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1.
Percept Mot Skills ; 128(6): 2561-2581, 2021 Dec.
Artículo en Inglés | MEDLINE | ID: mdl-34396818

RESUMEN

The Rey-Osterrieth Complex Figure Test (RCFT) permits quantifying diverse cognitive abilities, including executive function (EF). We evaluated the psychometric properties of a scoring procedure for the RCFT, the Savage Organizational Scoring System (SOSS), that awards points for drawing the largest structural elements of the figures as continuous wholes. This was a two-phase study: first, we conducted a systematic literature search for studies using the SOSS, and aggregated previously published data for healthy controls to create a normative database; second, we observed performances from veterans evaluated for traumatic brain injury (TBI), examining the reliability of their SOSS scores, the SOSS correlations with two EF measures and the participants' self-reported cognitive functioning, and then compared their mean scores to normative expectations. Across our literature-derived normative database, the aggregated mean SOSS score was 4.12 (SD = 1.72), which was marginally higher than that of our veteran participants evaluated for TBI, 3.72 (SD = 1.79). The SOSS had modest internal consistency (α = .59). Unlike the criterion EF measures, the SOSS was not significantly related to self-reported cognitive functioning. The SOSS shared a small, significant correlation with Trails B and Shipley Abstraction; but RCFT Copy scores were more strongly related to these tests, and the SOSS added no significant incremental predictive value beyond the RCFT Copy score. However, SOSS scores did predict RCFT Recall beyond RCFT Copy scores. We conclude that the SOSS has modest reliability and is predictive of RCFT Recall scores, but it is not strongly correlated with other EF measures, and it is only minimally affected by mild TBI.


Asunto(s)
Lesiones Traumáticas del Encéfalo , Veteranos , Función Ejecutiva , Humanos , Pruebas Neuropsicológicas , Reproducibilidad de los Resultados
2.
Hum Brain Mapp ; 38(10): 5180-5194, 2017 10.
Artículo en Inglés | MEDLINE | ID: mdl-28714589

RESUMEN

Magnetoencephalography (MEG), a direct measure of neuronal activity, is an underexplored tool in the search for biomarkers of Alzheimer's disease (AD). In this study, we used MEG source estimates of auditory gating generators, nonlinear correlations with neuropsychological results, and multivariate analyses to examine the sensitivity and specificity of gating topology modulation to detect AD. Our results demonstrated the use of MEG localization of a medial prefrontal (mPFC) gating generator as a discrete (binary) detector of AD at the individual level and resulted in recategorizing the participant categories in: (1) controls with mPFC generator localized in response to both the standard and deviant tones; (2) a possible preclinical stage of AD participants (a lower functioning group of controls) in which mPFC activation was localized to the deviant tone only; and (3) symptomatic AD in which mPFC activation was not localized to either the deviant or standard tones. This approach showed a large effect size (0.9) and high accuracy, sensitivity, and specificity (100%) in identifying symptomatic AD patients within a limited research sample. The present results demonstrate high potential of mPFC activation as a noninvasive biomarker of AD pathology during putative preclinical and clinical stages. Hum Brain Mapp 38:5180-5194, 2017. © 2017 Wiley Periodicals, Inc.


Asunto(s)
Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/fisiopatología , Percepción Auditiva/fisiología , Magnetoencefalografía , Corteza Prefrontal/fisiopatología , Filtrado Sensorial/fisiología , Estimulación Acústica , Anciano , Anciano de 80 o más Años , Enfermedad de Alzheimer/diagnóstico por imagen , Enfermedad de Alzheimer/psicología , Análisis por Conglomerados , Femenino , Humanos , Imagen por Resonancia Magnética , Masculino , Persona de Mediana Edad , Pruebas Neuropsicológicas , Corteza Prefrontal/diagnóstico por imagen , Análisis de Componente Principal , Sensibilidad y Especificidad , Procesamiento de Señales Asistido por Computador
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