1
|
Ma H, Zhu Y, Liang X, Wu L, Wang Y, Li X, Qian L, Cheung GL, Zhou F. In patients with mild disability NMOSD: is the alteration in the cortical morphological or functional network topological properties more significant. Front Immunol 2024; 15:1345843. [PMID: 38375481 PMCID: PMC10875087 DOI: 10.3389/fimmu.2024.1345843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 01/15/2024] [Indexed: 02/21/2024] Open
Abstract
Objective To assess the alteration of individual brain morphological and functional network topological properties and their clinical significance in patients with neuromyelitis optica spectrum disorder (NMOSD). Materials and methods Eighteen patients with NMOSD and twenty-two healthy controls (HCs) were included. The clinical assessment of NMOSD patients involved evaluations of disability status, cognitive function, and fatigue impact. For each participant, brain images, including high-resolution T1-weighted images for individual morphological brain networks (MBNs) and resting-state functional MR images for functional brain networks (FBNs) were obtained. Topological properties were calculated and compared for both MBNs and FBNs. Then, partial correlation analysis was performed to investigate the relationships between the altered network properties and clinical variables. Finally, the altered network topological properties were used to classify NMOSD patients from HCs and to analyses time- to-progression of the patients. Results The average Expanded Disability Status Scale score of NMOSD patients was 1.05 (range from 0 to 2), indicating mild disability. Compared to HCs, NMOSD patients exhibited a higher normalized characteristic path length (λ) in their MBNs (P = 0.0118, FDR corrected) but showed no significant differences in the global properties of FBNs (p: 0.405-0.488). Network-based statistical analysis revealed that MBNs had more significantly altered connections (P< 0.01, NBS corrected) than FBNs. Altered nodal properties of MBNs were correlated with disease duration or fatigue scores (P< 0.05/6 with Bonferroni correction). Using the altered nodal properties of MBNs, the accuracy of classification of NMOSD patients versus HCs was 96.4%, with a sensitivity of 93.3% and a specificity of 100%. This accuracy was better than that achieved using the altered nodal properties of FBNs. Nodal properties of MBN significantly predicted Expanded Disability Status Scale worsening in patients with NMOSD. Conclusion The results indicated that patients with mild disability NMOSD exhibited compensatory increases in local network properties to maintain overall stability. Furthermore, the alterations in the morphological network nodal properties of NMOSD patients not only had better relevance for clinical assessments compared with functional network nodal properties, but also exhibited predictive values of EDSS worsening.
Collapse
Affiliation(s)
- Haotian Ma
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
- Queen Mary College, Nanchang University, Nanchang, China
| | - Yanyan Zhu
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Xiao Liang
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Lin Wu
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Yao Wang
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Xiaoxing Li
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
| | - Long Qian
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing, China
| | | | - Fuqing Zhou
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China
- Neuroimaging Laboratory, Jiangxi Medical Imaging Research Institute, Nanchang, China
| |
Collapse
|
2
|
Iandolo R, Avci E, Bommarito G, Sandvig I, Rohweder G, Sandvig A. Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults. Neuroimage Clin 2024; 41:103569. [PMID: 38281363 PMCID: PMC10839532 DOI: 10.1016/j.nicl.2024.103569] [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: 07/10/2023] [Revised: 01/19/2024] [Accepted: 01/21/2024] [Indexed: 01/30/2024]
Abstract
BACKGROUND White matter hyperintensities (WMH) are a prevalent radiographic finding in the aging brain studies. Research on WMH association with motor impairment is mostly focused on the lower-extremity function and further investigation on the upper-extremity is needed. How different degrees of WMH burden impact the network of activation recruited during upper limb motor performance could provide further insight on the complex mechanisms of WMH pathophysiology and its interaction with aging and neurological disease processes. METHODS 40 healthy elderly subjects without a neurological/psychiatric diagnosis were included in the study (16F, mean age 69.3 years). All subjects underwent ultra-high field 7 T MRI including structural and finger tapping task-fMRI. First, we quantified the WMH lesion load and its spatial distribution. Secondly, we performed a data-driven stratification of the subjects according to their periventricular and deep WMH burdens. Thirdly, we investigated the distribution of neural recruitment and the corresponding activity assessed through BOLD signal changes among different brain regions for groups of subjects. We clustered the degree of WMH based on location, numbers, and volume into three categories; ranging from mild, moderate, and severe. Finally, we explored how the spatial distribution of WMH, and activity elicited during task-fMRI relate to motor function, measured with the 9-Hole Peg Test. RESULTS Within our population, we found three subgroups of subjects, partitioned according to their periventricular and deep WMH lesion load. We found decreased activity in several frontal and cingulate cortex areas in subjects with a severe WMH burden. No statistically significant associations were found when performing the brain-behavior statistical analysis for structural or functional data. CONCLUSION WMH burden has an effect on brain activity during fine motor control and the activity changes are associated with varying degrees of the total burden and distributions of WMH lesions. Collectively, our results shed new light on the potential impact of WMH on motor function in the context of aging and neurodegeneration.
Collapse
Affiliation(s)
- Riccardo Iandolo
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Esin Avci
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Giulia Bommarito
- Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ioanna Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Gitta Rohweder
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Stroke Unit, Department of Medicine, St Olav's University Hospital, Trondheim, Norway
| | - Axel Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, St. Olav's University Hospital, Trondheim, Norway; Department of Clinical Neurosciences, Division of Neuro, Head and Neck, Umeå University Hospital, Umeå, Sweden; Department of Community Medicine and Rehabilitation, Umeå University Hospital, Umeå, Sweden.
| |
Collapse
|
3
|
Belge JB, Mulders P, Van Diermen L, Sienaert P, Sabbe B, Abbott CC, Tendolkar I, Schrijvers D, van Eijndhoven P. Reviewing the neurobiology of electroconvulsive therapy on a micro- meso- and macro-level. Prog Neuropsychopharmacol Biol Psychiatry 2023; 127:110809. [PMID: 37331685 DOI: 10.1016/j.pnpbp.2023.110809] [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: 01/22/2023] [Revised: 05/27/2023] [Accepted: 06/07/2023] [Indexed: 06/20/2023]
Abstract
BACKGROUND Electroconvulsive therapy (ECT) remains the one of the most effective of biological antidepressant interventions. However, the exact neurobiological mechanisms underlying the efficacy of ECT remain unclear. A gap in the literature is the lack of multimodal research that attempts to integrate findings at different biological levels of analysis METHODS: We searched the PubMed database for relevant studies. We review biological studies of ECT in depression on a micro- (molecular), meso- (structural) and macro- (network) level. RESULTS ECT impacts both peripheral and central inflammatory processes, triggers neuroplastic mechanisms and modulates large scale neural network connectivity. CONCLUSIONS Integrating this vast body of existing evidence, we are tempted to speculate that ECT may have neuroplastic effects resulting in the modulation of connectivity between and among specific large-scale networks that are altered in depression. These effects could be mediated by the immunomodulatory properties of the treatment. A better understanding of the complex interactions between the micro-, meso- and macro- level might further specify the mechanisms of action of ECT.
Collapse
Affiliation(s)
- Jean-Baptiste Belge
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Department of Psychiatry, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands.
| | - Peter Mulders
- Department of Psychiatry, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands; Donders Institute for Brain, Cognition and Behavior, Centre for Neuroscience, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands
| | - Linda Van Diermen
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Psychiatric Center Bethanië, Andreas Vesaliuslaan 39, Zoersel 2980, Belgium
| | - Pascal Sienaert
- KU Leuven - University of Leuven, University Psychiatric Center KU Leuven, Academic Center for ECT and Neuromodulation (AcCENT), Leuvensesteenweg 517, Kortenberg 3010, Belgium
| | - Bernard Sabbe
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | | | - Indira Tendolkar
- Department of Psychiatry, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands; Donders Institute for Brain, Cognition and Behavior, Centre for Neuroscience, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands
| | - Didier Schrijvers
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Department of Psychiatry, University Psychiatric Center Duffel, Stationstraat 22, Duffel 2570, Belgium
| | - Philip van Eijndhoven
- Department of Psychiatry, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands; Donders Institute for Brain, Cognition and Behavior, Centre for Neuroscience, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands
| |
Collapse
|
4
|
Kraft JN, Hausman HK, Hardcastle C, Albizu A, O'Shea A, Evangelista ND, Boutzoukas EM, Van Etten EJ, Bharadwaj PK, Song H, Smith SG, DeKosky S, Hishaw GA, Wu S, Marsiske M, Cohen R, Alexander GE, Porges E, Woods AJ. Task-based functional connectivity of the Useful Field of View (UFOV) fMRI task. GeroScience 2023; 45:293-309. [PMID: 35948860 PMCID: PMC9886714 DOI: 10.1007/s11357-022-00632-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 07/20/2022] [Indexed: 02/03/2023] Open
Abstract
Declines in processing speed performance occur in aging and are a critical marker of functional independence in older adults. Numerous studies suggest that Useful Field of View (UFOV) training may ameliorate cognitive decline in older adults. Despite its efficacy, little is known about the neural correlates of this task. The current study is the first to investigate the coherence of functional connectivity during UFOV task completion. A total of 336 participants completed the UFOV task while undergoing task-based functional magnetic resonance imaging (fMRI). Ten spherical regions of interest (ROIs), selected a priori, were created based on regions with the greatest peak BOLD activation patterns in the UFOV fMRI task and regions that have been shown to significantly relate to UFOV fMRI task performance. We used a weighted ROI-to-ROI connectivity analysis to model task-specific functional connectivity strength between these a priori selected ROIs. We found that our UFOV fMRI network was functionally connected during task performance and was significantly associated to UFOV fMRI task performance. Within-network connectivity of the UFOV fMRI network showed comparable or better predictive power in accounting for UFOV accuracy compared to 7 resting state networks, delineated by Yeo and colleagues. Finally, we demonstrate that the within-network connectivity of UFOV fMRI task accounted for scores on a measure of "near transfer", the Double Decision task, better than the aforementioned resting state networks. Our data elucidate functional connectivity patterns of the UFOV fMRI task. This may assist in future targeted interventions that aim to improve synchronicity within the UFOV fMRI network.
Collapse
Affiliation(s)
- Jessica N Kraft
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Hanna K Hausman
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Cheshire Hardcastle
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Alejandro Albizu
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Andrew O'Shea
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Nicole D Evangelista
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Emanuel M Boutzoukas
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Emily J Van Etten
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Gainesville, FL, USA
| | - Pradyumna K Bharadwaj
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Gainesville, FL, USA
| | - Hyun Song
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Gainesville, FL, USA
| | - Samantha G Smith
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Gainesville, FL, USA
| | - Steven DeKosky
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Neurology, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Georg A Hishaw
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Consortium, Tucson, AZ, USA
| | - Samuel Wu
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Michael Marsiske
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Ronald Cohen
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Gene E Alexander
- Department of Neurology, College of Medicine, University of Florida, Gainesville, FL, USA
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Consortium, Tucson, AZ, USA
| | - Eric Porges
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA.
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.
| |
Collapse
|
5
|
Cardona Jiménez J, de B. Pereira CA. Assessing dynamic effects on a Bayesian matrix-variate dynamic linear model: An application to task-based fMRI data analysis. Comput Stat Data Anal 2021. [DOI: 10.1016/j.csda.2021.107297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
|
6
|
Kraft JN, Albizu A, O'Shea A, Hausman HK, Evangelista ND, Boutzoukas E, Hardcastle C, Van Etten EJ, Bharadwaj PK, Song H, Smith SG, DeKosky S, Hishaw GA, Wu S, Marsiske M, Cohen R, Alexander GE, Porges E, Woods AJ. Functional Neural Correlates of a Useful Field of View (UFOV)-Based fMRI Task in Older Adults. Cereb Cortex 2021; 32:1993-2012. [PMID: 34541604 PMCID: PMC9070333 DOI: 10.1093/cercor/bhab332] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 08/10/2021] [Accepted: 08/11/2021] [Indexed: 11/13/2022] Open
Abstract
Declines in processing speed performance occur in aging and are a critical marker of functional independence in older adults. Studies suggest that Useful Field of View (UFOV) training may ameliorate cognitive decline. Despite its efficacy, little is known about the neural correlates of this task. Within the current study, 233 healthy older adults completed a UFOV-based task while undergoing functional magnetic resonance imaging (fMRI). During the "stimulus" portion of this task, participants must identify a target in the center of the screen and the location of a target in the periphery, among distractors. During the "probe" portion, participants must decide if the object in the center and the location of the target in the periphery were identical to the "stimulus" screen. Widespread bilateral whole-brain activation was observed when activation patterns of the "probe" contrast were subtracted from the "stimulus" contrast. Conversely, the subtraction of "stimulus" from "probe" was associated with discrete activation patterns consisting of 13 clusters. Additionally, when evaluating the variance associated with task accuracy, specific subregions were identified that may be critical for task performance. Our data elucidate the functional neural correlates of a UFOV-based task, a task used in both cognitive training paradigms and assessment of function.
Collapse
Affiliation(s)
- Jessica N Kraft
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Alejandro Albizu
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Andrew O'Shea
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA
| | - Hanna K Hausman
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA
| | - Nicole D Evangelista
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA
| | - Emanuel Boutzoukas
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA
| | - Cheshire Hardcastle
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA
| | - Emily J Van Etten
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ 85721, USA
| | - Pradyumna K Bharadwaj
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ 85721, USA
| | - Hyun Song
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ 85721, USA
| | - Samantha G Smith
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ 85721, USA
| | - Steven DeKosky
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Neurology, College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Georg A Hishaw
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Consortium, Phoenix, AZ 85014, USA
| | - Samuel Wu
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA
| | - Michael Marsiske
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA
| | - Ronald Cohen
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA
| | - Gene E Alexander
- Department of Neurology, College of Medicine, University of Florida, Gainesville, FL 32610, USA.,Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Consortium, Phoenix, AZ 85014, USA
| | - Eric Porges
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA.,Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL 32610, USA.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32610, USA
| |
Collapse
|
7
|
Belge JB, Mulders PCR, Oort JV, Diermen LV, Poljac E, Sabbe B, de Timary P, Constant E, Sienaert P, Schrijvers D, van Eijndhoven P. Movement, mood and cognition: Preliminary insights into the therapeutic effects of electroconvulsive therapy for depression through a resting-state connectivity analysis. J Affect Disord 2021; 290:117-127. [PMID: 33993078 DOI: 10.1016/j.jad.2021.04.069] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 03/10/2021] [Accepted: 04/23/2021] [Indexed: 01/22/2023]
Abstract
BACKGROUND Electroconvulsive therapy (ECT) is a highly effective treatment for depression but how it achieves its clinical effects remains unclear. METHODS We set out to study the brain's response to ECT from a large-scale brain-network perspective. Using a voxelwise analysis, we looked at resting-state functional connectivity before and after a course of ECT at the whole-brain and the between- and within-network levels in 17 patients with a depressive episode. Using a group-independent component analysis approach, we focused on four networks known to be affected in depression: the salience network (SN), the default mode network (DMN), the cognitive executive network (CEN), and a subcortical network (SCN). Our clinical measures included mood, cognition, and psychomotor symptoms. RESULTS We found ECT to have increased the connectivity of the left CEN with the left angular gyrus and left middle frontal gyrus as well as its within-network connectivity. Both the right CEN and the SCN showed increased connectivity with the precuneus and the anterior DMN with the left amygdala. Finally, improvement of psychomotor retardation was positively correlated with an increase of within-posterior DMN connectivity. LIMITATIONS The limitations of our study include its small sample size and the lack of a control dataset to confirm our findings. CONCLUSION Our voxelwise data demonstrate that ECT induces a significant increase of connectivity across the whole brain and at the within-network level. Furthermore, we provide the first evidence on the association between an increase of within-posterior DMN connectivity and an improvement of psychomotor retardation, a core symptom of depression.
Collapse
Affiliation(s)
- Jan-Baptist Belge
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, University Psychiatric Center Duffel, Stationstraat 22, Duffel 2570, Belgium; Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Adult Psychiatry Department and Institute of Neuroscience, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Woluwe-Saint-Lambert, Belgium.
| | - Peter C R Mulders
- Department of Psychiatry, Radboud University Medical Centre, Huispost 961, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behavior, Centre for Neuroscience, P.O. Box 9010, 6500 GL Nijmegen, the Netherlands
| | - Jasper Van Oort
- Department of Psychiatry, Radboud University Medical Centre, Huispost 961, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behavior, Centre for Neuroscience, P.O. Box 9010, 6500 GL Nijmegen, the Netherlands
| | - Linda Van Diermen
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, University Psychiatric Center Duffel, Stationstraat 22, Duffel 2570, Belgium; Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Psychiatric Center Bethanië, Andreas Vesaliuslaan 39, 2980 Zoersel, Belgium
| | - Ervin Poljac
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, University Psychiatric Center Duffel, Stationstraat 22, Duffel 2570, Belgium; Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Bernard Sabbe
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, University Psychiatric Center Duffel, Stationstraat 22, Duffel 2570, Belgium; Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Philippe de Timary
- Adult Psychiatry Department and Institute of Neuroscience, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Woluwe-Saint-Lambert, Belgium
| | - Eric Constant
- Adult Psychiatry Department and Institute of Neuroscience, Cliniques Universitaires Saint-Luc, Université Catholique de Louvain, Woluwe-Saint-Lambert, Belgium
| | - Pascal Sienaert
- KU Leuven - University of Leuven, University Psychiatric Center KU Leuven, Academic Center for ECT and Neuromodulation (AcCENT), Kortenberg, Belgium
| | - Didier Schrijvers
- Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, University Psychiatric Center Duffel, Stationstraat 22, Duffel 2570, Belgium; Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
| | - Philip van Eijndhoven
- Department of Psychiatry, Radboud University Medical Centre, Huispost 961, P.O. Box 9101, 6500 HB Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behavior, Centre for Neuroscience, P.O. Box 9010, 6500 GL Nijmegen, the Netherlands
| |
Collapse
|
8
|
Chen HJ, Zou ZY, Zhang XH, Shi JY, Huang NX, Lin YJ. Dynamic Changes in Functional Network Connectivity Involving Amyotrophic Lateral Sclerosis and Its Correlation With Disease Severity. J Magn Reson Imaging 2021; 54:239-248. [PMID: 33559360 DOI: 10.1002/jmri.27521] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 12/28/2020] [Accepted: 12/29/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Aberrant static functional connectivity (FC) has been well demonstrated in amyotrophic lateral sclerosis (ALS); however, ALS-related alterations in FC dynamic properties remain unclear, although dynamic FC analyses contribute to uncover mechanisms underlying neurodegenerative disorders. PURPOSE To explore dynamic functional network connectivity (dFNC) in ALS and its correlation with disease severity. STUDY TYPE Prospective. SUBJECTS Thirty-two ALS patients and 45 healthy controls. FIELD STRENGTH/SEQUENCE Multiband resting-state functional images using gradient echo echo-planar imaging and T1-weighted images were acquired at 3.0 T. ASSESSMENT Disease severity was evaluated with the revised ALS Functional Rating Scale (ALSFRS-R) and patients were stratified according to diagnostic category. Independent component analysis was conducted to identify the components of seven intrinsic brain networks (ie, visual/sensorimotor (SMN)/auditory/cognitive-control (CCN)/default-mode (DMN)/subcortical/cerebellar networks). A sliding-window correlation approach was used to compute dFNC. FNC states were determined by k-mean clustering, and state-specific FNC and dynamic indices (fraction time/mean dwell time/transition number) were calculated. STATISTICAL TESTS Two-sample t test used for comparisons on dynamic measures and Spearman's correlation analysis. RESULTS ALS patients showed increased FNC between DMN-SMN in state 1 and between CCN-SMN in state 4. Patients remained in state 2 (showing the weakest FNC) for a significantly longer time (mean dwell time: 49.8 ± 40.1 vs. 93.6 ± 126.3; P < 0.05) and remained in state 1 (showing a relatively strong FNC) for a shorter time (fraction time: 0.27 ± 0.25 vs. 0.13 ± 0.20; P < 0.05). ALS patients exhibited less temporal variability in their FNC (transition number: 10.2 ± 4.4 vs. 7.8 ± 3.8; P < 0.05). A significant correlation was observed between ALSFRS-R and mean dwell time in state 2 (r = -0.414, P < 0.05) and transition number (r = 0.452, P < 0.05). No significant between-subgroup difference in dFNC properties was found (all P > 0.05). DATA CONCLUSION Our findings suggest aberrant dFNC properties in ALS, which is associated with disease severity. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 3.
Collapse
Affiliation(s)
- Hua-Jun Chen
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Zhang-Yu Zou
- Department of Neurology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xiao-Hong Zhang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Jia-Yan Shi
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Nao-Xin Huang
- Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Yan-Juan Lin
- Department of Cardiovascular Surgery, Fujian Medical University Union Hospital, Fuzhou, China.,Department of Nursing, Fujian Medical University Union Hospital, Fuzhou, China
| |
Collapse
|
9
|
Tu W, Ma Z, Ma Y, Dopfel D, Zhang N. Suppressing Anterior Cingulate Cortex Modulates Default Mode Network and Behavior in Awake Rats. Cereb Cortex 2021; 31:312-323. [PMID: 32820327 PMCID: PMC7727348 DOI: 10.1093/cercor/bhaa227] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 06/30/2020] [Accepted: 07/26/2020] [Indexed: 12/28/2022] Open
Abstract
The default mode network (DMN) is a principal brain network in the mammalian brain. Although the DMN in humans has been extensively studied with respect to network structure, function, and clinical implications, our knowledge of DMN in animals remains limited. In particular, the functional role of DMN nodes, and how DMN organization relates to DMN-relevant behavior are still elusive. Here we investigated the causal relationship of inactivating a pivotal node of DMN (i.e., dorsal anterior cingulate cortex [dACC]) on DMN function, network organization, and behavior by combining chemogenetics, resting-state functional magnetic resonance imaging (rsfMRI) and behavioral tests in awake rodents. We found that suppressing dACC activity profoundly changed the activity and connectivity of DMN, and these changes were associated with altered DMN-related behavior in animals. The chemo-rsfMRI-behavior approach opens an avenue to mechanistically dissecting the relationships between a specific node, brain network function, and behavior. Our data suggest that, like in humans, DMN in rodents is a functional network with coordinated activity that mediates behavior.
Collapse
Affiliation(s)
- Wenyu Tu
- Neuroscience Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA
| | - Zilu Ma
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Yuncong Ma
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - David Dopfel
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Nanyin Zhang
- Neuroscience Program, The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA 16802, USA
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| |
Collapse
|
10
|
Kraft JN, O'Shea A, Albizu A, Evangelista ND, Hausman HK, Boutzoukas E, Nissim NR, Van Etten EJ, Bharadwaj PK, Song H, Smith SG, Porges E, DeKosky S, Hishaw GA, Wu S, Marsiske M, Cohen R, Alexander GE, Woods AJ. Structural Neural Correlates of Double Decision Performance in Older Adults. Front Aging Neurosci 2020; 12:278. [PMID: 33117145 PMCID: PMC7493680 DOI: 10.3389/fnagi.2020.00278] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 08/11/2020] [Indexed: 11/13/2022] Open
Abstract
Speed of processing is a cognitive domain that encompasses the speed at which an individual can perceive a given stimulus, interpret the information, and produce a correct response. Speed of processing has been shown to decline more rapidly than other cognitive domains in an aging population, suggesting that this domain is particularly vulnerable to cognitive aging (Chee et al., 2009). However, given the heterogeneity of neuropsychological measures used to assess the domains underpinning speed of processing, a diffuse pattern of brain regions has been implicated. The current study aims to investigate the structural neural correlates of speed of processing by assessing cortical volume and speed of processing scores on the POSIT Double Decision task within a healthy older adult population (N = 186; mean age = 71.70 ± 5.32 years). T1-weighted structural images were collected via a 3T Siemens scanner. The current study shows that less cortical thickness in right temporal, posterior frontal, parietal and occipital lobe structures were significantly associated with poorer Double Decision scores. Notably, these include the lateral orbitofrontal gyrus, precentral gyrus, superior, transverse, and inferior temporal gyrus, temporal pole, insula, parahippocampal gyrus, fusiform gyrus, lingual gyrus, superior and inferior parietal gyrus and lateral occipital gyrus. Such findings suggest that speed of processing performance is associated with a wide array of cortical regions that provide unique contributions to performance on the Double Decision task.
Collapse
Affiliation(s)
- Jessica N Kraft
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Andrew O'Shea
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Alejandro Albizu
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Nicole D Evangelista
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Hanna K Hausman
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Emanuel Boutzoukas
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States
| | - Nicole R Nissim
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Emily J Van Etten
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
| | - Pradyumna K Bharadwaj
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
| | - Hyun Song
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
| | - Samantha G Smith
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States
| | - Eric Porges
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Steven DeKosky
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Neurology, College of Medicine, University of Florida, Gainesville, FL, United States
| | - Georg A Hishaw
- Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Consortium, Tucson, AZ, United States
| | - Samuel Wu
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Michael Marsiske
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Ronald Cohen
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| | - Gene E Alexander
- Brain Imaging, Behavior and Aging Laboratory, Department of Psychology and Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, United States.,Department of Psychiatry, Neuroscience and Physiological Sciences Graduate Interdisciplinary Programs, and BIO5 Institute, University of Arizona and Arizona Alzheimer's Consortium, Tucson, AZ, United States
| | - Adam J Woods
- Center for Cognitive Aging and Memory Clinical Translational Research, McKnight Brain Institute, University of Florida, Gainesville, FL, United States.,Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, United States.,Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, United States
| |
Collapse
|
11
|
O’Neill A, Carey E, Dooley N, Healy C, Coughlan H, Kelly C, Frodl T, O’Hanlon E, Cannon M. Multiple Network Dysconnectivity in Adolescents with Psychotic Experiences: A Longitudinal Population-Based Study. Schizophr Bull 2020; 46:1608-1618. [PMID: 32614036 PMCID: PMC7846103 DOI: 10.1093/schbul/sbaa056] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Abnormal functional connectivity (FC, the temporal synchronization of activation across distinct brain regions) of the default mode (DMN), salience (SN), central executive (CEN), and motor (MN) networks is well established in psychosis. However, little is known about FC in individuals, particularly adolescents, reporting subthreshold psychotic experiences (PE) and their trajectory over time. Thus, the aim of this study was to investigate the FC of these networks in adolescents with PE. In this population-based case-control study, 24 adolescents (mean age = 13.58) meeting the criteria for PE were drawn from a sample of 211 young people recruited and scanned for a neuroimaging study, with a follow-up scan 2 years later (n = 18, mean age = 15.78) and compared to matched controls drawn from the same sample. We compared FC of DMN, SN, CEN, and MN regions between PE and controls using whole-brain FC analyses. At both timepoints, the PE group displayed significant hypoconnectivity compared to controls. At baseline, FC in the PE group was decreased between MN and DMN regions. At follow-up, dysconnectivity in the PE group was more widespread. Over time, controls displayed greater FC changes than the PE group, with FC generally increasing between MN, DMN, and SN regions. Adolescents with PE exhibit hypoconnectivity across several functional networks also found to be hypoconnected in established psychosis. Our findings highlight the potential for studies of adolescents reporting PE to reveal early neural correlates of psychosis and support further investigation of the role of the MN in PE and psychotic disorders.
Collapse
Affiliation(s)
- Aisling O’Neill
- Department of Psychiatry, Smurfit Building, Royal College of Surgeons Ireland at Beaumont Hospital, Dublin, Ireland,Trinity College Institute of Neuroscience, Room 336, Lloyd Building, Trinity College Dublin, Dublin, Ireland,To whom correspondence should be addressed; Department of Psychiatry, Smurfit Building, Royal College of Surgeons Ireland at Beaumont Hospital, Dublin 9, Ireland; tel: +353-1-896 8484, fax: +353-1-896 3183, e-mail:
| | - Eleanor Carey
- Department of Psychiatry, Smurfit Building, Royal College of Surgeons Ireland at Beaumont Hospital, Dublin, Ireland,Trinity College Institute of Neuroscience, Room 336, Lloyd Building, Trinity College Dublin, Dublin, Ireland
| | - Niamh Dooley
- Department of Psychiatry, Smurfit Building, Royal College of Surgeons Ireland at Beaumont Hospital, Dublin, Ireland,Trinity College Institute of Neuroscience, Room 336, Lloyd Building, Trinity College Dublin, Dublin, Ireland
| | - Colm Healy
- Department of Psychiatry, Smurfit Building, Royal College of Surgeons Ireland at Beaumont Hospital, Dublin, Ireland
| | - Helen Coughlan
- Department of Psychiatry, Smurfit Building, Royal College of Surgeons Ireland at Beaumont Hospital, Dublin, Ireland
| | - Clare Kelly
- Trinity College Institute of Neuroscience, Room 336, Lloyd Building, Trinity College Dublin, Dublin, Ireland
| | - Thomas Frodl
- Trinity College Institute of Neuroscience, Room 336, Lloyd Building, Trinity College Dublin, Dublin, Ireland,Department of Psychiatry and Psychotherapy, University Hospital Magdeburg A.ö.R., Magdeburg, Germany
| | - Erik O’Hanlon
- Department of Psychiatry, Smurfit Building, Royal College of Surgeons Ireland at Beaumont Hospital, Dublin, Ireland,Trinity College Institute of Neuroscience, Room 336, Lloyd Building, Trinity College Dublin, Dublin, Ireland
| | - Mary Cannon
- Department of Psychiatry, Smurfit Building, Royal College of Surgeons Ireland at Beaumont Hospital, Dublin, Ireland,Trinity College Institute of Neuroscience, Room 336, Lloyd Building, Trinity College Dublin, Dublin, Ireland
| |
Collapse
|
12
|
Leroy A, Foucher JR, Pins D, Delmaire C, Thomas P, Roser MM, Lefebvre S, Amad A, Fovet T, Jaafari N, Jardri R. fMRI capture of auditory hallucinations: Validation of the two-steps method. Hum Brain Mapp 2017; 38:4966-4979. [PMID: 28660668 PMCID: PMC6866805 DOI: 10.1002/hbm.23707] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 06/08/2017] [Accepted: 06/18/2017] [Indexed: 02/06/2023] Open
Abstract
Our purpose was to validate a reliable method to capture brain activity concomitant with hallucinatory events, which constitute frequent and disabling experiences in schizophrenia. Capturing hallucinations using functional magnetic resonance imaging (fMRI) remains very challenging. We previously developed a method based on a two-steps strategy including (1) multivariate data-driven analysis of per-hallucinatory fMRI recording and (2) selection of the components of interest based on a post-fMRI interview. However, two tests still need to be conducted to rule out critical pitfalls of conventional fMRI capture methods before this two-steps strategy can be adopted in hallucination research: replication of these findings on an independent sample and assessment of the reliability of the hallucination-related patterns at the subject level. To do so, we recruited a sample of 45 schizophrenia patients suffering from frequent hallucinations, 20 schizophrenia patients without hallucinations and 20 matched healthy volunteers; all participants underwent four different experiments. The main findings are (1) high accuracy in reporting unexpected sensory stimuli in an MRI setting; (2) good detection concordance between hypothesis-driven and data-driven analysis methods (as used in the two-steps strategy) when controlled unexpected sensory stimuli are presented; (3) good agreement of the two-steps method with the online button-press approach to capture hallucinatory events; (4) high spatial consistency of hallucinatory-related networks detected using the two-steps method on two independent samples. By validating the two-steps method, we advance toward the possible transfer of such technology to new image-based therapies for hallucinations. Hum Brain Mapp 38:4966-4979, 2017. © 2017 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Arnaud Leroy
- Univ Lille, CNRS, UMR 9193 ‐ SCALab ‐ Sciences Cognitives et Sciences AffectivesLilleF‐59000France
- CHU Lille, Psychiatry Dpt., CURE platformLilleF‐59000France
| | - Jack R. Foucher
- Univ Strasbourg, CNRS, UMR 7357 ‐ ICube ‐ Laboratoire des Sciences de l'Ingénieur, de l'Informatique et de l'Imagerie and Fédération de Médecine Translationnelle de Strasbourg (FMTS)StrasbourgF‐67000France
- CHU Strasbourg, CEntre de neuroModulation Non Invasive de Strasbourg (CEMNIS)StrasbourgF‐67000France
| | - Delphine Pins
- Univ Lille, CNRS, UMR 9193 ‐ SCALab ‐ Sciences Cognitives et Sciences AffectivesLilleF‐59000France
- CHU Lille, Psychiatry Dpt., CURE platformLilleF‐59000France
| | | | - Pierre Thomas
- Univ Lille, CNRS, UMR 9193 ‐ SCALab ‐ Sciences Cognitives et Sciences AffectivesLilleF‐59000France
- CHU Lille, Psychiatry Dpt., CURE platformLilleF‐59000France
| | - Mathilde M. Roser
- Univ Strasbourg, CNRS, UMR 7357 ‐ ICube ‐ Laboratoire des Sciences de l'Ingénieur, de l'Informatique et de l'Imagerie and Fédération de Médecine Translationnelle de Strasbourg (FMTS)StrasbourgF‐67000France
- CHU Strasbourg, CEntre de neuroModulation Non Invasive de Strasbourg (CEMNIS)StrasbourgF‐67000France
| | - Stéphanie Lefebvre
- Univ Lille, CNRS, UMR 9193 ‐ SCALab ‐ Sciences Cognitives et Sciences AffectivesLilleF‐59000France
- CHU Lille, Psychiatry Dpt., CURE platformLilleF‐59000France
| | - Ali Amad
- Univ Lille, CNRS, UMR 9193 ‐ SCALab ‐ Sciences Cognitives et Sciences AffectivesLilleF‐59000France
- CHU Lille, Psychiatry Dpt., CURE platformLilleF‐59000France
| | - Thomas Fovet
- Univ Lille, CNRS, UMR 9193 ‐ SCALab ‐ Sciences Cognitives et Sciences AffectivesLilleF‐59000France
- CHU Lille, Psychiatry Dpt., CURE platformLilleF‐59000France
| | - Nemat Jaafari
- Henri Laborit Hospital Centre, Unité de recherche clinique intersectorielle en psychiatrie à vocation régionale Pierre DenikerPoitiersF‐86022France
- Univ Poitiers and CHU Poitiers, INSERM, CIC‐P 1402 and U‐1084 Experimental and Clinical Neurosciences LaboratoryPoitiersF‐86022France
| | - Renaud Jardri
- Univ Lille, CNRS, UMR 9193 ‐ SCALab ‐ Sciences Cognitives et Sciences AffectivesLilleF‐59000France
- CHU Lille, Psychiatry Dpt., CURE platformLilleF‐59000France
| |
Collapse
|
13
|
Diwadkar VA, Asemi A, Burgess A, Chowdury A, Bressler SL. Potentiation of motor sub-networks for motor control but not working memory: Interaction of dACC and SMA revealed by resting-state directed functional connectivity. PLoS One 2017; 12:e0172531. [PMID: 28278267 PMCID: PMC5344349 DOI: 10.1371/journal.pone.0172531] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Accepted: 02/06/2017] [Indexed: 12/20/2022] Open
Abstract
The dorsal Anterior Cingulate Cortex (dACC) and the Supplementary Motor Area (SMA) are known to interact during motor coordination behavior. We previously discovered that the directional influences underlying this interaction in a visuo-motor coordination task are asymmetric, with the dACC→SMA influence being significantly greater than that in the reverse direction. To assess the specificity of this effect, here we undertook an analysis of the interaction between dACC and SMA in two distinct contexts. In addition to the motor coordination task, we also assessed these effects during a (n-back) working memory task. We applied directed functional connectivity analysis to these two task paradigms, and also to the rest condition of each paradigm, in which rest blocks were interspersed with task blocks. We report here that the previously known asymmetric interaction between dACC and SMA, with dACC→SMA dominating, was significantly larger in the motor coordination task than the memory task. Moreover the asymmetry between dACC and SMA was reversed during the rest condition of the motor coordination task, but not of the working memory task. In sum, the dACC→SMA influence was significantly greater in the motor task than the memory task condition, and the SMA→dACC influence was significantly greater in the motor rest than the memory rest condition. We interpret these results as suggesting that the potentiation of motor sub-networks during the motor rest condition supports the motor control of SMA by dACC during the active motor task condition.
Collapse
Affiliation(s)
- Vaibhav A. Diwadkar
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, Michigan, United States of America
- * E-mail:
| | - Avisa Asemi
- Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, Florida, United States of America
| | - Ashley Burgess
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, Michigan, United States of America
| | - Asadur Chowdury
- Dept. of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, Michigan, United States of America
| | - Steven L. Bressler
- Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, Florida, United States of America
- Department of Psychology, Florida Atlantic University, Boca Raton, Florida, United States of America
| |
Collapse
|