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Ravikumar S, Denning AE, Lim S, Chung E, Sadeghpour N, Ittyerah R, Wisse LEM, Das SR, Xie L, Robinson JL, Schuck T, Lee EB, Detre JA, Tisdall MD, Prabhakaran K, Mizsei G, de Onzono Martin MMI, Arroyo Jiménez MDM, Mũnoz M, Marcos Rabal MDP, Cebada Sánchez S, Delgado González JC, de la Rosa Prieto C, Irwin DJ, Wolk DA, Insausti R, Yushkevich PA. Postmortem imaging reveals patterns of medial temporal lobe vulnerability to tau pathology in Alzheimer's disease. Nat Commun 2024; 15:4803. [PMID: 38839876 PMCID: PMC11153494 DOI: 10.1038/s41467-024-49205-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 05/28/2024] [Indexed: 06/07/2024] Open
Abstract
Our current understanding of the spread and neurodegenerative effects of tau neurofibrillary tangles (NFTs) within the medial temporal lobe (MTL) during the early stages of Alzheimer's Disease (AD) is limited by the presence of confounding non-AD pathologies and the two-dimensional (2-D) nature of conventional histology studies. Here, we combine ex vivo MRI and serial histological imaging from 25 human MTL specimens to present a detailed, 3-D characterization of quantitative NFT burden measures in the space of a high-resolution, ex vivo atlas with cytoarchitecturally-defined subregion labels, that can be used to inform future in vivo neuroimaging studies. Average maps show a clear anterior to poster gradient in NFT distribution and a precise, spatial pattern with highest levels of NFTs found not just within the transentorhinal region but also the cornu ammonis (CA1) subfield. Additionally, we identify granular MTL regions where measures of neurodegeneration are likely to be linked to NFTs specifically, and thus potentially more sensitive as early AD biomarkers.
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Affiliation(s)
- Sadhana Ravikumar
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
| | - Amanda E Denning
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Sydney Lim
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Eunice Chung
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Ranjit Ittyerah
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura E M Wisse
- Institute for Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Sandhitsu R Das
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Long Xie
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - John L Robinson
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Theresa Schuck
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - John A Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - M Dylan Tisdall
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Gabor Mizsei
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Monica Mũnoz
- Human Neuroanatomy Laboratory, University of Castilla La Mancha, Albacete, Spain
| | | | | | | | | | - David J Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ricardo Insausti
- Human Neuroanatomy Laboratory, University of Castilla La Mancha, Albacete, Spain
| | - Paul A Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
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Debiasi G, Mazzonetto I, Bertoldo A. The effect of processing pipelines, input images and age on automatic cortical morphology estimates. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 242:107825. [PMID: 37806120 DOI: 10.1016/j.cmpb.2023.107825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Revised: 09/01/2023] [Accepted: 09/20/2023] [Indexed: 10/10/2023]
Abstract
BACKGROUND AND OBJECTIVE Magnetic resonance imaging of the brain allows to enrich the study of the relationship between cortical morphology, healthy ageing, diseases and cognition. Since manual segmentation of the cerebral cortex is time consuming and subjective, many software packages have been developed. FreeSurfer (FS) and Advanced Normalization Tools (ANTs) are the most used and allow as inputs a T1-weighted (T1w) image or its combination with a T2-weighted (T2w) image. In this study we evaluated the impact of different software and input images on cortical estimates. Additionally, we investigated whether the variation of the results depending on software and inputs is also influenced by age. METHODS For 240 healthy subjects, cortical thickness was computed with ANTs and FreeSurfer. Estimates were derived using both the T1w image and adding the T2w image. Significant effects due to software, input images and age range were investigated with ANOVA statistical analysis. Moreover, the accuracy of the cortical thickness estimates was assessed based on their age-prediction precision. RESULTS Using FreeSurfer and ANTs with T1w or T1w-T2w images resulted in significant differences in the cortical thickness estimates. These differences change with the age range of the subjects. Regardless of the images used, the more recent FS version tested exhibited the best performances in terms of age prediction. CONCLUSIONS Our study points out the importance of i) consistently processing data using the same tool; ii) considering the software, input images and the age range of the subjects when comparing multiple studies.
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Affiliation(s)
- Giulia Debiasi
- Department of Information Engineering, University of Padova, via Gradenigo 6/b, Padova 35131, Italy
| | - Ilaria Mazzonetto
- Department of Information Engineering, University of Padova, via Gradenigo 6/b, Padova 35131, Italy
| | - Alessandra Bertoldo
- Department of Information Engineering, University of Padova, via Gradenigo 6/b, Padova 35131, Italy; Padova Neuroscience Center (PNC), University of Padova, via Orus 2/b, Padova 35131, Italy.
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3
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Zheng Y, Li T, Xie T, Zhang Y, Liu Y, Zeng X, Wang Z, Wang L, Li H, Xie Y, Lv X, Wang J, Yu X, Wang H. Characteristics and Potential Neural Substrates of Encoding and Retrieval During Memory Binding in Amnestic Mild Cognitive Impairment. J Alzheimers Dis 2023; 94:1405-1415. [PMID: 37424465 DOI: 10.3233/jad-230154] [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] [Indexed: 07/11/2023]
Abstract
BACKGROUND Whether encoding or retrieval failure contributes to memory binding deficit in amnestic mild cognitive impairment (aMCI) has not been elucidated. Also, the potential brain structural substrates of memory binding remained undiscovered. OBJECTIVE To investigate the characteristics and brain atrophy pattern of encoding and retrieval performance during memory binding in aMCI. METHODS Forty-three individuals with aMCI and 37 cognitively normal controls were recruited. The Memory Binding Test (MBT) was used to measure memory binding performance. The immediate and delayed memory binding indices were computed by using the free and cued paired recall scores. Partial correlation analysis was performed to map the relationship between regional gray matter volume and memory binding performance. RESULTS The memory binding performance in the learning and retrieval phases was worse in the aMCI group than in the control group (F = 22.33 to 52.16, all p < 0.001). The immediate and delayed memory binding index in the aMCI group was lower than that in the control group (p < 0.05). The gray matter volume of the left inferior temporal gyrus was positively correlated with memory binding test scores (r = 0.49 to 0.61, p < 0.05) as well as the immediate (r = 0.39, p < 0.05) and delayed memory binding index (r = 0.42, p < 0.05) in the aMCI group. CONCLUSION aMCI may be primarily characterized by a deficit in encoding phase during the controlled learning process. Volumetric losses in the left inferior temporal gyrus may contribute to encoding failure.
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Affiliation(s)
- Yaonan Zheng
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
| | - Tao Li
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
| | - Teng Xie
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
| | - Ying Zhang
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
- Beijing Anding Hospital, Capital Medical University, Beijing, China
| | - Ying Liu
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Xiangzhu Zeng
- Department of Radiology, Peking University Third Hospital, Beijing, China
| | - Zhijiang Wang
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
| | - Luchun Wang
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
| | - Huizi Li
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
| | - Yuhan Xie
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
| | - Xiaozhen Lv
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
| | - Jing Wang
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
| | - Xin Yu
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
| | - Huali Wang
- Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China
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Rechberger S, Li Y, Kopetzky SJ, Butz-Ostendorf M. Automated High-Definition MRI Processing Routine Robustly Detects Longitudinal Morphometry Changes in Alzheimer's Disease Patients. Front Aging Neurosci 2022; 14:832828. [PMID: 35747446 PMCID: PMC9211026 DOI: 10.3389/fnagi.2022.832828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 05/06/2022] [Indexed: 11/21/2022] Open
Abstract
Longitudinal MRI studies are of increasing importance to document the time course of neurodegenerative diseases as well as neuroprotective effects of a drug candidate in clinical trials. However, manual longitudinal image assessments are time consuming and conventional assessment routines often deliver unsatisfying study outcomes. Here, we propose a profound analysis pipeline that consists of the following coordinated steps: (1) an automated and highly precise image processing stream including voxel and surface based morphometry using latest highly detailed brain atlases such as the HCP MMP 1.0 atlas with 360 cortical ROIs; (2) a profound statistical assessment using a multiplicative model of annual percent change (APC); and (3) a multiple testing correction adopted from genome-wide association studies that is optimally suited for longitudinal neuroimaging studies. We tested this analysis pipeline with 25 Alzheimer's disease patients against 25 age-matched cognitively normal subjects with a baseline and a 1-year follow-up conventional MRI scan from the ADNI-3 study. Even in this small cohort, we were able to report 22 significant measurements after multiple testing correction from SBM (including cortical volume, area and thickness) complementing only three statistically significant volume changes (left/right hippocampus and left amygdala) found by VBM. A 1-year decrease in brain morphometry coincided with an increasing clinical disability and cognitive decline in patients measured by MMSE, CDR GLOBAL, FAQ TOTAL and NPI TOTAL scores. This work shows that highly precise image assessments, APC computation and an adequate multiple testing correction can produce a significant study outcome even for small study sizes. With this, automated MRI processing is now available and reliable for routine use and clinical trials.
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Affiliation(s)
| | - Yong Li
- Biomax Informatics, Munich, Germany
| | - Sebastian J. Kopetzky
- Biomax Informatics, Munich, Germany
- School of Life Sciences, Technical University of Munich, Freising, Germany
| | - Markus Butz-Ostendorf
- Biomax Informatics, Munich, Germany
- Parallel Programming, Department of Computer Science, Technical University of Darmstadt, Darmstadt, Germany
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5
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Yushkevich PA, Muñoz López M, Iñiguez de Onzoño Martin M, Ittyerah R, Lim S, Ravikumar S, Bedard ML, Pickup S, Liu W, Wang J, Hung LY, Lasserve J, Vergnet N, Xie L, Dong M, Cui S, McCollum L, Robinson JL, Schuck T, de Flores R, Grossman M, Tisdall MD, Prabhakaran K, Mizsei G, Das SR, Artacho-Pérula E, Arroyo Jiménez MDM, Marcos Raba MP, Molina Romero FJ, Cebada Sánchez S, Delgado González JC, de la Rosa-Prieto C, Córcoles Parada M, Lee EB, Trojanowski JQ, Ohm DT, Wisse LEM, Wolk DA, Irwin DJ, Insausti R. Three-dimensional mapping of neurofibrillary tangle burden in the human medial temporal lobe. Brain 2021; 144:2784-2797. [PMID: 34259858 PMCID: PMC8783607 DOI: 10.1093/brain/awab262] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 05/19/2021] [Accepted: 06/21/2021] [Indexed: 11/14/2022] Open
Abstract
Tau protein neurofibrillary tangles are closely linked to neuronal/synaptic loss and cognitive decline in Alzheimer's disease and related dementias. Our knowledge of the pattern of neurofibrillary tangle progression in the human brain, critical to the development of imaging biomarkers and interpretation of in vivo imaging studies in Alzheimer's disease, is based on conventional two-dimensional histology studies that only sample the brain sparsely. To address this limitation, ex vivo MRI and dense serial histological imaging in 18 human medial temporal lobe specimens (age 75.3 ± 11.4 years, range 45 to 93) were used to construct three-dimensional quantitative maps of neurofibrillary tangle burden in the medial temporal lobe at individual and group levels. Group-level maps were obtained in the space of an in vivo brain template, and neurofibrillary tangles were measured in specific anatomical regions defined in this template. Three-dimensional maps of neurofibrillary tangle burden revealed significant variation along the anterior-posterior axis. While early neurofibrillary tangle pathology is thought to be confined to the transentorhinal region, we found similar levels of burden in this region and other medial temporal lobe subregions, including amygdala, temporopolar cortex, and subiculum/cornu ammonis 1 hippocampal subfields. Overall, the three-dimensional maps of neurofibrillary tangle burden presented here provide more complete information about the distribution of this neurodegenerative pathology in the region of the cortex where it first emerges in Alzheimer's disease, and may help inform the field about the patterns of pathology spread, as well as support development and validation of neuroimaging biomarkers.
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Affiliation(s)
- Paul A Yushkevich
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Mónica Muñoz López
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | | | - Ranjit Ittyerah
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Sydney Lim
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Sadhana Ravikumar
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Madigan L Bedard
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Stephen Pickup
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Weixia Liu
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Jiancong Wang
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Ling Yu Hung
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Jade Lasserve
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Nicolas Vergnet
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Long Xie
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Mengjin Dong
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Salena Cui
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - Lauren McCollum
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - John L Robinson
- Department of Pathology, University of Pennsylvania, Philadelphia, USA
| | - Theresa Schuck
- Department of Pathology, University of Pennsylvania, Philadelphia, USA
| | - Robin de Flores
- Institut National de la Santé et de la Recherche Médicale (INSERM), Caen, France
| | - Murray Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - M Dylan Tisdall
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | | | - Gabor Mizsei
- Department of Radiology, University of Pennsylvania, Philadelphia, USA
| | - Sandhitsu R Das
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - Emilio Artacho-Pérula
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | | | - Marı’a Pilar Marcos Raba
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | | | - Sandra Cebada Sánchez
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | | | - Carlos de la Rosa-Prieto
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | - Marta Córcoles Parada
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
| | - Edward B Lee
- Department of Pathology, University of Pennsylvania, Philadelphia, USA
| | | | - Daniel T Ohm
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - Laura E M Wisse
- Department of Diagnostic Radiology, University of Lund, Lund, Sweden
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - David J Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - Ricardo Insausti
- Human Neuroanatomy Laboratory, Neuromax CSIC Associated Unit, University of Castilla-La Mancha, Albacete, Spain
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6
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Manga A, Madurka P, Vakli P, Kirwan CB, Vidnyánszky Z. Investigation of the relationship between visual feature binding in short- and long-term memory in healthy aging. Learn Mem 2021; 28:109-113. [PMID: 33723030 PMCID: PMC7970738 DOI: 10.1101/lm.052548.120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 01/16/2021] [Indexed: 11/24/2022]
Abstract
Binding visual features into coherent object representations is essential both in short- and long-term memory. However, the relationship between feature binding processes at different memory delays remains unexplored. Here, we addressed this question by using the Mnemonic Similarity Task and a delayed-estimation working memory task on a large sample of older adults. The results revealed that higher propensity to misbind object features in working memory is associated with lower lure discrimination performance in the mnemonic similarity task, suggesting that shared feature binding processes underlie the formation of coherent short- and long-term visual object memory representations.
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Affiliation(s)
- Annamária Manga
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest 1117, Hungary
- Department of Cognitive Science, Budapest University of Technology and Economics, Budapest 1111, Hungary
| | - Petra Madurka
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest 1117, Hungary
| | - Pál Vakli
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest 1117, Hungary
| | - C Brock Kirwan
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo, Utah 84602, USA
| | - Zoltán Vidnyánszky
- Brain Imaging Centre, Research Centre for Natural Sciences, Budapest 1117, Hungary
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7
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Samudra N, Jacobs M, Aulino JM, Abou-Khalil B. Baseline neuropsychological characteristics in patients with epilepsy with left temporal lobe encephaloceles compared with left mesial temporal sclerosis. Epilepsy Behav 2020; 112:107397. [PMID: 32919200 DOI: 10.1016/j.yebeh.2020.107397] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Revised: 08/02/2020] [Accepted: 08/02/2020] [Indexed: 12/18/2022]
Abstract
BACKGROUND Temporal lobe encephaloceles (TE) are increasingly recognized as a cause of drug-resistant temporal lobe epilepsy. Improved recognition of these lesions offers an opportunity to treat them with a limited resection sparing the hippocampus. However, as they can be difficult to identify on imaging, additional clues pointing to the diagnosis can be helpful. We sought to understand the baseline cognitive/neuropsychological profile in patients with left temporal lobe epilepsy caused by encephaloceles compared with that caused by mesial temporal sclerosis (MTS), a common entity in the differential diagnosis. METHODS Neuropsychological testing, including language (semantic and phonemic fluency and naming), verbal memory, intelligence quotient (IQ), and executive function measures were compared across two groups (five patients with left TE and five age- and gender-matched patients with left MTS). Other clinical variables related to cognition, including patient age, electroencephalographic characteristics, epilepsy duration, and factors related to antiseizure medication dosing, were also compared between groups. RESULTS More patients with left MTS had atypical language lateralization (3/5 with right-sided language in the group with MTS compared with 0/5 in the group with TE). Patients with MTS had significantly worse scores on the Verbal Comprehension Index (VCI) subscore of the Wechsler Adult Intelligence Scale (WAIS; p = 0.026). General IQ was also worse in patients with MTS (p = 0.028). There was a trend towards worse executive function in patients with MTS as measured on Trails B (p = 0.096). Other measures related to language and verbal memory did not differ significantly between the groups nor did other relevant clinical variables, except epilepsy duration, which was significantly longer in patients with MTS (p = 0.0001). CONCLUSIONS This pilot study demonstrates few significant differences between the groups with left MTS and TE surveyed. A higher rate of atypical language lateralization was noted in patients with left MTS. The higher baseline global IQ and VCI scores in patients with left TE compared with patients with MTS may be attributable to longer duration of epilepsy in patients with left MTS. Future work with a larger sample size will focus on establishing a unique neuropsychological profile related to epilepsy due to TE.
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Affiliation(s)
- Niyatee Samudra
- Department of Neurology, Vanderbilt University Medical Center, A-0118 Medical Center North, 1161 21st Avenue South, Nashville, TN 37232, United States
| | - Monica Jacobs
- Department of Neurology, Vanderbilt University Medical Center, A-0118 Medical Center North, 1161 21st Avenue South, Nashville, TN 37232, United States
| | - Joseph M Aulino
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, United States
| | - Bassel Abou-Khalil
- Department of Neurology, Vanderbilt University Medical Center, A-0118 Medical Center North, 1161 21st Avenue South, Nashville, TN 37232, United States.
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8
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Tustison NJ, Holbrook AJ, Avants BB, Roberts JM, Cook PA, Reagh ZM, Duda JT, Stone JR, Gillen DL, Yassa MA. Longitudinal Mapping of Cortical Thickness Measurements: An Alzheimer's Disease Neuroimaging Initiative-Based Evaluation Study. J Alzheimers Dis 2020; 71:165-183. [PMID: 31356207 DOI: 10.3233/jad-190283] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Longitudinal studies of development and disease in the human brain have motivated the acquisition of large neuroimaging data sets and the concomitant development of robust methodological and statistical tools for quantifying neurostructural changes. Longitudinal-specific strategies for acquisition and processing have potentially significant benefits including more consistent estimates of intra-subject measurements while retaining predictive power. Using the first phase of the Alzheimer's Disease Neuroimaging Initiative (ADNI-1) data, comprising over 600 subjects with multiple time points from baseline to 36 months, we evaluate the utility of longitudinal FreeSurfer and Advanced Normalization Tools (ANTs) surrogate thickness values in the context of a linear mixed-effects (LME) modeling strategy. Specifically, we estimate the residual variability and between-subject variability associated with each processing stream as it is known from the statistical literature that minimizing the former while simultaneously maximizing the latter leads to greater scientific interpretability in terms of tighter confidence intervals in calculated mean trends, smaller prediction intervals, and narrower confidence intervals for determining cross-sectional effects. This strategy is evaluated over the entire cortex, as defined by the Desikan-Killiany-Tourville labeling protocol, where comparisons are made with the cross-sectional and longitudinal FreeSurfer processing streams. Subsequent linear mixed effects modeling for identifying diagnostic groupings within the ADNI cohort is provided as supporting evidence for the utility of the proposed ANTs longitudinal framework which provides unbiased structural neuroimage processing and competitive to superior power for longitudinal structural change detection.
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Affiliation(s)
- Nicholas J Tustison
- Department of Radiology & Medical Imaging, University of Virginia, Charlottesville, VA, USA.,Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | | | - Brian B Avants
- Department of Radiology & Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Jared M Roberts
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Philip A Cook
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Zachariah M Reagh
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Jeffrey T Duda
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - James R Stone
- Department of Radiology & Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Daniel L Gillen
- Department of Statistics, University of California, Irvine, CA, USA
| | - Michael A Yassa
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
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9
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Maaß SC, Riemer M, Wolbers T, van Rijn H. Timing deficiencies in amnestic Mild Cognitive Impairment: Disentangling clock and memory processes. Behav Brain Res 2019; 373:112110. [DOI: 10.1016/j.bbr.2019.112110] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Revised: 06/27/2019] [Accepted: 07/20/2019] [Indexed: 12/16/2022]
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10
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Xie L, Wisse LEM, Pluta J, de Flores R, Piskin V, Manjón JV, Wang H, Das SR, Ding S, Wolk DA, Yushkevich PA. Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer's disease. Hum Brain Mapp 2019; 40:3431-3451. [PMID: 31034738 PMCID: PMC6697377 DOI: 10.1002/hbm.24607] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2019] [Accepted: 04/15/2019] [Indexed: 12/14/2022] Open
Abstract
Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology-and thus are promising biomarkers for Alzheimer's disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS-T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross-validation experiments indicated good segmentation accuracy of ASHS-T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS-T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain-behavior studies of these regions.
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Affiliation(s)
- Long Xie
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Laura E. M. Wisse
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - John Pluta
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Robin de Flores
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Virgine Piskin
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Jose V. Manjón
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA)Universidad Politécnica de ValenciaValenciaSpain
| | | | - Sandhitsu R. Das
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Song‐Lin Ding
- Allen Institute for Brain ScienceSeattleWashington
- Institute of Neuroscience, School of Basic Medical SciencesGuangzhou Medical UniversityGuangzhouPeople's Republic of China
| | - David A. Wolk
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
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Medial Temporal Lobe Atrophy is Related to Learning Strategy Changes in Amnestic Mild Cognitive Impairment. J Int Neuropsychol Soc 2019; 25:706-717. [PMID: 31023395 DOI: 10.1017/s1355617719000353] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
OBJECTIVE Deficits in the semantic learning strategy were observed in subjects with amnestic mild cognitive impairment (aMCI) in our previous study. In the present study, we explored the contributions of executive function and brain structure changes to the decline in the semantic learning strategy in aMCI. METHODS A neuropsychological battery was used to test memory and executive function in 96 aMCI subjects and 90 age- and gender-matched healthy controls (HCs). The semantic clustering ratio on the verbal learning test was calculated to evaluate learning strategy. Medial temporal lobe atrophy (MTA) and white matter hyperintensities (WMH) were measured on MRI with the MTA and Fazekas visual rating scales, respectively. RESULTS Compared to HCs, aMCI subjects had poorer performance in terms of memory, executive function, and the semantic clustering ratio (P < .001). In aMCI subjects, no significant correlation between learning strategy and executive function was observed. aMCI subjects with obvious MTA demonstrated a lower semantic clustering ratio than those without MTA (P < .001). There was no significant difference in the learning strategies between subjects with high-grade WMH and subjects with low-grade WMH. CONCLUSION aMCI subjects showed obvious impairment in the semantic learning strategy, which was attributable to MTA but independent of executive dysfunction and subcortical WMH. These findings need to be further validated in large cohorts with biomarkers identified using volumetric brain measurements. (JINS, 2019, 25, 706-717).
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Delhaye E, Mechanic-Hamilton D, Saad L, Das SR, Wisse LEM, Yushkevich PA, Wolk DA, Bastin C. Associative memory for conceptually unitized word pairs in mild cognitive impairment is related to the volume of the perirhinal cortex. Hippocampus 2019; 29:630-638. [PMID: 30588714 PMCID: PMC6565465 DOI: 10.1002/hipo.23063] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 11/23/2018] [Accepted: 11/30/2018] [Indexed: 11/06/2022]
Abstract
Unitization, that is, the encoding of an association as one integrated entity, has been shown to improve associative memory in populations presenting with associative memory deficit due to hippocampal dysfunction, such as amnesic patients with focal hippocampal lesions and healthy older adults. One reason for this benefit is that encoding of unitized associations would rely on the perirhinal cortex (PrC) and thus minimize the need for hippocampal recruitment. Mild cognitive impairment (MCI) is accompanied by a deficit in associative memory. However, unitization has never been studied to explore the potential benefit in associative memory in MCI, maybe because MCI is characterized by PrC pathology. However, the PrC may potentially still function sufficiently to allow for the successful adoption of unitization. In this study, we aimed at assessing whether unitization could attenuate MCI patients' associative memory deficit, and whether the ability to remember unitized associations would be modulated by the integrity of the PrC in MCI patients. Unitization was manipulated at a conceptual level, by encouraging participants to encode unrelated word pairs as new compound words. Participants also underwent a structural MRI exam, and measures of PrC were extracted (Brodmann Areas [BA] 35 and 36). Results showed that, contrary to healthy controls, MCI patients did not benefit from unitization. Moreover, their memory performance for unitized associations was related to the measure of PrC integrity (BA35), while it was not the case in controls. This finding thus suggests that unitization does not help to attenuate the associative deficit in MCI patients, and brings support to the literature linking unitization to the PrC function.
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Affiliation(s)
- Emma Delhaye
- GIGA-CRC In-Vivo Imaging, Liege University, Liège, Belgium
- PsyNCog, Faculty of Psychology, Liege, Belgium
| | - Dawn Mechanic-Hamilton
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Laura Saad
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sandhitsu R. Das
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Laura E. M. Wisse
- Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
- Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Christine Bastin
- GIGA-CRC In-Vivo Imaging, Liege University, Liège, Belgium
- PsyNCog, Faculty of Psychology, Liege, Belgium
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13
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Alzheimer's disease patients activate attention networks in a short-term memory task. NEUROIMAGE-CLINICAL 2019; 23:101892. [PMID: 31203170 PMCID: PMC6580312 DOI: 10.1016/j.nicl.2019.101892] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 05/28/2019] [Accepted: 06/06/2019] [Indexed: 11/24/2022]
Abstract
Network functioning during cognitive tasks is of major interest in Alzheimer's disease (AD). Cognitive functioning in AD includes variable performance in short-term memory (STM). In most studies, the verbal STM functioning in AD patients has been interpreted within the phonological loop subsystem of Baddeley's working memory model. An alternative account considers that domain-general attentional processes explain the involvement of frontoparietal networks in verbal STM beside the functioning of modality-specific subsystems. In this study, we assessed the functional integrity of the dorsal attention network (involved in task-related attention) and the ventral attention network (involved in stimulus-driven attention) by varying attentional control demands in a STM task. Thirty-five AD patients and twenty controls in the seventies performed an fMRI STM task. Variation in load (five versus two items) allowed the dorsal (DAN) and ventral attention networks (VAN) to be studied. ANOVA revealed that performance decreased with increased load in both groups. AD patients performed slightly worse than controls, but accuracy remained above 70% in all patients. Statistical analysis of fMRI brain images revealed DAN activation for high load in both groups. There was no between-group difference or common activation for low compared to high load conditions. Psychophysiological interaction showed a negative relationship between the DAN and the VAN for high versus low load conditions in patients. In conclusion, the DAN remained activated and connected to the VAN in mild AD patients who succeeded in performing an fMRI verbal STM task. DAN was necessary for the task, but not sufficient to reach normal performance. Slightly lower performance in early AD patients compared to controls might be related to maintained bottom-up attention to distractors, to decrease in executive functions, to impaired phonological processing or to reduced capacity in serial order processing. Patients with early AD succeeded in performing an fMRI short-term memory task. Dorsal attention network activation did not differ between patients and controls. Dorsal and ventral attention networks remained connected in high load task in AD. DAN was necessary for the task, but not sufficient to reach normal performance.
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14
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Liao JL, Zhang YH, Xiong ZB, Hao L, Liu GL, Ren YP, Wang Q, Duan LP, Zheng ZX, Xiong ZY, Dong J. The Association of Cognitive Impairment with Peritoneal Dialysis-Related Peritonitis. Perit Dial Int 2019; 39:229-235. [PMID: 30852523 DOI: 10.3747/pdi.2018.00180] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2018] [Accepted: 12/22/2018] [Indexed: 11/15/2022] Open
Abstract
Background:Research on the association between cognitive impairment (CI) and peritoneal dialysis (PD)-related peritonitis is limited. Therefore, we investigated whether CI contributed to the risk of PD-related peritonitis.Methods:This prospective cohort study enrolled 458 patients from 5 PD centers between 1 March 2013, and 30 November 2013, and continued until 31 May 2016. We used the Modified Mini-Mental State Examination (3MS) to assess general cognition, the Trail-Making Test to assess executive function, and subtests of the Battery for the Assessment of Neuropsychological Status to assess immediate and delayed memory, visuospatial skills, and language ability. Patients were assigned to CI and non-CI groups based on their 3MS scores. The first episode of peritonitis was the primary endpoint event. Treatment failure of peritonitis was defined as peritonitis-associated death or transfer to hemodialysis. We used competing risk models to analyze the association between CI and the risk of peritonitis. The association of CI with treatment failure after peritonitis was analyzed using logistic regression models.Results:Ninety-four first episodes of peritonitis were recorded during a median follow-up of 31.4 months, 18.1% of which led to treatment failure. No significant group differences were observed for the occurrence, distribution of pathogenic bacteria, or outcomes of first-episode peritonitis. Immediate memory dysfunction was independently associated with a higher risk of PD-related peritonitis (hazard ratio [HR] 1.736, 95% confidence interval [CI] 1.064 - 2.834, p < 0.05), adjusting for confounders.Conclusions:Immediate memory dysfunction was a significant, independent predictor of PD-related peritonitis. Neither general nor specific domains of CI predicted treatment failure of peritonitis.
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Affiliation(s)
- Jin-Lan Liao
- Renal Division, Peking University Shenzhen Hospital, Shenzhen, China
| | - Yu-Hui Zhang
- Renal Division, Department of Medicine, Peking University First Hospital; Institute of Nephrology, Peking University; Key Laboratory of Renal Disease, Ministry of Health; Key Laboratory of Renal Disease, Ministry of Education, Beijing, China
| | - Zi-Bo Xiong
- Renal Division, Peking University Shenzhen Hospital, Shenzhen, China
| | - Li Hao
- Renal Division, the Second Hospital of Anhui Medical University, Anhui, China
| | - Gui-Ling Liu
- Renal Division, the Second Hospital of Anhui Medical University, Anhui, China
| | - Ye-Ping Ren
- Renal Division, the Second Affiliated Hospital of Harbin Medical University, Heilongjiang, China
| | - Qin Wang
- Renal Division, Handan Central Hospital, Hebei, China
| | - Li-Ping Duan
- Renal Division, Handan Central Hospital, Hebei, China
| | | | - Zu-Ying Xiong
- Renal Division, Peking University Shenzhen Hospital, Shenzhen, China
| | - Jie Dong
- Renal Division, Department of Medicine, Peking University First Hospital; Institute of Nephrology, Peking University; Key Laboratory of Renal Disease, Ministry of Health; Key Laboratory of Renal Disease, Ministry of Education, Beijing, China
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15
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Tautvydaitė D, Manuel AL, Nahum L, Adam‐Darqué A, Ptak R, Schnider A. Absence of an early hippocampal encoding signal after medial temporal lesions: No consequence for the spacing effect. Hippocampus 2018; 29:587-594. [DOI: 10.1002/hipo.23053] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 10/30/2018] [Accepted: 11/03/2018] [Indexed: 11/07/2022]
Affiliation(s)
- Domilė Tautvydaitė
- Laboratory of Cognitive Neurorehabilitation, Division of Neurorehabilitation, Department of Clinical NeuroscienceUniversity Hospital of Geneva and University of Geneva Geneva Switzerland
| | - Aurélie L. Manuel
- Laboratory of Cognitive Neurorehabilitation, Division of Neurorehabilitation, Department of Clinical NeuroscienceUniversity Hospital of Geneva and University of Geneva Geneva Switzerland
| | - Louis Nahum
- Laboratory of Cognitive Neurorehabilitation, Division of Neurorehabilitation, Department of Clinical NeuroscienceUniversity Hospital of Geneva and University of Geneva Geneva Switzerland
| | - Alexandra Adam‐Darqué
- Laboratory of Cognitive Neurorehabilitation, Division of Neurorehabilitation, Department of Clinical NeuroscienceUniversity Hospital of Geneva and University of Geneva Geneva Switzerland
| | - Radek Ptak
- Laboratory of Cognitive Neurorehabilitation, Division of Neurorehabilitation, Department of Clinical NeuroscienceUniversity Hospital of Geneva and University of Geneva Geneva Switzerland
| | - Armin Schnider
- Laboratory of Cognitive Neurorehabilitation, Division of Neurorehabilitation, Department of Clinical NeuroscienceUniversity Hospital of Geneva and University of Geneva Geneva Switzerland
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16
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Fan LY, Lai YM, Chen TF, Hsu YC, Chen PY, Huang KZ, Cheng TW, Tseng WYI, Hua MS, Chen YF, Chiu MJ. Diminution of context association memory structure in subjects with subjective cognitive decline. Hum Brain Mapp 2018. [PMID: 29516634 DOI: 10.1002/hbm.24022] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
Alzheimer's disease (AD) progresses insidiously from the preclinical stage to dementia. While people with subjective cognitive decline (SCD) have normal cognitive performance, some may be in the preclinical stage of AD. Neurofibrillary tangles appear first in the transentorhinal cortex, followed by the entorhinal cortex in the clinically silent stage of AD. We expected the earliest changes in subjects with SCD to occur in medial temporal subfields other than the hippocampal proper. These selective structural changes would affect specific memory subcomponents. We used the Family Picture subtest of the Wechsler Memory Scale-III, which was modified to separately compute character, activity, and location subscores for episodic memory subcomponents. We recruited 43 subjects with SCD, 44 subjects with amnesic mild cognitive impairment, and 34 normal controls. MRI was used to assess cortical thickness, subcortical gray matter volume, and fractional anisotropy. The results demonstrated that SCD subjects showed significant cortical atrophy in their bilateral parahippocampus and perirhinal and the left entorhinal cortices but not in their hippocampal regions. SCD subjects also exhibited significantly decreased mean fractional anisotropy in their bilateral uncinate fasciculi. The diminution of cortical thickness over the mesial temporal subfields corresponded to brain areas with early tangle deposition, and early degradation of the uncinate fasciculus was in accordance with the retrogenesis hypothesis. The parahippocampus and perirhinal cortex contribute mainly to context association memory while the entorhinal cortex, along with the uncinate fasciculus, contributes to content-related contextual memory. We proposed that context association and related memory structures are vulnerable in the SCD stage.
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Affiliation(s)
- Ling-Yun Fan
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.,Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ya-Mei Lai
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.,Center for Clinical Psychology, National Taiwan University Hospital, Taipei, Taiwan
| | - Ta-Fu Chen
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Yung-Chin Hsu
- Graduate Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Pin-Yu Chen
- Graduate Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Kuo-Zhou Huang
- Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ting-Wen Cheng
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.,Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Wen-Yi Isaac Tseng
- Graduate Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan.,Department of Medical Imaging, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Mau-Sun Hua
- Department of Psychology, Asia University, Taichung, Taiwan.,Department of Psychology, College of Science, National Taiwan University, Taipei, Taiwan
| | - Ya-Fang Chen
- Department of Medical Imaging, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ming-Jang Chiu
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.,Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, Taiwan.,Department of Psychology, College of Science, National Taiwan University, Taipei, Taiwan.,Graduate Institute of Biomedical Engineering and Bioinformatics, National Taiwan University, Taipei, Taiwan
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17
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Moscovitch M, Cabeza R, Winocur G, Nadel L. Episodic Memory and Beyond: The Hippocampus and Neocortex in Transformation. Annu Rev Psychol 2016; 67:105-34. [PMID: 26726963 PMCID: PMC5060006 DOI: 10.1146/annurev-psych-113011-143733] [Citation(s) in RCA: 558] [Impact Index Per Article: 69.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The last decade has seen dramatic technological and conceptual changes in research on episodic memory and the brain. New technologies, and increased use of more naturalistic observations, have enabled investigators to delve deeply into the structures that mediate episodic memory, particularly the hippocampus, and to track functional and structural interactions among brain regions that support it. Conceptually, episodic memory is increasingly being viewed as subject to lifelong transformations that are reflected in the neural substrates that mediate it. In keeping with this dynamic perspective, research on episodic memory (and the hippocampus) has infiltrated domains, from perception to language and from empathy to problem solving, that were once considered outside its boundaries. Using the component process model as a framework, and focusing on the hippocampus, its subfields, and specialization along its longitudinal axis, along with its interaction with other brain regions, we consider these new developments and their implications for the organization of episodic memory and its contribution to functions in other domains.
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Affiliation(s)
- Morris Moscovitch
- Department of Psychology, University of Toronto, Toronto, Ontario M5S 3G3, Canada;
- Rotman Research Institute, Baycrest Center, Toronto, Ontario, M6A 2E1 Canada
- Department of Psychology, Baycrest Center, Toronto, Ontario M6A 2E1, Canada
| | - Roberto Cabeza
- Center for Cognitive Neuroscience, Duke University, Durham, North Carolina 27708;
| | - Gordon Winocur
- Rotman Research Institute, Baycrest Center, Toronto, Ontario, M6A 2E1 Canada
- Department of Psychology, Trent University, Peterborough, Ontario K9J 7B8, Canada
- Department of Psychiatry, University of Toronto, Toronto, Ontario M5T 1R8, Canada;
| | - Lynn Nadel
- Department of Psychology and Cognitive Science Program, University of Arizona, Tucson, Arizona 85721;
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18
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Wisse LEM, Butala N, Das SR, Davatzikos C, Dickerson BC, Vaishnavi SN, Yushkevich PA, Wolk DA. Suspected non-AD pathology in mild cognitive impairment. Neurobiol Aging 2015; 36:3152-3162. [PMID: 26422359 PMCID: PMC4641774 DOI: 10.1016/j.neurobiolaging.2015.08.029] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Revised: 07/29/2015] [Accepted: 08/31/2015] [Indexed: 01/18/2023]
Abstract
We aim to better characterize mild cognitive impairment (MCI) patients with suspected non-Alzheimer's disease (AD) pathology (SNAP) based on their longitudinal outcome, cognition, biofluid, and neuroimaging profile. MCI participants (n = 361) from ADNI-GO/2 were designated "amyloid positive" with abnormal amyloid-beta 42 levels (AMY+) and "neurodegeneration positive" (NEU+) with abnormal hippocampal volume or hypometabolism using fluorodeoxyglucose-positron emission tomography. SNAP was compared with the other MCI groups and with AMY- controls. AMY-NEU+/SNAP, 16.6%, were older than the NEU- groups but not AMY- controls. They had a lower conversion rate to AD after 24 months than AMY+NEU+ MCI participants. SNAP-MCI participants had similar amyloid-beta 42 levels, florbetapir and tau levels, but larger white matter hyperintensity volumes than AMY- controls and AMY-NEU- MCI participants. SNAP participants performed worse on all memory domains and on other cognitive domains, than AMY-NEU- participants but less so than AMY+NEU+ participants. Subthreshold levels of cerebral amyloidosis are unlikely to play a role in SNAP-MCI, but pathologies involving the hippocampus and cerebrovascular disease may underlie the neurodegeneration and cognitive impairment in this group.
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Affiliation(s)
- Laura E M Wisse
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
| | - Nirali Butala
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Sandhitsu R Das
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Christos Davatzikos
- Section of Biomedical Image Analysis, University of Pennsylvania, Philadelphia, PA, USA
| | - Bradford C Dickerson
- Psychiatric Neuroimaging Division, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | | | - Paul A Yushkevich
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
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