Humans are capable of acquiring multiple types of information presented in the same information stream. It has been suggested that at least two parallel learning processes are important during learning of sequential patterns—statistical learning and rule‐based learning. Yet, the neurophysiological underpinnings of these parallel learning processes are not fully understood. To differentiate between the simultaneous mechanisms at the single trial level, we apply a temporal EEG signal decomposition approach together with sLORETA source localization method to delineate whether distinct statistical and rule‐based learning codes can be distinguished in EEG data and can be related to distinct functional neuroanatomical structures. We demonstrate t...
Sequence learning underlies numerous motor, cognitive, and social skills. Previous models and empiri...
First published: 09 January 2020Statistical learning is a set of cognitive mechanisms allowing for e...
We investigated whether the temporal structure of movement sequences can be represented and learned ...
International audienceProbabilistic sequence learning supports the development of skills and enables...
We propose and validate a multivariate classification algorithm for characterizing changes in human ...
Extracting the statistics of event streams in natural environments is critical for interpreting curr...
Statistical learning is a powerful ability that extracts regularities from our environment and makes...
We propose and validate a multivariate classification algorithm for characterizing changes in human ...
The prefrontal cortex (PF) has a key role in learning rules and generating associations between stim...
When we are exposed to a novel stimulus sequence, we can learn the sequence by extracting a statisti...
Performing sequences of movements easily and automatically is an integral part of our everyday lives...
Successful human behavior depends on the brain's ability to extract meaningful structure from inform...
Making predictions about future events relies on interpreting streams of information that may initia...
Brain function can be conceived as a hierarchy of generative models that optimizes predictions of se...
Procedural learning facilitates the efficient processing of complex environmental stimuli and contri...
Sequence learning underlies numerous motor, cognitive, and social skills. Previous models and empiri...
First published: 09 January 2020Statistical learning is a set of cognitive mechanisms allowing for e...
We investigated whether the temporal structure of movement sequences can be represented and learned ...
International audienceProbabilistic sequence learning supports the development of skills and enables...
We propose and validate a multivariate classification algorithm for characterizing changes in human ...
Extracting the statistics of event streams in natural environments is critical for interpreting curr...
Statistical learning is a powerful ability that extracts regularities from our environment and makes...
We propose and validate a multivariate classification algorithm for characterizing changes in human ...
The prefrontal cortex (PF) has a key role in learning rules and generating associations between stim...
When we are exposed to a novel stimulus sequence, we can learn the sequence by extracting a statisti...
Performing sequences of movements easily and automatically is an integral part of our everyday lives...
Successful human behavior depends on the brain's ability to extract meaningful structure from inform...
Making predictions about future events relies on interpreting streams of information that may initia...
Brain function can be conceived as a hierarchy of generative models that optimizes predictions of se...
Procedural learning facilitates the efficient processing of complex environmental stimuli and contri...
Sequence learning underlies numerous motor, cognitive, and social skills. Previous models and empiri...
First published: 09 January 2020Statistical learning is a set of cognitive mechanisms allowing for e...
We investigated whether the temporal structure of movement sequences can be represented and learned ...