12 papers · ranked by Valyu relevance
Mehrdad Kashefi, Sasha Reschechtko, Giacomo Ariani, Mahdiyar Shahbazi + 3 more
Real world actions often comprise of a series of movements that cannot be entirely planned before initiation. When these actions are executed rapidly, the planning of multiple future movements needs to occur simultaneously with the ongoing action. How the brain solves this task remains unknown. Here we address this…
Si Cheng, Siyi Chen, Zhuanghua Shi
Our current perception and decision-making are shaped by recent experiences, a phenomenon known as serial dependence. While serial dependence is well-documented in visual perception and has been recently explored in time perception, their functional similarities across non-temporal and temporal domains remain elusive…
Noémi Éltető, Dezső Nemeth, Karolina Janacsek, Peter Dayan
Humans can implicitly learn complex perceptuo-motor skills over the course of large numbers of trials. This likely depends on our becoming better able to take advantage of ever richer and temporally deeper predictive relationships in the environment. Here, we offer a novel characterization of this process, fitting a…
Jie Deng, Washington Taylor, Simon A. Levin, Serguei Saavedra
The dynamics of ecological communities in nature are typically characterized by probabilistic, sequential assembly processes (i.e., invasion dynamics). Because of technical challenges, however, the majority of theoretical and experimental studies have focused on the outcomes derived from simultaneous assembly processes…
Andrew D Levy, Peter Zeidman, Karl Friston
Sequential experimental paradigms are fundamental to cognitive neuroscience, yet standard event-related response analysis struggles with the temporal variability inherent to these designs. Conventional epoching treats each event within a sequence as an independent response, discarding the temporal dependencies between…
Kata Horváth, Csenge Török, Orsolya Pesthy, Dezso Nemeth + 1 more
Procedural learning facilitates the efficient processing of complex environmental stimuli and contributes to the acquisition of automatic behaviour. In the present study, we investigated two sub-components of procedural learning: statistical learning and sequence learning. The former one refers to the acquisition of…
Bernard Costa, Marcus V. C. Baldo, Carolina Feher da Silva
Adaptive human behaviour depends on the ability to detect regularities and probabilistic structures within a noisy environment. Repeated binary choice tasks, in which individuals predict one of two possible outcomes, have long served as a fundamental tool for investigating learning, reward processing, and…
Michael A. Boemo, Luca Cardelli, Conrad A. Nieduszynski
Biological systems are made up of components that change their actions (and interactions) over time and coordinate with other components nearby. Together with a large state space, the complexity of this behaviour can make it difficult to create concise mathematical models that can be easily extended or modified. This…
Yiren Ren, Vishwadeep Ahluwalia, Claire Arthur, Thackery Brown
Statistical learning—the ability to extract patterns from noisy continuous experiences—is fundamental to human cognition. Yet, how contextual factors shape this process remains poorly understood. Music is an important example of such contextual factors, because it is ubiquitous in human experience and provides a rich…
Ausaf A Farooqui, Tom Manly
Accounts of hierarchical cognition suggest that extended task episodes as one task entity and not individually execute their component acts. Such hierarchical execution is frequently thought to occur by first instantiating a sequence representation in working memory that then controls the identity and sequence of…
Johan Dahlberg, Johan Hermansson, Steinar Sturlaugsson, Pontus Larsson
Arteria is an automation system aimed at sequencing core facilities. It is built on existing open source technologies, with a modular design allowing for a community-driven effort to create plug-and-play micro-services. Herein we describe the Arteria system and elaborate on the underlying conceptual framework. The…
Josh M. Salet, Wouter Kruijne, Hedderik van Rijn, Eckart Zimmermann + 1 more
Timing studies on statistical learning predominantly present temporal regularities in a discrete, trial-by-trial manner. This, however, is a simplified representation of nature’s complex temporal structure in which regularities are embedded in a continuous stream of interrupting, irregular events. Recent studies using…