info:eu-repo/semantics/article
Representation of spatial sequences using nested rules in human prefrontal cortex
Fecha
2019-02Registro en:
Wang, Liping; Amalric, Marie; Fang, Wen; Jiang, Xinjian; Pallier, Christophe; et al.; Representation of spatial sequences using nested rules in human prefrontal cortex; Academic Press Inc Elsevier Science; Journal Neuroimag; 186; 2-2019; 245-255
1053-8119
CONICET Digital
CONICET
Autor
Wang, Liping
Amalric, Marie
Fang, Wen
Jiang, Xinjian
Pallier, Christophe
Figueira, Santiago
Sigman, Mariano
Dehaene, Stanislas
Resumen
Memory for spatial sequences does not depend solely on the number of locations to be stored, but also on the presence of spatial regularities. Here, we show that the human brain quickly stores spatial sequences by detecting geometrical regularities at multiple time scales and encoding them in a format akin to a programming language. We measured gaze-anticipation behavior while spatial sequences of variable regularity were repeated. Participants’ behavior suggested that they quickly discovered the most compact description of each sequence in a language comprising nested rules, and used these rules to compress the sequence in memory and predict the next items. Activity in dorsal inferior prefrontal cortex correlated with the amount of compression, while right dorsolateral prefrontal cortex encoded the presence of embedded structures. Sequence learning was accompanied by a progressive differentiation of multi-voxel activity patterns in these regions. We propose that humans are endowed with a simple “language of geometry” which recruits a dorsal prefrontal circuit for geometrical rules, distinct from but close to areas involved in natural language processing