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      Verbal intelligence and leisure activities are associated with cognitive performance and resting-state electroencephalogram


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          Cognitive reserve (CR) is the adaptability of cognitive processes that helps to explain differences in the susceptibility of cognitive or daily functions to resist the onslaught of brain-related injury or the normal aging process. The underlying brain mechanisms of CR studied through electroencephalogram (EEG) are scarcely reported. To our knowledge, few studies have considered a combination of exclusively dynamic proxy measures of CR. We evaluated the association of CR with cognition and resting-state EEG in older adults using three of the most frequently used dynamic proxy measures of CR: verbal intelligence, leisure activities, and physical activities. Multiple linear regression analyses with the CR proxies as independent variables and cognitive performance and the absolute power (AP) on six resting-state EEG components (beta, alpha1, alpha2, gamma, theta, and delta) as outcomes were performed. Eighty-eight healthy older adults aged 60–77 (58 female) were selected from previous study data. Verbal intelligence was a significant positive predictor of perceptual organization, working memory, processing speed, executive functions, and central delta power. Leisure activities were a significant positive predictor of posterior alpha2 power. The dynamic proxy variables of CR are differently associated with cognitive performance and resting-state EEG. Implementing leisure activities and tasks to increase vocabulary may promote better cognitive performance through compensation or neural efficiency mechanisms.

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          "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician.

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            EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis

            We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.
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              The Application of Electronic Computers to Factor Analysis


                Author and article information

                Front Aging Neurosci
                Front Aging Neurosci
                Front. Aging Neurosci.
                Frontiers in Aging Neuroscience
                Frontiers Media S.A.
                04 October 2022
                : 14
                : 921518
                [1] 1Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de México , Tlalnepantla, Mexico
                [2] 2Departamento de Neurobiología Conductual y Cognitiva, Instituto de Neurobiología, Universidad Nacional Autónoma de México , Juriquilla, Mexico
                [3] 3Departamento de Investigación, Instituto Nacional de Geriatría , Ciudad de México, Mexico
                Author notes

                Edited by: Jeannette R. Mahoney, Albert Einstein College of Medicine, United States

                Reviewed by: Rory Boyle, Massachusetts General Hospital and Harvard Medical School, United States; Andrea Zangrossi, University of Padua, Italy

                *Correspondence: Juan Silva-Pereyra, jsilvapereyra@ 123456gmail.com

                This article was submitted to Neurocognitive Aging and Behavior, a section of the journal Frontiers in Aging Neuroscience

                Copyright © 2022 Ferrari-Díaz, Bravo-Chávez, Silva-Pereyra, Fernández, García-Peña and Rodríguez-Camacho.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                : 16 April 2022
                : 06 September 2022
                Page count
                Figures: 2, Tables: 4, Equations: 0, References: 70, Pages: 13, Words: 8924
                Funded by: Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México, doi 10.13039/501100006087;
                Funded by: Consejo Nacional de Ciencia y Tecnología, doi 10.13039/501100003141;
                Original Research

                cognitive reserve,resting-state eeg,cognition,dynamic proxies,healthy aging,verbal intelligence,leisure activities


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