Latent-state and model-based learning in PTSD.
Trends Neurosci
; 47(2): 150-162, 2024 02.
Article
en En
| MEDLINE
| ID: mdl-38212163
ABSTRACT
Post-traumatic stress disorder (PTSD) is characterized by altered emotional and behavioral responding following a traumatic event. In this article, we review the concepts of latent-state and model-based learning (i.e., learning and inferring abstract task representations) and discuss their relevance for clinical and neuroscience models of PTSD. Recent data demonstrate evidence for brain and behavioral biases in these learning processes in PTSD. These new data potentially recast excessive fear towards trauma cues as a problem in learning and updating abstract task representations, as opposed to traditional conceptualizations focused on stimulus-specific learning. Biases in latent-state and model-based learning may also be a common mechanism targeted in common therapies for PTSD. We highlight key knowledge gaps that need to be addressed to further elaborate how latent-state learning and its associated neurocircuitry mechanisms function in PTSD and how to optimize treatments to target these processes.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Trastornos por Estrés Postraumático
Tipo de estudio:
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Trends Neurosci
Año:
2024
Tipo del documento:
Article
Pais de publicación:
Reino Unido