Long-horizon associative learning explains human sensitivity to statistical and network structures in auditory sequences
Networks are a useful mathematical tool for capturing the complexity of the world. In a
previous behavioral study, we showed that human adults were sensitive to the high-level …
previous behavioral study, we showed that human adults were sensitive to the high-level …
The successor representation subserves hierarchical abstraction for goal-directed behavior
S Wientjes, CB Holroyd - PLOS Computational Biology, 2024 - journals.plos.org
Humans have the ability to craft abstract, temporally extended and hierarchically organized
plans. For instance, when considering how to make spaghetti for dinner, we typically …
plans. For instance, when considering how to make spaghetti for dinner, we typically …
Time-resolved functional connectivity during visuomotor graph learning
S Loman, L Caciagli, AE Kahn, KP Szymula, N Nyema… - bioRxiv, 2024 - biorxiv.org
Humans naturally attend to patterns that emerge in our perceptual environments, building
mental models that allow for future experiences to be processed more effectively and …
mental models that allow for future experiences to be processed more effectively and …
Probing sensitivity to statistical structure in rapid sound sequences using deviant detection tasks
AE Milne, M Chait, CM Conway - bioRxiv, 2024 - biorxiv.org
Statistical structures and our ability to exploit them are a ubiquitous component of daily life.
Yet, we still do not fully understand how we track these sophisticated statistics and the role …
Yet, we still do not fully understand how we track these sophisticated statistics and the role …