Comparison between the Autism Diagnostic Interview Revised (ADI-R) and the Perceptual Behavioural Precision Scale (PS-PC-ASD)

Comparison between the Autism Diagnostic Interview Revised (ADI-R) and the Perceptual Behavioural Precision Scale (PS-PC-ASD) for the Diagnosis of Individuals with Autism Spectrum Disorder

PhD Manuel Ojea Rúa

European Modern Studies Journal, 9(6), 368-383

Abstract

Ojea (2023) has published a Perceptual-Behavioural Precision Scale (PS-PC-ASD) for the diagnosis of individuals with autism spectrum disorder (ASD), which are made up of three main domains weighted based on the number of items 
that each domain contains: 1) the perceptual-cognitive domain, 2) the social domain, and 3) the practical domain, in the aim of incorporating the measurement of cognitive values that involve the level of neuropsychological and biological processing of information, starting from the input of information of the sensory-perceptual memory into the semantic and episodic memory if possible, as well as the interconceptual relationships developed by the coding processes, which provide this access through working memory.

This study compared the data resulting from the ASD' diagnosis, found in accordance with the PS-PC-ASD Scale, in relation to the Autism Diagnostic Interview Revised (ADI-R) (Rutter et al., 2003), which is based mainly on the basic criteria of the currently official International Classification of the American Psychiatric Association (APA) (2013).

The main aim of this study is therefore to observe whether there're statistically significant differences in the diagnosis of people with ASD between the two Scales, the ADI-R Scale and the PS-PC-ASD Scale.

The comparative levels, found through the Wilcoxon statistical test, showed that there were significant differences in the diagnostic results of the participants, according to diagnostic Scale applied (sig: .00).

Furthermore, the Kruskal-Wallis non-parametric test found the variables of 'gender' and 'age' of the participants were interdependent for both Scales. Results didn't were shown significant differences in the variable ‘gender’ for the ADI-R Scale, non-significant critical levels were obtained (sig: .27), nor for the PS-PC-ASD Scale (sig: .81). However, when the PS-PC-ASD Scale was used, significant critical levels were observed for the variable ‘age’ (sig: .01), whereas in the ADI-R Scale, no statistically significant levels were found for ‘age’ variable (sig: .09).

Keywords: ASD, Diagnostic Scale, Cognition, Perception, Social, Behaviour, Neuropsychological Processing.

References

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders-text revision (4th ed.). Washington, DC: Author. https://doi.org/10.1176/appi.books.9780890425596

Baribeau, D. A., Doyle-Thomas, K. A., Dupuis, A., Iaboni, A., Crosbie, J., McGinn, H., ... Anagnostou, E. (2015). Examining and comparing social perception abilities across childhood-onset neurodevelopmental disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 54, 479–486. https://pubmed.ncbi.nlm.nih.gov/26004663/

Boogert, N. J, Giraldeau, L. A., & Lefebvre L. (2008). Song complexity correlates with learning ability in zebra finch males. Anim. Behav., 76, 51735–41. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://biology.mcgill.ca/faculty/lefebvre/articles/boogert_song&learning_08.pdf

Bramao, I., Karlsson, A., & Johannson, M. (2017). Mental Reinstatement of encoding Context Improves Episodic Remembering. Cortex, 94(1), 15-26. https://pubmed.ncbi.nlm.nih.gov/28710908/

Brunsdon, V. E., & Happé, F. (2014). Exploring the ‘fractionation’ of autism at the cognitive level. Autism, 18(1), 17–30. https://pubmed.ncbi.nlm.nih.gov/24126870/

Colombi, C., Liebal, K., Tomasello, M., Young, G., Warneken, F., & Rogers, S. J. (2009). Examining correlates of cooperation in autism imitation, joint attention, and understanding intentions. Autism, 13, 2143–63. https://pubmed.ncbi.nlm.nih.gov/19261685/

Cook, J. L., den Ouden, H. E. M., Heyes, C. M., & Cools, R. (2014). The social dominance paradox. Curr. Biol., 24(23), 2812–16. https://pubmed.ncbi.nlm.nih.gov/25454588/

Coveney, A. P., Switzer, T., Corrigan, M. A., & Redmond, H. P. (2013). Context-dependent memory in two learning environments: the tutorial room and the operating theatre. BMC Med Educ.,18(13) 1–7. https://pubmed.ncbi.nlm.nih.gov/24127650/

Davis, G., & Plaisted-Grant, K. (2015). Low endogenous neural noise in autism. Autism, 19(3), 351–362. https://pubmed.ncbi.nlm.nih.gov/25248666/

DeFelipe, J., Lopez-Cruz, P. L., Benavides-Piccione, R., Bielza, C., Larranaga, P., Anderson, S., ... Ascoli, G. A. (2013). New insights into the classification and nomenclature of cortical GABAergic interneurons. Nature Reviews Neuroscience, 14(3), 202–216. https://doi.org/10.1038/ nrn3444

Doss, A. J. (2005). Evidence-based diagnosis: Incorporating diagnostic instruments into clinical practice. Journal of the American Academy of Child and Adolescent Psychiatry, 44, 947–952. https://pubmed.ncbi.nlm.nih.gov/16113624/

Farmer, C. A., & Aman, M. G. (2009). Development of the Children’s Scale of Hostility and Aggression: Reactive/Proactive (C-SHARP). Research in Developmental Disabilities, 30, 1155–1167. https://pubmed.ncbi.nlm.nih.gov/19375274/

Fiske, S. T., & Taylor, S. E. (2013). Social Cognition: From Brains to Culture London: Sage. https://sk.sagepub.com/book/mono/social-cognition-2e/toc#_

Fletcher-Watson, S., Findlay, J. M., Leekam, S. R., & Benson, V. (2008). Rapid detection of person information in a naturalistic scene. Perception, 37, 4571–83. https://pubmed.ncbi.nlm.nih.gov/18546664/

Floyer-Lea, A., Wylezinska, M., Kincses, T., & Matthews, P. M. (2006). Rapid modulation of GABA concentration in human sensorimotor cortex during motor learning. Journal of Neurophysiology, 95(3), 1639–1644. https ://doi.org/10.1152/jn.00346 .2005

Ford, T. C., & Crewther, D. P. (2016). A comprehensive review of the 1H-MRS metabolite spectrum in autism spectrum disorder. Frontiers in Molecular Neuroscience, 9. https://doi.org/10.3389/ fnmol .2016.00014

Gaetz, W., Bloy, L., Wang, D. J., Port, R. G., Blaskey, L., Levy, S. E., & Roberts, T. P. L. (2014). GABA estimation in the brains of children on the autism spectrum: Measurement precision and regional cortical variation. Neuroimage, 86, 1–9. https://doi.org/10.1016/j.neuro image .2013.05.068

Goren, C. C., Sarty, M., & Wu, P. Y. K. (1975). Visual following and pattern discrimination of face-like stimuli by newborn infants. Pediatrics, 56, 4544–49. https://pubmed.ncbi.nlm.nih.gov/1165958/

Grant, H. M., Bredahl, L. C. Clay, J., Ferrie, J., Groves, J. E., McDorman, T.A., & Dark, V. J. (1998) Context dependent memory of meaningful material: Information for students. Applied Cognitive Psychology, 2(6), 617-623. https://psycnet.apa.org/record/1998-11899-006

Green, M. F, Horan, W. P, & Lee, J. (2015). Social cognition in schizophrenia. Nat. Rev. Neurosci., 16, 10620–31. https://pubmed.ncbi.nlm.nih.gov/26373471/

Happé, F., Cook, J. L., & Bird, G. (2017). The structure of social cognition: In(ter)dependence of sociocognitive processes. Annual Review of Psychology, 68, 243–267. https://www.annualreviews.org/content/journals/10.1146/annurev-psych-010416-044046

Happé, F., Frith, U. (2014). Annual research review: Towards a developmental neuroscience of atypical social cognition. J. Child Psychol. Psychiatry, 55, 6553–77. https://europepmc.org/article/med/24963529

Hashemi, E., Ariza, J., Rogers, H., Noctor, S. C., & Martinez-Cerdeno, V. (2017). The number of parvalbumin-expressing interneurons is decreased in the prefrontal cortex in autism. Cerebral Cortex, 27(3), 1931–1943. https://doi.org/10.1093/cercor/bhw021

Hattingen, E., Lückerath, C., Pellikan, S., Vronski, D., Roth, C., Knake, S., … Pilatus, U. (2014). Frontal and thalamic changes of GABA concentration indicate dysfunction of thalamofrontal networks in juvenile myoclonic epilepsy. Epilepsia, 55(7), 1030–1037. https ://doi.org/10.1111/epi.12656.

Hertrich, I., Dietrich, S., Blum, C., & Ackermann, H. (2021). The role of the dorsolateral prefrontal cortex for speech and language processing. Frontiers in Human Neuroscience, 15, Article 645209. https://doi.org/10.3389/fnhum.2021. 645209

Heyes, C. (2012). What's social about social learning?. J. Comp. Psychol., 126, 2193–202. https://pubmed.ncbi.nlm.nih.gov/21895355/

Heyes, C., & Pearce, J. M. (2015). Not-so-social learning strategies. Proc. R. Soc., 282, 1802, 20141709. https://royalsocietypublishing.org/rspb/article/282/1802/20141709/77539/Not-so-social-learning-strategiesNot-so-social

Hof, P. R., Glezer, I. I., Conde, F., Flagg, R. A., Rubin, M. B., Nimchinsky, E. A., & Vogt-Weisenhorn, D. M. (1999). Cellular distribution of the calcium-binding proteins parvalbumin, calbindin, and calretinin in the neocortex of mammals: Phylogenetic and developmental patterns. Journal of Chemical Neuroanatomy, 16(2), 77–116. https://doi.org/10.1016/s0891-0618(98)00065-9

Holden, B., & Gitlesen, J. P. (2009). The overlap between psychiatric symptoms and challenging behaviors: A preliminary study. Research in Developmental Disabilities, 30, 210–218. https://pubmed.ncbi.nlm.nih.gov/18455364/

Hupbach, A., Hardt, O., Gomez, R., & Nadel, L. (2008). The dynamics of memory: Context-dependent updating. Learning and Memory. 15(8) 574-579. https://pubmed.ncbi.nlm.nih.gov/18685148/

International Molecular Genetic Study of Autism Consortium (IMGSAC). (2001). A genomewide screen for autism: strong evidence for linkage to chromosomes 2q, 7q, and 16p. American Society of Human Genetics, 69, 570–58. https://pubmed.ncbi.nlm.nih.gov/11481586/

Isarida, T., & Isarida, T. K. (2014). Environmental context-dependent memory. [Online] Available at http://www.ssu.ac.jp/home/isarida/personal/Paper/Environmental%20context-dependent%20memory.pdf

Jansen, J. F. A., Backes, W. H., Nicolay, K., & Kooi, M. E. (2006). 1H MR spectroscopy of the brain: Absolute quantification of metabolites. Radiology, 240(2), 318–332. https://doi.org/10.1148/radio l.24020 50314.

Johansson, M., Gillberg, C., & Rastam, M. (2009). Autism spectrum conditions in individuals with Mobius sequence, CHARGE syndrome and oculoauriculo-veterbal spectrum: Diagnostic aspects. Research in Developmental Disabilities, 30, 9–24. https://pubmed.ncbi.nlm.nih.gov/19709852/

Kikuchi, Y., Senju, A., Tojo, Y., Osanai, H., & Hasegawa, T. (2009). Faces do not capture special attention in children with autism spectrum disorder: A change blindness study. Child Dev, 80, 51421–33. https://pubmed.ncbi.nlm.nih.gov/19765009/

Krnjević, K., & Schwartz, S. (1967). The action of γ-Aminobutyric acid on cortical neurones. Experimental Brain Research, 3(4), 320–336. https ://doi.org/10.1007/bf002 37558.

Lefebvre, L., & Giraldeau, L. (1996). Is social learning an adaptive specialization? En C. M. Heyes & B. G. Galef, Social Learning and the Roots of Culture (pp. 107–52). San Diego: Academic. https://www.researchgate.net/publication/232499114_Social_Learning_in_Animals_The_Roots_of_Culture

Lewczyk, C. M., Garland, A. F., Hurlburt, M. S., Gearity, J., & Hough, R. L. (2003). Comparing DISC-IV and clinician diagnoses among youth receiving public mental health services. Journal of the American Academy of Child and Adolescent Psychiatry, 42, 349–356. https://pubmed.ncbi.nlm.nih.gov/12595789/

Lord, C., Rutter, M., & LeCouteur, A. (1994). Autism Diagnostic Interview-Revised (ADI-R): A revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. Journal of Autism and Developmental Disorders, 24, 659–686. https://pubmed.ncbi.nlm.nih.gov/7814313/

Lord, C., Rutter, M., DiLavore, P. C., & Risi, S. (1999). ADOS. Autism Diagnostic Observation Schedule. Manual. Los Angeles: WPS. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.hogrefe-tea.com/recursos/Ejemplos/ADOS-2_extractoWEB.pdf

Lord, C., Petkova,E., Hus,V., Gan,W., Lu,F., Martin, D. M. ... Risi, S. (2012). Amultisite study of the clinical diagnosis of different autism spectrum disorders. Archives of General Psychiatry, 69, 306–313. https://pubmed.ncbi.nlm.nih.gov/22065253/

LoVullo, S. V., & Matson, J. L. (2009). Comorbid psychopathology in adults with autism spectrum disorders and intellectual disabilities. Research in Developmental Disabilities, 30, 1288–1298. https://pubmed.ncbi.nlm.nih.gov/19505790/

Margari, L., De Giacomo, A., Craig, F., Palumbi, R., Peschechera, A., Margari, M., … Dicuonzo, F. (2018). Frontal lobe metabolic alterations in autism spectrum disorder: A (1)H-magnetic resonance spectroscopy study. Neuropsychiatric disease and treatment, 14, 1871–1876. https ://doi.org/10.2147/NDT.S1653 75.

Matson, J. L., González, M., & Wilkins, J. (2009). Validity study of the Autism Spectrum Disorders-diagnostic for children (ASD-DC). Research in Autism Spectrum Disorders, 3, 196–206. https://www.sciencedirect.com/science/article/pii/S1750946708000561

McDermott, K. B., & Roediger, H. L. (2013) Memory, encoding, storage, retrieval. (Online). Available at http://nobaproject.com/modules/memory-encoding-storage-retrieval

Miniscalco, C., & Gillberg, C. (2009). Non-word repetition in young school-ages children with language impairment and/or neuropsychiatric disorder. Research in Developmental Disabilities, 30, 1145–1154. https://pubmed.ncbi.nlm.nih.gov/19375275/

Morton, J., & Johnson, M. H. (1991). CONSPEC and CONLERN: A two-process theory of infant face recognition. Psychol. Rev., 98, 2164–81. https://pubmed.ncbi.nlm.nih.gov/2047512/

Nijmeijer, J. S., Minderaa, R. B., Buitelaar, J. K., Mulligan, A., Hartman, C. A., & Hoekstra, P. J. (2008). Attention-deficit/hyperactivity disorder and social dysfunctioning. Clinical Psychology Review, 28(4), 692–708. https://pubmed.ncbi.nlm.nih.gov/18036711/

Ojea, M. (2023). Perceptual-Behavioural Precision Scale. PS-PC-ASD. Lima (Perú): Ed. Barcelona. https://libreriaites.com/producto/escala-de-precision-perceptivo-conductual-ep-pc-tea/

Pellicano, E. (2012). The development of executive function in autism. Autism Research and Treatment, 146132. https://pubmed.ncbi.nlm.nih.gov/22934168/

Pellicano, E., & Burr, D. (2006). When the world becomes ‘too real’: A Bayesian explanation of autistic perception. Trends in Cognitive Sciences, 16, 504–510. https://pubmed.ncbi.nlm.nih.gov/22959875/

Pizzarelli, R., & Cherubini, E. (2011). Alterations of GABAergic signaling in autism spectrum disorders. Neural Plasticity. https ://doi. org/10.1155/2011/297153

Purcell, D. G., & Stewart, A. L. (1988). The face-detection effect: configuration enhances detection. Percept. Psychophys, 43, 4355–66. https://pubmed.ncbi.nlm.nih.gov/3362664/

Puts, N. A. J., Wodka, E. L., Harris, A. D., Crocetti, D., Tommerdahl, M., Mostofsky, S. H., & Edden, R. A. E. (2017). Reduced GABA and altered somatosensory function in children with autism spectrum disorder. Autism Research, 10(4), 608–619. https://doi.org/10.1002/ aur.1691

Reader, S. M., & Laland, K. N. (2002). Social intelligence, innovation, and enhanced brain size in primates. Proc Natl Acad Sci USA, 99(7), 4436–41. https://pubmed.ncbi.nlm.nih.gov/11891325/

Reader, S. M., Hager, Y., & Laland, K. N. (2011). The evolution of primate general and cultural intelligence. Philos. Trans. R. Soc. B 366, 15671017–27. https://pmc.ncbi.nlm.nih.gov/articles/PMC3049098/

Risi, S., Lord, C., Gotham, K., Corsello, C., Chrysler, C., Szatmari, P., Cook-Jr, E. H., ... Pikles, A. (2006). Combining information from multiple sources in the diagnosis of autism spectrum disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 45, 1094–1103. https://pubmed.ncbi.nlm.nih.gov/16926617/

Rutter, M., Le Couteur, A., & Lord, C. (2003). ADI-R Autism Diagnostic Interview Revised Manual. Los Angeles: Western Psychological Services. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.hogrefe-tea.com/recursos/Ejemplos/ADI-R-Extracto-Manual.pdf

Salva, O. R, Farroni, T., Regolin, L., Vallortigara, G., & Johnson, M. H. (2011). The evolution of social orienting: evidence from chicks (Gallus gallus) and human newborns. PLOS ONE, 6, 4e18802. https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0018802

Seyfarth, R. M., & Cheney, D. L. (2015). Social cognition. Anim. Behav., 103, 191–202. https://psycnet.apa.org/record/2015-19417-027

Shah, P., Gaule, A., Bird, G., & Cook, R. (2013). Robust orienting to protofacial stimuli in autism. Curr. Biol., 23, 24, R1087–8. https://pubmed.ncbi.nlm.nih.gov/24355781/

Smith, S. Handy, J., Angello, G., & Manzaon, I. (2014). Effects of Similarity on Environmental Context Cueing. Memory, 22(5), 493–508. https://pubmed.ncbi.nlm.nih.gov/23721293/

Smith, S., & Vela, E. (2001) Environmental context-dependent memory: A review and meta-analysis. Psychonomic Bulletin & Review, 8(2), 203-220. https://psycnet.apa.org/record/2001-07942-002

Snow, P. J. (2016). The structural and functional organization of cognition. Frontiers in Human Neuroscience, 10, Article 501. https://doi.org/10.3389/fnhum.2016.00501

Sodian, B., & Thoermer, C. (2008). Precursors to a theory of mind in infancy: Perspectives for research on autism. Quarterly Journal of Experimental Psychology (Hove), 61(1), 27–39. https://pubmed.ncbi.nlm.nih.gov/18038336/

Sung, Y., Dawson, G., Munson, J., Estes, A., Schellenberg, G. D., & Wijsman, E. M. (2005). Genetic investigation of quantitative traits related to autism: Use of multivariate polygenic models with ascertainment adjustment. American Journal of Human Genetics, 76, 68–81. https://pubmed.ncbi.nlm.nih.gov/15547804/

Tanji, J., & Hoshi, E. (2008). Role of the lateral prefrontal cortex in executive behavioral control. Physiological Reviews, 88(1), 37–57. https://doi.org/10.1152/physrev.00014.2007

Tomalski, P., Csibra, G., & Johnson, M. H. (2009). Rapid orienting toward face-like stimuli with gaze-relevant contrast information. Perception, 38, 4569–78. https://pubmed.ncbi.nlm.nih.gov/19522324/

Tulving, E., & Thomson, D. M. (1973). Encoding specificity and retrieval processes in episodic memory. Psychological Review, 80(5) 352-373. https://psycnet.apa.org/record/2005-09647-002

Wang, Y., Zhang, P., & Wyskiel, D. R. (2016). Chandelier cells in functional and dysfunctional neural circuits. Frontiers in Neural Circuits, 10, Article 33. https://doi.org/10.3389/ fncir.2016.00033

Zaitsev, A. V., Gonzalez-Burgos, G., Povysheva, N. V., Kroner, S., Lewis, D. A., & Krimer, L. S. (2005). Localization of calcium-binding proteins in physiologically and morphologically characterized interneurons of monkey dorsolateral prefrontal cortex. Cerebral Cortex, 15(8), 1178–1186. https://doi.org/10.1093/cercor/bhh218

 Localización del Instituto de Investagaciones Científicas en Autismo, localizado en la Universidad de Vigo.

VALIDATION OF THE PRECISION SCALE PERCEPTIVE-COGNITIVE TO PEOLE WITH ASD DIAGNOSIS 'PS-PC-ASD'

Please, check the publication: https://ejtas.com/index.php/journal/article/view/1751

VALIDATION OF PRECISON SCALE PERCEPTIVE-COGNITVE TO PEOPLE WIHT ASD DIAGNOSIS 'PS-PC-ASD'

INTRODUCTION

Ojea, M. (2026). Validation of Precision Sale Perceptive-Cognitive to Peple with ASD diagnosis PS-PC-ASD'.  European Journal of Theoretical and Applied Sciences, 4(1), 147-168.

Ojea (2023) has published the Precision Scale Perceptivo- Cognitive (PS-PC-ASD), with the aim of determining the diagnosis of people with autism spectrum disorder (ASD), which consists of three main weighted domains: 1) the perceptual-cognitive domain, 2) the social domain, and 3) the practical domain, in order to incorporate the measurement of cognitive neural values, which involve the level of neuropsychological and biological processing of information, from the input of information through perceptual sensory memory to semantic memory and its related episodic memory, as well as the development of interconceptual relationships that develop throughout the processes of information coding through working memory.

In this study, the PS-PC-ASD scale has been validated for a total of N: 346 participants, which is a significantly broad sample, being a highly specific group, of which 112 don’t have any specific diagnosis, 140 have a level 1 autism diagnosis, 67 have level 2, and 27 have level 3, as the International Classification of the American Psychiatric Association (APA, 2013).

The comparative data, obtained using a one-way ANOVA test, as well as the subsequent transformation of all direct scores (DS) found in the observation questionnaire into typical scores (Z), were used to construct the three categorical dimensions with typified scores: 1) processing category, 2) social category, and 3) behavioural category, whose typical sum provides a highly accurate analysis of explanatory variance, analysed using stepwise linear regression analysis, in which the three dimensions exhibit significant critical levels explaining the diagnostic data within the three categories (sig: .00).

Finally, the correspondence of the total sum of typical scores found in accordance with the corresponding percentile, in intervals of five, the 50th percentile has corresponded to the typical average sum of -1.38, from which point a diagnosis compatible with autism can be definitively considered. From this percentile onwards, an increase in intensity implies greater severity in the diagnostic group for this disorder.

In essence, the initial data found for the construction of the Scale has been corroborated, concluding that the Diagnostic Precision scale is a highly effective and positive instrument for the specific diagnostic precision of individuals with ASD.

Keywords: autism spectrum disorder, diagnostic test, perception, cognition, semantic memory, source memory, episodic memory.

REFERENCES

Abell, F., Krams, M., Ashburner, J., Passingham, R., Friston, K., Frackowiak, R., ... Frith, U. (1999). The neuroanatomy of autism: A voxel-based whole brain analysis of structural scans. NeuroReport, 10(8), 1647–1651. https://pubmed.ncbi.nlm.nih.gov/10501551/

Adorjan, I., Ahmed, B., Feher, V., Torso, M., Krug, K., Esiri, M., … Szele, F. G. (2017). Calretinin interneuron density in the caudate nucleus is lower in autism spectrum disorder. Brain, 140(7), 2028–2040. https://doi.org/10.1093/brain/awx131

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. https://doi.org/10.1176/appi.books.9780890425596

Amina, S., Falcone, C., Hong, T., Wolf-Ochoa, M. W., Vakilzadeh, G., Allen, E., … Martinez-Cerdeno, V. (2021). Chandelier cartridge density is reduced in the prefrontal cortex in autism. Cerebral Cortex, 31(6), 2944–2951. https://doi.org/10.1093/cercor/bhaa402

Ariza, J., Rogers, H., Hashemi, E., Noctor, S. C., & Martinez-Cerdeno, V. (2018). The number of chandelier and basket cells are differentially decreased in prefrontal cortex in autism. Cerebral Cortex, 28(2), 411–420. https://doi.org/10.1093/cercor/bhw349

Beer, J. S., John, O. P., Scabini, D., & Knight, R. T. (2006). Orbitofrontal cortex and social behavior: Integrating selfmonitoring and emotion-cognition interactions. Journal of Cognitive Neuroscience, 18(6), 871–879. https://doi.org/10.1162/jocn.2006.18.6.871

Behrens, T. E. J., Johansen-Berg, H., Woolrich, M. W., Smith, S. M., WheelerKingshott, C. A. M., Boulby, P. A., … Mathews, P. M. (2003). Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nature Neuroscience, 6(7), 750–757. https://pubmed.ncbi.nlm.nih.gov/12808459/

www.ejtas.com E u ropean Journal of Theoretical and Applied S(IcSiSeNn c2e7s8-76447 ) 2 026 | Volum4e | Numbe1r

19

Boucher, J., Cowell, P., Howard, M., Broks, P., Farrant, A., Roberts, N., & Mayes, A. (2005). A combined clinical, neuropsychological, and neuroanatomical study of adults with high functioning autism. Cognitive Neuropsychiatry, 10(3), 165–213. https://pubmed.ncbi.nlm.nih.gov/16571459/

Bowler, D. M., Gardiner, J. M., & Gaigg, S. B. (2007). Factors affecting conscious awareness in the recollective experience of adults with Asperger’s syndrome. Consciousness and Cognition, 16(1), 124–143. https://doi.org/10.1016/j.concog.2005.12.001

Bowler, D. M., Gardiner, J. M., & Grice, S. (2000). Episodic memory and remembering in adults with Asperger’s syndrome. Journal of Autism and Developmental Disorders, 30(4), 305–316. https://doi.org/10.1023/a:1005575216176

Carter, A. S., Volkmar, F. R., Sparrow, S. S., Wang, J. J., Lord, C., Dawson, G., … & Schopler, E. (1998). The Vineland Adaptive Behavior Scales: Supplementary norms for individuals with autism. Journal of Autism and Developmental Disorders, 28(4). 287-302. https://doi.org/10.1023/A:1026056518470

Casanova, M. F., van Kooten, I. A. J., Switala, A. E., van Engeland, H., Heinsen, H., Steinbusch, H. W. M., ... Schmitz, Ch. (2006). Abnormalities of cortical minicolumnar abnormalities in autism. Acta Neuropathologica, 112(3), 287–303. https://pubmed.ncbi.nlm.nih.gov/16819561/

Cohen, I. L. (2007). A neural network model of autism: Implications for theory and treatment. In D. Mareschal, S. Sirois, & G. Westermann (Eds.), Neuroconstructivism, Vol. II: Perspectives and prospects (pp. 231–264). Oxford, UK: Oxford University Press. https://www.researchgate.net/publication/232799076_A_neural_network_model_of_autism_Implications_for_theory_and_treatment

D’Angelo, E., & Casali, S. (2012). Seeking a unified framework for cerebellar function and dysfunction: From circuit operations to cognition. Frontiers in Neural Circuits, 6, 116. https://doi.org/10.3389/fncir.2012.00116

DeFelipe, J., Lopez-Cruz, P. L., Benavides-Piccione, R., Bielza, C., Larranaga, P., Anderson, S., … Ascoli, G. A. (2013). New insights into the classification and nomenclature of cortical GABAergic interneurons. Nature Reviews Neuroscience, 14(3), 202–216. https://doi.org/10.1038/nrn3444

Fatemi, S. H., Folsom, T. D., Reutiman, T. J., & Thuras, P. D. (2009). Expression of GABA(B) receptors is altered in brains of subjects with autism. Cerebellum, 8(1), 64–69. https://doi.org/10.1007/s12311-008-0075-3

Fields, R. D. (2008). White matter in learning, cognition and psychiatric disorders. Trends in Neurosciences, 31(7), 361–370. https://pubmed.ncbi.nlm.nih.gov/18538868/

Friston, K. (2009). Causal modelling and brain connectivity in functional magnetic resonance imaging. PLoS Biology, 7(2), e1000033. https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1000033

Gaigg, S. B., Gardiner, J. M., & Bowler, D. M. (2008). Free recall in autism spectrum disorder: the role of relational and item-specific encoding. Neuropsychologia, 46(4), 993–999. https://doi.org/10.1016/j.neuropsychologia.2007.11.011

Greicius, M. (2008). Resting-state functional connectivity in neuropsychiatric disorders. Current Opinion in Neurology, 21(4), 424–430. https://pubmed.ncbi.nlm.nih.gov/18607202/

Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Van Wedeen, J., & Spoms, O. (2008). Mapping the structural core of human cerebral cortex. PLoS Biology, 6(7), 1479–1493. https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.0060159

Hagmann, P., Thiran, J. P., Jonasson, L., Vandergheynst, P., Clarke, S., Maeder, P., & Meuli, R. (2003). DTI mapping of human brain connectivity: Statistical fibre tracking and virtual dissection. NeuroImage, 19(3), 545–554. https://pubmed.ncbi.nlm.nih.gov/12880786/

Happè, F. (1999). Autism: Cognitive deficit or cognitive style? Trends in Cognitive Sciences, 3(6), 216–222. https://pubmed.ncbi.nlm.nih.gov/10354574/

www.ejtas.com E u ropean Journal of Theoretical and Applied S(IcSiSeNn c2e7s8-76447 ) 2 026 | Volum4e | Numbe1r

20

Happè, 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. https://pubmed.ncbi.nlm.nih.gov/16450045/

Hashemi, E., Ariza, J., Rogers, H., Noctor, S. C., & Martinez-Cerdeno, V. (2017). The number of parvalbumin-expressing interneurons is decreased in the prefrontal cortex in autism. Cerebral Cortex, 27(3), 1931–1943. https://doi.org/10.1093/cercor/bhw021

Herbert, M. R. (2005). Large brains in autism: The challenge of pervasive abnormality. Neuroscientist, 11(5), 417–440. https://pubmed.ncbi.nlm.nih.gov/16151044/

Hertrich, I., Dietrich, S., Blum, C., & Ackermann, H. (2021). The role of the dorsolateral prefrontal cortex for speech and language processing. Frontiers in Human Neuroscience, 17(15), Article 645209. https://doi.org/10.3389/fnhum.2021.645209

Hof, P. R., Glezer, I. I., Conde, F., Flagg, R. A., Rubin, M. B., Nimchinsky, E. A., & Vogt Weisenhorn, D. M. (1999). Cellular distribution of the calcium-binding proteins parvalbumin, calbindin, and calretinin in the neocortex of mammals: Phylogenetic and developmental patterns. Journal of Chemical Neuroanatomy, 16(2), 77–116. https://doi.org/10.1016/s0891-0618(98)00065-9

Honey, C. J., Sporns, O., Cammoun, L., Gigandet, X., Thiran, J. P., Meulic, R., & Hagmann, P. (2009). Predicting human resting-state functional connectivity from structural connectivity. Proceedings of the National Academy of Sciences of the United States of America, 106(6), 2035–2040. https://pubmed.ncbi.nlm.nih.gov/19188601/

Horwitz, B., & Glabus, M. F. (2005). Neural modeling and functional brain imaging: The interplay between the data-fitting and simulation approaches. International Review of Neurobiology, 267–290. https://pubmed.ncbi.nlm.nih.gov/16387207/

Howlin, P., Moss, P., Savage, S., & Rutter, M. (2013). Social outcomes in mid- to later adulthood among individuals diagnosed with autism and average nonverbal IQ as children. Journal of the American Academy of Child and Adolescent Psychiatry, 52(6), 572-581. https://doi.org/10.1016/j.jaac.2013.02.017

Igelström, K. M., Webb, T. W., & Graziano, M. S. A. (2017). Functional connectivity between the temporoparietal cortex and cerebellum in autism spectrum disorder. Cerebral Cortex, 27, 2617– 2627. https://doi.org/10.1093/cercor/bhw079

Just, M. A., Cherkassky, V. L., Keller, T. A., & Minshew, N. J. (2004). Cortical activation and synchronization during sentence comprehension in high-functioning autism: Evidence of underconnectivity. Brain, 127(8), 1811–1821. https://pubmed.ncbi.nlm.nih.gov/15215213/

Just, M. A., Cherkassky, V. L., Keller, T. A., Kana, R. K., & Minshew, N. J. (2007). Functional and anatomical cortical underconnectivity in autism: Evidence from an fMRI study of an executive function task and corpus callosum morphometry. Cerebral Cortex, 17(4), 951–961. https://pubmed.ncbi.nlm.nih.gov/16772313/

Kana, R. K., Libero, L. E., & Moore, M. S. (2011). Disrupted cortical connectivity theory as an explanatory model for autism spectrum disorders. Physics of Life Reviews, 8, 410–437. https://doi.org/10.1016/j.plrev.2011.10.001

Kanne, S. M., Gerber, A. J., Quirmbach, L. M., Sparrow, S. S., Cicchetti, D. V., & Saulnier, C. A. (2011). The role of adaptive behavior in autism spectrum disorders: Implications for functional outcome. Journal of Autism and Developmental Disorders, 41(8), 1007-1018. https://doi.org/10.1007/s10803-010-1126-4

Karadottir, R., Hamilton, N. B., Bakiri, Y., & Attwell, D. (2008). Spiking and nonspiking classes of oligodendrocyte precursor glia in CNS white matter. Nature Neuroscience, 11(4), 450–456. https://pubmed.ncbi.nlm.nih.gov/18311136/

Karlsgodt, K. H., Sun, D., Jimenez, A. M., Lutkenhoff, E. S., Willhite, R., Van erp, T G. M., … Cannon, T. D. (2008). Developmental disruptions in neural connectivity in the pathophysiology of schizophrenia. Development

www.ejtas.com E u ropean Journal of Theoretical and Applied S(IcSiSeNn c2e7s8-76447 ) 2 026 | Volum4e | Numbe1r

21

and Psychopathology, 20(4), 1297–1327. https://pubmed.ncbi.nlm.nih.gov/18838043/

Khan, A. J., Nair, A., Keown, C. L., Datko, M. C., Lincoln, A. J., & Müller, R. A. (2015). Cerebro-cerebellar resting-state functional connectivity in children and adolescents with autism spectrum disorder. Biological Psychiatry, 78, 625–634. https://doi.org/10.1016/j.biopsych.2015.03.024 .

Kraijer, D. W. (2000). Review of adaptive behavior studies in men-tally retarded persons with autism/pervasive developmental disorder. Journal of Autism and Developmental Disorders, 30(1), 39-47. https://doi.org/10.1023/A:1005460027636

Lawrence, Y. A., Kemper, T. L., Bauman, M. L., & Blatt, G. J. (2010). Parvalbumin-, calbindin, and calretinin-immunoreactive hippocampal interneuron density in autism. Acta Neurologica Scandinavica, 121(2), 99–108. https://doi.org/10.1111/j.1600-0404.2009.01234.x

Lewis, J. D., & Elman, J. L. (2008). Growth-related neural reorganization and the autism phenotype: A test of the hypothesis that altered brain growth leads to altered connectivity. Developmental Science, 11(1), 135–155. https://pmc.ncbi.nlm.nih.gov/articles/PMC2706588/

Lewis, J. D., Theilmann, R. J., Sereno, M. I., & Townsend, J. (2009). The relation between connection length and degree of connectivity in young adults: A DTI analysis. Cerebral Cortex, 19(3), 554–562. https://pmc.ncbi.nlm.nih.gov/articles/PMC2638815/

Lind, S. E., & Bowler, D. M. (2010). Episodic memory and episodic future thinking in adults with autism. Journal of Abnormal Psychology, 119(4), 896–905. https://doi.org/10.1037/a0020631

Ma, D. Q., Whitehead, P. L., Menold, M. M., Martin, E. R., AshleyKoch, A. E., Mei, H., ... Gilbert, J. R. (2005). Identification of significant association and gene-gene interaction of GABA receptor subunit genes in autism. American Journal of Human Genetics, 77(3), 377– 388. https://doi.org/10.1086/433195

Matson, J. L., & Shoemaker, M. (2009). Intellectual disability and its relationship to autism spectrum disorders. Research in Developmental Disabilities, 30(6), 1107-1114. https://doi.org/10.1016/j.ridd.2009.06.003

McClelland, J. L. (2000). The basis of hyperspecificity in autism: A preliminary suggestion based on properties of neural nets. Journal of Autism and Developmental Disorders, 30(5), 497–502. https://pubmed.ncbi.nlm.nih.gov/11098891/

McQuaid, G. A., Pelphrey, K. A., Bookheimer, S. Y, Dapretto, D., Webb, S. J., Bernier, R. A., … & Wallace, G. L. (2021). The gap between IQ and adaptive functioning in autism spectrum disorder: Disentangling diagnostic and sex differences. Autism, 25(6), 1565-1579. DOI: 10.1177/1362361321995620. journals.sagepub.com/home/aut

Menon, V. (2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends in Cognitive Sciences, 15, 483–506. https://doi.org/10.1016/j.tics.2011.08.003.

Mottron, L., Dawson, M., Soulieres, I., Hubert, B., & Burack, J. (2006). Enhanced perceptual functioning in autism: An update, and eight principles of autistic perception. Journal of Autism and Developmental Disorders, 36(1), 27–43. https://pubmed.ncbi.nlm.nih.gov/16453071/

Oishi, K., Zilles, K., Amunts, K., Faria, A., Jiang, H., Li, X., … Mori, S. (2008). Human brain white matter atlas: Identification and assignment of common anatomical structures in superficial white matter. NeuroImage, 43(3), 447–457. https://pubmed.ncbi.nlm.nih.gov/18692144/

Ojea, M. (2023). The Precicion Scale Cognitive-Perceptive to people with ASD ‘PS-PC-ASD’. Lima (Perú): Ed. Barcelona. https://libreriaites.com/producto/escala-de-precision-perceptivo-conductual-ep-pc-tea/

Oldehinkel, M., Mennes, M., Marquand, A., Charman, T., Tillmann, J., Ecker, C., … Zwiers, M. P. (2019). Altered connectivity between cerebellum, visual, and sensory-motor networks in autism spectrum disorder: Results from the

www.ejtas.com E u ropean Journal of Theoretical and Applied S(IcSiSeNn c2e7s8-76447 ) 2 026 | Volum4e | Numbe1r

22

EU-AIMS Longitudinal European Autism Project. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 4, 260–270. https://doi.org/10.1016/j.bpsc.2018.11.010

Olivito, G., Clausi, S., Laghi, F., Tedesco, A. M., Baiocco, R., Mastropasqua, C., … Leggio, M. (2016). Resting-state functional connectivity changes between dentate nucleus and cortical social brain regions in autism spectrum disorders. Cerebellum. https://doi.org/10.1007/s1231 1-016-0795-8

Olivito, G., Lupo, M., Laghi, F., Clausi, S., Baiocco, R., Cercignani, M., … Leggio, M. (2017). Lobular patterns of cerebellar resting-state connectivity in adults with Autism Spectrum Disorder. European Journal of Neuroscience. https://doi.org/10.1111/ejn.13752

Pardo, C. A., & Eberhart, C. G. (2007). The neurobiology of autism. Brain Pathology, 17(4), 434–447. https://onlinelibrary.wiley.com/doi/10.1111/j.1750-3639.2007.00102.x

Plaisted, K., O’Riordan, M., & Baron-Cohen, S. (1998). Enhanced visual search for a conjunctive target in autism: A research note. Journal of Child Psychology and Psychiatry and Allied Disciplines, 39(5), 777–783. https://pubmed.ncbi.nlm.nih.gov/9690940/

Redcay, E., & Courchesne, E. (2005). When is the brain enlarged in autism? A metaanalysis of all brain size reports. Biological Psychiatry, 58(1), 1–9. https://pubmed.ncbi.nlm.nih.gov/15935993/

Schummers, J., Yu, H., & Sur, M. (2008). Tuned responses of astrocytes and their influence on hemodynamic signals in the visual cortex. Science, 320(5883), 1638–1643. https://pubmed.ncbi.nlm.nih.gov/18566287/

Shah, A., & Frith, U. (1983). An islet of ability in autistic children: A research note. Journal of Child Psychology and Psychiatry and Allied Disciplines, 24(4), 613–620. Shaw, P., Kabani, N. J., Lerch, J. P., Eckstrand, K., Lenroot, R., Gogtay, N., et al. (2008). Neurodevelopmental trajectories of the human cerebral cortex. Journal of Neuroscience, 28(14), 3586–3594. https://pubmed.ncbi.nlm.nih.gov/6630333/

Snow, P. J. (2016). The structural and functional organization of cognition. Frontiers in Human Neuroscience, 10, Article 501. https://doi.org/10.3389/fnhum.2016.00501

Tanji, J., & Hoshi, E. (2008). Role of the lateral prefrontal cortex in executive behavioral control. Physiological Reviews, 88(1), 37–57. https://doi.org/10.1152/physrev.00014.2007

Van Overwalle, F., & Mariën, P. (2016). Functional connectivity between the cerebrum and cerebellum in social cognition: A multi-study analysis. NeuroImage, 124, 248–255. https//doi.org/10.1016/j.neuroimage.2015.09.001

Wang, Y., Zhang, P., & Wyskiel, D. R. (2016). Chandelier cells in functional and dysfunctional neural circuits. Frontiers in Neural Circuits, 10(33), 1–8. https://www.frontiersin.org/journals/neural-circuits/articles/10.3389/fncir.2016.00033/full

Wedeen, V. J., Wang, R. P., Schmahmann, J. D., Benner, T., Tseng, W. Y. I., Dai, G., ... de Crespigny, A. J. (2008). Diffusion spectrum magnetic resonance imaging (DSI) tractography of crossing fibers. NeuroImage, 41(4), 1267–1277. https://pubmed.ncbi.nlm.nih.gov/18495497/

Zaitsev, A. V., Gonzalez-Burgos, G., Povysheva, N. V., Kroner, S., Lewis, D. A., & Krimer, L. S. (2005). Localization of calcium-binding proteins in physiologically and morphologically characterized interneurons of monkey dorsolateral prefrontal cortex. Cerebral Cortex, 15(8), 1178–1186. https://doi.org/10.1093/cercor/bhh218

Ziskin, J. L., Nishiyama, A., Rubio, M., Fukaya, M., & Bergles, D. E. (2007). Vesicular release of glutamate from unmyelinated axons in white matter. Nature Neuroscience, 10(3), 321–330. https://pubmed.ncbi.nlm.nih.gov/17293857/

ANÁLISIS COMPARATIVO DE LOS MODELOS DE ENSEÑANZA-APRENDIZAJE EN ESTUDIANTES CON TRASTORNO DEL ESPECTRO AUTISTA

ANÁLISIS COMPARATIVO DE LOS MODELOS DE ENSEÑANZA-APRENDIZAJE EN ESTUDIANTES CON TRASTORNO DEL ESPECTRO AUTISTA. 

En B. Silva et al. XVIII Congresso Internacional de Psicopedagogía, 2025 (pp. 2083-2092). Braga (Portugal): Centro de Investigação em Educação, do Instituto de Educação, da Universidade do Minho  Universidade do Mihno.

Manuel Ojea Rúa

Resumen 

Conceptualmente, el trastorno del espectro autista (TEA) se define como una discapacidad relacionada con las alteraciones del neurodesarrollo, en relación con la vía de transmisión de la información a nivel cerebral, a través del sistema funcional del ácido gamma- aminobutírico o sistema GABAérgico, que es observado conductualmente a través de déficits manifiestos en el ámbito de la comunicación, la interacción social y los comportamientos repetitivos y restrictivos, como así está recogido por la Clasificación Internacional de las Enfermedades: DSM-5 (Asociación Americana de Psiquiatría (APA), 2013). La tasa prevalente, según los Centros para el Control y la Prevención de Enfermedades, se sitúa alrededor de 1/44 personas nacidas, en una proporción de 4 hombres por 1.5 mujeres. Pues bien, con el fin de analizar si existen diferencias significativas en la adquisición de competencias cognoscitivas y el desarrollo de las habilidades complejas cognitivas en los estudiantes con TEA, el diseño de esta investigación se ha basado en la realización de 30 encuestas en centros educativos regulares (N= 30), en los cuales se escolarizan estudiantes con TEA. Los datos han sido analizados mediante la prueba comparativa no paramétrica U de Mann-Wihtney. Las conclusiones indican que los estudiantes con TEA, que han seguido un modelo basado en proyectos cooperativos, mejoran sensiblemente en el ámbito psico- social y educativo, en relación con sus pares que han continuado una enseñanza tradicional de tipo magistral. Palabras- clave: Trastorno del espectro autista, desarrollo curricular, cognición, análisis relacional. 

Abstract 

Conceptually, Autism Spectrum Disorder (ASD) is made up of a disability regarding to neurodevelopmental disorders, relationship with the transmission pathway of information at brain level, through the functional system of gamma-aminobutyric acid or GABAergic system, which is observed through manifest deficits in the field of communication, social interaction and restrictive behaviours, as it´s included in the International Classification of Diseases: DSM-5 (American Psychiatric Association (APA), 2013), whose prevalence, according Center for Disease Control and Prevention, around 1/44 persons born has been reported with a ratio of 4 males to 1.5 females. In this research, in seeking to observe whether there're significant differences regarding the acquisition of cognitive competences and the development of complex cognitive abilities in students with ASD, the research design based on 30 interviews in regular educational centres (N=30), where students with ASD are schooled. Data found tested using the non-parametric Mann-Wihtney U Test. Conclusions indicate that students with ASD, who have followed a cooperative project-based model, improve significantly in the psycho-social and educational domains, regarding to their peers who have received a traditional master class teaching. Keywords: Autism spectrum disorder, curriculum development, cognition, relational analysis. 

Referencias

Adorjan, I., Ahmed, B., Feher, V., Torso, M., Krug, K., Esiri, M., … & Szele, F. G. (2017). Calretinin interneuron density in the caudate nucleus is lower in autism spectrum disorder. Brain, 140(7), 2028–2040. https://doi.org/10.1093/brain/awx131

American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (5th ed.). https://doi.org/10.1176/appi.books.9780890425596

Amina, S., Falcone, C., Hong, T., Wolf-Ochoa, M. W., Vakilzadeh, G., Allen, E., … & Martinez-Cerdeno, V. (2021). Chandelier cartridge density is reduced in the prefrontal cortex in autism. Cerebral Cortex, 31(6), 2944–2951. https://doi.org/10.1093/cercor/bhaa402

Ariza, J., Rogers, H., Hashemi, E., Noctor, S. C., & Martinez- Cerdeno, V. (2018). The number of chandelier and basket cells are differentially decreased in prefrontal cortex in autism. Cerebral Cortex, 28(2), 411–420. https://doi.org/10.1093/cercor/bhw349

Biederman, J. (2005). Attention-Deficit/Hyperactivity disorder: A selective overview. Biological Psychia­try, 57(11), 1215–1220. https://doi.org/10.1016/j.biopsych.2004.10.020.

Bishop-Fitzpatrick L, Smith DaWalt L, Greenberg J. & Mailick, M. R. (2017) Participation in recreational activities buffers the impact of perceived stress on quality of life in adults with autism spectrum disorder. Autism Research 10(5), 973–982. https://pubmed.ncbi.nlm.nih.gov/28244233/

Brown, M., Matson, J., Callahan, M., & Tevis, C. (2023). Examining the relationship between social functioning and daily living skills in children with and without autism spectrum disorder. Journal of Developmental and Physical Disabilities, 35, 577–588. https://doi.org/10.1007/s10882-022-09865-6

Castro, L., & Ojea, M. (2024a). Genetic-Environmental Components Associated with the Etiology of Autism Spectrum Disorder. European Journal of Science, Innovation and Technology,4(3), 394-410. ISSN: 2786-4936. https://ejsit-journal.com/index.php/ejsit/article/view/466

Cohen, R. A. (2011). Sustained Attention. In J. S. Kreutzer, J. DeLuca, & B. Caplan (eds.), Ency­clopedia of Clinical Neuropsychology (pp. 2440–2443). Springer New York. https://doi. org/10.1007/978-0-387-79948-3_1334

Craig, F., Savino, R., & Trabacca, A. (2019). A systematic review of comorbidity between cerebral palsy, autism spectrum disorders and attention deficit hyperactivity disorder. European Journal of Paediatric Neurology, 23(1), 31–42. https://doi.org/10.1016/j.ejpn.2018.10.005

DeFelipe, J., Lopez-Cruz, P. L., Benavides-Piccione, R., Bielza, C., Larranaga, P., Anderson, S., … & Ascoli, G. A. (2013). New insights into the classification and nomenclature of cortical GABAergic interneurons. Nature Reviews Neuroscience, 14(3), 202–216. https://doi.org/10.1038/nrn3444

Hashemi, E., Ariza, J., Rogers, H., Noctor, S. C., & Martinez- Cerdeno, V. (2017). The number of parvalbumin-expressing interneurons is decreased in the prefrontal cortex in autism. Cerebral Cortex, 27(3), 1931–1943. https://doi.org/10.1093/cercor/bhw021

Hertrich, I., Dietrich, S., Blum, C., & Ackermann, H. (2021). The role of the dorsolateral prefrontal cortex for speech and language processing. Frontiers in Human Neuroscience, 15, Article 645209. https://doi.org/10.3389/fnhum.2021.645209

Hof, P. R., Glezer, I. I., Conde, F., Flagg, R. A., Rubin, M. B., Nimchinsky, E. A., ... & Vogt-Weisenhorn, D. M. (1999). Cellular distribution of the calcium-binding proteins parvalbumin, calbindin, and calretinin in the neocortex of mammals: Phylogenetic and developmental patterns. Journal of Chemical Neuroanatomy, 16(2), 77–116. https://doi.org/10.1016/s0891-0618(98)00065-9

Hommel, B., Chapman, C. S., Cisek, P., Neyedli, H. F., Song, J. H., & Welsh, T. N. (2019). No one knows what attention is. Attention Perception & Psychophysics, 81(7), 2288–2303. https://doi.org/10.3758/ s13414-019-01846-w.

Kilroy S, Egan J, Walsh M, Wals, M., & McManus, S. (2014). Staff perceptions of the quality of life of individuals with an intellectual disability who transition from a residential campus to community living in Ireland: an exploratory study. Journal of Intellectual and Developmental Disability 40(1), 68–77. https://www.researchgate.net/publication/273311330_Staff_perceptions_of_the_quality_of_life_of_individuals_with_an_intellectual_disability_who_transition_from_a_residential_campus_to_community_living_in_Ireland_An_exploratory_study

Lawrence, Y. A., Kemper, T. L., Bauman, M. L., & Blatt, G. J. (2010). Parvalbumin-, calbindin and calretinin-immunoreactive hippocampal interneuron density in autism. Acta Neurologica Scandinavica, 121(2), 99–108. https://doi.org/10.1111/j.1600-0404.2009.01234.x

Maenner, M. J., Shaw, K. A., Bakian, A. V., Bilder, D. A., Durkin, M. S., Esler, A., & Cogswell, M. E. (2021). Prevalence and characteristics of Autism Spectrum Disorder among children aged 8 years- autism and developmental disabilities monitoring network, 11 sites, United States, 2018. MMWR Surveillance Summaries, 70(11), 1. https://pubmed.ncbi.nlm.nih.gov/34855725/

Ojea, M., & Castro, L. (2024b). Neuronal Remodelling as a Predictor of Autism Spectrum Disorder Diagnosis. International Journal of Psychological Studies, 16(3), 74- 85. DOI:10.5539/ijps.v16n3p74. https://www.ccsenet.org/journal/index.php/ijps/article/view/0/50560

Shaw, P., Stringaris, A., Nigg, J., & Leibenluft, E. (2014). Emotion dysregulation in attention deficit hyper­activity disorder. American Journal of Psychiatry, 171(3), 276–293. https://doi.org/10.1176/appi. ajp.2013.13070966.

Snow, P. J. (2016). The structural and functional organization of cognition. Frontiers in Human Neuroscience, 10, Article 501. https://doi.org/10.3389/fnhum.2016.00501

Wang, Y., Zhang, P., & Wyskiel, D. R. (2016). Chandelier cells in functional and dysfunctional neural circuits. Frontiers in Neural Circuits, 10, Article 33. https://doi.org/10.3389/fncir.2016.00033

Zaitsev, A. V., Gonzalez-Burgos, G., Povysheva, N. V., Kroner, S., Lewis, D. A., & Krimer, L. S. (2005). Localization of calcium-binding proteins in physiologically and morphologically characterized interneurons of monkey dorsolateral prefrontal cortex. Cerebral Cortex, 15(8), 1178–1186. https://doi.org/10.1093/cercor/bhh218

VER CAPÍTULO COMPLETO