Contextual reinstatement affects semantic organization.

The Context Dependency Effect is the well-established finding in which memory performance is enhanced under conditions in which the encoding and retrieval contexts overlap (i.e., Same-Context) and diminished when the overlap between encoding and retrieval contexts is low (i.e., Different-Context). Despite much research on context-dependent memory, most prior work examined only mean performance levels. The current experiment examined the influence of context change, manipulated by using three different pieces of background music, on semantic organization during free recall. Recall driven by semantic organization captures an important, ecologically valid aspect of memory retrieval: because narratives of real-life events are typically comprised of semantically related concepts (e.g., "sea," "bathing suit," and "sand" when recalling a trip to the beach), their recall is likely driven by semantic organization. Participants in the current study were tested in the same or different context as the material was learned. The results showed that although the mean number of correctly recalled items was numerically greater in the Same-Context condition compared to the Different-Context condition, the Context Dependency Effect was not significant. In contrast, however, semantic clustering-an established measure of semantic organization-was greater in the Different-Context condition compared to the Same-Context condition. Together, these results suggest that when contextual cues at recall are relatively meager, participants instead use semantic information as cues to guide memory retrieval. In line with previous findings, temporal organization, patterns of errors, and serial position analyses showed no differences between the two context conditions. The present experiment provides novel evidence on how external context change affects recall organization.

A top-down measure of gene-to-gene coordination for analyzing cell-to-cell variability.

Recent technological advances, such as single-cell RNA sequencing (scRNA-seq), allow the measurement of gene expression profiles of individual cells. These expression profiles typically exhibit substantial variations even across seemingly homogeneous populations of cells. Two main different sources contribute to this measured variability: actual differences between the biological activity of the cells and technical measurement errors. Analysis of the biological variability may provide information about the underlying gene regulation of the cells, yet distinguishing it from the technical variability is a challenge. Here, we apply a recently developed computational method for measuring the global gene coordination level (GCL) to systematically study the cell-to-cell variability in numerical models of gene regulation. We simulate 'biological variability' by introducing heterogeneity in the underlying regulatory dynamic of different cells, while 'technical variability' is represented by stochastic measurement noise. We show that the GCL decreases for cohorts of cells with increased 'biological variability' only when it is originated from the interactions between the genes. Moreover, we find that the GCL can evaluate and compare-for cohorts with the same cell-to-cell variability-the ratio between the introduced biological and technical variability. Finally, we show that the GCL is robust against spurious correlations that originate from a small sample size or from the compositionality of the data. The presented methodology can be useful for future analysis of high-dimensional ecological and biochemical dynamics.

Age-related loss of gene-to-gene transcriptional coordination among single cells.

A long-standing model holds that stochastic aberrations of transcriptional regulation play a key role in the process of ageing. While transcriptional dysregulation is observed in many cell types in the form of increased cell-to-cell variability, its generality to all cell types remains doubted. Here, we propose a new approach for analysing transcriptional regulation in single-cell RNA sequencing data by focusing on the global coordination between the genes rather than the variability of individual genes or correlations between pairs of genes. Consistently, across very different organisms and cell types, we find a decrease in the gene-to-gene transcriptional coordination in ageing cells. In addition, we find that loss of gene-to-gene transcriptional coordination is associated with high mutational load of a specific, age-related signature and with radiation-induced DNA damage. These observations suggest a general, potentially universal, stochastic attribute of transcriptional dysregulation in ageing.