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Amygdala network dysfunction in late-life depression phenotypes: Relationships with symptom dimensions

Wenjun Li, B. Douglas Ward, Chunming Xie, Jennifer L. Jones, Piero G. Antuono, Shi-Jiang Li, Joseph S. Goveas
2015 Journal of Psychiatric Research  
However, the overlapping and diverging amygdala network function abnormalities underlying two clinical LLD phenotypes (i.e., LLD alone and LLD with mild cognitive impairment [LLD-MCI]) are unknown.  ...  The amygdala, a crucial hub of the emotional processing neural system, has been implicated in late-life depression (LLD) pathophysiology.  ...  In addition, depression often coexists with mild cognitive impairment (MCI) in the elderly (Bhalla et al., 2009 ).  ... 
doi:10.1016/j.jpsychires.2015.09.002 pmid:26424431 pmcid:PMC4605880 fatcat:cflqborkinauxdxut4irsaf2cm

Late-life depression, mild cognitive impairment and hippocampal functional network architecture

Chunming Xie, Wenjun Li, Gang Chen, B. Douglas Ward, Malgorzata B. Franczak, Jennifer L. Jones, Piero G. Antuono, Shi-Jiang Li, Joseph S. Goveas
2013 NeuroImage: Clinical  
Late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are associated with medial temporal lobe structural abnormalities.  ...  By utilizing R-fMRI technique, this study provides novel insights into the neural mechanisms underlying LLD and aMCI in the functional network level.  ...  All authors have made substantial intellectual contribution to this manuscript in one or more of the following areas: design or conceptualization of the study, analysis or interpretation of the data, or  ... 
doi:10.1016/j.nicl.2013.09.002 pmid:24273715 pmcid:PMC3814948 fatcat:go5ct5wborbnzky5ezrkfird6y

Page 3578 of Psychological Abstracts Vol. 84, Issue 8 [page]

1997 Psychological Abstracts  
The individually specific meaning of profile variables in the context of their interaction with personality and life-situational factors (as uncovered through comparative analysis of pre- and post-injury  ...  (U Buenos Aires Facultad de Medicina, De- partamento de Fisiologia y Biofisica, Lab de Neurofisiologia, Ar- gentina) Classification of quantitative EEG data by an artificial neural network: A preliminary  ... 

Mental Health Status Detection through Handwriting Analysis

Prof. Vinay M G
2022 International Journal for Research in Applied Science and Engineering Technology  
They predict it will transform the society yet again, this time through the vital importance of changing the human intelligence to machine intelligence.  ...  The project is said to use five classes depression, anxiety, stress, panic and normal.  ...  "Artificial Neural Network for human behavior prediction through handwriting analysis" The authors of the research [3] employed a technique to estimate a person's personality based on their handwriting's  ... 
doi:10.22214/ijraset.2022.45744 fatcat:k2t56ychwvdxjcn2c7mf62457e

An Artificial Neural Network Estimation of Gait Balance Control in the Elderly Using Clinical Evaluations

Vipul Lugade, Victor Lin, Arthur Farley, Li-Shan Chou, Francisco J. Esteban
2014 PLoS ONE  
The purpose of this study was to demonstrate that given clinical measures, an artificial neural network (ANN) could determine dynamic balance control, as defined by the interaction of the center of mass  ...  Using a feed-forward neural network with back propagation, combinations of five functional domains, the number of hidden layers and error goals were evaluated to determine the best parameters to assess  ...  Acknowledgments The authors would like to thank Drs. Tzurei Chen and Masahiro Fujimoto for their assistance during data collections. Author Contributions  ... 
doi:10.1371/journal.pone.0097595 pmid:24836062 pmcid:PMC4023967 fatcat:4afzo2fhprfqta47wuh74vo7xy

Using artificial neural networks in clinical neuropsychology: High performance in mild cognitive impairment and Alzheimer's disease

María Quintana, Joan Guàrdia, Gonzalo Sánchez-Benavides, Miguel Aguilar, José Luis Molinuevo, Alfredo Robles, María Sagrario Barquero, Carmen Antúnez, Carlos Martínez-Parra, Anna Frank-García, Manuel Fernández, Rafael Blesa (+2 others)
2012 Journal of Clinical and Experimental Neuropsychology  
MCI = mild cognitive impairment; AD = Alzheimer's disease. a The most important input in ANN (artificial neural networks) model.  ...  Percentage of subjects correctly classified. LDA = linear discriminant analysis; ANN = artificial neural networks; MCI = mild cognitive impairment; AD = Alzheimer's disease.  ... 
doi:10.1080/13803395.2011.630651 pmid:22165863 fatcat:2smitg2b6ncfxglypncvxefafy

Complex Networks and Machine Learning: From Molecular to Social Sciences

David Quesada, Maykel Cruz-Monteagudo, Terace Fletcher, Aliuska Duardo-Sanchez, Humbert González-Díaz
2019 Applied Sciences  
Combining complex networks analysis methods with machine learning (ML) algorithms have become a very useful strategy for the study of complex systems in applied sciences.  ...  In this context, we decided to launch one special issue focused on the benefits of using ML and complex network analysis (in combination or separately) to study complex systems in applied sciences.  ...  [4] used ML algorithms known as artificial neural networks (ANN) for detecting patients with depression-related mild cognitive impairment, which is common mostly among elderly people.  ... 
doi:10.3390/app9214493 fatcat:ijewsj5frffopknv53icr235h4

Comparison of RCF Scoring System to Clinical Decision for the Rey Complex Figure Using Machine-Learning Algorithm

Chanda Simfukwe, Seong Soo An, Young Chul Youn
2021 Dementia and Neurocognitive Disorders  
The interpretation of RCF using clinical decision by clinicians might not be accurate in the diagnosing of mild cognitive impairment (MCI) or dementia patients in comparison with the RCF scoring system  ...  Models were trained using a convolutional neural network for machine learning.  ...  ACKNOWLEDGEMENTS We would like to thank the Department of Neurology at Chung-Ang University Hospital for providing the necessary tools to make this research successful.  ... 
doi:10.12779/dnd.2021.20.4.70 pmid:34795770 pmcid:PMC8585537 fatcat:qlraus3wgzgztffox3gkxsfpja

Mild cognitive impairment understanding: an empirical study by data-driven approach

Liyuan Liu, Bingchen Yu, Meng Han, Shanshan Yuan, Na Wang
2019 BMC Bioinformatics  
We found that depression, physical health, cigarette usage, education level, and sleep time play an important role in cognitive decline, which is consistent with the previous discovery.  ...  Cognitive decline has emerged as a significant threat to both public health and personal welfare, and mild cognitive decline/impairment (MCI) can further develop into Dementia/Alzheimer's disease.  ...  Acknowledgments We thank the anonymous referees for their useful suggestions. About this supplement  ... 
doi:10.1186/s12859-019-3057-1 pmid:31874606 pmcid:PMC6929464 fatcat:izl4ravp4bbpjkwyogomwjis2u

The Predictive Brain State: Timing Deficiency in Traumatic Brain Injury?

Jamshid Ghajar, Richard B. Ivry
2008 Neurorehabilitation and Neural Repair  
The authors discuss the role of this anticipatory neural system for understanding the varied symptoms and potential rehabilitation interventions for TBI.  ...  Preparatory neural activity normally allows the efficient integration of sensory information with goal-based representations.  ...  ACKNOWLEDGMENTS We thank Susan Fitzpatrick, PhD, for helpful comments on the manuscript and Akiyo Kodera for assistance in preparation of the manuscript. Supported by the Rachel L.  ... 
doi:10.1177/1545968308315600 pmid:18460693 pmcid:PMC4338277 fatcat:zulpuim4jjacfbv56nj6fplb6a

Two different Alzheimer diseases in men and women: Clues from advanced neural networks and artificial intelligence

Enzo Grossi, Giulia Massini, Massimo Buscema, Rita Savarè, Guido Maurelli
2005 Gender Medicine  
Studies of the gender-related differences in the clinical presentation of Alzheimer's disease (AD) have focused on specific aspects of the disease (eg, circulating metabolites, cognitive capacity, or epidemiologic  ...  Objective: This study accounts for several descriptors of the disease simultaneously, providing a multidimensional analysis of a cohort of patients with AD.  ...  CONCLUSIONS According to the neural networks approach, sex is a discriminating factor in the natural multidimensional clustering of patients with AD.  ... 
doi:10.1016/s1550-8579(05)80017-8 pmid:16115605 fatcat:eqdqgs55azfodkqbojrqxzdn6y

Neural Network Modeling and Correlation Analysis of Brain Plasticity Mechanisms in Stroke Patients

Stepanyan I.V., Mayorova L.A., Alferova V.V., Ivanova E.G., Nesmeyanova E.S., Petrushevsky A.G., Tiktinsky-Shklovsky V.M.
2019 International Journal of Intelligent Systems and Applications  
This work describes a new method of applying a group of artificial neural network algorithms for each of the criteria and for each period of rehabilitation, and it is aimed at analyzing the structural  ...  The using of clinical parameters and mathematical modeling for analysis of brain plasticity mechanisms in stroke patients allowed in some cases to predict cognitive functions within the accuracy of 85-  ...  In this diffusion tensor imaging study, authors used a new fiber tract modeling method to investigate white matter integrity in 50 elderly controls (CTL), 113 people with mild cognitive impairment (MCI  ... 
doi:10.5815/ijisa.2019.06.03 fatcat:smtqcetzvrhwzgfayy6ynnoyfy

The Neuropsychology of Traumatic Brain Injury: Looking Back, Peering Ahead

Keith Owen Yeates, Harvey S. Levin, Jennie Ponsford
2017 Journal of the International Neuropsychological Society  
to the betterment of the quality of life of persons with TBI.  ...  of the importance of non-injury factors in determining recovery from TBI; and the growth of cognitive rehabilitation.  ...  Neural mechanisms of social cognitive and behavioral sequelae can also be understood by analysis of the relevant brain networks.  ... 
doi:10.1017/s1355617717000686 pmid:29198271 fatcat:hc6dztjowzcmrfu6vscogdwnai

Cognitive Impairment and Dementia in Primary Care: Current Knowledge and Future Directions Based on Findings From a Large Cross-Sectional Study in Crete, Greece

Antonios Bertsias, Emmanouil Symvoulakis, Chariklia Tziraki, Symeon Panagiotakis, Lambros Mathioudakis, Ioannis Zaganas, Maria Basta, Dimitrios Boumpas, Panagiotis Simos, Alexandros Vgontzas, Christos Lionis
2020 Frontiers in Medicine  
A two-layer artificial neural network model was used to classify participants as impaired (dementia/MCI) vs. non-impaired.Results: In the total sample of 3,140 participants (42.1% men; mean age 73.7 SD  ...  For the diagnosis of dementia and Mild-Cognitive-Impairment (MCI), the Diagnostic and Statistical Manual-of-Mental-Disorders (DSM-IV) criteria and the International-Working-Group (IWG) criteria were used  ...  We would like to thank the following study nurses who played an important role in recruitment of participants and conducted the interviews and tests: Sofia Marinaki, Marina Lyroni, Maria Maniou, Georgia  ... 
doi:10.3389/fmed.2020.592924 pmid:33330553 pmcid:PMC7719838 fatcat:t3qvkwj25ba6nfdf62xaunqa6e

Algorithms to retrospectively diagnose mild cognitive impairment and dementia in a longitudinal study of aging and dementia

Luca Finelli, Ursula Kunze, Aurelie Gautier, Baltazar Gomez-Mancilla, Andreas U. Monsch
2009 Alzheimer's & Dementia  
Two-way ANOVA with the covariance of educational level was performed to show the time differences of each cognitive domain.  ...  This means that recent memory impairment, even a slight decline, may be an early sign of dementia which could be discriminated from the healthy aging process.  ...  P4 P4-085 AN EXPLORATORY ANALYSIS OF VARIABLES ASSOCIATED WITH MCI EVOLUTION THROUGH DATA MINING WITH NOVEL ARTIFICIAL NEURAL NETWORKS Arianna Montali 1 , Enzo Grossi 2 , Letizia Concari 3 , Sandra Copelli  ... 
doi:10.1016/j.jalz.2009.04.853 fatcat:z4ajde3m6ndd5egd2gaip4qsxe
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