Internally generated sequences in learning and executing goal-directed behavior.
By Giovanni Pezzulo, Matthijs A. A. van der Meer, Carien Lansink, Cyriel M. A. Pennartz. 2014
216 citations recorded by the source corpus.
Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cellular and Molecular Neuroscience
- Karl J. Friston
- R. J. Dolan
- Zeb Kurth-Nelson
- ChrisD . Frith
- Thomas H. B. FitzGerald
- J. Allan Hobson
- Giovanni Pezzulo
- Ryota Kanai
In Cognitive Neuroscience
- Karl J. Friston
- ChrisD . Frith
- Giovanni Pezzulo
- R. J. Dolan
- Francesco Rigoli
- Timothy Edward John Behrens
- Thomas H. B. FitzGerald
- Philipp Schwartenbeck
Citations in the corpus
- On the link between conscious function and general intelligence in humans and machines (2022, background): “Preplay can thus be thought of as a form of prospective experience generation, whereby an animal may plan out or learn from potential future behavior (Pezzulo et al., 2014).”
- Active Inference: A Process Theory (2017, background): “This distinction may be particularly important for understanding planning and metacognition and their physiological correlates (Lisman & Redish, 2009; Penny et al., 2013; Pezzulo et al., 2014).”
- Navigating the Affordance Landscape: Feedback Control as a Process Model of Behavior and Cognition. (2016, unknown): “At the same time, these covert operations can be put into practice (to support situated action) by re-engaging brain dynamics operating at the appropriate timescale for action–perception loops [37,56,59].”
- Active Inference, Curiosity and Insight (2017, background): “Indeed, in the rodent hippocampus, one sees (sharp wave-ripple associated) sequences not only during sleep but whenever a rat is disengaged from exploratory or foraging behavior (and associated theta rhythms), such as during short rests or grooming after consuming a reward (Pezzulo et al., 2014).”
- Human Replay Spontaneously Reorganizes Experience (2019, background): “, 2015), that have never been experienced suggests replay might be important for building and sampling internal models of space (Foster, 2017; Pezzulo et al., 2014).”
- Small Sample Learning in Big Data Era (2018, background): “Specifically, humans can more flexibly select actions based on predictions of long-term outputs, that are generated from an internal model of the environment learned through experiences (Dolan and Dayan, 2013; Pezzulo et al., 2014).”