Reconhecimento de padrões atencionais e correlatos neurobiológicos em indivíduos com transtorno do déficit de atenção

• Autor(a) principal: Rossi, Adriana Suzart Ungaretti [UNIFESP]
• Data de Publicação: 2015
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UNIFESP
• Texto Completo: https://sucupira.capes.gov.br/sucupira/public/consultas/coleta/trabalhoConclusao/viewTrabalhoConclusao.jsf?popup=true&id_trabalho=2683237; http://repositorio.unifesp.br/handle/11600/48995
• topic: Transtorno do Déficit de Atenção com Hiperatividade; Atenção; Substância branca; Reconhecimento de padrões; Imagem de Tensor de Difusão; Attention-Deficit/Hyperactivity Disorder; Attention; White matter; Pattern Recognition; Diffusion Tensor Imaging

Currently it is widely known that diagnostic categories, including ADHD (Attention-Deficit/Hyperactivity Disorder), are quite heterogeneous conditions. In accordance to the Research Domain Criteria approach, the present study aimed to analyze attentional patterns between ADHD of inattentive type and typically development individuals, regrouping the subjects in respect to their attentional performance, regardless of the groups of origin. Possible differences on brain connectivity between the established groups were also explored. A diagnostic traditional analysis comparing ADHD to typically developing individuals was also conducted in order to better delineate the cognitive, behavioral and neurobiological characteristics of the inattentive type. Methods: Recruited participants included 29 ADHD of inattentive type aged 7 to 15 years and 29 typically developed children matched by age, sex and type of school assisted. Latent Class Analysis were applied to reclassify subjects regarding their attentional performance through cognitive (Conners? Continuous Performance Test and digit span backwards) and behavioral measures (Child Behavioral Checklist). Measures of working memory and verbal fluency were also adopted on the categorical analysis. The new classes, as well as diagnostic classes, were compared in respect to white matter measures (fractional anisotropy). Results: Participants were clustered in three new classes regarding their attencional profile. Nonetheless, considering clinical and statistical parameters, analysis were followed selecting a model with two-classes solution: Class 1 - ultra-high risk for attentional problems and Class 2 - normal development of attentional functions. Group comparison in respect to 20 tracts? fractional anisotropy mean values revealed that Class 1 individuals presented increased fractional anisotropy values on left inferior fronto-occipital fasciculus and left inferior longitudinal fasciculus. In what refers to categorical analysis, ADHD individuals, when compared to typically developing ones, revealed higher intraindividual variability, lower processing speed and worse vigilance, selective and sustained attention. When comparison of fractional anisotropy mean values was made between diagnostic categories (ADHD versus typically developing subjects), there were found no evidences of statistically significant differences in respect to the 20 analyzed fiber tracts. Conclusion: The results highlight that even among individuals with same disorder subtype it is possible to identify subsets with more homogeneous neuropsychological profiles, and, subsequently, with underpinning neurobiological differences. It is noteworthy that although the classical categorical approach did not indicate differences in respect to white matter measures between diagnostic groups, when subjects were compared through a more refined analysis - based on dimensions of observable attentional measures - neurobiological differences were found. These data emphasize that specific data-driven clustering allows a better comprehension of some disorders? pathophysiology, what reiterates that brain-behavior relationships may not respect the arbitrary limits imposed by diagnostic classification.