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Amygdala network dysfunction in late-life depression phenotypes: Relationships with symptom dimensions
2015
Journal of Psychiatric Research
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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
2013
NeuroImage: Clinical
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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
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The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
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
2022
International Journal for Research in Applied Science and Engineering Technology
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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
2014
PLoS ONE
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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
2012
Journal of Clinical and Experimental Neuropsychology
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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
2019
Applied Sciences
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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
2021
Dementia and Neurocognitive Disorders
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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
2019
BMC Bioinformatics
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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?
2008
Neurorehabilitation and Neural Repair
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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
2005
Gender Medicine
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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
2019
International Journal of Intelligent Systems and Applications
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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
2017
Journal of the International Neuropsychological Society
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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
2020
Frontiers in Medicine
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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
2009
Alzheimer's & Dementia
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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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