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Advances in knowledge and computational modeling of the autistic brain: A literature review

dc.contributor.authorPuerto Cuadros, Eduard Gilberto
dc.date.accessioned2021-10-29T22:12:20Z
dc.date.available2021-10-29T22:12:20Z
dc.date.issued2017-12
dc.identifier.issn2027-8101
dc.identifier.urihttp://repositorio.ufps.edu.co/handle/ufps/498
dc.description.abstractEl estudio del funcionamiento del cerebro permite, no sólo el descubrimiento de sus principios, sino también en la construcción de máquinas que lo emulen cada vez más inteligentes. En ese sentido, las neurociencias están aportando importantes conocimientos sobre cómo los diferentes elementos del cerebro interactúan en el procesamiento de información, para dar origen a funciones cognitivas de alto nivel (aprendizaje, conciencia, qualía, etc.), que caracterizan la conducta humana. Por otra parte, existen cerebros que viene con una maquinaria neuronal distinta caracterizados por sus capacidades cognitivas extraordinarias, comúnmente conocidos como autistas. A partir de estos dos hechos se planteó el siguiente interrogante. ¿Qué tanto se sabe sobre el autismo y como se ha avanzado en su modelado a nivel computacional?. Este artículo da una respuesta particular a modo de síntesis teórica del fenómeno autista y avances que a nivel computacional se han logrado en cuanto a simulación, emulación y desarrollo de herramientas de apoyo relacionados con este complejo fenómeno. Lo anterior con base en más de 50 estudios tomados de bases de datos científicas, tales como: Nature, Scopus, ACM, IEEE, Google scholar, entre otras.spa
dc.description.abstractThe study of the functioning of the brain allows, not only the discovery of its principles, but also in the construc-tion of machines that emulate getting smarter. In that sense, neurosciences are providing important insights into how different elements of the brain interact in information processing to give rise to high-level cognitive func-tions (learning, awareness, quality, etc.) that characterize human behavior. On the other hand, there are brains that come with distinct neuronal machinery characterized by their extraordinary cognitive abilities, commonly known as autistic. From these two facts the following question arises. How much is known about autism and how it has advanced in its modeling at the computational level?. This article gives a particular answer as a theoretical synthesis of the autistic phenomenon and advances that at computational level have been achieved in relation to simulation, emulation and development of support tools related to this complex phenomenon. The above based on more than 50 studies taken from scientific databases, such as: Nature, Scopus, ACM, IEEE, Google Scholar, among others.eng
dc.format.extent18 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.language.isospaspa
dc.publisherCuaderno Activaspa
dc.relation.ispartofCuaderno Activa
dc.rightsCuaderno Activa provee acceso libre inmediato a su contenido bajo el principio de hacer disponible gratuitamente la producción investigativa al ´´público, fomentando un mayor intercambio de conocimiento científico.spa
dc.sourcehttps://ojs.tdea.edu.co/index.php/cuadernoactiva/article/view/425spa
dc.titleAvances en el conocimiento y modelado computacional del cerebro autista: Una revisión de literaturaspa
dc.titleAdvances in knowledge and computational modeling of the autistic brain: A literature revieweng
dc.typeArtículo de revistaspa
dcterms.referencesAguilar, J. (2005). A survey about fuzzy cognitive maps papers. International journal of computational cognition, 3(2), 27-33.spa
dcterms.referencesAlivisatos, P., Chun, M., Church, G., Greenspan, R., Roukes, M., & Yuste, R. (2012). The brain activity map project and the challenge of functional connectomics. Neuron, 74(6), 970-974.spa
dcterms.referencesVeros, M. (2016). VirtuaCyL: desarrollo y validación de un sistema ubicuo basado en Android para refuerzo educativo de niños con autismo dentro de la metodología Teacch (tesis máster en Inteligencia Artificial). Universidad Politécnica de Valencia, Valencia, España.spa
dcterms.referencesAmerican Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (Fifth edition). Recuperado de http://dsm.psychiatryonline.org/doi/book/10.1176/appi.books.9780890425596spa
dcterms.referencesAnderson, J. (2013). The architecture of cognition. Psychology Press. 340.spa
dcterms.referencesBaron, S, et al. (2002). Development of a new screening instrument for autism spectrum disorders - the Q-CHAT. Paper presented at the International Meeting for Autism Research. Orlando, FL.spa
dcterms.referencesBaron, S., Leslie, A. M., & Frith, U. (1985). Does the autistic child have a “theory of mind”?. Cognition, 21(1), 37-46.spa
dcterms.referencesBellani, M., Fornasari, L., Chittaro, L., & Brambilla, P. (2011). Virtual reality in autism: state of the art. Epidemiology and psychiatric sciences, 20(03), 235-238.spa
dcterms.referencesBone, D., Bishop, S., Black, M., Goodwin, M., Lord, C., & Narayanan, S. (2016). Use of machine learning to improve autism screening and diagnostic instruments: Effectiveness, efficiency, and multinstrument fusion. Journal of Child Psychology and Psychiatry, 57(8), 927-937.spa
dcterms.referencesCai, D., & otros. (2013). Improved tools for the brainbow toolbox. Nature methods, 10(6), 540-547.spa
dcterms.referencesCarandini, M., & Heeger, D. (2013). Normalization as a canonical neural computation. Nature Reviews Neuroscience, 14(2), 152-152.spa
dcterms.referencesVidal, L., Carvalho, N., & Fiszman, A. (July 1999). A neurocomputational model for autism. Proceedings oe the IV Brazilian Conference on Neural networks. Congresso Brasileiro de Redes Neurais. Sao José dos Campos, Brazil.spa
dcterms.referencesCastillo, T., Pérez, C., Lara, C., Somodevilla, M., Pineda, I., de Alba, K., y Romero, E. (2016). Authic: Herramienta computacional para niños con espectro autista. XVIII Simposio Internacional de Informática Educativa, Puebla, México.spa
dcterms.referencesCattell, R., & Parker, A. (2012). Challenges for brain emulation: why is building a brain so difficult. Natural intelligence, 1(3), 17-31.spa
dcterms.referencesCererols, R. (2011). Descubrir el Asperger (Segunda edición), 184.spa
dcterms.referencesCorrigan, N., Richards, T., Treffert, D., & Dager, S. (2012). Toward a better understanding of the savant brain. Comprehensive psychiatry, 53(6), 706-717.spa
dcterms.referencesWłodzisław, D., Wiesław, N., Jaroslaw M., Grzegorz, O., Krzysztof, D., Dariusz, M., & Grzegorz, M. (2012). Computational approach to understanding autism spectrum disorders. Computer Science, 13(2), 47-61.spa
dcterms.referencesFrey, J., Mühl, C., Lotte, F., & Hachet, M. (2013). Review of the use of electroencephalography as an evaluation method for human-computer interaction. Recuperado de https://arxiv.org/pdf/1311.2222.pdfspa
dcterms.referencesFriston, K., & Buzsáki, G. (2016). The Functional Anatomy of Time: What and when in the Brain. Trends in cognitive sciences, 20(7). 500-511.spa
dcterms.referencesGalitsky, B. (2013). A computational simulation tool for training autistic reasoning about mental attitudes. Knowledge-based systems, 50(C), 25-43.spa
dcterms.referencesGrandin, T., & Panek, R. (2013). The autistic brain: Thinking across the spectrum. Houghton Mifflin Harcourt. 253.spa
dcterms.referencesHappé, F., & Frith, U. (2006). The weak coherence account: detail-focused cognitive style in autism spectrum disorders. Journal of autism and developmental disorders, 36(1), 5-25.spa
dcterms.referencesHarper, S. (2010). nano-TAB: Specification to facilitate data exchange among nanotechnology resources. Cancer biomedical informatics grid, 32.spa
dcterms.referencesHoudé, O., & Tzourio-Mazoyer, N. (2003). Neural foundations of logical and mathematical cognition. Nature Reviews Neuroscience, 4(6), 507-514.spa
dcterms.referencesHowlin, P. (2012). Understanding savant skills in autism. Developmental Medicine & Child Neurology, 54 (6), 484-484.spa
dcterms.referencesJunek, W. (2007). Mind reading: The interactive guide to emotions. Journal of the Canadian Academy of Child and Adolescent Psychiatry, 16 (4), 182.spa
dcterms.referencesKapur N. (1996). Paradoxical functional facilitation in brain-behavior research. A critical review. Brain, 119(5), 1775-1790.spa
dcterms.referencesKitchenham, B. (2004). Procedures for performing systematic reviews. Software Engineering Group, Department of Computer Science, 33.spa
dcterms.referencesKodandaramaiah, S. B., y otros. (2016). Assembly and operation of the autopatcher for automated intracellular neural recording in vivo. Nature protocols, 11(4), 634-654.spa
dcterms.referencesLecun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436-444.spa
dcterms.referencesLi, K., Guo, L., Li, G., & Liu, T. (2009). Review of methods for functional brain connectivity detection using fMRI. Computerized Medical Imaging and Graphics, 33(2), 131-139.spa
dcterms.referencesLiu, E., & Konkle, A. (2016). Extreme male brain theory of autism. Revue interdisciplinaire des sciences de la santé-Interdisciplinary Journal of Health Sciences, 2(1), 32-43.spa
dcterms.referencesLou, H., Changeux, J., & Rosenstand, A. (2016). Towards a cognitive neuroscience of self-awareness. Neuroscience & Biobehavioral Reviews. 75, 9.spa
dcterms.referencesLovaas, O., Koegel, R., & Schreibman, L. (1979). Stimulus overselectivity in autism: a review of research. Psychological bulletin, 86(6), 1236-1254.spa
dcterms.referencesMarkram, K., & Markram, H. (2010). The intense world theory-a unifying theory of the neurobiology of autism. doi: doi.org/10.3389/fnhum.2010.00224spa
dcterms.referencesMccoy, D., Arrigoni, M., & Gallaher, N. (2015). Optogenetics research drives new laser technologies. Recuperado de http://www.laserfocusworld.com/articles/print/volume-51/issue-06/biooptics-world/biooptics-features/optogenetics-optogenetics-research-drives-new-laser-technologies.htmlspa
dcterms.referencesMen, W., Falk, D., Sun, T., Chen, W., Li, J., Yin, D., Zang, L., & Fan, M. (2013). The corpus callosum of Albert Einstein‘s brain: another clue to his high intelligence?. doi.org/10.1093/brain/awt252spa
dcterms.referencesMottron, L., & Burack, J. (2001). Enhanced perceptual functionning in the development of autism. Lawrence Earlbaum Associates,148. J. Burack, T. Charman, N. Yirmiya, P. Zelazo (Eds.) (2001), , The Development of Autism: Perspectives from Theory and Research.spa
dcterms.referencesLawrence Erlbaum Associates, Mahwah. Mottron, L., Bouvet, L., Bonnel, A., Samson, F., Burack, J. A., Dawson, M., & Heaton, P. (2013). Veridical mapping in the development of exceptional autistic abilities. Neuroscience & Biobehavioral Reviews, 37(2), 209-228.spa
dcterms.referencesMuñoz, R., Nöel, R., Kreisel, S., y Mancilla, F. (2012). Proyect@ Emociones: software para estimular el desarrollo de la empatía en niños y niñas con trastornos del espectro autista. Nuevas Ideas en Informática Educativa, 59-64.spa
dcterms.referencesNeubauer, S. (2003). Tomografía por emisión de positrones (PET). Recuperado de http://www.cirujanosdechile.cl/revista_anteriores/PDF%20Cirujanos%202003_01/spa
dcterms.referencesNguyen, A., Yosinski, J., & Clune, J. (2016). Understanding innovation engines: Automated creativity and improved stochastic optimization via deep learning. Evolutionary Computation, 24(3), 545-572.spa
dcterms.referencesO’Laughlin, C., & Thagard, P. (2000). Autism and coherence: A computational model. Mind & Language, 15(4), 375-392.spa
dcterms.referencesOjeda, J. (2015). Un método basado en algoritmos genéticos de apoyo al diagnóstico TEA. Actas de Ingeniería, 1, 84-93.spa
dcterms.referencesOlds, J., Rubin, P., MacGregor, D., Madou, M., McLaughlin, A., Oliva, A.,€¦Wong, P. (2013). Implications: Human cognition and communication and the emergence of the cognitive society. Science Policy Reports, 223-253.spa
dcterms.referencesOzonoff, S., Pennington, B., & Rogers, S. (1991). Executive function deficits in high-functioning autistic individuals: relationship to theory of mind. Journal of child Psychology and Psychiatry, 32(7), 1081-1105.spa
dcterms.referencesParsons, S., & Cobb, S. (2011). State-of-theart of virtual reality technologies for children on the autism spectrum. European Journal of Special Needs Education, 26(3), 355-366.spa
dcterms.referencesPellicano, E., & Burr, D. (2012). When the world becomes ‘too real’: a Bayesian explanation of autistic perception. Trends in cognitive sciences, 16(10), 504-510.spa
dcterms.referencesPlomin, R., Haworth, & Davis, O. (2009). Common disorders are quantitative traits. Nature Reviews Genetics, 10, 872-878.spa
dcterms.referencesPortero, P. (2016). Automatización de las torres de Hanói: Herramienta de apoyo para el estudio de la función ejecutiva “Planificación” en niños con síndrome de Asperger. CIAIQ2016, 4, 104-112.spa
dcterms.referencesPuerto, E. (2016). Estado actual de los estudios cerebrales a nivel computacional. Metanoia, 15.spa
dcterms.referencesRamachandran, V. (2012). Lo que el cerebro nos dice. Paidós, 304-313.spa
dcterms.referencesRamachandran, V., & Oberman, L. (2007). Broken mirrors: a theory of autism. Scientific American, 17, 20-29.spa
dcterms.referencesRizzolatti, G., & Sinigaglia, C. (2016). The mirror mechanism: a basic principle of brain function. Nature Reviews Neuroscience, 17(12), 757-765.spa
dcterms.referencesRosenberg, A., Patterson, J., & Angelaki, D.(2015). A computational perspective on autism. Proceedings of the National Academy of Sciences, 112(30), 9158-9165.spa
dcterms.referencesScassellati, B. (2005). Quantitative metrics of social response for autism diagnosis. doi:10.1109/ROMAN.2005.1513843.spa
dcterms.referencesSelfe, L., & Nadia. (1977). Nadia: A case of extraordinary drawing ability in an autistic child. Academic Press, 143.spa
dcterms.referencesSon, J., & Mishra, A. (2016). A Survey of Brain Inspired Technologies for Engineering. doi: 10.1109/RoboMech.2016.7813135spa
dcterms.referencesTammet, D. (2007). Born on a blue day: Inside the extraordinary mind of an autistic savant. Simon and Schuster, 240.spa
dcterms.referencesTarantino, L., Mazza, M., Valenti, M., & De Gasperis, G. (2016). Towards an integrated approach to diagnosis, assessment and treatment in autism spectrum disorders via a gamified TEL system. In Methodologies and intelligent systems for technology enhanced learning, 6th International Conference, Sevilla, España.spa
dcterms.referencesTreffert, D., & Christensen, D. (2005). Inside the mind of a savant. Scientific American, 293(6), 108-113.spa
dcterms.referencesTronnier, V., & Rasche, D. (2015). Deep brain stimulation. Textbook of Neuromodulation, 61-72.spa
dcterms.referencesUniversity-of-Maryland. (2012). Tomografía por emisión de positrones (TEP). Retrieved from http://umm.edu/Health/Medical/SpanishEncy/Articles/Tomografia-por-emision-de-positrones-TEPspa
dcterms.referencesVattikuti, S., & Chow, C. (2010). A computational model for cerebral cortical dysfunction in autism spectrum disorders. Biological psychiatry, 67(7), 672-678.spa
dcterms.referencesWelling, H. (1994). Prime number identification in idiots savants: Can they calculate them?. Journal of autism and developmental disorders, 24(2), 199-207.spa
dcterms.referencesYeo, B., & Eickhoff, S. (2016). Systems neuroscience: A modern map of the human cerebral cortex. Nature, 536, 152-154.spa
dcterms.referencesZimmerman, A. (Ed.). (2008). Autism: Current theories and evidence. Baltimore, EEUUspa
dc.publisher.placeColombiaspa
dc.relation.citationeditionVol.9 (2017)spa
dc.relation.citationendpage125spa
dc.relation.citationissue(2017)spa
dc.relation.citationstartpage109spa
dc.relation.citationvolume9spa
dc.relation.citesPuerto, E. (2017). Avances en el conocimiento y modelado computacional del cerebro autista: Una revisión de literatura. Cuaderno activa, 9, 109-125.
dc.relation.ispartofjournalCuaderno Activaspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.creativecommonsAtribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)spa
dc.subject.proposalNeurociencia computacionalspa
dc.subject.proposalComputational neuroscienceeng
dc.subject.proposalautismospa
dc.subject.proposalautismeng
dc.subject.proposaltecnologías de exploración cerebralspa
dc.subject.proposalbrain scanning technologieseng
dc.subject.proposalsavanteng
dc.subject.proposalmodelos computacionales TEAspa
dc.subject.proposalcomputational models of TEAeng
dc.subject.proposalherramientas de apoyo TEAspa
dc.subject.proposalsupport tools TEAeng
dc.subject.proposalanatomía del cerebro autistaspa
dc.subject.proposalanatomy of the autistic braineng
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