Predição de sintomas de TEPT a partir da ativação cerebral em pessoas expostas a imagens de mutilação

  • Liana C. L. Portugal UERJ / UFF
  • Taiane C. Ramos UFF
  • Orlando Fernandes Jr. UFF
  • Aline F. Bastos UFRJ
  • Bruna Campos UFRJ
  • Mauro V. Mendlowicz UFF
  • Mariana da Luz UFRJ
  • Carla Portella UFRJ
  • Eliane Volchan UFRJ
  • Isabel A. David UFF
  • Fátima Erthal UFRJ
  • Mirtes G. Pereira UFF
  • Leticia Oliveira UFF


O objetivo do presente estudo foi verificar a possibilidade de predição dos sintomas do Transtorno de Estresse Pós-Traumático (TEPT) a partir dos padrões de atividade cerebral. Os participantes expostos a situações traumáticas foram submetidos a exames de Ressonância Magnética Funcional (RMf) enquanto eram expostos a fotos neutras e de corpos mutilados. Neste experimento, foram criados dois contextos de imagens aversivas (real e seguro). O modelo de aprendizado de máquina foi capaz de predizer sintomas de TEPT a partir de padrões de atividade cerebral em resposta às imagens de mutilação no contexto real, mas não no contexto seguro. As regiões cerebrais que apresentaram maior contribuição para o modelo foram as regiões occipitoparietais, incluindo o giro parietal superior e inferior, e o giro supramarginal.


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PORTUGAL, Liana C. L. et al. Predição de sintomas de TEPT a partir da ativação cerebral em pessoas expostas a imagens de mutilação. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 23. , 2023, São Paulo/SP. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 174-185. ISSN 2763-8952. DOI: