Understanding the Neural Bases of Implicit and Statistical Learning

© 2019 Cognitive Science Society, Inc. Both implicit learning and statistical learning focus on the ability of learners to pick up on patterns in the environment. It has been suggested that these two lines of research may be combined into a single construct of “implicit statistical learning.” However, by comparing the neural processes that give rise to implicit versus statistical learning, we may determine the extent to which these two learning paradigms do indeed describe the same core mechanisms. In this review, we describe current knowledge about neural mechanisms underlying both implicit learning and statistical learning, highlighting converging findings between these two literatures. A common thread across all paradigms is that learning is supported by interactions between the declarative and nondeclarative memory systems of the brain. We conclude by discussing several outstanding research questions and future directions for each of these two research fields. Moving forward, we suggest that the two literatures may interface by defining learning according to experimental paradigm, with “implicit learning” reserved as a specific term to denote learning without awareness, which may potentially occur across all paradigms. By continuing to align these two strands of research, we will be in a better position to characterize the neural bases of both implicit and statistical learning, ultimately improving our understanding of core mechanisms that underlie a wide variety of human cognitive abilities

Barrier-properties of Nup98 FG phases ruled by FG motif identity and inter-FG spacer length

Nup98 FG repeat domains comprise hydrophobic FG motifs linked through uncharged spacers. FG motifs capture nuclear transport receptors (NTRs) during nuclear pore complex (NPC) passage, confer inter-repeat cohesion, and condense the domains into a selective phase with NPC-typical barrier properties. We found that shortening inter-FG spacers enhances cohesion, increases phase density, and tightens such barrier – consistent with a sieve-like phase. Phase separation tolerated mutations of Nup98-typical GLFG motifs, provided the domain-hydrophobicity remained preserved. NTR-entry, however, was sensitive to (certain) deviations from canonical FG motifs, suggesting a co-evolutionary adaptation. Unexpectedly, we found that arginines promote efficient FG-phase entry also by means other than cation-π interactions. Although incompatible with NTR·cargo complexes, a YG phase displayed remarkable transport selectivity, particularly for evolved GFPNTR-variants. GLFG to FSFG mutations made the FG phase hypercohesive, precluding NTR-entry. Longer spacers relieved this hypercohesive phenotype. The antagonism between cohesion and NTR·FG interactions appears thus key to transport selectivity

Does Preference for Abstract Patterns Relate to Information Processing and Perceived Duration?

Repetitive prestimulation, in the form of click trains, is known to alter a wide range of cognitive and perceptual judgments. To date, no research has explored whether click trains also influence subjective preferences. This is plausible because preference is related to perceptual fluency and clicks may increase fluency, or, because preference is related to arousal and clicks may increase arousal. In Experiment 1, participants heard a click train, white noise, or silence through headphones and then saw an abstract symmetrical pattern on the screen for 0.5, 1, or 1.5 s. They rated the pattern on a 7-point scale. Click trains had no effect on preference ratings, although patterns that lasted longer were preferred. In Experiment 2, we again presented a click train, silence, or white noise but included both symmetrical and random patterns. Participants made both a duration and a preference judgment on every trial. Auditory click trains increased perceived duration, and symmetrical patterns were perceived as lasting longer than random patterns. Again there was no effect of auditory click trains on preference, and again patterns that were presented for longer were preferred. We conclude that click trains alter perceptual and cognitive processes, but not preferences. This helps clarify the nature of the click train effect and shows which predictions implicit in the existing literature are supported