Stress effects on working memory, explicit memory, and implicit memory for neutral and emotional stimuli in healthy men

Stress is a strong modulator of memory function. However, memory is not a unitary process and stress seems to exert different effects depending on the memory type under study. Here, we explored the impact of social stress on different aspects of human memory, including tests for explicit memory and working memory (for neutral materials), as well as implicit memory (perceptual priming, contextual priming and classical conditioning for emotional stimuli). A total of 35 young adult male students were randomly assigned to either the stress or the control group, with stress being induced by the Trier Social Stress Test (TSST). Salivary cortisol levels were assessed repeatedly throughout the experiment to validate stress effects. The results support previous evidence indicating complex effects of stress on different types of memory: A pronounced working memory deficit was associated with exposure to stress. No performance differences between groups of stressed and unstressed subjects were observed in verbal explicit memory (but note that learning and recall took place within 1 h and immediately following stress) or in implicit memory for neutral stimuli. Stress enhanced classical conditioning for negative but not positive stimuli. In addition, stress improved spatial explicit memory. These results reinforce the view that acute stress can be highly disruptive for working memory processing. They provide new evidence for the facilitating effects of stress on implicit memory for negative emotional materials. Our findings are discussed with respect to their potential relevance for psychiatric disorders, such as post traumatic stress disorder.

Transactional Memory in a Dynamic Language

Concurrency control is mostly based on locks and is therefore notoriously difficult to use. Even though some programming languages provide high-level constructs, these add complexity and potentially hard-to-detect bugs to the application. Transactional memory is an attractive mechanism that does not have the drawbacks of locks, however the underlying implementation is often difficult to integrate into an existing language. In this paper we show how we have introduced transactional semantics into Smalltalk by using the reflective facilities of the language. Our approach is based on method annotations, incremental parse tree transformations and an optimistic commit protocol. The implementation does not depend on modifications to the virtual machine and therefore can be changed at the language level. We report on a practical case study, benchmarks and further and on-going work.

The Role of Consciousness in Memory

Conscious events interact with memory systems in learning, rehearsal and retrieval (Ebbinghaus 1885/1964; Tulving 1985). Here we present hypotheses that arise from the IDA computional model (Franklin, Kelemen and McCauley 1998; Franklin 2001b) of global workspace theory (Baars 1988, 2002). Our primary tool for this exploration is a flexible cognitive cycle employed by the IDA computational model and hypothesized to be a basic element of human cognitive processing. Since cognitive cycles are hypothesized to occur five to ten times a second and include interaction between conscious contents and several of the memory systems, they provide the means for an exceptionally fine-grained analysis of various cognitive tasks. We apply this tool to the small effect size of subliminal learning compared to supraliminal learning, to process dissociation, to implicit learning, to recognition vs. recall, and to the availability heuristic in recall. The IDA model elucidates the role of consciousness in the updating of perceptual memory, transient episodic memory, and procedural memory. In most cases, memory is hypothesized to interact with conscious events for its normal functioning. The methodology of the paper is unusual in that the hypotheses and explanations presented are derived from an empirically based, but broad and qualitative computational model of human cognition.

On trend estimation under monotone Gaussian subordination with long-memory: application to fossil pollen series

Fossil pollen data from stratigraphic cores are irregularly spaced in time due to non-linear age-depth relations. Moreover, their marginal distributions may vary over time. We address these features in a nonparametric regression model with errors that are monotone transformations of a latent continuous-time Gaussian process Z(T). Although Z(T) is unobserved, due to monotonicity, under suitable regularity conditions, it can be recovered facilitating further computations such as estimation of the long-memory parameter and the Hermite coefficients. The estimation of Z(T) itself involves estimation of the marginal distribution function of the regression errors. These issues are considered in proposing a plug-in algorithm for optimal bandwidth selection and construction of confidence bands for the trend function. Some high-resolution time series of pollen records from Lago di Origlio in Switzerland, which go back ca. 20,000 years are used to illustrate the methods.