.1117/1.nph.8.3.035008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 09/16/2021] [Indexed: 05/03/2023]
Abstract
Significance: Clinical use of fNIRS-derived features has always suffered low sensitivity and specificity due to signal contamination from background systemic physiological fluctuations. We provide an algorithm to extract cognition-related features by eliminating the effect of background signal contamination, hence improving the classification accuracy. Aim: The aim in this study is to investigate the classification accuracy of an fNIRS-derived biomarker based on global efficiency (GE). To this end, fNIRS data were collected during a computerized Stroop task from healthy controls and patients with migraine, obsessive compulsive disorder, and schizophrenia. Approach: Functional connectivity (FC) maps were computed from [HbO] time series data for neutral (N), congruent (C), and incongruent (I) stimuli using the partial correlation approach. Reconstruction of FC matrices with optimal choice of principal components yielded two independent networks: cognitive mode network (CM) and default mode network (DM). Results: GE values computed for each FC matrix after applying principal component analysis (PCA) yielded strong statistical significance leading to a higher specificity and accuracy. A new index, neurocognitive ratio (NCR), was computed by multiplying the cognitive quotients (CQ) and ratio of GE of CM to GE of DM. When mean values of NCR ( N C R ¯ ) over all stimuli were computed, they showed high sensitivity (100%), specificity (95.5%), and accuracy (96.3%) for all subjects groups. Conclusions: N C R ¯ can reliable be used as a biomarker to improve the classification of healthy to neuropsychiatric patients.
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Affiliation(s)
- Ata Akın
- Acibadem University, Department of Medical Engineering, Ataşehir, Istanbul, Turkey
- Address all correspondence to Ata Akn,
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Yan T, Zhuang K, He L, Liu C, Zeng R, Qiu J. Left temporal pole contributes to creative thinking via an individual semantic network. Psychophysiology 2021; 58:e13841. [PMID: 34159607 DOI: 10.1111/psyp.13841] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 01/09/2021] [Accepted: 02/03/2021] [Indexed: 11/29/2022]
Abstract
The neural substrates that contribute to creative thinking through the recruitment of semantic memory structures remain largely unknown. This study sought to investigate the properties of semantic networks using a semantic judgment rating task at the individual level and explore the relationship among creative abilities, the topological properties of semantic networks, and their underlying brain structures. We first used a semantic judgment rating to assess individual semantic networks and computed their topological properties. The analysis confirmed a significant correlation between the creative thinking abilities assessed by an alternate uses task and all three topological properties. In addition, voxel-based morphometry was employed to assess the neural correlates of gray matter volume (GMV) related to different topological properties of the semantic network. Results revealed a positive correlation between global efficiency and the left temporal pole cortex, considered to be involved in semantic information transmission and processing. Furthermore, mediation analysis found that the global efficiency of the individual semantic network mediated the association between the left temporal pole GMV and creative thinking, showing that the relationship between left temporal pole GMV and creative thinking may be affected by the semantic networks. To the best of our knowledge, this study is the first to combine a behavioral investigation of semantic networks with magnetic resonance imaging to shed light on the cerebral structural basis of semantic memory networks, in addition to their relationship to creativity.
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Affiliation(s)
- Tingrui Yan
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Kaixiang Zhuang
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Li He
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Cheng Liu
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Rongcan Zeng
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China
| | - Jiang Qiu
- Key Laboratory of Cognition and Personality of Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, China.,Southwest University Branch, Collaborative Innovation Center of Assessment Toward Basic Education Quality, Beijing Normal University, Beijing, China
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Tan W, Liu Z, Xi C, Deng M, Long Y, Palaniyappan L, Yang J. Decreased integration of the frontoparietal network during a working memory task in major depressive disorder. Aust N Z J Psychiatry 2021; 55:577-587. [PMID: 33322919 DOI: 10.1177/0004867420978284] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
BACKGROUND Working memory deficits are a common feature in major depressive disorder and are associated with poor functional outcomes. Intact working memory performance requires the recruitment of large-scale brain networks. However, it is unknown how the disrupted recruitment of distributed regions belonging to these large-scale networks at the whole-brain level brings about working memory impairment seen in major depressive disorder. METHODS We used graph theory to examine the functional connectomic metrics (local and global efficiency) at the whole-brain and large-scale network levels in 38 patients with major depressive disorder and 41 healthy controls during a working memory task. Altered connectomic metrics were studied in a moderation model relating to clinical symptoms and working memory accuracy in patients, and a machine learning method was employed to assess whether these metrics carry enough illness-specific information to discriminate patients from controls. RESULTS Global efficiency of the frontoparietal network was reduced in major depressive disorder (false discovery rate corrected, p = 0.014); this reduction predicted worse working memory performance in patients with less severe illness burden indexed by Brief Psychiatric Rating Scale (β =-0.43, p = 0.035, t =-2.2, 95% confidence interval = [-0.043,-0.002]). We achieved a classification accuracy and area under the curve of 73.42% and 0.734, respectively, to discriminate patients from controls based on connectomic metrics, and the global efficiency of the frontoparietal network contributed most to the diagnostic classification. CONCLUSIONS We report a putative mechanistic link between the global efficiency of the frontoparietal network and impaired n-back performance in major depressive disorder. This relationship is more pronounced at lower levels of symptom burden, indicating the possibility of multiple pathways to cognitive deficits in severe major depressive disorder.
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Affiliation(s)
- Wenjian Tan
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhening Liu
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Chang Xi
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Mengjie Deng
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yicheng Long
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Lena Palaniyappan
- Department of Psychiatry, University of Western Ontario, London, ON, Canada.,Robarts Research Institute, University of Western Ontario, London, ON, Canada.,Lawson Health Research Institute, London, ON, Canada
| | - Jie Yang
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, China.,National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, China
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Iordan AD, Moored KD, Katz B, Cooke KA, Buschkuehl M, Jaeggi SM, Polk TA, Peltier SJ, Jonides J, Reuter‐Lorenz PA. Age differences in functional network reconfiguration with working memory training. Hum Brain Mapp 2021; 42:1888-1909. [PMID: 33534925 PMCID: PMC7978135 DOI: 10.1002/hbm.25337] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 12/21/2020] [Accepted: 12/22/2020] [Indexed: 12/16/2022] Open
Abstract
Demanding cognitive functions like working memory (WM) depend on functional brain networks being able to communicate efficiently while also maintaining some degree of modularity. Evidence suggests that aging can disrupt this balance between integration and modularity. In this study, we examined how cognitive training affects the integration and modularity of functional networks in older and younger adults. Twenty three younger and 23 older adults participated in 10 days of verbal WM training, leading to performance gains in both age groups. Older adults exhibited lower modularity overall and a greater decrement when switching from rest to task, compared to younger adults. Interestingly, younger but not older adults showed increased task-related modularity with training. Furthermore, whereas training increased efficiency within, and decreased participation of, the default-mode network for younger adults, it enhanced efficiency within a task-specific salience/sensorimotor network for older adults. Finally, training increased segregation of the default-mode from frontoparietal/salience and visual networks in younger adults, while it diffusely increased between-network connectivity in older adults. Thus, while younger adults increase network segregation with training, suggesting more automated processing, older adults persist in, and potentially amplify, a more integrated and costly global workspace, suggesting different age-related trajectories in functional network reorganization with WM training.
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Affiliation(s)
| | - Kyle D. Moored
- Department of Mental Health, Bloomberg School of Public HealthJohns Hopkins UniversityBaltimoreMarylandUSA
| | - Benjamin Katz
- Department of Human Development and Family ScienceVirginia TechBlacksburgVirginiaUSA
| | | | | | - Susanne M. Jaeggi
- School of EducationUniversity of California‐IrvineIrvineCaliforniaUSA
| | - Thad A. Polk
- Department of PsychologyUniversity of MichiganAnn ArborMichiganUSA
| | - Scott J. Peltier
- Functional MRI LaboratoryUniversity of MichiganAnn ArborMichiganUSA
- Department of Biomedical EngineeringUniversity of MichiganAnn ArborMichiganUSA
| | - John Jonides
- Department of PsychologyUniversity of MichiganAnn ArborMichiganUSA
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11
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Evensmoen HR, Rimol LM, Winkler AM, Betzel R, Hansen TI, Nili H, Håberg A. Allocentric representation in the human amygdala and ventral visual stream. Cell Rep 2021; 34:108658. [PMID: 33472067 DOI: 10.1016/j.celrep.2020.108658] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 10/01/2020] [Accepted: 12/21/2020] [Indexed: 12/27/2022] Open
Abstract
The hippocampus and the entorhinal cortex are considered the main brain structures for allocentric representation of the external environment. Here, we show that the amygdala and the ventral visual stream are involved in allocentric representation. Thirty-one young men explored 35 virtual environments during high-resolution functional magnetic resonance imaging (fMRI) of the medial temporal lobe (MTL) and were subsequently tested on recall of the allocentric pattern of the objects in each environment-in other words, the positions of the objects relative to each other and to the outer perimeter. We find increasingly unique brain activation patterns associated with increasing allocentric accuracy in distinct neural populations in the perirhinal cortex, parahippocampal cortex, fusiform cortex, amygdala, hippocampus, and entorhinal cortex. In contrast to the traditional view of a hierarchical MTL network with the hippocampus at the top, we demonstrate, using recently developed graph analyses, a hierarchical allocentric MTL network without a main connector hub.
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Affiliation(s)
- Hallvard Røe Evensmoen
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), 7489 Trondheim, Norway; Department of Medical Imaging, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway.
| | - Lars M Rimol
- Department of Psychology, NTNU, 7489 Trondheim, Norway
| | - Anderson M Winkler
- National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA
| | - Richard Betzel
- Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, USA
| | - Tor Ivar Hansen
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), 7489 Trondheim, Norway
| | - Hamed Nili
- Department of Experimental Psychology, University of Oxford, South Parks Road, OX1 3UD Oxford, UK
| | - Asta Håberg
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), 7489 Trondheim, Norway; Department of Medical Imaging, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway; Department of Circulation and Medical Imaging, NTNU, Trondheim, Norway
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12
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保 学, 董 浩, 刘 迢, 郑 旭. [Connectivity pattern of action potentials causal network in prefrontal cortex during anxiety]. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 2020; 37:389-398. [PMID: 32597079 PMCID: PMC10319569 DOI: 10.7507/1001-5515.201907011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Indexed: 11/03/2022]
Abstract
Anxiety disorder is a common emotional handicap, which seriously affects the normal life of patients and endangers their physical and mental health. The prefrontal cortex is a key brain region which is responsible for anxiety. Action potential and behavioral data of rats in the elevated plus maze (EPM) during anxiety (an innate anxiety paradigm) can be obtained simultaneously by using the in vivo and in conscious animal multi-channel microelectrode array recording technique. Based on maximum likelihood estimation (MLE), the action potential causal network was established, network connectivity strength and global efficiency were calculated, and action potential causal network connectivity pattern of the medial prefrontal cortex was quantitatively characterized. We found that the entries (44.13±6.99) and residence period (439.76±50.43) s of rats in the closed arm of the elevated plus maze were obviously higher than those in the open arm [16.50±3.25, P<0.001; (160.23±48.22) s, P<0.001], respectively. The action potential causal network connectivity strength (0.017 3±0.003 6) and the global efficiency (0.044 2±0.012 8) in the closed arm were both higher than those in the open arm (0.010 4±0.003 2, P<0.01; 0.034 8±0.011 4, P<0.001), respectively. The results suggest that the changes of action potential causal network in the medial prefrontal cortex are related to anxiety state. These data could provide support for the study of the brain network mechanism in prefrontal cortex during anxiety.
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Affiliation(s)
- 学辉 保
- 天津医科大学 生物医学工程与技术学院(天津 300070)School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, P.R.China
| | - 浩然 董
- 天津医科大学 生物医学工程与技术学院(天津 300070)School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, P.R.China
| | - 迢迢 刘
- 天津医科大学 生物医学工程与技术学院(天津 300070)School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, P.R.China
| | - 旭媛 郑
- 天津医科大学 生物医学工程与技术学院(天津 300070)School of Biomedical Engineering and Technology, Tianjin Medical University, Tianjin 300070, P.R.China
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13
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Gopalsamy V, Rajasekaran K, Kamaraj L, Sivasaravanan S, Kok M. Influence of Dimensionless Parameter on De-Ionized Water-alumina Nanofluid Based Parabolic Trough Solar Collector. Recent Pat Nanotechnol 2019; 13:206-221. [PMID: 30968780 DOI: 10.2174/1872210513666190410123503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 12/18/2018] [Accepted: 03/18/2019] [Indexed: 06/09/2023]
Abstract
BACKGROUND Aqueous-alumina nanofluid was prepared using magnetic stirrer and ultrasonication process. Then, the prepared nanofluid was subjected to flow through the unshielded receiver of the parabolic trough solar collector to investigate the performance of the nanofluid and the effects of the dimensionless parameter were determined. METHODS The experimental work has been divided into two sections. First, the nanofluid was prepared and tested for its morphology, dimensions, and sedimentation using X-Ray Diffraction and Raman shift method. Then, the nanofluids of various concentrations from 0 to 4.0% are used as heat transfer fluid in unshielded type collector. Finally, the effect of the dimensionless parameter on the performance was determined. RESULTS For the whole test period, depending upon the bulk mean temperature, the dimensionless parameters such as Re and Nu varied from 1098 to 4552 & 19.30 to 46.40 for air and 2150 to 7551 & 11.11 to 48.54 for nanofluid. The enhancement of thermal efficiency found for 0% and 4.0% nanoparticle concentrations was 32.84% for the mass flow rate of 0.02 kg/s and 13.26% for the mass flow rate of 0.06 kg/s. CONCLUSION Re and Nu of air depend on air velocity and ambient temperature. Re increased with the mass flow rate and decreased with concentration. Heat loss occurred by convection mode of heat transfer. Heat transfer coefficient and global efficiency increased with increased mass flow rate and volume fraction. The thermal efficiency of both 0% and 4.0% concentrations became equal for increased mass flow rate. It has been proven that at high mass flow rates, the time available to absorb the heat energy from the receiver is insufficient.
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Affiliation(s)
- Vijayan Gopalsamy
- Department of Mechanical Engineering, Anna University-Chennai, Tamilnadu, India
| | - Karunakaran Rajasekaran
- Department of Mechanical Engineering, University College of Engineering, Anna University-Kanchipuram, Tamilnadu, India
| | - Logesh Kamaraj
- Department of Mechanical Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600062, India
| | - Siva Sivasaravanan
- Department of Mechanical Engineering, Sathyabama Institute of Science and Technology, Chennai 600119, India
| | - Metin Kok
- Department of Machinery and Metal Technologies, Kahramanmaras Sutcu Imam Universitesi, Kahramanmaras, Turkey
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14
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Abstract
Alzheimer's disease is a primary age-related neurodegenerative disorder that can result in impaired cognitive and memory functions. Although connections between changes in brain networks of Alzheimer's disease patients have been established, the mechanisms that drive these alterations remain incompletely understood. This study, which was conducted in 2018 at Northeastern University in China, included data from 97 participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset covering genetics, imaging, and clinical data. All participants were divided into two groups: normal control (n = 52; 20 males and 32 females; mean age 73.90 ± 4.72 years) and Alzheimer's disease (n = 45, 23 males and 22 females; mean age 74.85 ± 5.66). To uncover the wiring mechanisms that shaped changes in the topology of human brain networks of Alzheimer's disease patients, we proposed a local naïve Bayes brain network model based on graph theory. Our results showed that the proposed model provided an excellent fit to observe networks in all properties examined, including clustering coefficient, modularity, characteristic path length, network efficiency, betweenness, and degree distribution compared with empirical methods. This proposed model simulated the wiring changes in human brain networks between controls and Alzheimer's disease patients. Our results demonstrate its utility in understanding relationships between brain tissue structure and cognitive or behavioral functions. The ADNI was performed in accordance with the Good Clinical Practice guidelines, US 21CFR Part 50-Protection of Human Subjects, and Part 56-Institutional Review Boards (IRBs)/Research Good Clinical Practice guidelines Institutional Review Boards (IRBs)/Research Ethics Boards (REBs).
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Affiliation(s)
- Shuai-Zong Si
- School of Computer Science and Engineering, Northeastern University, Shenyang, China
| | - Xiao Liu
- School of Computer Science and Engineering, Northeastern University, Shenyang, China
| | - Jin-Fa Wang
- School of Computer Science and Engineering, Northeastern University, Shenyang, China
| | - Bin Wang
- School of Computer Science and Engineering, Northeastern University, Shenyang, China
| | - Hai Zhao
- School of Computer Science and Engineering, Northeastern University, Shenyang, China
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15
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Akın A. Partial correlation-based functional connectivity analysis for functional near-infrared spectroscopy signals. J Biomed Opt 2017; 22:1-10. [PMID: 29243416 DOI: 10.1117/1.jbo.22.12.126003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Accepted: 11/20/2017] [Indexed: 05/20/2023]
Abstract
A theoretical framework, a partial correlation-based functional connectivity (PC-FC) analysis to functional near-infrared spectroscopy (fNIRS) data, is proposed. This is based on generating a common background signal from a high passed version of fNIRS data averaged over all channels as the regressor in computing the PC between pairs of channels. This approach has been employed to real data collected during a Stroop task. The results show a strong significance in the global efficiency (GE) metric computed by the PC-FC analysis for neutral, congruent, and incongruent stimuli (NS, CS, IcS; GEN=0.10±0.009, GEC=0.11±0.01, GEIC=0.13±0.015, p=0.0073). A positive correlation (r=0.729 and p=0.0259) is observed between the interference of reaction times (incongruent-neutral) and interference of GE values (GEIC-GEN) computed from [HbO] signals.
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Affiliation(s)
- Ata Akın
- Acibadem University, Department of Medical Engineering, Atasehir, Istanbul, Turkey
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16
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Einalou Z, Maghooli K, Setarehdan SK, Akin A. Graph theoretical approach to functional connectivity in prefrontal cortex via fNIRS. Neurophotonics 2017; 4:041407. [PMID: 28840159 PMCID: PMC5565675 DOI: 10.1117/1.nph.4.4.041407] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Accepted: 07/19/2017] [Indexed: 05/20/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) has been proposed as an affordable, fast, and robust alternative to many neuroimaging modalities yet it still has long way to go to be adapted in the clinic. One request from the clinicians has been the delivery of a simple and straightforward metric (a so-called biomarker) from the vast amount of data a multichannel fNIRS system provides. We propose a simple-straightforward signal processing algorithm derived from [Formula: see text] data collected during a modified version of the color-word matching Stroop task that consists of three different conditions. The algorithm starts with a wavelet-transform-based preprocessing, then uses partial correlation analysis to compute the functional connectivity matrices at each condition and then computes the global efficiency values. To this end, a continuous wave 16 channels fNIRS device (ARGES Cerebro, Hemosoft Inc., Turkey) was used to measure the changes in [Formula: see text] concentrations from 12 healthy volunteers. We have considered 10% of strongest connections in each network. A strong Stroop interference effect was found between the incongruent against neutral condition ([Formula: see text]) while a similar significance was observed for the global efficiency values decreased from neutral to congruent to incongruent conditions [[Formula: see text], [Formula: see text]]. The findings bring us closer to delivering a biomarker derived from fNIRS data that can be reliably and easily adopted by the clinicians.
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Affiliation(s)
- Zahra Einalou
- Department of Biomedical Engineering, North Tehran Branch, Islamic Azad University, Tehran, Iran
| | - Keivan Maghooli
- Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
- Address all correspondence to: Keivan Maghooli, E-mail:
| | - Seyaed Kamaledin Setarehdan
- University of Tehran, Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, Tehran, Iran
| | - Ata Akin
- Acibadem University, Department of Medical Engineering, Istanbul, Turkey
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17
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Cocchi L, Yang Z, Zalesky A, Stelzer J, Hearne LJ, Gollo LL, Mattingley JB. Neural decoding of visual stimuli varies with fluctuations in global network efficiency. Hum Brain Mapp 2017; 38:3069-3080. [PMID: 28342260 DOI: 10.1002/hbm.23574] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2017] [Revised: 02/25/2017] [Accepted: 03/07/2017] [Indexed: 12/14/2022] Open
Abstract
Functional magnetic resonance imaging (fMRI) studies have shown that neural activity fluctuates spontaneously between different states of global synchronization over a timescale of several seconds. Such fluctuations generate transient states of high and low correlation across distributed cortical areas. It has been hypothesized that such fluctuations in global efficiency might alter patterns of activity in local neuronal populations elicited by changes in incoming sensory stimuli. To test this prediction, we used a linear decoder to discriminate patterns of neural activity elicited by face and motion stimuli presented periodically while participants underwent time-resolved fMRI. As predicted, decoding was reliably higher during states of high global efficiency than during states of low efficiency, and this difference was evident across both visual and nonvisual cortical regions. The results indicate that slow fluctuations in global network efficiency are associated with variations in the pattern of activity across widespread cortical regions responsible for representing distinct categories of visual stimulus. More broadly, the findings highlight the importance of understanding the impact of global fluctuations in functional connectivity on specialized, stimulus driven neural processes. Hum Brain Mapp 38:3069-3080, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Luca Cocchi
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia.,QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Zhengyi Yang
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Australia
| | - Johannes Stelzer
- Department of Biomedical Magnetic Resonance Imaging, University Hospital Tuebingen, Germany.,Magnetic Resonance Centre, Max-Planck-Institute for Biological Cybernetics, Tuebingen, Germany
| | - Luke J Hearne
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | | | - Jason B Mattingley
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia.,School of Psychology, The University of Queensland, Brisbane, Australia
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18
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Paolini BM, Laurienti PJ, Simpson SL, Burdette JH, Lyday RG, Rejeski WJ. Global integration of the hot-state brain network of appetite predicts short term weight loss in older adult. Front Aging Neurosci 2015; 7:70. [PMID: 25999855 PMCID: PMC4423432 DOI: 10.3389/fnagi.2015.00070] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Accepted: 04/20/2015] [Indexed: 12/30/2022] Open
Abstract
Obesity is a public health crisis in North America. While lifestyle interventions for weight loss (WL) remain popular, the rate of success is highly variable. Clearly, self-regulation of eating behavior is a challenge and patterns of activity across the brain may be an important determinant of success. The current study prospectively examined whether integration across the Hot-State Brain Network of Appetite (HBN-A) predicts WL after 6-months of treatment in older adults. Our metric for network integration was global efficiency (GE). The present work is a sub-study (n = 56) of an ongoing randomized clinical trial involving WL. Imaging involved a baseline food-cue visualization functional MRI (fMRI) scan following an overnight fast. Using graph theory to build functional brain networks, we demonstrated that regions of the HBN-A (insula, anterior cingulate cortex (ACC), superior temporal pole (STP), amygdala and the parahippocampal gyrus) were highly integrated as evidenced by the results of a principal component analysis (PCA). After accounting for known correlates of WL (baseline weight, age, sex, and self-regulatory efficacy) and treatment condition, which together contributed 36.9% of the variance in WL, greater GE in the HBN-A was associated with an additional 19% of the variance. The ACC of the HBN-A was the primary driver of this effect, accounting for 14.5% of the variance in WL when entered in a stepwise regression following the covariates, p = 0.0001. The HBN-A is comprised of limbic regions important in the processing of emotions and visceral sensations and the ACC is key for translating such processing into behavioral consequences. The improved integration of these regions may enhance awareness of body and emotional states leading to more successful self-regulation and to greater WL. This is the first study among older adults to prospectively demonstrate that, following an overnight fast, GE of the HBN-A during a food visualization task is predictive of WL.
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Affiliation(s)
- Brielle M Paolini
- Department of Radiology, Wake Forest University School of Medicine Winston-Salem, NC, USA
| | - Paul J Laurienti
- Department of Radiology, Wake Forest University School of Medicine Winston-Salem, NC, USA ; Translational Science Center, Wake Forest University Winston-Salem, NC, USA
| | - Sean L Simpson
- Department of Biostatistical Sciences, Wake Forest University Winston-Salem, NC, USA
| | - Jonathan H Burdette
- Department of Radiology, Wake Forest University School of Medicine Winston-Salem, NC, USA
| | - Robert G Lyday
- Department of Radiology, Wake Forest University School of Medicine Winston-Salem, NC, USA
| | - W Jack Rejeski
- Translational Science Center, Wake Forest University Winston-Salem, NC, USA ; Department of Health and Exercise Science, Wake Forest University Winston-Salem, NC, USA ; Department of Geriatric Medicine, Wake Forest University Winston-Salem, NC, USA
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19
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Pereira JB, Aarsland D, Ginestet CE, Lebedev AV, Wahlund LO, Simmons A, Volpe G, Westman E. Aberrant cerebral network topology and mild cognitive impairment in early Parkinson's disease. Hum Brain Mapp 2015; 36:2980-95. [PMID: 25950288 DOI: 10.1002/hbm.22822] [Citation(s) in RCA: 75] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2014] [Revised: 03/18/2015] [Accepted: 04/15/2015] [Indexed: 12/13/2022] Open
Abstract
The aim of this study was to assess whether mild cognitive impairment (MCI) is associated with disruption in large-scale structural networks in newly diagnosed, drug-naïve patients with Parkinson's disease (PD). Graph theoretical analyses were applied to 3T MRI data from 123 PD patients and 56 controls from the Parkinson's progression markers initiative (PPMI). Thirty-three patients were classified as having Parkinson's disease with mild cognitive impairment (PD-MCI) using the Movement Disorders Society Task Force criteria, while the remaining 90 PD patients were classified as cognitively normal (PD-CN). Global measures (clustering coefficient, characteristic path length, global efficiency, small-worldness) and regional measures (regional clustering coefficient, regional efficiency, hubs) were assessed in the structural networks that were constructed based on cortical thickness and subcortical volume data. PD-MCI patients showed a marked reduction in the average correlation strength between cortical and subcortical regions compared with controls. These patients had a larger characteristic path length and reduced global efficiency in addition to a lower regional efficiency in frontal and parietal regions compared with PD-CN patients and controls. A reorganization of the highly connected regions in the network was observed in both groups of patients. This study shows that the earliest stages of cognitive decline in PD are associated with a disruption in the large-scale coordination of the brain network and with a decrease of the efficiency of parallel information processing. These changes are likely to signal further cognitive decline and provide support to the role of aberrant network topology in cognitive impairment in patients with early PD.
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Affiliation(s)
- Joana B Pereira
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Dag Aarsland
- Department of Psychiatry, Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway.,Department of Neurobiology, Care Sciences and Society, Centre for Alzheimer's Disease Research, Karolinska Institute, Stockholm, Sweden
| | - Cedric E Ginestet
- Department of Biostatistics, King's College London, London, United Kingdom
| | - Alexander V Lebedev
- Department of Psychiatry, Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Lars-Olof Wahlund
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Andrew Simmons
- Institute of Psychiatry, King's College London, London, United Kingdom.,NIHR Biomedical Research Centre for Mental Health, London, United Kingdom.,NIHR Biomedical Research Unit for Dementia, London, United Kingdom
| | - Giovanni Volpe
- Department of Physics, Soft Matter Lab, Bilkent University, Ankara, Turkey.,UNAM - National Nanotechnology Research Center, Bilkent University, Ankara, Turkey
| | - Eric Westman
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Karolinska Institutet, Stockholm, Sweden
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20
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Abstract
Neuroimaging studies of functional connectivity using graph theory have furthered our understanding of the network structure in temporal lobe epilepsy (TLE). Brain network effects of anti-epileptic drugs could influence such studies, but have not been systematically studied. Resting-state functional MRI was analyzed in 25 patients with TLE using graph theory analysis. Patients were divided into two groups based on anti-epileptic medication use: those taking carbamazepine/oxcarbazepine (CBZ/OXC) (n=9) and those not taking CBZ/OXC (n=16) as a part of their medication regimen. The following graph topology metrics were analyzed: global efficiency, betweenness centrality (BC), clustering coefficient, and small-world index. Multiple linear regression was used to examine the association of CBZ/OXC with graph topology. The two groups did not differ from each other based on epilepsy characteristics. Use of CBZ/OXC was associated with a lower BC. Longer epilepsy duration was also associated with a lower BC. These findings can inform graph theory-based studies in patients with TLE. The changes observed are discussed in relation to the anti-epileptic mechanism of action and adverse effects of CBZ/OXC.
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Affiliation(s)
- Zulfi Haneef
- 1 Department of Neurology, Baylor College of Medicine , Houston, Texas.,2 Neurology Care Line, VA Medical Center , Houston, Texas
| | - Harvey S Levin
- 3 Department of Physical Medicine, Baylor College of Medicine , Houston, Texas
| | - Sharon Chiang
- 4 Department of Statistics, Rice University , Houston, Texas
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21
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Xue Q, Wang ZY, Xiong XC, Tian CY, Wang YP, Xu P. Altered brain connectivity in patients with psychogenic non-epileptic seizures: a scalp electroencephalography study. J Int Med Res 2013; 41:1682-90. [PMID: 24026773 DOI: 10.1177/0300060513496170] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
OBJECTIVE To determine the role of altered brain connectivity in patients with psychogenic non-epileptic seizures (PNES). METHODS Patients with PNES and age- and sex-matched healthy control subjects were enrolled. Participants underwent neuropsychological evaluation (anxiety, depression and dissociation) and interictal scalp electroencephalography (EEG). A brain network was constructed. Between-group differences in clustering coefficient and global efficiency were analysed. RESULTS Patients with PNES (n = 15) had significantly decreased clustering coefficients in the gamma band compared with controls (n = 15). Difference topology revealed that patients with PNES had decreased long linkage between the frontal region and other regions compared with controls. There were no significant between-group differences in global efficiency. Neuropsychological scores were significantly higher in patients than controls, but there were no correlations with network properties. CONCLUSION Altered brain connectivity in patients with PNES suggests an underlying pathophysiological mechanism. EEG and network analysis allow noninvasive exploration of the neurological processes of this disease.
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Affiliation(s)
- Qing Xue
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
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22
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Clemens B, Puskás S, Besenyei M, Spisák T, Opposits G, Hollódy K, Fogarasi A, Fekete I, Emri M. Neurophysiology of juvenile myoclonic epilepsy: EEG-based network and graph analysis of the interictal and immediate preictal states. Epilepsy Res 2013; 106:357-69. [PMID: 23886656 DOI: 10.1016/j.eplepsyres.2013.06.017] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2013] [Revised: 05/10/2013] [Accepted: 06/28/2013] [Indexed: 11/26/2022]
Abstract
INTRODUCTION The neuronal mechanisms of enduring seizure propensity and seizure precipitation in juvenile myoclonic epilepsy (JME) are not known. We investigated these issues, within the framework of the "network concept" of epilepsy. METHODS Design1: 19, unmedicated JME patients were compared with nineteen, age-, and sex-matched normal control persons (NC). A total of 120s, artifact-free, paroxysm-free, eyes-closed, resting state EEG background activity was analyzed for each person. Design2: interictal and immediate preictal periods of the JME patients were compared in order to explore interictal-preictal network differences. For both comparison designs, statistically significant differences of EEG functional connectivity (EEGfC), nodal and global graph parameters were evaluated. MAIN RESULTS Design1: maximum abnormalities were: increased delta, theta, alpha1 EEGfC and decreased alpha2 and beta EEGfC in the JME group as compared to the NC group, mainly among cortical areas that are involved in sensory-motor integration. Nodal degree and efficiency of three, medial, basal frontal nodes were greater in JME than in NC, in the alpha1 band. Design2: preictal delta EEGfC showed further increase in the above-mentioned areas, as compared to the interictal state. DISCUSSION Increased EEGfC indicates a hypercoupled state among the specified cortical areas. This interictal abnormality further increases in the preictal state. Nodal graph statistics indicates abnormal neuronal dynamics in the cortical area that is the ictal onset zone in JME. SIGNIFICANCE Interictal and preictal neuronal dysfunction has been described in terms of network dynamics and topography in JME patients. Forthcoming investigations of seizure precipitation and therapeutic drug effects are encouraged on this basis.
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Affiliation(s)
- B Clemens
- Kenézy Hospital Ltd., Department of Neurology, Debrecen, Hungary
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Arienzo D, Leow A, Brown JA, Zhan L, Gadelkarim J, Hovav S, Feusner JD. Abnormal brain network organization in body dysmorphic disorder. Neuropsychopharmacology 2013; 38:1130-9. [PMID: 23322186 DOI: 10.1038/npp.2013.18] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Body dysmorphic disorder (BDD) is characterized by preoccupation with misperceived defects of appearance, causing significant distress and disability. Previous studies suggest abnormalities in information processing characterized by greater local relative to global processing. The purpose of this study was to probe whole-brain and regional white matter network organization in BDD, and to relate this to specific metrics of symptomatology. We acquired diffusion-weighted 34-direction MR images from 14 unmedicated participants with DSM-IV BDD and 16 healthy controls, from which we conducted whole-brain deterministic diffusion tensor imaging tractography. We then constructed white matter structural connectivity matrices to derive whole-brain and regional graph theory metrics, which we compared between groups. Within the BDD group, we additionally correlated these metrics with scores on psychometric measures of BDD symptom severity as well as poor insight/delusionality. The BDD group showed higher whole-brain mean clustering coefficient than controls. Global efficiency negatively correlated with BDD symptom severity. The BDD group demonstrated greater edge betweenness centrality for connections between the anterior temporal lobe and the occipital cortex, and between bilateral occipital poles. This represents the first brain network analysis in BDD. Results suggest disturbances in whole brain structural topological organization in BDD, in addition to correlations between clinical symptoms and network organization. There is also evidence of abnormal connectivity between regions involved in lower-order visual processing and higher-order visual and emotional processing, as well as interhemispheric visual information transfer. These findings may relate to disturbances in information processing found in previous studies.
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