title: Predicting the future: from implicit learning to consolidation.
abstract: Sequence learning can be differentiated according to phases (rapid and slower), modalities (perceptual and motor), and whether or not it is conscious (implicit and explicit). Implicit sequence learning occurs when information is acquired from an environment of complex stimuli without conscious access either to what was learned or to the fact that learning occurred. In everyday life, this learning mechanism is crucial for adapting to the environment and for predicting events unconsciously. Implicit sequence learning underlies not only motor, but also cognitive and social skills; it is therefore an important aspect of life from infancy to old age. Moreover, this kind of learning does not occur only during practice, in the so-called online periods, but also between practice periods, during the so-called offline periods. The process that occurs during the offline periods is referred to as consolidation, which denotes the stabilization of a memory trace after the initial acquisition; this can result in increased resistance to interference or even improvement in performance following an offline period. Understanding the multiple aspects and influencing factors of consolidation can help us to reveal the nature of memory and changes in brain plasticity. Our review focuses on how consolidation varies with factors such as awareness, the length of offline periods, the type of information to be learned, and the age of participants. We highlight that consolidation is not a single process; instead, there are multiple mechanisms in the offline period, which are differently influenced by these factors.
authors.affiliation: Institute of Psychology, University of Szeged, Egyetem u.2, Szeged, Hungary.
authors.forename: Karolina
authors.initials: K
authors.lastname: Janacsek
authors.forename: Dezso
authors.initials: D
authors.lastname: Nemeth
mesh_terms: D000375:Aging / Q000502:physiology*; D000818:Animals; D001364:Awareness / Q000502:physiology*; D005544:Forecasting; D006801:Humans; D007858:Learning / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology; D013997:Time Factors