1
|
Wang H, Zhu Z, Bi H, Jiang Z, Cao Y, Wang S, Zou L. Changes in Community Structure of Brain Dynamic Functional Connectivity States in Mild Cognitive Impairment. Neuroscience 2024; 544:1-11. [PMID: 38423166 DOI: 10.1016/j.neuroscience.2024.02.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 01/22/2024] [Accepted: 02/24/2024] [Indexed: 03/02/2024]
Abstract
Recent researches have noted many changes of short-term dynamic modalities in mild cognitive impairment (MCI) patients' brain functional networks. In this study, the dynamic functional brain networks of 82 MCI patients and 85 individuals in the normal control (NC) group were constructed using the sliding window method and Pearson correlation. The window size was determined using single-scale time-dependent (SSTD) method. Subsequently, k-means was applied to cluster all window samples, identifying three dynamic functional connectivity (DFC) states. Collective sparse symmetric non-negative matrix factorization (cssNMF) was then used to perform community detection on these states and quantify differences in brain regions. Finally, metrics such as within-community connectivity strength, community strength, and node diversity were calculated for further analysis. The results indicated high similarity between the two groups in state 2, with no significant differences in optimal community quantity and functional segregation (p < 0.05). However, for state 1 and state 3, the optimal community quantity was smaller in MCI patients compared to the NC group. In state 1, MCI patients had lower within-community connectivity strength and overall strength than the NC group, whereas state 3 showed results opposite to state 1. Brain regions with statistical difference included MFG.L, ORBinf.R, STG.R, IFGtriang.L, CUN.L, CUN.R, LING.R, SOG.L, and PCUN.R. This study on DFC states explores changes in the brain functional networks of patients with MCI from the perspective of alterations in the community structures of DFC states. The findings could provide new insights into the pathological changes in the brains of MCI patients.
Collapse
Affiliation(s)
- Hongwei Wang
- School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Zhihao Zhu
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Hui Bi
- School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Zhongyi Jiang
- School of Computer Science and Artificial Intelligence, Aliyun School of Big Data, School of Software, Changzhou University, Changzhou, Jiangsu 213164, China
| | - Yin Cao
- The Affiliated Changzhou Second People's Hospital of Nanjing Medical University, Changzhou, Jiangsu 213164, China
| | - Suhong Wang
- Clinical Psychology, The Third Affiliated Hospital of Soochow University, Juqian Road No. 185, Changzhou, Jiangsu 213164, China
| | - Ling Zou
- School of Microelectronics and Control Engineering, Changzhou University, Changzhou, Jiangsu 213164, China; The Key Laboratory of Brain Machine Collaborative Intelligence Foundation of Zhejiang Province, Hangzhou, Zhejiang 310018, China.
| |
Collapse
|
2
|
Wang J, Sun T, Zhang Y, Yu X, Wang H. Distinct Effects of the Apolipoprotein E ε4 Genotype on Associations Between Delayed Recall Performance and Resting-State Electroencephalography Theta Power in Elderly People Without Dementia. Front Aging Neurosci 2022; 14:830149. [PMID: 35693343 PMCID: PMC9178171 DOI: 10.3389/fnagi.2022.830149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 05/06/2022] [Indexed: 11/21/2022] Open
Abstract
Background Abnormal electroencephalography (EEG) activity has been demonstrated in mild cognitive impairment (MCI), and theta rhythm might be inversely related to memory. The apolipoprotein E (ApoE) epsilon 4 (ε4) allele, as a genetic vulnerability factor for pathologic and normal age-related cognitive decline, may influence different patterns of cognitive dysfunction. Therefore, the present study primarily aimed to verify the role of resting theta rhythm in delayed recall deficits, and further explore the effects of the ApoE genotype on the associations between the resting theta power and delayed recall performance in the elderly individuals without dementia. Methods A total of 47 individuals without dementia, including 23 MCI and 24 healthy subjects (HCs), participated in the study. All subjects were administered the Hopkins Verbal Learning Test–Revised (HVLT-R) to measure delayed recall performance. Power spectra based on resting-state EEG data were used to examine brain oscillations. Linear regression was used to examine the relationships between EEG power and delayed recall performance in each subgroup. Results The increased theta power in the bilateral central and temporal areas (Ps = 0.02–0.044, uncorrected) was found in the patients with MCI, and were negatively correlated with delayed recall performance (rs = −0.358 to −0.306, Ps = 0.014–0.036, FDR corrected) in the elderly individuals without dementia. The worse delayed recall performance was associated with higher theta power in the left central and temporal areas, especially in ApoE ε4 non-carriers and not in carriers (rs = −0.404 to −0.369, Ps = 0.02–0.035, uncorrected). Conclusion Our study suggests that theta disturbances might contribute to delayed recall memory decline. The ApoE genotype may have distinct effects on EEG-based neural correlates of episodic memory performance.
Collapse
Affiliation(s)
- Jing Wang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Tingting Sun
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
- Department of Psychiatry, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ying Zhang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Xin Yu
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Huali Wang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
- *Correspondence: Huali Wang,
| |
Collapse
|
3
|
Güntekin B, Aktürk T, Arakaki X, Bonanni L, Del Percio C, Edelmayer R, Farina F, Ferri R, Hanoğlu L, Kumar S, Lizio R, Lopez S, Murphy B, Noce G, Randall F, Sack AT, Stocchi F, Yener G, Yıldırım E, Babiloni C. Are there consistent abnormalities in event-related EEG oscillations in patients with Alzheimer's disease compared to other diseases belonging to dementia? Psychophysiology 2022; 59:e13934. [PMID: 34460957 DOI: 10.1111/psyp.13934] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 07/31/2021] [Accepted: 08/09/2021] [Indexed: 01/30/2023]
Abstract
Cerebrospinal and structural-molecular neuroimaging in-vivo biomarkers are recommended for diagnostic purposes in Alzheimer's disease (AD) and other dementias; however, they do not explain the effects of AD neuropathology on neurophysiological mechanisms underpinning cognitive processes. Here, an Expert Panel from the Electrophysiology Professional Interest Area of the Alzheimer's Association reviewed the field literature and reached consensus on the event-related electroencephalographic oscillations (EROs) that show consistent abnormalities in patients with significant cognitive deficits due to Alzheimer's, Parkinson's (PD), Lewy body (LBD), and cerebrovascular diseases. Converging evidence from oddball paradigms showed that, as compared to cognitively unimpaired (CU) older adults, AD patients had lower amplitude in widespread delta (>4 Hz) and theta (4-7 Hz) phase-locked EROs as a function of disease severity. Similar effects were also observed in PD, LBD, and/or cerebrovascular cognitive impairment patients. Non-phase-locked alpha (8-12 Hz) and beta (13-30 Hz) oscillations were abnormally reduced (event-related desynchronization, ERD) in AD patients relative to CU. However, studies on patients with other dementias remain lacking. Delta and theta phase-locked EROs during oddball tasks may be useful neurophysiological biomarkers of cognitive systems at work in heuristic and intervention clinical trials performed in AD patients, but more research is needed regarding their potential role for other dementias.
Collapse
Affiliation(s)
- Bahar Güntekin
- Research Institute for Health Sciences and Technologies (SABITA), Regenerative and Restorative Medicine Research Center (REMER), Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Tuba Aktürk
- Research Institute for Health Sciences and Technologies (SABITA), Regenerative and Restorative Medicine Research Center (REMER), Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
- Vocational School, Program of Electroneurophysiology, Istanbul Medipol University, Istanbul, Turkey
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | | | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Francesca Farina
- School of Psychology, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | | | - Lütfü Hanoğlu
- Department of Neurology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
| | - Sanjeev Kumar
- Adult Neurodevelopmental and Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | | | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | | | - Fiona Randall
- Vertex Pharmaceuticals Incorporated, Boston, Massachusetts, USA
| | - Alexander T Sack
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Görsev Yener
- Izmir Biomedicine and Genome Center, Dokuz Eylul University Health Campus, Izmir, Turkey
| | - Ebru Yıldırım
- Research Institute for Health Sciences and Technologies (SABITA), Regenerative and Restorative Medicine Research Center (REMER), Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
- Vocational School, Program of Electroneurophysiology, Istanbul Medipol University, Istanbul, Turkey
| | - Claudio Babiloni
- Alzheimer's Association, Chicago, Illinois, USA
- Institute for Research and Medical Care, Hospital San Raffaele of Cassino, Cassino, Italy
| |
Collapse
|
4
|
Xue C, Sun H, Yue Y, Wang S, Qi W, Hu G, Ge H, Yuan Q, Rao J, Tian L, Xiao C, Chen J. Structural and Functional Disruption of Salience Network in Distinguishing Subjective Cognitive Decline and Amnestic Mild Cognitive Impairment. ACS Chem Neurosci 2021; 12:1384-1394. [PMID: 33825444 DOI: 10.1021/acschemneuro.1c00051] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Salience network (SN), playing a vital role in advanced cognitive function, is regarded to be impaired in subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The purpose of the study was to explore the importance of structural and functional features of SN in the diagnosis of SCD and aMCI. Structural and resting-state functional magnetic resonance imaging were collected from SCD, aMCI, and healthy control (HC). Cortex thickness, gray matter (GM) volume, spontaneous brain activity, functional connectivity (FC) within SN, and its relationship with cognitive function were analyzed. Moreover, the receiver operating characteristic analysis was performed to assess diagnostic efficacy of altered indictors for SCD and aMCI. Compared to HC, both SCD and aMCI showed decreased GM volume, decreased spontaneous brain activity, and increased FC within SN, while aMCI showed additional decreased cortex thickness. Furthermore, the altered FC in SCD and aMCI was significantly correlated with cognitive function. Particularly, the best-fitting classification models of SCD and aMCI were based on the combined multiple indicators. In conclusion, structure and function of SN were disrupted in SCD and aMCI, which involved in cognitive decline. The combined multiple indicators of SN provided powerful biomarkers for the diagnosis of SCD and aMCI.
Collapse
Affiliation(s)
- Chen Xue
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu210029, China
| | - Haiting Sun
- Department of Pediatrics, Xijing Hospital, the Fourth Milit ary Medical University (Air Force Medical University), Xi’an, Shaanxi 710032, China
| | - Yingying Yue
- Department of Psychosomatics and Psychiatry, ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu 210009, China
| | - Siyu Wang
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, China
| | - Wenzhang Qi
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu210029, China
| | - Guanjie Hu
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, China
| | - Honglin Ge
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, China
| | - Qianqian Yuan
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu210029, China
| | - Jiang Rao
- Department of Rehabilitation, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Lei Tian
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu210029, China
| | - Chaoyong Xiao
- Department of Radiology, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu210029, China
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, China
| | - Jiu Chen
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, China
- Institute of Neuropsychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| |
Collapse
|
5
|
Sun P, Lou W, Liu J, Shi L, Li K, Wang D, Mok VC, Liang P. Mapping the patterns of cortical thickness in single- and multiple-domain amnestic mild cognitive impairment patients: a pilot study. Aging (Albany NY) 2019; 11:10000-10015. [PMID: 31756169 PMCID: PMC6914405 DOI: 10.18632/aging.102362] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Accepted: 10/05/2019] [Indexed: 01/26/2023]
Abstract
Amnestic mild cognitive impairment (aMCI) is considered as a transitional stage between the expected cognitive decline of normal aging and Alzheimer’s disease (AD). Structural brain difference has shown the potential in cognitive related diagnosis, however cortical thickness patterns transferred from aMCI to AD, especially in the subtypes of aMCI, is still unclear. In this study, we investigated the cortical thickness discrepancies among AD, aMCI and normal control (NC) entities, especially for two subtypes of aMCI - multiple-domain aMCI (aMCI-m) and single-domain aMCI (aMCI-s). Both region of interest (ROI)-based and vertex-based statistical strategies were performed for group-level cortical thickness comparison. Spearman correlation was utilized to identify the correlation between cortical thickness and clinical neuropsychological scores. The result demonstrated that there was a significant cortical thickness decreasing tendency in fusiform gyrus from NC to aMCI-s to aMCI-m to finally AD in both left and right hemispheres. Meanwhile, the two subtypes of aMCI showed cortical thickness difference in middle temporal gyrus in left hemisphere. Spearman correlation indicated that neuropsychological scores had significant correlations with entorhinal, inferior temporal and middle temporal gyrus. The findings suggested that cortical thickness might serve as a potential imaging biomarker for the differential diagnosis of cognitive impairment.
Collapse
Affiliation(s)
- Pan Sun
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Wutao Lou
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Jianghong Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Lin Shi
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, China.,BrainNow Research Institute, Shenzhen, China
| | - Kuncheng Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Beijing Key Lab of MRI and Brain Informatics, Beijing, China
| | - Defeng Wang
- School of Instrumentation Science and Opto-electronics Engineering, Beihang University, Beijing, China
| | - Vincent Ct Mok
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China.,Therese Pei Fong Chow Research Centre for Prevention of Dementia, The Chinese University of Hong Kong, Hong Kong, China
| | - Peipeng Liang
- Beijing Key Laboratory of Learning and Cognition, School of Psychology, Capital Normal University, Beijing, China
| |
Collapse
|
6
|
Dozolme D, Prigent E, Yang YF, Amorim MA. The neuroelectric dynamics of the emotional anticipation of other people's pain. PLoS One 2018; 13:e0200535. [PMID: 30067781 PMCID: PMC6070195 DOI: 10.1371/journal.pone.0200535] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Accepted: 06/28/2018] [Indexed: 12/14/2022] Open
Abstract
When we observe a dynamic emotional facial expression, we usually automatically anticipate how that expression will develop. Our objective was to study a neurocognitive biomarker of this anticipatory process for facial pain expressions, operationalized as a mismatch effect. For this purpose, we studied the behavioral and neuroelectric (Event-Related Potential, ERP) correlates, of a match or mismatch, between the intensity of an expression of pain anticipated by the participant, and the intensity of a static test expression of pain displayed with the use of a representational momentum paradigm. Here, the paradigm consisted in displaying a dynamic facial pain expression which suddenly disappeared, and participants had to memorize the final intensity of the dynamic expression. We compared ERPs in response to congruent (intensity the same as the one memorized) and incongruent (intensity different from the one memorized) static expression intensities displayed after the dynamic expression. This paradigm allowed us to determine the amplitude and direction of this intensity anticipation by measuring the observer's memory bias. Results behaviorally showed that the anticipation was backward (negative memory bias) for high intensity expressions of pain (participants expected a return to a neutral state) and more forward (memory bias less negative, or even positive) for less intense expressions (participants expected increased intensity). Detecting mismatch (incongruent intensity) led to faster responses than detecting match (congruent intensity). The neuroelectric correlates of this mismatch effect in response to the testing of expression intensity ranged from P100 to LPP (Late Positive Potential). Path analysis and source localization suggested that the medial frontal gyrus was instrumental in mediating the mismatch effect through top-down influence on both the occipital and temporal regions. Moreover, having the facility to detect incongruent expressions, by anticipating emotional state, could be useful for prosocial behavior and the detection of trustworthiness.
Collapse
Affiliation(s)
- Dorian Dozolme
- CIAMS, Univ. Paris Sud, Université Paris-Saclay, France
- CIAMS, Université d’Orléans, Orléans, France
| | - Elise Prigent
- LIMSI, CNRS, Univ. Paris-Sud, Université Paris-Saclay, Orsay, France
| | - Yu-Fang Yang
- CIAMS, Univ. Paris Sud, Université Paris-Saclay, France
- CIAMS, Université d’Orléans, Orléans, France
| | - Michel-Ange Amorim
- CIAMS, Univ. Paris Sud, Université Paris-Saclay, France
- CIAMS, Université d’Orléans, Orléans, France
| |
Collapse
|