Verbal working memory is one of the most studied non-motor functions with robust cerebellar involvement. While the superior cerebellum (lobule VI) has been associated with articulatory control, the inferior cerebellum (lobule VIIIa) has been linked to phonological storage. The present study was aimed to elucidate the differential roles of these regions by investigating whether the cerebellum might contribute to verbal working memory via predictions based on sequence learning/detection. 19 healthy adult subjects completed an fMRI-based Sternberg task which included repeating and novel letter sequences that were phonologically similar or dissimilar. It was hypothesized that learning a repeating sequence of study letters would reduce phonological storage demand and associated right inferior cerebellar activations and that this effect would be modulated by phonological similarity of the study letters. Specifically, while increased phonological storage demand due to high phonological similarity was expected to be reflected in increased right inferior cerebellar activations for similar relative to dissimilar study letters, the reduction in activation for repeating relative to novel sequences was expected to be more profound for phonologically similar than for dissimilar study letters, especially at higher memory load. Results confirmed the typical effects of cognitive load (5 vs. 2 study letters) and phonological similarity in several cerebellar and neocortical brain regions as well as in behavioral data (accuracy and response time). Importantly, activations in superior and inferior cerebellar regions were differentially modulated as a function of similarity and sequence novelty, indicating that particularly lobule VIIIa may contribute to verbal working memory by generating predictions of letter sequences that reduce the likelihood of phonological loop failure before stored items need to be retrieved. The present study is consistent with other investigations that support prediction, which can be based on sequence learning or detection, as an overarching cerebellar function. Electronic supplementary material The online version of this article (10.1007/s00429-018-1784-0) contains supplementary material, which is available to authorized users.
Colloidal crystals are interesting materials owing to their customizable photonic properties, high surface area, and analogy to chemical structures. The flexibility of these materials has been greatly enhanced through mixing particles with varying sizes, compositions, and surface charges. In this way, distinctive patterns or analogies to chemical stoichiometries are produced; however, to date, this body of research is limited to particles with nanoscale dimensions. A simple method is now presented for bottom-up assembly of non-Brownian particle mixtures to create a new class of hierarchically-ordered materials that mimic those found in nature (both in pore distribution as well as stoichiometry). Additionally, these crystals serve as a template to create particle-based inverted crystalline structures with customizable properties.
Colloidal crystals are interesting materials owing to their customizable photonic properties, high surface area, and analogy to chemical structures. The flexibility of these materials has been greatly enhanced through mixing particles with varying sizes, compositions, and surface charges. In this way, distinctive patterns or analogies to chemical stoichiometries are produced; however, to date, this body of research is limited to particles with nanoscale dimensions. A simple method is now presented for bottom‐up assembly of non‐Brownian particle mixtures to create a new class of hierarchically‐ordered materials that mimic those found in nature (both in pore distribution as well as stoichiometry). Additionally, these crystals serve as a template to create particle‐based inverted crystalline structures with customizable properties.
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