Does Sleep Improve Your Grammar? : Preferential Consolidation of Arbitrary Components of New Linguistic Knowledge

We examined the role of sleep-related memory consolidation processes in learning new form-meaning mappings. Specifically, we examined a Complementary Learning Systems account, which implies that sleep-related consolidation should be more beneficial for new hippocampally dependent arbitrary mappings (e.g. new vocabulary items) relative to new systematic mappings (e.g. grammatical regularities), which can be better encoded neocortically. The hypothesis was tested using a novel language with an artificial grammatical gender system. Stem-referent mappings implemented arbitrary aspects of the new language, and determiner/suffix+natural gender mappings implemented systematic aspects (e.g. tib scoiffesh + ballerina, tib mofeem + bride; ked jorool + cowboy, ked heefaff + priest). Importantly, the determiner-gender and the suffix-gender mappings varied in complexity and salience, thus providing a range of opportunities to detect beneficial effects of sleep for this type of mapping. Participants were trained on the new language using a word-picture matching task, and were tested after a 2-hour delay which included sleep or wakefulness. Participants in the sleep group outperformed participants in the wake group on tests assessing memory for the arbitrary aspects of the new mappings (individual vocabulary items), whereas we saw no evidence of a sleep benefit in any of the tests assessing memory for the systematic aspects of the new mappings: Participants in both groups extracted the salient determiner-natural gender mapping, but not the more complex suffix-natural gender mapping. The data support the predictions of the complementary systems account and highlight the importance of the arbitrariness/systematicity dimension in the consolidation process for declarative memories

Stochastic flowering phenology in Dactylis Glomerata populations described by Markov chain modelling

Understanding the relationship between flowering patterns and pollen dispersal is important in climate change modelling, pollen forecasting, forestry and agriculture. Enhanced understanding of this connection can be gained through detailed spatial and temporal flowering observations on a population level, combined with modelling simulating the dynamics. Species with large distribution ranges, long flowering seasons, high pollen production and naturally large populations can be used to illustrate these dynamics. Revealing and simulating species-specific demographic and stochastic elements in the flowering process will likely be important in determining when pollen release is likely to happen in flowering plants. Spatial and temporal dynamics of eight populations of Dactylis glomerata were collected over the course of two years to determine high-resolution demographic elements. Stochastic elements were accounted for using Markov Chain approaches in order to evaluate tiller-specific contribution to overall population dynamics. Tiller-specific developmental dynamics were evaluated using three different RV matrix correlation coefficients. We found that the demographic patterns in population development were the same for all populations with key phenological events differing only by a few days over the course of the seasons. Many tillers transitioned very quickly from non-flowering to full flowering, a process that can be replicated with Markov Chain modelling. Our novel approach demonstrates the identification and quantification of stochastic elements in the flowering process of D. glomerata, an element likely to be found in many flowering plants. The stochastic modelling approach can be used to develop detailed pollen release models for Dactylis, other grass species and probably other flowering plants