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for their technical assistance. In addition, the authors thank the following sources of financial support: PAPIIT (IN226001, IN204103) and CONACYT (69145). The data for this article were collected for PLA' Bachelor of Arts thesis in Psychology under the supervision of TF. Of great importance in this work was the contribution of JSP in interpreting the results and the design of this article. MCR assisted PLA in the application and qualification tests at the stage of sample collection. BPC contributed to the task that was applied during the EEG recording and as assistant of JSP. GA and MC participated in the phase of analysis results. LCV was the neurologist who supported the diagnosis at the stage of sample collection.

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Author´s contribution to this paper was as follows: BPC: assessing children, experimental design, statistical analysis of the data, writing and reviewing of manuscript; MRC: experimental design, statistical analysis, writing and reviewing manuscript, GYT: assessing children and reviewing the manuscript; JBH: experimental design and reviewing manuscript. JSP: statistical analysis, LL: assessing children;

It is important to understand learning disabilities (LD) because they are prevalent worldwide. Currently there is great controversy about LD definition, as some studies focus on the discrepancy between intelligence and academic skills, while others focus only on academic skill assessments. The DSM-IV-TR provides the most commonly used definition for LD, which includes specific learning disabilities (reading, writing, arithmetic) and unspecified learning disabilities. For specific one would expect a significant discrepancy between academic skills and IQ, in contrast, significant discrepancies should not be observed in the unspecified. The literature also reports comorbidities among LD types. The objective of this study was to evaluate reading, writing, and arithmetic task performance profiles in 127 public elementary school children. Based on DSM-IV-TR criteria, we determined academic skill profiles, the presence of LD, LD type, and potential comorbidities in our sample. Using normalized test scores for reading, writing, and arithmetic, we applied a hierarchical cluster analysis to identify academic skill patterns. The results showed the following clusters among school children: 1) children with normal academic skills (n = 80), 2) children with unspecified LD including deficiencies in all three academic processes (n = 27), and 3) children with specific reading LD including arithmetic and writing deficiencies (n = 20). These classification types may later help identify specific neuropsychological characteristics underlying a specific disability, and subsequently facilitate treatments. Key words: Learning disabilities, reading disabilities, LD subtypes, hierarchical-clusters.