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Qi Z, Xiong H, Zhuo J, Cao D, Liu H, Shi W, Lang Y, Liu Y, Zhang G, Jiang T. Intracranial EEGs evidenced visual object processing in the human medial temporal lobe subregions. Neuroscience 2024; 555:205-212. [PMID: 39053670 DOI: 10.1016/j.neuroscience.2024.07.030] [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: 12/30/2023] [Revised: 07/10/2024] [Accepted: 07/18/2024] [Indexed: 07/27/2024]
Abstract
The perirhinal cortex (PRC) and parahippocampal cortex (PHC) are core regions along the visual dual-stream. The specific functional roles of the PRC and PHC and their interactions with the downstream hippocampus cortex (HPC) are crucial for understanding visual memory. Our research used human intracranial EEGs to study the neural mechanism of the PRC, PHC, and HPC in visual object encoding. Single-regional function analyses found evidence that the PRC, PHC, and HPC are activated ∼100 ms within the broad-gamma band and that the PRC was more strongly activated than either the PHC or the HPC after an object stimulus. Inter-regional analyses showed strong bidirectional interactions of the PRC with both the PHC and HPC in the low-frequency band, whereas the interactions between the PHC and HPC were not significant. These findings demonstrated the core role of the PRC in encoding visual object information and supported the hypothesis of PRC-HPC-ventral object pathway. The recruitment of the PHC and its interaction with the PRC in visual object encoding also provide new insights beyond the traditional dorsal-stream hypothesis.
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Affiliation(s)
- Zihui Qi
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hui Xiong
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Junjie Zhuo
- Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Hainan 570228, China
| | - Dan Cao
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Hao Liu
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weiyang Shi
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Yongcui Lang
- Department of Neurosurgery, Epilepsy Center, Aviation General Hospital, No. 3 Beiyuan Road, Chaoyang District, Beijing 100012, China
| | - Yaoling Liu
- Department of Neurosurgery, Epilepsy Center, Aviation General Hospital, No. 3 Beiyuan Road, Chaoyang District, Beijing 100012, China
| | - Guangming Zhang
- Department of Neurosurgery, Epilepsy Center, Aviation General Hospital, No. 3 Beiyuan Road, Chaoyang District, Beijing 100012, China.
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China; Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, Yongzhou 425000, Hunan Province, China.
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Lv T, Chen Y, Hou X, Qin R, Yang Z, Hu Z, Bai F. Anterior-temporal hippocampal network mechanisms of left angular gyrus-navigated rTMS for memory improvement in aMCI: A sham-controlled study. Behav Brain Res 2024; 471:115117. [PMID: 38908485 DOI: 10.1016/j.bbr.2024.115117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 06/03/2024] [Accepted: 06/15/2024] [Indexed: 06/24/2024]
Abstract
INTRODUCTION Neuro-navigated repetitive transcranial magnetic stimulation (rTMS) of the left angular gyrus has been broadly investigated for the treatment of amnestic mild cognitive impairment (aMCI). Although abnormalities in two hippocampal networks, the anterior-temporal (AT) and posterior-medial (PM) networks, are consistent with aMCI and are potential therapeutic targets for rTMS, the underlying mechanisms of the therapeutic effects of rTMS on hippocampal network connections remain unknown. Here, we assessed the impact of left angular gyrus rTMS on activity in these networks and explored whether the treatment response was due to the distance between the clinically applied target (the group average optimal site) and the personalized target in patients with aMCI. METHODS Sixty subjects clinically diagnosed with aMCI participated in this study after 20 sessions of sham-controlled rTMS targeting the left angular gyrus. Resting-state functional magnetic resonance imaging and neuropsychological assessments were performed before and after rTMS. Functional connectivity alterations in the PM and AT networks were assessed using seed-based functional connectivity analysis and two-factor repeated measures analysis of variance (ANOVA). We then computed the correlations between the functional connectivity changes and clinical rating scales. Finally, we examined whether the Euclidean distance between the clinically applied and personalized targets predicted the subsequent treatment response. RESULTS Compared with the sham group, the active rTMS group showed rTMS-induced deactivation of functional connectivity within the medial temporal lobe-AT network, with a negative correlation with episodic memory score changes. Moreover, the active rTMS lowers the interdependency of changes in the PM and AT networks. Finally, the Euclidean distance between the clinically applied and personalized target distances could predict subsequent network lever responses in the active rTMS group. CONCLUSIONS Neuro-navigated rTMS selectively modulates widespread functional connectivity abnormalities in the PM and AT hippocampal networks in aMCI patients, and the modulation of hippocampal-AT network connectivity can efficiently reverse memory deficits. The results also highlight the necessity of personalized targets for fMRI.
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Affiliation(s)
- Tingyu Lv
- Geriatric Medicine Center, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210046, China; Institute of Geriatric Medicine, Medical School of Nanjing University, Nanjing 210046, China; Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China; Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China
| | - Ya Chen
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China
| | - Xinle Hou
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China
| | - Ruomeng Qin
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China
| | - Zhiyuan Yang
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China
| | - Zheqi Hu
- Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China
| | - Feng Bai
- Geriatric Medicine Center, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210046, China; Institute of Geriatric Medicine, Medical School of Nanjing University, Nanjing 210046, China; Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China; Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, China.
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Wang T, Yan S, Lu J. The effects of noninvasive brain stimulation on cognitive function in patients with mild cognitive impairment and Alzheimer's disease using resting-state functional magnetic resonance imaging: A systematic review and meta-analysis. CNS Neurosci Ther 2023; 29:3160-3172. [PMID: 37349974 PMCID: PMC10580344 DOI: 10.1111/cns.14314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 05/08/2023] [Accepted: 06/06/2023] [Indexed: 06/24/2023] Open
Abstract
OBJECTIVE The aim of this systematic review and meta-analysis was to evaluate the efficacy of noninvasive brain stimulation (NIBS) on cognition using functional magnetic resonance imaging (fMRI) in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD), thus providing the neuroimaging mechanism of cognitive intervention. METHODS English articles published up to April 30, 2023 were searched in the PubMed, Web of Science, Embase, and Cochrane Library databases. We included randomized controlled trials where resting-state fMRI was used to observe the effect of NIBS in patients with MCI or AD. RevMan software was used to analyze the continuous variables, and SDM-PSI software was used to perform an fMRI data analysis. RESULTS A total of 17 studies comprising 258 patients in the treatment group and 256 in the control group were included. After NIBS, MCI patients in the treatment group showed hyperactivation in the right precuneus and decreased activity in the left cuneus and right supplementary motor area. In contrast, patients in the control group showed decreased activity in the right middle frontal gyrus and no hyperactivation. The clinical cognitive scores in MCI patients were significantly improved by NIBS, while not in AD. Some evidence regarding the modulation of NIBS in resting-state brain activity and functional brain networks in patients with AD was found. CONCLUSIONS NIBS could improve cognitive function in patients with MCI and AD. fMRI evaluations could be added to evaluate the contribution of specific NIBS treatment therapeutic effectiveness.
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Affiliation(s)
- Tao Wang
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
| | - Shaozhen Yan
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain InformaticsBeijingChina
- Key Laboratory of Neurodegenerative DiseasesMinistry of EducationBeijingChina
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Zhou Y, Wei L, Gao S, Wang J, Hu Z. Characterization of diffusion magnetic resonance imaging revealing relationships between white matter disconnection and behavioral disturbances in mild cognitive impairment: a systematic review. Front Neurosci 2023; 17:1209378. [PMID: 37360170 PMCID: PMC10285107 DOI: 10.3389/fnins.2023.1209378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 05/23/2023] [Indexed: 06/28/2023] Open
Abstract
White matter disconnection is the primary cause of cognition and affection abnormality in mild cognitive impairment (MCI). Adequate understanding of behavioral disturbances, such as cognition and affection abnormality in MCI, can help to intervene and slow down the progression of Alzheimer's disease (AD) promptly. Diffusion MRI is a non-invasive and effective technique for studying white matter microstructure. This review searched the relevant papers published from 2010 to 2022. Sixty-nine studies using diffusion MRI for white matter disconnections associated with behavioral disturbances in MCI were screened. Fibers connected to the hippocampus and temporal lobe were associated with cognition decline in MCI. Fibers connected to the thalamus were associated with both cognition and affection abnormality. This review summarized the correspondence between white matter disconnections and behavioral disturbances such as cognition and affection, which provides a theoretical basis for the future diagnosis and treatment of AD.
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Affiliation(s)
- Yu Zhou
- College of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
| | - Lan Wei
- Business School, The University of Sydney, Sydney, NSW, Australia
| | - Song Gao
- College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang, China
| | - Jun Wang
- School of Information Engineering, Henan University of Science and Technology, Luoyang, China
| | - Zhigang Hu
- College of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China
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Zhou Y, Si X, Chao YP, Chen Y, Lin CP, Li S, Zhang X, Sun Y, Ming D, Li Q. Automated Classification of Mild Cognitive Impairment by Machine Learning With Hippocampus-Related White Matter Network. Front Aging Neurosci 2022; 14:866230. [PMID: 35774112 PMCID: PMC9237212 DOI: 10.3389/fnagi.2022.866230] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 03/21/2022] [Indexed: 11/13/2022] Open
Abstract
Background Detection of mild cognitive impairment (MCI) is essential to screen high risk of Alzheimer’s disease (AD). However, subtle changes during MCI make it challenging to classify in machine learning. The previous pathological analysis pointed out that the hippocampus is the critical hub for the white matter (WM) network of MCI. Damage to the white matter pathways around the hippocampus is the main cause of memory decline in MCI. Therefore, it is vital to biologically extract features from the WM network driven by hippocampus-related regions to improve classification performance. Methods Our study proposes a method for feature extraction of the whole-brain WM network. First, 42 MCI and 54 normal control (NC) subjects were recruited using diffusion tensor imaging (DTI), resting-state functional magnetic resonance imaging (rs-fMRI), and T1-weighted (T1w) imaging. Second, mean diffusivity (MD) and fractional anisotropy (FA) were calculated from DTI, and the whole-brain WM networks were obtained. Third, regions of interest (ROIs) with significant functional connectivity to the hippocampus were selected for feature extraction, and the hippocampus (HIP)-related WM networks were obtained. Furthermore, the rank sum test with Bonferroni correction was used to retain significantly different connectivity between MCI and NC, and significant HIP-related WM networks were obtained. Finally, the classification performances of these three WM networks were compared to select the optimal feature and classifier. Results (1) For the features, the whole-brain WM network, HIP-related WM network, and significant HIP-related WM network are significantly improved in turn. Also, the accuracy of MD networks as features is better than FA. (2) For the classification algorithm, the support vector machine (SVM) classifier with radial basis function, taking the significant HIP-related WM network in MD as a feature, has the optimal classification performance (accuracy = 89.4%, AUC = 0.954). (3) For the pathologic mechanism, the hippocampus and thalamus are crucial hubs of the WM network for MCI. Conclusion Feature extraction from the WM network driven by hippocampus-related regions provides an effective method for the early diagnosis of AD.
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Affiliation(s)
- Yu Zhou
- School of Microelectronics, Tianjin University, Tianjin, China
| | - Xiaopeng Si
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China
- Institute of Applied Psychology, Tianjin University, Tianjin, China
- *Correspondence: Xiaopeng Si,
| | - Yi-Ping Chao
- Graduate Institute of Biomedical Engineering, Chang Gung University, Taoyuan, Taiwan
- Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan
| | - Yuanyuan Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Sicheng Li
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China
| | - Xingjian Zhang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China
| | - Yulin Sun
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China
- Dong Ming,
| | - Qiang Li
- School of Microelectronics, Tianjin University, Tianjin, China
- Qiang Li,
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de Flores R, Das SR, Xie L, Wisse LEM, Lyu X, Shah P, Yushkevich PA, Wolk DA. Medial Temporal Lobe Networks in Alzheimer's Disease: Structural and Molecular Vulnerabilities. J Neurosci 2022; 42:2131-2141. [PMID: 35086906 PMCID: PMC8916768 DOI: 10.1523/jneurosci.0949-21.2021] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 11/30/2021] [Accepted: 12/04/2021] [Indexed: 11/21/2022] Open
Abstract
The medial temporal lobe (MTL) is connected to the rest of the brain through two main networks: the anterior-temporal (AT) and the posterior-medial (PM) systems. Given the crucial role of the MTL and networks in the physiopathology of Alzheimer's disease (AD), the present study aimed at (1) investigating whether MTL atrophy propagates specifically within the AT and PM networks, and (2) evaluating the vulnerability of these networks to AD proteinopathies. To do that, we used neuroimaging data acquired in human male and female in three distinct cohorts: (1) resting-state functional MRI (rs-fMRI) from the aging brain cohort (ABC) to define the AT and PM networks (n = 68); (2) longitudinal structural MRI from Alzheimer's disease neuroimaging initiative (ADNI)GO/2 to highlight structural covariance patterns (n = 349); and (3) positron emission tomography (PET) data from ADNI3 to evaluate the networks' vulnerability to amyloid and tau (n = 186). Our results suggest that the atrophy of distinct MTL subregions propagates within the AT and PM networks in a dissociable manner. Brodmann area (BA)35 structurally covaried within the AT network while the parahippocampal cortex (PHC) covaried within the PM network. In addition, these networks are differentially associated with relative tau and amyloid burden, with higher tau levels in AT than in PM and higher amyloid levels in PM than in AT. Our results also suggest differences in the relative burden of tau species. The current results provide further support for the notion that two distinct MTL networks display differential alterations in the context of AD. These findings have important implications for disease spread and the cognitive manifestations of AD.SIGNIFICANCE STATEMENT The current study provides further support for the notion that two distinct medial temporal lobe (MTL) networks, i.e., anterior-temporal (AT) and the posterior-medial (PM), display differential alterations in the context of Alzheimer's disease (AD). Importantly, neurodegeneration appears to occur within these networks in a dissociable manner marked by their covariance patterns. In addition, the AT and PM networks are also differentially associated with relative tau and amyloid burden, and perhaps differences in the relative burden of tau species [e.g., neurofibriliary tangles (NFTs) vs tau in neuritic plaques]. These findings, in the context of a growing literature consistent with the present results, have important implications for disease spread and the cognitive manifestations of AD in light of the differential cognitive processes ascribed to them.
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Affiliation(s)
- Robin de Flores
- Department of Neurology, University of Pennsylvania, Philadelphia 19104, Pennsylvania
- Université de Caen Normandie, Institut National de la Santé et de la Recherche Médicale Unité Mixte de Recherche Scientifique (UMRS) Unité 1237, Caen 14000, France
| | - Sandhitsu R Das
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Long Xie
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia 19104, Pennsylvania
- Department of Radiology, University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Laura E M Wisse
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia 19104, Pennsylvania
- Department of Diagnostic Radiology, Lund University, Lund 22185, Sweden
| | - Xueying Lyu
- Department of Bioengineering, University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Preya Shah
- Department of Bioengineering, University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - Paul A Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia 19104, Pennsylvania
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia 19104, Pennsylvania
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The human mediodorsal thalamus: Organization, connectivity, and function. Neuroimage 2022; 249:118876. [PMID: 34998970 DOI: 10.1016/j.neuroimage.2022.118876] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 12/06/2021] [Accepted: 01/04/2022] [Indexed: 01/10/2023] Open
Abstract
The human mediodorsal thalamic nucleus (MD) is crucial for higher cognitive functions, while the fine anatomical organization of the MD and the function of each subregion remain elusive. In this study, using high-resolution data provided by the Human Connectome Project, an anatomical connectivity-based method was adopted to unveil the topographic organization of the MD. Four fine-grained subregions were identified in each hemisphere, including the medial (MDm), central (MDc), dorsal (MDd), and lateral (MDl), which recapitulated previous cytoarchitectonic boundaries from histological studies. The subsequent connectivity analysis of the subregions also demonstrated distinct anatomical and functional connectivity patterns, especially with the prefrontal cortex. To further evaluate the function of MD subregions, partial least squares analysis was performed to examine the relationship between different prefrontal-subregion connectivity and behavioral measures in 1012 subjects. The results showed subregion-specific involvement in a range of cognitive functions. Specifically, the MDm predominantly subserved emotional-cognition domains, while the MDl was involved in multiple cognitive functions especially cognitive flexibility and inhibition. The MDc and MDd were correlated with fluid intelligence, processing speed, and emotional cognition. In conclusion, our work provides new insights into the anatomical and functional organization of the MD and highlights the various roles of the prefrontal-thalamic circuitry in human cognition.
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Shurtleff HA, Poliakov A, Barry D, Wright JN, Warner MH, Novotny EJ, Marashly A, Buckley R, Goldstein HE, Hauptman JS, Ojemann JG, Shaw DWW. A clinically applicable functional MRI memory paradigm for use with pediatric patients. Epilepsy Behav 2022; 126:108461. [PMID: 34896785 DOI: 10.1016/j.yebeh.2021.108461] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 11/19/2021] [Accepted: 11/24/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVE Clinically employable functional MRI (fMRI) memory paradigms are not yet established for pediatric patient epilepsy surgery workups. Seeking to establish such a paradigm, we evaluated the effectiveness of memory fMRI tasks we developed by quantifying individual activation in a clinical pediatric setting, analyzing patterns of activation relative to the side of temporal lobe (TL) pathology, and comparing fMRI and Wada test results. METHODS We retrospectively identified 72 patients aged 6.7-20.9 years with pathology (seizure focus and/or tumor) limited to the TL who had attempted memory and language fMRI tasks over a 9-year period as part of presurgical workups. Memory fMRI tasks required visualization of autobiographical memories in a block design alternating with covert counting. Language fMRI protocols involved verb and sentence generation. Scans were both qualitatively interpreted and quantitatively assessed for blood oxygenation level dependent (BOLD) signal change using region of interest (ROI) masks. We calculated the percentage of successfully scanned individual cases, compared 2 memory task activation masks in cases with left versus right TL pathology, and compared fMRI with Wada tests when available. Patients who had viable fMRI and Wada tests had generally concordant results. RESULTS Of the 72 cases, 60 (83%), aged 7.6-20.9 years, successfully performed the memory fMRI tasks and 12 (17%) failed. Eleven of 12 unsuccessful scans were due to motion and/or inability to perform the tasks, and the success of a twelfth was indeterminate due to orthodontic metal artifact. Seven of the successful 60 cases had distorted anatomy that precluded employing predetermined masks for quantitative analysis. Successful fMRI memory studies showed bilateral mesial temporal activation and quantitatively demonstrated: (1) left activation (L-ACT) less than right activation (R-ACT) in cases with left temporal lobe (L-TL) pathology, (2) nonsignificant R-ACT less than L-ACT in cases with right temporal lobe (R-TL) pathology, and (3) lower L-ACT plus R-ACT activation for cases with L-TL versus R-TL pathology. Patients who had viable fMRI and Wada tests had generally concordant results. SIGNIFICANCE This study demonstrates evidence of an fMRI memory task paradigm that elicits reliable activation at the individual level and can generally be accomplished in clinically involved pediatric patients. This autobiographical memory paradigm showed activation in mesial TL structures, and cases with left compared to right TL pathology showed differences in activation consistent with extant literature in TL epilepsy. Further studies will be required to assess outcome prediction.
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Affiliation(s)
- Hillary A Shurtleff
- Neurosciences Institute, Seattle Children's Hospital, United States; Center for Integrated Brain Research Seattle Children's, United States.
| | | | - Dwight Barry
- Clinical Analytics, Seattle Children's Hospital, United States
| | - Jason N Wright
- Radiology, Seattle Children's Hospital, United States; Department of Radiology, University of Washington School of Medicine, United States
| | - Molly H Warner
- Neurosciences Institute, Seattle Children's Hospital, United States; Center for Integrated Brain Research Seattle Children's, United States
| | - Edward J Novotny
- Neurosciences Institute, Seattle Children's Hospital, United States; Center for Integrated Brain Research Seattle Children's, United States; Neurology, Seattle Children's Hospital, United States; Department of Neurology, University of Washington School of Medicine, United States
| | - Ahmad Marashly
- Neurosciences Institute, Seattle Children's Hospital, United States; Center for Integrated Brain Research Seattle Children's, United States; Neurology, Seattle Children's Hospital, United States; Department of Neurology, University of Washington School of Medicine, United States
| | - Robert Buckley
- Department of Neurological Surgery, University of Washington School of Medicine, United States
| | - Hannah E Goldstein
- Neurosciences Institute, Seattle Children's Hospital, United States; Department of Neurological Surgery, University of Washington School of Medicine, United States; Neurological Surgery, Seattle Children's Hospital, United States
| | - Jason S Hauptman
- Neurosciences Institute, Seattle Children's Hospital, United States; Department of Neurological Surgery, University of Washington School of Medicine, United States; Neurological Surgery, Seattle Children's Hospital, United States
| | - Jeffrey G Ojemann
- Neurosciences Institute, Seattle Children's Hospital, United States; Center for Integrated Brain Research Seattle Children's, United States; Department of Neurological Surgery, University of Washington School of Medicine, United States; Neurological Surgery, Seattle Children's Hospital, United States
| | - Dennis W W Shaw
- Radiology, Seattle Children's Hospital, United States; Department of Radiology, University of Washington School of Medicine, United States
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9
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Zhou Y, Si X, Chen Y, Chao Y, Lin CP, Li S, Zhang X, Ming D, Li Q. Hippocampus- and Thalamus-Related Fiber-Specific White Matter Reductions in Mild Cognitive Impairment. Cereb Cortex 2021; 32:3159-3174. [PMID: 34891164 DOI: 10.1093/cercor/bhab407] [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: 06/08/2021] [Revised: 09/04/2021] [Accepted: 10/20/2021] [Indexed: 11/13/2022] Open
Abstract
Early diagnosis of mild cognitive impairment (MCI) fascinates screening high-risk Alzheimer's disease (AD). White matter is found to degenerate earlier than gray matter and functional connectivity during MCI. Although studies reveal white matter degenerates in the limbic system for MCI, how other white matter degenerates during MCI remains unclear. In our method, regions of interest with a high level of resting-state functional connectivity with hippocampus were selected as seeds to track fibers based on diffusion tensor imaging (DTI). In this way, hippocampus-temporal and thalamus-related fibers were selected, and each fiber's DTI parameters were extracted. Then, statistical analysis, machine learning classification, and Pearson's correlations with behavior scores were performed between MCI and normal control (NC) groups. Results show that: 1) the mean diffusivity of hippocampus-temporal and thalamus-related fibers are significantly higher in MCI and could be used to classify 2 groups effectively. 2) Compared with normal fibers, the degenerated fibers detected by the DTI indexes, especially for hippocampus-temporal fibers, have shown significantly higher correlations with cognitive scores. 3) Compared with the hippocampus-temporal fibers, thalamus-related fibers have shown significantly higher correlations with depression scores within MCI. Our results provide novel biomarkers for the early diagnoses of AD.
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Affiliation(s)
- Yu Zhou
- School of Microelectronics, Tianjin University, Tianjin 300072, China
| | - Xiaopeng Si
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China.,Institute of Applied Psychology, Tianjin University, Tianjin 300350, China
| | - Yuanyuan Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Yiping Chao
- Graduate Institute of Biomedical Engineering, Chang Gung University, Taoyuan 33302, Taiwan.,Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan 33302, Taiwan
| | - Ching-Po Lin
- Institute of Neuroscience Hsinchu City, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan
| | - Sicheng Li
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Xingjian Zhang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin 300072, China
| | - Qiang Li
- School of Microelectronics, Tianjin University, Tianjin 300072, China
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10
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Salmon E, Bahri MA, Plenevaux A, Becker G, Seret A, Delhaye E, Degueldre C, Balteau E, Lemaire C, Luxen A, Bastin C. In vivo exploration of synaptic projections in frontotemporal dementia. Sci Rep 2021; 11:16092. [PMID: 34373529 PMCID: PMC8352914 DOI: 10.1038/s41598-021-95499-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 07/20/2021] [Indexed: 11/15/2022] Open
Abstract
The purpose of this exploratory research is to provide data on synaptopathy in the behavioral variant of frontotemporal dementia (bvFTD). Twelve patients with probable bvFTD were compared to 12 control participants and 12 patients with Alzheimer’s disease (AD). Loss of synaptic projections was assessed with [18F]UCBH-PET. Total distribution volume was obtained with Logan method using carotid artery derived input function. Neuroimages were analyzed with SPM12. Verbal fluency, episodic memory and awareness of cognitive impairment were equally impaired in patients groups. Compared to controls, [18F]UCBH uptake tended to decrease in the right anterior parahippocampal gyrus of bvFTD patients. Loss of synaptic projections was observed in the right hippocampus of AD participants, but there was no significant difference in [18F]UCBH brain uptake between patients groups. Anosognosia for clinical disorder was correlated with synaptic density in the caudate nucleus and the anteromedial prefrontal cortex. This study suggests that synaptopathy in bvFTD targets the temporal social brain and self-referential processes.
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Affiliation(s)
- Eric Salmon
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium.
| | - Mohamed Ali Bahri
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium
| | - Alain Plenevaux
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium
| | - Guillaume Becker
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium
| | - Alain Seret
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium
| | - Emma Delhaye
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium
| | - Christian Degueldre
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium
| | - Evelyne Balteau
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium
| | - Christian Lemaire
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium
| | - André Luxen
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium
| | - Christine Bastin
- GIGA Cyclotron Research Centre, University of Liège, B30 Sart Tilman, 4000, Liège, Belgium
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11
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Dautricourt S, de Flores R, Landeau B, Poisnel G, Vanhoutte M, Delcroix N, Eustache F, Vivien D, de la Sayette V, Chételat G. Longitudinal Changes in Hippocampal Network Connectivity in Alzheimer's Disease. Ann Neurol 2021; 90:391-406. [PMID: 34279043 PMCID: PMC9291910 DOI: 10.1002/ana.26168] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 07/13/2021] [Accepted: 07/15/2021] [Indexed: 11/05/2022]
Abstract
Objective The hippocampus is connected to 2 distinct cortical brain networks, the posterior–medial and the anterior–temporal networks, involving different medial temporal lobe (MTL) subregions. The aim of this study was to assess the functional alterations of these 2 networks, their changes over time, and links to cognition in Alzheimer's disease. Methods We assessed MTL connectivity in 53 amyloid‐β–positive patients with mild cognitive impairment and AD dementia and 68 healthy elderly controls, using resting‐state functional magnetic resonance imaging, cross‐sectionally and longitudinally. First, we compared the functional connectivity of the posterior–medial and anterior–temporal networks within the control group to highlight their specificities. Second, we compared the connectivity of these networks between groups, and between baseline and 18‐month follow‐up in patients. Third, we assessed the association in the connectivity changes between the 2 networks, and with cognitive performance. Results We found decreased connectivity in patients specifically between the hippocampus and the posterior–medial network, together with increased connectivity between several MTL subregions and the anterior–temporal network. Moreover, changes in the posterior–medial and anterior–temporal networks were interrelated such that decreased MTL–posterior–medial connectivity was associated with increased MTL–anterior–temporal connectivity. Finally, both MTL–posterior–medial decrease and MTL–anterior–temporal increase predicted cognitive decline. Interpretation Our findings demonstrate that longitudinal connectivity changes in the posterior–medial and anterior–temporal hippocampal networks are linked together and that they both contribute to cognitive decline in Alzheimer's disease. These results shed light on the critical role of the posterior–medial and anterior–temporal networks in Alzheimer's disease pathophysiology and clinical symptoms. ANN NEUROL 2021;90:391–406
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Affiliation(s)
- Sophie Dautricourt
- Normandie Univ, UNICAEN, INSERM, PhIND.,Neurology Department, Caen-Normandie University Hospital, Caen, France
| | | | | | | | | | - Nicolas Delcroix
- CNRS, Unité Mixte de Service-3408, GIP CYCERON, Bd Henri Becquerel, BP5229, 14074 Caen cedex, France
| | - Francis Eustache
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Denis Vivien
- Normandie Univ, UNICAEN, INSERM, PhIND.,Department of Clinical Research, Caen-Normandie University Hospital, Caen, France
| | - Vincent de la Sayette
- Neurology Department, Caen-Normandie University Hospital, Caen, France.,Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
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12
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Fiorilli J, Bos JJ, Grande X, Lim J, Düzel E, Pennartz CMA. Reconciling the object and spatial processing views of the perirhinal cortex through task-relevant unitization. Hippocampus 2021; 31:737-755. [PMID: 33523577 PMCID: PMC8359385 DOI: 10.1002/hipo.23304] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 11/27/2020] [Accepted: 01/02/2021] [Indexed: 12/21/2022]
Abstract
The perirhinal cortex is situated on the border between sensory association cortex and the hippocampal formation. It serves an important function as a transition area between the sensory neocortex and the medial temporal lobe. While the perirhinal cortex has traditionally been associated with object coding and the "what" pathway of the temporal lobe, current evidence suggests a broader function of the perirhinal cortex in solving feature ambiguity and processing complex stimuli. Besides fulfilling functions in object coding, recent neurophysiological findings in freely moving rodents indicate that the perirhinal cortex also contributes to spatial and contextual processing beyond individual sensory modalities. Here, we address how these two opposing views on perirhinal cortex-the object-centered and spatial-contextual processing hypotheses-may be reconciled. The perirhinal cortex is consistently recruited when different features can be merged perceptually or conceptually into a single entity. Features that are unitized in these entities include object information from multiple sensory domains, reward associations, semantic features and spatial/contextual associations. We propose that the same perirhinal network circuits can be flexibly deployed for multiple cognitive functions, such that the perirhinal cortex performs similar unitization operations on different types of information, depending on behavioral demands and ranging from the object-related domain to spatial, contextual and semantic information.
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Affiliation(s)
- Julien Fiorilli
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
| | - Jeroen J. Bos
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud University and Radboud University Medical CentreNijmegenThe Netherlands
| | - Xenia Grande
- Institute of Cognitive Neurology and Dementia ResearchOtto‐von‐Guericke University MagdeburgMagdeburgGermany
- German Center for Neurodegenerative DiseasesMagdeburgGermany
| | - Judith Lim
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia ResearchOtto‐von‐Guericke University MagdeburgMagdeburgGermany
- German Center for Neurodegenerative DiseasesMagdeburgGermany
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
| | - Cyriel M. A. Pennartz
- Cognitive and Systems Neuroscience Group, SILS Center for NeuroscienceUniversity of AmsterdamAmsterdamThe Netherlands
- Research Priority Area Brain and CognitionUniversity of AmsterdamAmsterdamThe Netherlands
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13
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Barnett AJ, Reilly W, Dimsdale-Zucker HR, Mizrak E, Reagh Z, Ranganath C. Intrinsic connectivity reveals functionally distinct cortico-hippocampal networks in the human brain. PLoS Biol 2021; 19:e3001275. [PMID: 34077415 PMCID: PMC8202937 DOI: 10.1371/journal.pbio.3001275] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 06/14/2021] [Accepted: 05/07/2021] [Indexed: 12/13/2022] Open
Abstract
Episodic memory depends on interactions between the hippocampus and interconnected neocortical regions. Here, using data-driven analyses of resting-state functional magnetic resonance imaging (fMRI) data, we identified the networks that interact with the hippocampus-the default mode network (DMN) and a "medial temporal network" (MTN) that included regions in the medial temporal lobe (MTL) and precuneus. We observed that the MTN plays a critical role in connecting the visual network to the DMN and hippocampus. The DMN could be further divided into 3 subnetworks: a "posterior medial" (PM) subnetwork comprised of posterior cingulate and lateral parietal cortices; an "anterior temporal" (AT) subnetwork comprised of regions in the temporopolar and dorsomedial prefrontal cortex; and a "medial prefrontal" (MP) subnetwork comprised of regions primarily in the medial prefrontal cortex (mPFC). These networks vary in their functional connectivity (FC) along the hippocampal long axis and represent different kinds of information during memory-guided decision-making. Finally, a Neurosynth meta-analysis of fMRI studies suggests new hypotheses regarding the functions of the MTN and DMN subnetworks, providing a framework to guide future research on the neural architecture of episodic memory.
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Affiliation(s)
- Alexander J. Barnett
- Center for Neuroscience, University of California at Davis, Davis, California, United States of America
| | - Walter Reilly
- Center for Neuroscience, University of California at Davis, Davis, California, United States of America
| | | | - Eda Mizrak
- Center for Neuroscience, University of California at Davis, Davis, California, United States of America
- Department of Psychology, University of Zurich, Zürich, Switzerland
| | - Zachariah Reagh
- Center for Neuroscience, University of California at Davis, Davis, California, United States of America
- Department of Neurology, University of California at Davis, Sacramento, California, United States of America
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Charan Ranganath
- Center for Neuroscience, University of California at Davis, Davis, California, United States of America
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14
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Nordin K, Nyberg L, Andersson M, Karalija N, Riklund K, Bäckman L, Salami A. Distinct and Common Large-Scale Networks of the Hippocampal Long Axis in Older Age: Links to Episodic Memory and Dopamine D2 Receptor Availability. Cereb Cortex 2021; 31:3435-3450. [PMID: 33676372 PMCID: PMC8196260 DOI: 10.1093/cercor/bhab023] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 01/22/2021] [Accepted: 01/22/2021] [Indexed: 01/29/2023] Open
Abstract
The hippocampal longitudinal axis has been linked to dissociated functional networks relevant to episodic memory. However, the organization of axis-dependent networks and their relation to episodic memory in aging remains less explored. Moreover, age-related deterioration of the dopamine (DA) system, affecting memory and functional network properties, might constitute a source of reduced specificity of hippocampal networks in aging. Here, we characterized axis-dependent large-scale hippocampal resting-state networks, their relevance to episodic memory, and links to DA in older individuals (n = 170, 64–68 years). Partial least squares identified 2 dissociated networks differentially connected to the anterior and posterior hippocampus. These overlapped with anterior–temporal/posterior–medial networks in young adults, indicating preserved organization of axis-dependent connectivity in old age. However, axis-specific networks were overall unrelated to memory and hippocampal DA D2 receptor availability (D2DR) measured with [11C]-raclopride positron emission tomography. Further analyses identified a memory-related network modulated by hippocampal D2DR, equally connected to anterior–posterior regions. This network included medial frontal, posterior parietal, and striatal areas. The results add to the current understanding of large-scale hippocampal connectivity in aging, demonstrating axis-dependent connectivity with dissociated anterior and posterior networks, as well as a primary role in episodic memory of connectivity shared by regions along the hippocampalaxis.
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Affiliation(s)
- Kristin Nordin
- Umeå Center for Functional Brain Imaging, Umeå University, S-90187 Umeå, Sweden.,Department of Integrative Medical Biology, Umeå University, S-90187 Umeå, Sweden.,Wallenberg Centre for Molecular Medicine, Umeå University, S-90187 Umeå, Sweden
| | - Lars Nyberg
- Umeå Center for Functional Brain Imaging, Umeå University, S-90187 Umeå, Sweden.,Department of Integrative Medical Biology, Umeå University, S-90187 Umeå, Sweden.,Wallenberg Centre for Molecular Medicine, Umeå University, S-90187 Umeå, Sweden.,Department of Radiation Sciences, Umeå University, S-90187 Umeå, Sweden
| | - Micael Andersson
- Umeå Center for Functional Brain Imaging, Umeå University, S-90187 Umeå, Sweden.,Department of Integrative Medical Biology, Umeå University, S-90187 Umeå, Sweden
| | - Nina Karalija
- Umeå Center for Functional Brain Imaging, Umeå University, S-90187 Umeå, Sweden.,Department of Radiation Sciences, Umeå University, S-90187 Umeå, Sweden
| | - Katrine Riklund
- Umeå Center for Functional Brain Imaging, Umeå University, S-90187 Umeå, Sweden.,Department of Radiation Sciences, Umeå University, S-90187 Umeå, Sweden
| | - Lars Bäckman
- Aging Research Center, Karolinska Institutet, S-11330 Stockholm, Sweden
| | - Alireza Salami
- Umeå Center for Functional Brain Imaging, Umeå University, S-90187 Umeå, Sweden.,Department of Integrative Medical Biology, Umeå University, S-90187 Umeå, Sweden.,Wallenberg Centre for Molecular Medicine, Umeå University, S-90187 Umeå, Sweden.,Aging Research Center, Karolinska Institutet, S-11330 Stockholm, Sweden
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15
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Stark SM, Frithsen A, Stark CE. Age-related alterations in functional connectivity along the longitudinal axis of the hippocampus and its subfields. Hippocampus 2021; 31:11-27. [PMID: 32918772 PMCID: PMC8354549 DOI: 10.1002/hipo.23259] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 07/31/2020] [Accepted: 08/07/2020] [Indexed: 12/13/2022]
Abstract
Hippocampal circuit alterations that differentially affect hippocampal subfields are associated with age-related memory decline. Additionally, functional organization along the longitudinal axis of the hippocampus has revealed distinctions between anterior and posterior (A-P) connectivity. Here, we examined the functional connectivity (FC) differences between young and older adults at high-resolution within the medial temporal lobe network (entorhinal, perirhinal, and parahippocampal cortices), allowing us to explore how hippocampal subfield connectivity across the longitudinal axis of the hippocampus changes with age. Overall, we found reliably greater connectivity for younger adults than older adults between the hippocampus and parahippocampal cortex (PHC) and perirhinal cortex (PRC). This drop in functional connectivity was more pronounced in the anterior regions of the hippocampus than the posterior ones, consistent for each of the hippocampal subfields. Further, intra-hippocampal connectivity also reflected an age-related decrease in functional connectivity within the anterior hippocampus in older adults that was offset by an increase in posterior hippocampal functional connectivity. Interestingly, the anterior-posterior dysfunction in older adults between hippocampus and PHC was predictive of lure discrimination performance on the Mnemonic similarity task (MST), suggesting a role in memory performance. While age-related dysfunction within the hippocampal subfields has been well-documented, these results suggest that the age-related dysfunction in hippocampal connectivity across the longitudinal axis may also contribute significantly to memory decline in older adults.
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Affiliation(s)
- Shauna M. Stark
- Department of Neurobiology and Behavior, University of California Irvine
| | - Amy Frithsen
- Department of Neurobiology and Behavior, University of California Irvine
| | - Craig E.L. Stark
- Department of Neurobiology and Behavior, University of California Irvine
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16
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He B, Cao L, Xia X, Zhang B, Zhang D, You B, Fan L, Jiang T. Fine-Grained Topography and Modularity of the Macaque Frontal Pole Cortex Revealed by Anatomical Connectivity Profiles. Neurosci Bull 2020; 36:1454-1473. [PMID: 33108588 PMCID: PMC7719154 DOI: 10.1007/s12264-020-00589-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 07/30/2020] [Indexed: 11/25/2022] Open
Abstract
The frontal pole cortex (FPC) plays key roles in various higher-order functions and is highly developed in non-human primates. An essential missing piece of information is the detailed anatomical connections for finer parcellation of the macaque FPC than provided by the previous tracer results. This is important for understanding the functional architecture of the cerebral cortex. Here, combining cross-validation and principal component analysis, we formed a tractography-based parcellation scheme that applied a machine learning algorithm to divide the macaque FPC (2 males and 6 females) into eight subareas using high-resolution diffusion magnetic resonance imaging with the 9.4T Bruker system, and then revealed their subregional connections. Furthermore, we applied improved hierarchical clustering to the obtained parcels to probe the modular structure of the subregions, and found that the dorsolateral FPC, which contains an extension to the medial FPC, was mainly connected to regions of the default-mode network. The ventral FPC was mainly involved in the social-interaction network and the dorsal FPC in the metacognitive network. These results enhance our understanding of the anatomy and circuitry of the macaque brain, and contribute to FPC-related clinical research.
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Affiliation(s)
- Bin He
- School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, 150080, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, 100190, China
| | - Long Cao
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China
| | - Xiaoluan Xia
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,College of Information and Computer, Taiyuan University of Technology, Taiyuan, 030600, China
| | - Baogui Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, 100190, China
| | - Dan Zhang
- Core Facility, Center of Biomedical Analysis, Tsinghua University, Beijing, 100084, China
| | - Bo You
- School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, 150080, China.
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China. .,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, 100190, China. .,Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, CAS, Beijing, 100190, China. .,University of CAS, Beijing, 100049, China.
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China. .,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, 100190, China. .,Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, CAS, Beijing, 100190, China. .,Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China. .,The Queensland Brain Institute, University of Queensland, Brisbane, QLD, 4072, Australia. .,University of CAS, Beijing, 100049, China. .,Chinese Institute for Brain Research, Beijing, 102206, China.
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17
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Zhang L, Ni H, Yu Z, Wang J, Qin J, Hou F, Yang A. Investigation on the Alteration of Brain Functional Network and Its Role in the Identification of Mild Cognitive Impairment. Front Neurosci 2020; 14:558434. [PMID: 33100958 PMCID: PMC7556272 DOI: 10.3389/fnins.2020.558434] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Accepted: 09/04/2020] [Indexed: 01/13/2023] Open
Abstract
Mild cognitive impairment (MCI) is generally regarded as a prodromal stage of Alzheimer’s disease (AD). In coping with the challenges caused by AD, we analyzed resting-state functional magnetic resonance imaging data of 82 MCI subjects and 93 normal controls (NCs). The alteration of brain functional network in MCI was investigated on three scales, including global metrics, nodal characteristics, and modular properties. The results supported the existence of small worldness, hubs, and community structure in the brain functional networks of both groups. Compared with NCs, the network altered in MCI over all the three scales. In scale I, we found significantly decreased characteristic path length and increased global efficiency in MCI. Moreover, altered global network metrics were associated with cognitive level evaluated by neuropsychological assessments. In scale II, the nodal betweenness centrality of some global hubs, such as the right Crus II of cerebellar hemisphere (CERCRU2.R) and fusiform gyrus (FFG.R), changed significantly and associated with the severity and cognitive impairment in MCI. In scale III, although anatomically adjacent regions tended to be clustered into the same module regardless of group, discrepancies existed in the composition of modules in both groups, with a prominent separation of the cerebellum and a less localized organization of community structure in MCI compared with NC. Taking advantages of random forest approach, we achieved an accuracy of 91.4% to discriminate MCI patients from NCs by integrating cognitive assessments and network analysis. The importance of the used features fed into the classifier further validated the nodal characteristics of CERCRU2.R and FFG.R could be potential biomarkers in the identification of MCI. In conclusion, the present study demonstrated that the brain functional connectome data altered at the stage of MCI and could assist the automatic diagnosis of MCI patients.
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Affiliation(s)
- Lulu Zhang
- Key Laboratory of Biomedical Functional Materials, School of Science, China Pharmaceutical University, Nanjing, China
| | - Huangjing Ni
- Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, China
| | - Zhinan Yu
- Key Laboratory of Biomedical Functional Materials, School of Science, China Pharmaceutical University, Nanjing, China
| | - Jun Wang
- Smart Health Big Data Analysis and Location Services Engineering Lab of Jiangsu Province, School of Geographic and Biologic Information, Nanjing University of Posts and Telecommunications, Nanjing, China
| | - Jiaolong Qin
- Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education, School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China
| | - Fengzhen Hou
- Key Laboratory of Biomedical Functional Materials, School of Science, China Pharmaceutical University, Nanjing, China
| | - Albert Yang
- Division of Interdisciplinary Medicine and Biotechnology, Department of Medicine, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston, MA, United States
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18
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Bilgiç B, Kurt E, Makar ÇC, Ulasoglu-Yildiz C, Samancı B, Gürvit H, Demiralp T, Emre M. Functional neural substrates of football fanaticism: Different pattern of brain responses and connectivity in fanatics. Psychiatry Clin Neurosci 2020; 74:480-487. [PMID: 32474956 DOI: 10.1111/pcn.13076] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 04/20/2020] [Accepted: 05/22/2020] [Indexed: 11/28/2022]
Abstract
AIM Sports activities provide social interaction for humans. Commitment to a given team is a salient feature of being a sports fan and becomes a prominent part of self-identification for fanatics. Emotion, subjective hedonic experience, and non-romantic love are related to fan behaviors. Few studies have evaluated the neural basis of sports fanaticism. METHODS Thirty men, including 16 football fanatics and 14 non-fanatics, with a mean age of 27.4 ± 6.4 years (range, 20-48 years) were enrolled. Subjects underwent functional MRI while watching a set of goals scored by favorite, rival, and neutral teams. RESULTS The analysis of variance in a general linear model revealed a significant Group × Condition interaction effect in the bilateral dorsal anterior cingulate cortex (dACC) that was more prominent in the left hemisphere. In the post-hoc comparisons, fanatics showed increased activation in bilateral dACC, supplementary motor area, superior frontal cortex, right dorsolateral prefrontal cortex, and right insula for Favorite > Neutral contrast and an increased activation in bilateral dACC and supplementary motor area for Rival > Neutral contrast. Seed-based connectivity analyses using the areas with significant activation differences revealed increased connectivity between dACC and several regions, including the left posterior lateral temporal area, insula, bilateral medial temporal area, and medial superior frontal area as well as the basal ganglia in fanatics compared to non-fanatics. CONCLUSION Our results suggest that football fanatics exhibit a different brain activation and connectivity pattern from non-fanatics, both under favorable and unfavorable conditions. This brain activity and connectivity pattern under emotionally laden conditions may represent higher responses to rewards, higher emotional valence attribution, and stronger motivational state of football fanatics, which might underlie their unusual behavioral responses.
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Affiliation(s)
- Başar Bilgiç
- Istanbul Faculty of Medicine, Department of Neurology, Istanbul University, Istanbul, Turkey.,Hulusi Behçet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, Istanbul, Turkey
| | - Elif Kurt
- Hulusi Behçet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, Istanbul, Turkey.,Aziz Sancar Institute of Experimental Medicine, Department of Neuroscience, Istanbul University, Istanbul, Turkey
| | - Çağrı Can Makar
- Istanbul Faculty of Medicine, Department of Neurology, Istanbul University, Istanbul, Turkey
| | - Cigdem Ulasoglu-Yildiz
- Hulusi Behçet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, Istanbul, Turkey.,Aziz Sancar Institute of Experimental Medicine, Department of Neuroscience, Istanbul University, Istanbul, Turkey
| | - Bedia Samancı
- Istanbul Faculty of Medicine, Department of Neurology, Istanbul University, Istanbul, Turkey
| | - Hakan Gürvit
- Istanbul Faculty of Medicine, Department of Neurology, Istanbul University, Istanbul, Turkey.,Hulusi Behçet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, Istanbul, Turkey
| | - Tamer Demiralp
- Hulusi Behçet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, Istanbul, Turkey.,Istanbul Faculty of Medicine, Department of Physiology, Istanbul University, Istanbul, Turkey
| | - Murat Emre
- Istanbul Faculty of Medicine, Department of Neurology, Istanbul University, Istanbul, Turkey
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19
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Lawrence AV, Cardoza J, Ryan L. Medial temporal lobe regions mediate complex visual discriminations for both objects and scenes: A process-based view. Hippocampus 2020; 30:879-891. [PMID: 32163223 DOI: 10.1002/hipo.23203] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 02/14/2020] [Accepted: 02/23/2020] [Indexed: 11/08/2022]
Abstract
Debate continues regarding the role of medial temporal lobe regions in object and scene processing. Considerable evidence indicates that the perirhinal cortex (PRC) plays an important role in the perception of objects-namely, in disambiguating complex objects that share conjunctions of features. These findings support a content-specific view of medial temporal lobe functioning in which PRC is critically important for processing complex objects, while the parahippocampal cortex (PHC) and hippocampus (HC) may be selectively engaged during scene processing. However, emerging evidence from both animal and human studies suggest that the PRC is sensitive to spatial configural information as well as object information. In this fMRI study, we observed preliminary evidence for BOLD activation in the PRC during a complex visual discrimination task for objects and scenes, as well as robust activation for both stimulus types in PHC and HC. The results are discussed in light of a recent process-based model of medial temporal lobe functioning.
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Affiliation(s)
- Ashley V Lawrence
- Department of Psychology, University of Arizona, Tucson, Arizona, USA
| | - Jose Cardoza
- Department of Psychology, University of Arizona, Tucson, Arizona, USA
| | - Lee Ryan
- Department of Psychology, University of Arizona, Tucson, Arizona, USA.,Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, Arizona, USA
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20
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Xia X, Fan L, Hou B, Zhang B, Zhang D, Cheng C, Deng H, Dong Y, Zhao X, Li H, Jiang T. Fine-Grained Parcellation of the Macaque Nucleus Accumbens by High-Resolution Diffusion Tensor Tractography. Front Neurosci 2019; 13:709. [PMID: 31354418 PMCID: PMC6635473 DOI: 10.3389/fnins.2019.00709] [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: 03/19/2019] [Accepted: 06/24/2019] [Indexed: 11/13/2022] Open
Abstract
Limited in part by the spatial resolution of typical in vivo magnetic resonance imaging (MRI) data, recent neuroimaging studies have only identified a connectivity-based shell-core-like partitioning of the nucleus accumbens (Acb) in humans. This has hindered the process of making a more refined description of the Acb using non-invasive neuroimaging technologies and approaches. In this study, high-resolution ex vivo macaque brain diffusion MRI data were acquired to investigate the tractography-based parcellation of the Acb. Our results identified a shell-core-like partitioning in macaques that is similar to that in humans as well as an alternative solution that subdivided the Acb into four parcels, the medial shell, the lateral shell, the ventral core, and the dorsal core. Furthermore, we characterized the specific anatomical and functional connectivity profiles of these Acb subregions and generalized their specialized functions to establish a fine-grained macaque Acb brainnetome atlas. This atlas should be helpful in neuroimaging, stereotactic surgery, and comparative neuroimaging studies to reveal the neurophysiological substrates of various diseases and cognitive functions associated with the Acb.
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Affiliation(s)
- Xiaoluan Xia
- College of Information and Computer, Taiyuan University of Technology, Jinzhong, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Bing Hou
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Baogui Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Dan Zhang
- Core Facility, Center of Biomedical Analysis, Tsinghua University, Beijing, China
| | - Chen Cheng
- College of Information and Computer, Taiyuan University of Technology, Jinzhong, China.,Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Hongxia Deng
- College of Information and Computer, Taiyuan University of Technology, Jinzhong, China
| | - Yunyun Dong
- College of Information and Computer, Taiyuan University of Technology, Jinzhong, China
| | - Xudong Zhao
- State Key Laboratory of Brain and Cognitive Sciences, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
| | - Haifang Li
- College of Information and Computer, Taiyuan University of Technology, Jinzhong, China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
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21
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Xia X, Fan L, Cheng C, Yao R, Deng H, Zhao D, Li H, Jiang T. Interspecies Differences in the Connectivity of Ventral Striatal Components Between Humans and Macaques. Front Neurosci 2019; 13:623. [PMID: 31258468 PMCID: PMC6587664 DOI: 10.3389/fnins.2019.00623] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 05/29/2019] [Indexed: 12/21/2022] Open
Abstract
Although the evolutionarily conserved functions of the ventral striatal components have been used as a priori knowledge for further study, whether these functions are conserved between species remains unclear. In particular, whether macroscopic connectivity supports this given the disproportionate volumetric differences between species in the brain regions that project to the ventral striatum, including the prefrontal and limbic areas, has not been established In this study, the human and macaque striatum was first tractographically parcellated to define the ventral striatum and its two subregions, the nucleus accumbens (Acb)-like and the neurochemically unique domains of the Acb and putamen (NUDAPs)-like divisions. Our results revealed a similar topographical distribution of the connectivity-based ventral striatal components in the two primate brains. Successively, a set of targets was extracted to construct a connectivity fingerprint to characterize these parcellation results, enabling cross-species comparisons. Our results indicated that the connectivity fingerprints of the ventral striatum-like divisions were dissimilar in the two species. We localized this difference to specific targets to analyze possible interspecies functional modifications. Our results also revealed interspecies-convergent connectivity ratio fingerprints of the target group to these two ventral striatum-like subregions. This convergence may suggest synchronous connectional changes of these ventral striatal components during primate evolution.
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Affiliation(s)
- Xiaoluan Xia
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chen Cheng
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Rong Yao
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - HongXia Deng
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Dongqin Zhao
- Experimental Teaching Center, Shanxi University of Finance and Economics, Taiyuan, China
| | - Haifang Li
- College of Information and Computer, Taiyuan University of Technology, Taiyuan, China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
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22
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Fritz HJ, Ray N, Dyrba M, Sorg C, Teipel S, Grothe MJ. The corticotopic organization of the human basal forebrain as revealed by regionally selective functional connectivity profiles. Hum Brain Mapp 2019; 40:868-878. [PMID: 30311315 PMCID: PMC6865372 DOI: 10.1002/hbm.24417] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Revised: 08/06/2018] [Accepted: 10/01/2018] [Indexed: 12/25/2022] Open
Abstract
The cholinergic basal forebrain (CBF), comprising different groups of cortically projecting cholinergic neurons, plays a crucial role in higher cognitive processes and has been implicated in diverse neuropsychiatric disorders. A distinct corticotopic organization of CBF projections has been revealed in animal studies, but little is known about their organization in the human brain. We explored regional differences in functional connectivity (FC) profiles within the human CBF by applying a clustering approach to resting-state functional magnetic resonance imaging (rs-fMRI) data of healthy adult individuals (N = 85; 19-85 years). We further examined effects of age on FC of the identified CBF clusters and assessed the reproducibility of cluster-specific FC profiles in independent data from healthy older individuals (N = 25; 65-89 years). Results showed that the human CBF is functionally organized into distinct anterior-medial and posterior-lateral subdivisions that largely follow anatomically defined boundaries of the medial septum/diagonal band and nucleus basalis Meynert. The anterior-medial CBF subdivision was characterized by connectivity with the hippocampus and interconnected nodes of an extended medial cortical memory network, whereas the posterior-lateral subdivision was specifically connected to anterior insula and dorsal anterior cingulate components of a salience/attention network. FC of both CBF subdivisions declined with increasing age, but the overall topography of subregion-specific FC profiles was reproduced in independent rs-fMRI data of healthy older individuals acquired in a typical clinical setting. Rs-fMRI-based assessments of subregion-specific CBF function may complement established volumetric approaches for the in vivo study of CBF involvement in neuropsychiatric disorders.
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Affiliation(s)
- Hans‐Christian J. Fritz
- Clinical Dementia Research SectionGerman Center for Neurodegenerative Diseases (DZNE)RostockGermany
- Department of Psychosomatic and Psychotherapeutic MedicineRostock University Medical CenterRostockGermany
| | - Nicola Ray
- Department of PsychologyManchester Metropolitan UniversityManchesterUK
| | - Martin Dyrba
- Clinical Dementia Research SectionGerman Center for Neurodegenerative Diseases (DZNE)RostockGermany
| | - Christian Sorg
- Departments of Neuroradiology and Psychiatry, TUM‐Neuroimaging Center of Klinikum rechts der IsarTechnische Universität München TUMMunichGermany
| | - Stefan Teipel
- Clinical Dementia Research SectionGerman Center for Neurodegenerative Diseases (DZNE)RostockGermany
- Department of Psychosomatic and Psychotherapeutic MedicineRostock University Medical CenterRostockGermany
| | - Michel J. Grothe
- Clinical Dementia Research SectionGerman Center for Neurodegenerative Diseases (DZNE)RostockGermany
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23
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Reagh ZM, Ranganath C. What does the functional organization of cortico-hippocampal networks tell us about the functional organization of memory? Neurosci Lett 2018; 680:69-76. [PMID: 29704572 PMCID: PMC6467646 DOI: 10.1016/j.neulet.2018.04.050] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2017] [Revised: 04/23/2018] [Accepted: 04/24/2018] [Indexed: 12/12/2022]
Abstract
Historically, research on the cognitive processes that support human memory proceeded, to a large extent, independently of research on the neural basis of memory. Accumulating evidence from neuroimaging, however, has enabled the field to develop a broader and more integrative perspective. Here, we briefly outline how advances in cognitive neuroscience can potentially shed light on concepts and controversies in human memory research. We argue that research on the functional properties of cortico-hippocampal networks informs us about how memories might be organized in the brain, which, in turn, helps to reconcile seemingly disparate perspectives in cognitive psychology. Finally, we discuss several open questions and directions for future research.
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Affiliation(s)
- Zachariah M Reagh
- Center for Neuroscience, United States; Department of Neurology, University of California, Davis, United States.
| | - Charan Ranganath
- Center for Neuroscience, United States; Memory and Plasticity (MAP) Program, United States; Department of Psychology, University of California, Davis, United States.
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24
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Burke SN, Gaynor LS, Barnes CA, Bauer RM, Bizon JL, Roberson ED, Ryan L. Shared Functions of Perirhinal and Parahippocampal Cortices: Implications for Cognitive Aging. Trends Neurosci 2018; 41:349-359. [PMID: 29555181 PMCID: PMC5970964 DOI: 10.1016/j.tins.2018.03.001] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2017] [Revised: 02/16/2018] [Accepted: 03/01/2018] [Indexed: 01/13/2023]
Abstract
A predominant view of perirhinal cortex (PRC) and postrhinal/parahippocampal cortex (POR/PHC) function contends that these structures are tuned to represent objects and spatial information, respectively. However, known anatomical connectivity, together with recent electrophysiological, neuroimaging, and lesion data, indicate that both brain areas participate in spatial and nonspatial processing. Instead of content-based organization, the PRC and PHC/POR may participate in two computationally distinct cortical-hippocampal networks: one network that is tuned to process coarse information quickly, forming gist-like representations of scenes/environments, and a second network tuned to process information about the specific sensory details that are necessary for discrimination across sensory modalities. The available data suggest that the latter network may be more vulnerable in advanced age.
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Affiliation(s)
- Sara N Burke
- McKnight Brain Institute, Department of Neuroscience, University of Florida, Gainesville, FL, USA; Institute on Aging, University of Florida, Gainesville, FL, USA.
| | - Leslie S Gaynor
- McKnight Brain Institute, Department of Neuroscience, 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
| | - Carol A Barnes
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA; Division of Neural Systems Memory and Aging, University of Arizona, Tucson, AZ, USA; Department of Psychology, University of Arizona, Tucson, AZ, USA; Department of Neurology and Neuroscience, University of Arizona, Tucson, AZ, USA
| | - Russell M Bauer
- Department of Clinical and Health Psychology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
| | - Jennifer L Bizon
- McKnight Brain Institute, Department of Neuroscience, University of Florida, Gainesville, FL, USA
| | - Erik D Roberson
- Evelyn F. McKnight Brain Institute, Alzheimer's Disease Center, Center for Neurodegeneration and Experimental Therapeutics, Departments of Neurology and Neurobiology, University of Alabama at Birmingham, AL, USA
| | - Lee Ryan
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ, USA; Department of Psychology, University of Arizona, Tucson, AZ, USA.
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25
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Martin CB, Douglas D, Newsome RN, Man LLY, Barense MD. Integrative and distinctive coding of visual and conceptual object features in the ventral visual stream. eLife 2018; 7:e31873. [PMID: 29393853 PMCID: PMC5832413 DOI: 10.7554/elife.31873] [Citation(s) in RCA: 104] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2017] [Accepted: 02/01/2018] [Indexed: 12/12/2022] Open
Abstract
A significant body of research in cognitive neuroscience is aimed at understanding how object concepts are represented in the human brain. However, it remains unknown whether and where the visual and abstract conceptual features that define an object concept are integrated. We addressed this issue by comparing the neural pattern similarities among object-evoked fMRI responses with behavior-based models that independently captured the visual and conceptual similarities among these stimuli. Our results revealed evidence for distinctive coding of visual features in lateral occipital cortex, and conceptual features in the temporal pole and parahippocampal cortex. By contrast, we found evidence for integrative coding of visual and conceptual object features in perirhinal cortex. The neuroanatomical specificity of this effect was highlighted by results from a searchlight analysis. Taken together, our findings suggest that perirhinal cortex uniquely supports the representation of fully specified object concepts through the integration of their visual and conceptual features.
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Affiliation(s)
- Chris B Martin
- Department of PsychologyUniversity of TorontoTorontoCanada
| | | | | | - Louisa LY Man
- Department of PsychologyQueen's UniversityKingstonCanada
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26
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How landmark suitability shapes recognition memory signals for objects in the medial temporal lobes. Neuroimage 2017; 166:425-436. [PMID: 29108942 DOI: 10.1016/j.neuroimage.2017.11.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2017] [Revised: 10/31/2017] [Accepted: 11/01/2017] [Indexed: 11/20/2022] Open
Abstract
A role of perirhinal cortex (PrC) in recognition memory for objects has been well established. Contributions of parahippocampal cortex (PhC) to this function, while documented, remain less well understood. Here, we used fMRI to examine whether the organization of item-based recognition memory signals across these two structures is shaped by object category, independent of any difference in representing episodic context. Guided by research suggesting that PhC plays a critical role in processing landmarks, we focused on three categories of objects that differ from each other in their landmark suitability as confirmed with behavioral ratings (buildings > trees > aircraft). Participants made item-based recognition-memory decisions for novel and previously studied objects from these categories, which were matched in accuracy. Multi-voxel pattern classification revealed category-specific item-recognition memory signals along the long axis of PrC and PhC, with no sharp functional boundaries between these structures. Memory signals for buildings were observed in the mid to posterior extent of PhC, signals for trees in anterior to posterior segments of PhC, and signals for aircraft in mid to posterior aspects of PrC and the anterior extent of PhC. Notably, item-based memory signals for the category with highest landmark suitability ratings were observed only in those posterior segments of PhC that also allowed for classification of landmark suitability of objects when memory status was held constant. These findings provide new evidence in support of the notion that item-based memory signals for objects are not limited to PrC, and that the organization of these signals along the longitudinal axis that crosses PrC and PhC can be captured with reference to landmark suitability.
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27
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Li H, Fan L, Zhuo J, Wang J, Zhang Y, Yang Z, Jiang T. ATPP: A Pipeline for Automatic Tractography-Based Brain Parcellation. Front Neuroinform 2017; 11:35. [PMID: 28611620 PMCID: PMC5447055 DOI: 10.3389/fninf.2017.00035] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2017] [Accepted: 05/15/2017] [Indexed: 12/18/2022] Open
Abstract
There is a longstanding effort to parcellate brain into areas based on micro-structural, macro-structural, or connectional features, forming various brain atlases. Among them, connectivity-based parcellation gains much emphasis, especially with the considerable progress of multimodal magnetic resonance imaging in the past two decades. The Brainnetome Atlas published recently is such an atlas that follows the framework of connectivity-based parcellation. However, in the construction of the atlas, the deluge of high resolution multimodal MRI data and time-consuming computation poses challenges and there is still short of publically available tools dedicated to parcellation. In this paper, we present an integrated open source pipeline (https://www.nitrc.org/projects/atpp), named Automatic Tractography-based Parcellation Pipeline (ATPP) to realize the framework of parcellation with automatic processing and massive parallel computing. ATPP is developed to have a powerful and flexible command line version, taking multiple regions of interest as input, as well as a user-friendly graphical user interface version for parcellating single region of interest. We demonstrate the two versions by parcellating two brain regions, left precentral gyrus and middle frontal gyrus, on two independent datasets. In addition, ATPP has been successfully utilized and fully validated in a variety of brain regions and the human Brainnetome Atlas, showing the capacity to greatly facilitate brain parcellation.
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Affiliation(s)
- Hai Li
- Brainnetome Center, Institute of Automation, Chinese Academy of SciencesBeijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of SciencesBeijing, China.,University of Chinese Academy of SciencesBeijing, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of SciencesBeijing, China.,University of Chinese Academy of SciencesBeijing, China
| | - Junjie Zhuo
- Brainnetome Center, Institute of Automation, Chinese Academy of SciencesBeijing, China
| | - Jiaojian Wang
- Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China
| | - Yu Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of SciencesBeijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of SciencesBeijing, China
| | - Zhengyi Yang
- Brainnetome Center, Institute of Automation, Chinese Academy of SciencesBeijing, China
| | - Tianzi Jiang
- Brainnetome Center, Institute of Automation, Chinese Academy of SciencesBeijing, China.,National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of SciencesBeijing, China.,University of Chinese Academy of SciencesBeijing, China.,Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of ChinaChengdu, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of SciencesBeijing, China.,Queensland Brain Institute, The University of QueenslandBrisbane, QLD, Australia
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28
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Bejanin A, Desgranges B, La Joie R, Landeau B, Perrotin A, Mézenge F, Belliard S, de La Sayette V, Eustache F, Chételat G. Distinct white matter injury associated with medial temporal lobe atrophy in Alzheimer's versus semantic dementia. Hum Brain Mapp 2017; 38:1791-1800. [PMID: 27981671 PMCID: PMC6866822 DOI: 10.1002/hbm.23482] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Revised: 11/15/2016] [Accepted: 11/21/2016] [Indexed: 01/31/2023] Open
Abstract
This study aims at further understanding the distinct vulnerability of brain networks in Alzheimer's disease (AD) versus semantic dementia (SD) investigating the white matter injury associated with medial temporal lobe (MTL) atrophy in both conditions. Twenty-six AD patients, twenty-one SD patients, and thirty-nine controls underwent a high-resolution T1-MRI scan allowing to obtain maps of grey matter volume and white matter density. A statistical conjunction approach was used to identify MTL regions showing grey matter atrophy in both patient groups. The relationship between this common grey matter atrophy and white matter density maps was then assessed within each patient group. Patterns of grey matter atrophy were distinct in AD and SD but included a common region in the MTL, encompassing the hippocampus and amygdala. This common atrophy was associated with alterations in different white matter areas in AD versus SD, mainly including the cingulum and corpus callosum in AD, while restricted to the temporal lobe - essentially the uncinate and inferior longitudinal fasciculi - in SD. Complementary analyses revealed that these relationships remained significant when controlling for global atrophy or disease severity. Overall, this study provides the first evidence that atrophy of the same MTL region is related to damage in distinct white matter fibers in AD and SD. These different patterns emphasize the vulnerability of distinct brain networks related to the MTL in these two disorders, which might underlie the discrepancy in their symptoms. These results further suggest differences between AD and SD in the neuropathological processes occurring in the MTL. Hum Brain Mapp 38:1791-1800, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Alexandre Bejanin
- U1077, InsermCaenFrance
- UMR‐S1077, Université de Caen ‐ NormandieCaenFrance
- UMR‐S1077, Ecole Pratique des Hautes EtudesCaenFrance
- U1077, CHU de CaenCaenFrance
| | - Béatrice Desgranges
- U1077, InsermCaenFrance
- UMR‐S1077, Université de Caen ‐ NormandieCaenFrance
- UMR‐S1077, Ecole Pratique des Hautes EtudesCaenFrance
- U1077, CHU de CaenCaenFrance
| | - Renaud La Joie
- U1077, InsermCaenFrance
- UMR‐S1077, Université de Caen ‐ NormandieCaenFrance
- UMR‐S1077, Ecole Pratique des Hautes EtudesCaenFrance
- U1077, CHU de CaenCaenFrance
| | - Brigitte Landeau
- U1077, InsermCaenFrance
- UMR‐S1077, Université de Caen ‐ NormandieCaenFrance
- UMR‐S1077, Ecole Pratique des Hautes EtudesCaenFrance
- U1077, CHU de CaenCaenFrance
| | - Audrey Perrotin
- U1077, InsermCaenFrance
- UMR‐S1077, Université de Caen ‐ NormandieCaenFrance
- UMR‐S1077, Ecole Pratique des Hautes EtudesCaenFrance
- U1077, CHU de CaenCaenFrance
| | - Florence Mézenge
- U1077, InsermCaenFrance
- UMR‐S1077, Université de Caen ‐ NormandieCaenFrance
- UMR‐S1077, Ecole Pratique des Hautes EtudesCaenFrance
- U1077, CHU de CaenCaenFrance
| | - Serge Belliard
- U1077, InsermCaenFrance
- UMR‐S1077, Université de Caen ‐ NormandieCaenFrance
- UMR‐S1077, Ecole Pratique des Hautes EtudesCaenFrance
- Service de NeurologieCHU PontchaillouRennesFrance
| | - Vincent de La Sayette
- U1077, InsermCaenFrance
- UMR‐S1077, Université de Caen ‐ NormandieCaenFrance
- UMR‐S1077, Ecole Pratique des Hautes EtudesCaenFrance
- U1077, CHU de CaenCaenFrance
- Service de NeurologieCHU de CaenCaenFrance
| | - Francis Eustache
- U1077, InsermCaenFrance
- UMR‐S1077, Université de Caen ‐ NormandieCaenFrance
- UMR‐S1077, Ecole Pratique des Hautes EtudesCaenFrance
- U1077, CHU de CaenCaenFrance
| | - Gaël Chételat
- U1077, InsermCaenFrance
- UMR‐S1077, Université de Caen ‐ NormandieCaenFrance
- UMR‐S1077, Ecole Pratique des Hautes EtudesCaenFrance
- U1077, CHU de CaenCaenFrance
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29
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Kafkas A, Migo EM, Morris RG, Kopelman MD, Montaldi D, Mayes AR. Material Specificity Drives Medial Temporal Lobe Familiarity But Not Hippocampal Recollection. Hippocampus 2016; 27:194-209. [PMID: 27859925 PMCID: PMC5299537 DOI: 10.1002/hipo.22683] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/07/2016] [Indexed: 12/04/2022]
Abstract
The specific role of the perirhinal (PRC), entorhinal (ERC) and parahippocampal cortices (PHC) in supporting familiarity‐based recognition remains unknown. An fMRI study explored whether these medial temporal lobe (MTL) structures responded in the same way or differentially to familiarity as a function of stimulus type at recognition. A secondary aim was to explore whether the hippocampus responds in the same way to equally strong familiarity and recollection and whether this is influenced by the kind of stimulus involved. Univariate and multivariate analyses revealed that familiarity responses in the PRC, ERC, PHC and the amygdala are material‐specific. Specifically, the PRC and ERC selectively responded to object familiarity, while the PHC responded to both object and scene familiarity. The amygdala only responded to familiarity memory for faces. The hippocampus did not respond to stimulus familiarity for any of the three types of stimuli, but it did respond to recollection for all three types of stimuli. This was true even when recollection was contrasted to equally accurate familiarity. Overall, the findings suggest that the role of the MTL neocortices and the amygdala in familiarity‐based recognition depends on the kind of stimulus in memory, whereas the role of the hippocampus in recollection is independent of the type of cuing stimulus. © 2016 The Authors Hippocampus Published by Wiley Periodicals, Inc.
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Affiliation(s)
- Alex Kafkas
- Memory Research Unit, School of Biological Sciences, Division of Neuroscience & Experimental Psychology, University of Manchester, United Kingdom
| | - Ellen M Migo
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Robin G Morris
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Michael D Kopelman
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Daniela Montaldi
- Memory Research Unit, School of Biological Sciences, Division of Neuroscience & Experimental Psychology, University of Manchester, United Kingdom
| | - Andrew R Mayes
- Memory Research Unit, School of Biological Sciences, Division of Neuroscience & Experimental Psychology, University of Manchester, United Kingdom
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Fan L, Li H, Zhuo J, Zhang Y, Wang J, Chen L, Yang Z, Chu C, Xie S, Laird AR, Fox PT, Eickhoff SB, Yu C, Jiang T. The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture. Cereb Cortex 2016; 26:3508-26. [PMID: 27230218 PMCID: PMC4961028 DOI: 10.1093/cercor/bhw157] [Citation(s) in RCA: 1573] [Impact Index Per Article: 196.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
The human brain atlases that allow correlating brain anatomy with psychological and cognitive functions are in transition from ex vivo histology-based printed atlases to digital brain maps providing multimodal in vivo information. Many current human brain atlases cover only specific structures, lack fine-grained parcellations, and fail to provide functionally important connectivity information. Using noninvasive multimodal neuroimaging techniques, we designed a connectivity-based parcellation framework that identifies the subdivisions of the entire human brain, revealing the in vivo connectivity architecture. The resulting human Brainnetome Atlas, with 210 cortical and 36 subcortical subregions, provides a fine-grained, cross-validated atlas and contains information on both anatomical and functional connections. Additionally, we further mapped the delineated structures to mental processes by reference to the BrainMap database. It thus provides an objective and stable starting point from which to explore the complex relationships between structure, connectivity, and function, and eventually improves understanding of how the human brain works. The human Brainnetome Atlas will be made freely available for download at http://atlas.brainnetome.org, so that whole brain parcellations, connections, and functional data will be readily available for researchers to use in their investigations into healthy and pathological states.
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Affiliation(s)
| | - Hai Li
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Junjie Zhuo
- Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Yu Zhang
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Jiaojian Wang
- Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Liangfu Chen
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Zhengyi Yang
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Congying Chu
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Sangma Xie
- Brainnetome Center National Laboratory of Pattern Recognition and
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center, San Antonio, TX, USA
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-1), Research Centre Juelich, Juelich 52425, Germany Institute for Clinical Neuroscience and Medical Psychology, Heinrich-Heine-University Düsseldorf, Düsseldorf 40225, Germany
| | - Chunshui Yu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Tianzi Jiang
- Brainnetome Center National Laboratory of Pattern Recognition and CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China Key Laboratory for NeuroInformation of the Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China The Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
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Fan L, Li H, Yu S, Jiang T. Human Brainnetome Atlas and Its Potential Applications in Brain-Inspired Computing. LECTURE NOTES IN COMPUTER SCIENCE 2016. [DOI: 10.1007/978-3-319-50862-7_1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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32
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A. Moss R. A Theory on the Singular Function of the Hippocampus: Facilitating the Binding of New Circuits of Cortical Columns. AIMS Neurosci 2016. [DOI: 10.3934/neuroscience.2016.3.264] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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