ResumenEn este artículo presentamos un estudio piloto en que se explora la relación entre la conceptualización del espacio y el desarrollo cognitivo. Para ello se pidió a ocho sujetos de cuatro rangos etarios (niños, adolescentes, adultos medios y mayores) describir la ubicación espacial de los elementos de una fotografía, a fin de identificar los aspectos que diferencian las expresiones referentes a la ubicación espacial entre rangos etarios. Se observa que, en nuestra muestra, la conceptualización del espacio se complejiza conforme avanza la edad, con diferencias en cinco parámetros: sistema de referencia, marco de referencia, punto de vista, multidimensionalidad y patrón de rastreo visual.Palabras clave: Conceptualización espacial, Desarrollo cognitivo, Marco de referencia, Descripción espacial, Lingüística cognitiva. AbstractIn this article we report a pilot study which explored the relationship between spatial categorization and cognitive development. Eight participants from four age ranges (infants, teenagers, middle aged adults, old adults) were asked to describe the location of certain elements in a picture, in order to examine which aspects of the spatial location expressions showed differences across age ranges. Analysis showed that spatial categorization grows complex with age, with differences being observed in relation to five parameters: system of reference, reference frame, viewpoint, multidimensionality and visual tracking pattern.

Objective: to describe the speech-language therapist role in the interdisciplinary team in the intervention of Orofacial motricity in the temporomandibular dysfunction documented in scientific publications. Methods: the search was conducted in well-known databases using the following terms or terminological associations: Temporomandibular dysfunction (TMD), stomatognathic system and TMD, Mastication, Speech and TMD. Interventions related to voice or temporomandibular joint indemnity were not included. Results: the interventions indicated in the scientific publications are described, giving an account of the role of the speech pathologist in the TMD intervention team. Conclusion: the therapist’s intervention in Orofacial Motricity restores the stomatognathic system by addressing its functions. An isolated treatment approach from professionals overlooks the relationship of interdependence between function and structure. An appeal for an integrated and interdisciplinary work model, setting it free from the traditional fragmentary and multidisciplinary model, is made.

In March 2020, the first version of EPIVIGILA was deployed in a productive environment a few days after the first local case of COVID- 19. This system is a technological integration plat-form for national epidemiological surveillance of notifiable diseases. Previously, Chile used a manual process that would probably have failed with a peak volume of more than 38 000 daily notifications; in a country with 18 million inhabitants, long and narrow geography, and centralized governance. This work highlights the importance of the national electronic surveillance system – EPIVIGILA – in managing the pandemic. The system’s main strength is its ability to adapt to the needs of reliable, precise, timely, and real- time information. EPIVIGILA was able to include, under the circumstances, different flows, actors, data, and functionalities with high expectations of accuracy. This valuable information allowed the authorities to assess the impact of the measures to manage and control the pandemic. Its versatility positions this platform among the few globally that operates national data with a high level of granularity in a single system through a pandemic. In Chile, EPIVIGILA is the primary source of information for daily reports, epidemiological reports, and data published on government websites about COVID- 19. Thus, electronic systems prove fundamental for public health because the recording and processing of data generate clear, reliable, and timely information, helping authorities make decisions to reduce the spread of infectious diseases, prevent deaths, and improve the population’s quality of life.

Mayor reserva se asocia con resistencia al deterioro en sujetos con enfermedades neurodegenerativas. En personas sanas explica las diferencias interindividuales en el rendimiento de tareas. Medir los factores de reserva cognitiva permite contar con un índice numérico de la ganancia cognitiva acumulada por un sujeto. Este índice puede ser correlacionado con otras funciones cuantificables. El presente trabajo tiene como objetivo presentar los índices de reserva obtenidos por una población chilena en la aplicación del Cognitive Reserve Index Questionnaire (CRIq). Para ello 90 adultos (18-85 años) sin evidencias de trastorno cognitivo, de la región de Valparaíso-Chile, fueron entrevistados sobre actividades de estudio, laborales y de tiempo libre ejecutadas desde los 18 años.Los resultados muestran que los índices de reserva de los sujetos varían en función del tiempo de ejecución de actividades promotoras de reserva y no por su edad. Se encontraron diferencias estadísticamente significativas entre los grupos etarios. Estos resultados permiten concluir que la ejecución de actividades de estudio, laborales, sociales, entre otras aumenta los índices de reserva cognitiva, que es una variable diferenciadora entre individuos. La medición de dichos índices puede ser útil en un amplio campo de disciplinas (medicina, neurología, neuropsicología, educación, psicología, fonoaudiología, neurociencias y en las ciencias cognitivas en general).

The 2019 Coronavirus disease (COVID-19) pandemic is a current challenge for the world’s health systems aiming to control this disease. From an epidemiological point of view, the control of the incidence of this disease requires an understanding of the influence of the variables describing a population. This research aims to predict the COVID-19 incidence in three risk categories using two types of machine learning models, together with an analysis of the relative importance of the available features in predicting the COVID-19 incidence in the Chilean urban commune of Concepción. The classification results indicate that the ConvLSTM (Convolutional Long Short-Term Memory) classifier performed better than the SVM (Support Vector Machine), with results between 93% and 96% in terms of accuracy (ACC) and F-measure (F1) metrics. In addition, when considering each one of the regional and national features as well as the communal features (DEATHS and MOBILITY), it was observed that at the regional level the CRITICAL BED OCCUPANCY and PATIENTS IN ICU features positively contributed to the performance of the classifiers, while at the national level the features that most impacted the performance of the SVM and ConvLSTM were those related to the type of hospitalization of patients and the use of mechanical ventilators.