Article
Clinical Neurology
Benjamin M. Hampstead, Anthony Y. Stringer, Alexandru D. Iordan, Robert Ploutz-Snyder, K. Sathian
Summary: Cognitive training is a potential technique for treating cognitive impairment caused by neurological injury and disease. Different training methods have different mechanisms of action and engage distinct brain regions. Mnemonic strategy training (MST) showed superior effects in the short term and increased activation and functional connectivity in multiple brain regions.
ALZHEIMERS & DEMENTIA
(2023)
Article
Clinical Neurology
Deepika Dinesh, Qing Shao, Madhuri Palnati, Sarah McDannold, Quanwu Zhang, Amir Abbas Tahami Monfared, Guneet K. Jasuja, Heather Davila, Weiming Xia, Lauren R. Moo, Donald R. Miller, Natalia Palacios
Summary: Based on electronic health records data, a study found that US veterans have a unique dementia risk profile that may be changing over time. From 2000 to 2019, the incidence and prevalence of Alzheimer's disease (AD) and related dementias (ADRD) decreased, while ADRD prevalence increased primarily due to an increase in dementia not otherwise specified. The prevalence and incidence of mild cognitive impairment (MCI) sharply increased, especially after 2010. The highest prevalence and incidence of AD, ADRD, and MCI were observed in the oldest veterans, female veterans, and African American and Hispanic veterans.
ALZHEIMERS & DEMENTIA
(2023)
Editorial Material
Cell Biology
Zhuang-Yao D. Wei, Ashok K. Shetty
Summary: This article discusses a recent study that suggests using a miRNA triad, consisting of miR-181a-5p, miR-146a-5p, and miR-148a-3p, for diagnosing ACI, MCI, and AD. The study explores the impact of elevated levels of this miRNA triad on neural plasticity and cognitive function in the brain and the potential of inhibiting it to improve cognitive function in MCI and AD.
Article
Neurosciences
Conor Owens-Walton, Chris Adamson, Mark Walterfang, Sara Hall, Danielle Westen, Oskar Hansson, Marnie Shaw, Jeffrey C. L. Looi
Summary: People diagnosed with Parkinson's disease can experience cognitive impairment and dementia, which may be related to structural changes in the corpus callosum. This study used magnetic resonance imaging to investigate the thickness of the corpus callosum and cortex in Parkinson's disease patients with varying levels of cognitive impairment. The results showed thinning of the callosum in patients with dementia, and a positive correlation between the thickness of the anterior callosum and the thickness of the cortex in patients with mild cognitive impairment.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2022)
Review
Psychology, Multidisciplinary
Alexandra Wolf, Kornkanok Tripanpitak, Satoshi Umeda, Mihoko Otake-Matsuura
Summary: Mild cognitive impairment (MCI) is a transitional zone between normal cognition and dementia, and has become a novel topic in clinical research. Early detection is crucial but logistically challenging, and technological advancements in cognitive scoring methodologies are needed. Non-invasive eye-tracking-based paradigms may contribute to early AD detection, but further longitudinal investigations are necessary for clinical applications.
FRONTIERS IN PSYCHOLOGY
(2023)
Article
Clinical Neurology
Salvatore Mazzeo, Assunta Ingannato, Giulia Giacomucci, Alberto Manganelli, Valentina Moschini, Juri Balestrini, Arianna Cavaliere, Carmen Morinelli, Giulia Galdo, Filippo Emiliani, Diletta Piazzesi, Chiara Crucitti, Daniele Frigerio, Cristina Polito, Valentina Berti, Silvia Bagnoli, Sonia Padiglioni, Sandro Sorbi, Benedetta Nacmias, Valentina Bessi
Summary: Plasma neurofilament light chain (NfL) can accurately predict Alzheimer's disease and the progression of cognitive decline, serving as an important non-invasive tool for early diagnosis.
EUROPEAN JOURNAL OF NEUROLOGY
(2023)
Article
Neurosciences
Jasmin E. Guevara, Natalie E. Kurniadi, Kevin Duff
Summary: This study quantifies cognitive change in patients with mild cognitive impairment (MCI) using standardized regression-based (SRB) z-scores. The findings show a significant decline in cognitive function over time, especially in learning and memory. Patients who progressed to dementia (MCI-Decline) showed more decline compared to those who remained stable (MCI-Stable). The study highlights the value of SRB in quantifying cognitive decline and identifying individuals at higher risk for MCI progression.
JOURNAL OF ALZHEIMERS DISEASE
(2023)
Article
Geriatrics & Gerontology
Woori Moon, Ji Won Han, Jong Bin Bae, Seung Wan Suh, Tae Hui Kim, Kyung Phil Kwak, Bong Jo Kim, Shin Gyeom Kim, Jeong Lan Kim, Seok Woo Moon, Joon Hyuk Park, Seung-Ho Ryu, Jong Chul Youn, Dong Young Lee, Dong Woo Lee, Seok Bum Lee, Jung Jae Lee, Jin Hyeong Jhoo, Ki Woong Kim
Summary: This study investigated the disease burden of various dementias and mild cognitive impairment in a representative South Korean population, predicting a significant increase in disability-adjusted life-years and years lived with disability due to these conditions by 2065.
JOURNAL OF THE AMERICAN MEDICAL DIRECTORS ASSOCIATION
(2021)
Article
Geriatrics & Gerontology
Kym McNicholas, Maxime Francois, Jian-Wei Liu, James D. Doecke, Jane Hecker, Jeff Faunt, John Maddison, Sally Johns, Tara L. Pukala, Robert A. Rush, Wayne R. Leifert
Summary: This study identified biomarkers in saliva that can be used for early detection of cognitive impairment and Alzheimer's disease. The findings suggest that combinations of specific proteins can effectively distinguish patients with cognitive impairment and Alzheimer's disease from cognitively normal individuals.
FRONTIERS IN AGING NEUROSCIENCE
(2022)
Article
Clinical Neurology
Ruben Sanz-Blasco, Jose M. Ruiz-Sanchez de Leon, Marina Avila-Villanueva, Meritxel Valenti-Soler, Jaime Gomez-Ramirez, Miguel A. Fernandez-Blazquez
Summary: The study examined the rate of reversion from mild cognitive impairment to normal cognition in a unidirectional manner within the Alzheimer's disease continuum. There were both non-modifiable factors (age, socioeconomic status, apolipoprotein E) and modifiable factors (cognitive training, absence of affective symptoms) associated with reversion. The likelihood of progression from MCI to dementia was found to be similar to that of reversion from MCI to NC.
ALZHEIMERS & DEMENTIA
(2022)
Article
Clinical Neurology
Soeren Mattke, Hankyung Jun, Emily Chen, Ying Liu, Andrew Becker, Christopher Wallick
Summary: This study aimed to compare the actual diagnosis rates of mild cognitive impairment (MCI) and dementia in the full Medicare population with the predicted diagnosis rates. The study found that the detection rate for MCI was low, especially among Black and Hispanic beneficiaries. Dementia was diagnosed more frequently, particularly in non-Hispanic White beneficiaries.
ALZHEIMERS RESEARCH & THERAPY
(2023)
Article
Geriatrics & Gerontology
Hillary J. Rouse, Zahinoor Ismail, Ross Andel, Victor A. Molinari, John A. Schinka, Brent J. Small
Summary: This study examined the impact of mild behavioral impairment (MBI) on cognitive performance among cognitively healthy older adults and those with mild cognitive impairment (MCI). The results showed that individuals with MBI performed worse on tasks of attention, episodic memory, executive function, language, and processing speed, and exhibited greater decline over time. The presence of MBI was also associated with poorer performance on tasks of visuospatial ability, executive function, and processing speed among individuals with MCI.
JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES
(2023)
Review
Endocrinology & Metabolism
Rachel Heutz, Jurgen Claassen, Sanne Feiner, Aaron Davies, Dewakar Gurung, Ronney B. Panerai, Rianne de Heus, Lucy C. Beishon
Summary: Dynamic cerebral autoregulation (dCA) is a key mechanism that regulates cerebral blood flow in response to transient changes in blood pressure. The literature remains conflicted on whether dCA is altered in Alzheimer's disease (AD) and mild cognitive impairment (MCI). A qualitative synthesis of eight studies suggests no significant difference in dCA parameters for spontaneous fluctuations between AD, MCI, and healthy controls. Limited data on induced fluctuations indicate preserved or possibly better autoregulatory functioning in AD and MCI compared to controls. Further research is needed to investigate dCA in dementia with induced fluctuations controlling for changes in end-tidal carbon dioxide.
JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM
(2023)
Article
Neurosciences
Catarina Bernardes, Marisa Lima, Diana Duro, Anuschka Silva-Spinola, Joao Duraes, Miguel Tabuas-Pereira, Ines Baldeiras, Sandra Freitas, Isabel Santana
Summary: This study confirms the role of cerebrospinal fluid Alzheimer's disease biomarkers in predicting conversion from mild cognitive impairment to dementia and suggests the utility of Montreal Cognitive Assessment in predicting conversion in highly educated subjects, supporting its use in the evaluation of MCI patients.
JOURNAL OF ALZHEIMERS DISEASE
(2023)
Review
Biochemistry & Molecular Biology
Kyoungjoo Cho
Summary: Cognitive impairment is a serious condition associated with aging and disruption of inflammation and innate immunity. Recent studies have shown that the innate immune system is prevalent in patients with Alzheimer's disease, and peripheral neutrophil markers can predict a decline in cognitive function in patients with mild cognitive impairment. Furthermore, altered levels of pro-inflammatory interleukins have been reported in patients with mild cognitive impairment, potentially playing a role in the progression from early cognitive impairment to dementia.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Gang Wang, Qunxi Dong, Jianfeng Wu, Yi Su, Kewei Chen, Qingtang Su, Xiaofeng Zhang, Jinguang Hao, Tao Yao, Li Liu, Caiming Zhang, Richard J. Caselli, Eric M. Reiman, Yalin Wang
Summary: A novel method for quantifying morphological changes induced by Alzheimer's disease was proposed and validated in the ADNI cohort, showing potential value in disease detection and assessment.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Clinical Neurology
Yu Fu, Jie Zhang, Yuan Li, Jie Shi, Ying Zou, Hanning Guo, Yongchao Li, Zhijun Yao, Yalin Wang, Bin Hu
Summary: In this study, a novel pipeline for ASD classification was proposed, which utilized surface-based features, patch-based surface sparse coding and dictionary learning, Max-pooling, and ensemble classifiers based on adaptive optimizers. By introducing only the surface features of bilateral hippocampus from 364 male subjects with ASD and 381 age-matched TD males, this pipeline achieved >80% accuracy in discriminating individuals with ASD from TD controls, outperforming previous MRI-based ASD classification studies. The results suggest that shape-related SBM features may further enhance the classification performance of MRI between ASD and TD.
PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY
(2021)
Article
Computer Science, Interdisciplinary Applications
Wen Zhang, B. Blair Braden, Gustavo Miranda, Kai Shu, Suhang Wang, Huan Liu, Yalin Wang
Summary: Researchers are interested in uncovering the fundamental biological mechanisms in the complex brain network, but extracting useful information from a limited sample size of brain networks is challenging. Collecting multimodal and longitudinal data has become common trends to gain more information, as these two types of data provide complementary information. The MMLC framework integrates cross-sectional similarity, multimodal coupling, and longitudinal consistency to better predict psychometric scores.
Article
Computer Science, Interdisciplinary Applications
Jie Zhang, Jianfeng Wu, Qingyang Li, Richard J. Caselli, Paul M. Thompson, Jieping Ye, Yalin Wang
Summary: The novel MMLC method proposed in this study addresses challenges in longitudinal brain imaging data analysis, achieving superior results in computational efficiency and predictive accuracy, showing great potential in assisting Alzheimer's disease prevention.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2021)
Article
Computer Science, Artificial Intelligence
Yonghui Fan, Gang Wang, Qunxi Dong, Yuxiang Liu, Natasha Lepore, Yalin Wang
Summary: The paper introduces a new Bayesian manifold learning framework based on tetrahedral spectral features for effective statistical analysis of grey matter morphology. By addressing technical issues and deriving new operators, a shape descriptor and regression framework are designed for analyzing Alzheimer's disease data. The proposed system shows promising results compared to baseline algorithms, suggesting potential for further research in medical image analysis using tetrahedral spectral features.
MEDICAL IMAGE ANALYSIS
(2021)
Article
Biochemical Research Methods
Yanshuai Tu, Duyan Ta, Zhong-Lin Lu, Yalin Wang
Summary: This study aims to address the issue of non-topological retinotopic maps caused by low signal-to-noise ratio and spatial resolution of fMRI, proposing a method that directly models the topological condition and generates topology-preserving and smooth retinotopic maps. Experimental results demonstrate that the proposed method can generate topological and smooth retinotopic maps in V1, V2, and V3 simultaneously.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Anatomy & Morphology
Yanshuai Tu, Xin Li, Zhong-Lin Lu, Yalin Wang
Summary: Retinotopic maps, which are important in vision science, are limited by the signal-to-noise ratio and spatial resolution of fMRI. We developed a new registration method called Diffeomorphic Registration for Retinotopic Maps (DRRM) to improve the quality of retinotopic maps by aligning them under the diffeomorphic condition. DRRM outperforms existing methods in achieving diffeomorphic registration in both synthetic and real datasets, and it may have applications in clinical settings.
BRAIN STRUCTURE & FUNCTION
(2022)
Article
Computer Science, Artificial Intelligence
Haoteng Tang, Lei Guo, Xiyao Fu, Yalin Wang, Scott Mackin, Olusola Ajilore, Alex D. Leow, Paul M. Thompson, Heng Huang, Liang Zhan
Summary: MRI-derived brain networks are widely used to understand interactions among brain regions and their relationships with brain development and diseases. Graph mining on these networks can help discover biomarkers for clinical phenotypes and neurodegenerative diseases. Most current studies focus on projecting structural networks onto functional networks to extract a fused representation.
MEDICAL IMAGE ANALYSIS
(2023)
Article
Neurosciences
Weimin Zheng, Honghong Liu, Zhigang Li, Kuncheng Li, Yalin Wang, Bin Hu, Qunxi Dong, Zhiqun Wang
Summary: This study investigated the differences in hippocampal morphometry among AD, MCI, and HC using multivariate morphometry statistics analysis. The results revealed significant hippocampal deformation, especially in the CA1 region, among these three groups. Furthermore, the study confirmed that hippocampal MMS can be used as a sensitive imaging biomarker for the early diagnosis of AD at the individual level.
CNS NEUROSCIENCE & THERAPEUTICS
(2023)
Article
Biochemical Research Methods
Duyan Ta, Negar Jalili Mallak, Zhong- Lin Lu, Yalin Wang
Summary: High-field functional magnetic resonance imaging is used to generate in vivo retinotopic maps, but quantifying them is challenging. This study presents a pipeline based on conformal geometry and Teichmuller theory for the quantitative characterization of human retinotopic maps. The pipeline includes steps for cortical surface parameterization and surface-spline-based smoothing, as well as a detailed description of Beltrami coefficient-based mapping. The framework has been applied to analyze the Human Connectome Project's V1 retinotopic maps.
Article
Computer Science, Cybernetics
Qunxi Dong, Zhigang Li, Weijia Liu, Kewei Chen, Yi Su, Jianfeng Wu, Richard J. Caselli, Eric M. Reiman, Yalin Wang, Jian Shen
Summary: This study aims to explore the relationship between plasma neurofilament light (NFL) levels and hippocampal morphometry using a proposed surface-based hippocampal morphometry system. Experimental results show that the system can effectively distinguish individuals with different plasma NFL levels and offers stronger statistical power compared to hippocampal volume measurement. This study is significant in revealing the pathology of Alzheimer's disease.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Proceedings Paper
Engineering, Biomedical
Sovanlal Mukherjee, Natacha Paquette, Niharika Gajawelli, Yalin Wang, Julia Wallace, Marvin D. Nelson, Ashok Panigrahy, Natasha Lepore
16TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION PROCESSING AND ANALYSIS
(2020)
Proceedings Paper
Engineering, Biomedical
Jianfeng Wu, Jie Zhang, Qingyang Li, Yi Su, Kewei Chen, Eric M. Reiman, Jie Wang, Natasha Lepore, Jieping Ye, Paul M. Thompson, Yalin Wang
16TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION PROCESSING AND ANALYSIS
(2020)
Proceedings Paper
Engineering, Biomedical
Yanshuai Tu, Duyan Ta, Zhong-Lin Lu, Yalin Wang
2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020)
(2020)
Proceedings Paper
Engineering, Biomedical
Yanshuai Tu, Duyan Ta, Xianfeng David Gu, Zhong-Lin Lu, Yalin Wang
2020 IEEE 17TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2020)
(2020)
