Individual differences in cognitive offloading: a comparison of intention offloading, pattern copy, and short-term memory capacity

The cognitive load of many everyday life tasks exceeds known limitations of short-term memory. One strategy to compensate for information overload is cognitive offloading which refers to the externalization of cognitive processes such as reminder setting instead of memorizing. There appears to be remarkable variance in offloading behavior between participants which poses the question whether there is a common factor influencing offloading behavior across different tasks tackling short-term memory processes. To pursue this question, we studied individual differences in offloading behavior between two well-established offloading paradigms: the intention offloading task which tackles memory for intentions and the pattern copy task which tackles continuous short-term memory load. Our study also included an unrelated task measuring short-term memory capacity. Each participant completed all tasks twice on two consecutive days in order to obtain reliability scores. Despite high reliability scores, individual differences in offloading behavior were uncorrelated between the two offloading tasks. In both tasks, however, individual differences in offloading behavior were correlated with the individual differences in an unrelated short-term memory task. Our results therefore show that offloading behavior cannot simply be explained in terms of a single common factor driving offloading behavior across tasks. We discuss the implications of this finding for future research investigating the interrelations of offloading behavior across different tasks

Sedimentological and Rheological Properties of the Water–Solid Bed Interface in the Weser and Ems Estuaries, North Sea, Germany: Implications for Fluid Mud Classification

Fine, cohesive sediment suspensions are a common feature of estuarine environments. Generally, multilayer models are used to describe the vertical distribution of such sediments. Such conceptional models normally distinguish at least high suspended sediment concentrations (SSCs) as a topmost layer and a consolidated bed layer, often including an intermediate, fluid mud layer. Rheological, and in particular sedimentological properties are rarely included in these models. New data from two different estuaries provide new insights that can contribute toward the classification of nearbed cohesive sediments. The water–solid bed interfaces within the turbidity maximum zones of the Weser and Ems estuaries were sampled with 2–4-m-long cores. At 10-cm intervals, values of SSC, viscosity, particulate organic matter, mud: sand ratio, temperature, salinity, and grain-size distributions were determined. By normalizing these parameters to SSC and performing a cluster analysis, sediment suspensions of <20 g/L SSC, fluid mud with up to 500 g/L SSC, and an underlying cohesive/consolidated bed can each clearly be distinguished. However, changes in flow behaviour and sedimentological characteristics represented by a shift in the cluster grouping support a subdivision of the fluid mud into a low-viscosity (I) (20–200 g/L SSC) and a high-viscosity (II) (200–500 g/L SSC) layer. Furthermore, by normalizing SSC measurements, site-specific differences were observed in the rheological behaviour of the fluid mud which might be caused by differences in grain-size composition. This suggests that the widely accepted 3-layer model of vertical SSC profiles should be extended by two layers of fluid mud identified in this study

Point of Regard from Eye Velocity in Stereoscopic Virtual Environments Based on Intersections of Hypothesis Surfaces

A new method is proposed for utilising scene information for stereo eye tracking in stereoscopic 3D virtual environments. The approach aims to improve gaze tracking accuracy and reduce the required user engagement with eye tracking calibration procedures. The approach derives absolute Point of Regard (POR) from the angular velocity of the eyes without user engaged calibration of drift. The method involves reduction of a hypothesis set for the 3D POR via a process of transformation during saccades and intersection with scene geometry during fixations. A basic implementation of this concept has been demonstrated in simulation using the depth buffer of the scene and a particle representation for the hypothesis set. Future research directions will focus on optimisation of the algorithm and improved utilisation of scene information. The technique shows promise in improving gaze tracking techniques in general, including relative paradigms such as electrooculography

Causality and continuity close the gaps in event representations

International audienceImagine you see a video of someone pulling back their leg to kick a soccer ball, and then a soccer ball soaring toward a goal. You would likely infer that these scenes are two parts of the same event, and this inference would likely cause you to remember having seen the moment the person kicked the soccer ball, even if that information was never actually presented (Strickland & Keil, 2011, Cognition, 121[3], 409–415). What cues trigger people to "fill in" causal events from incomplete information? Is it due to the experience they have had with soccer balls being kicked toward goals? Is it the visual similarity of the object in both halves of the video? Or is it the mere spatiotemporal continuity of the event? In three experiments, we tested these different potential mechanisms underlying the "filling-in" effect. Experiment 1 showed that filling in occurs equally in familiar and unfamiliar contexts, indicating that familiarity with specific event schemas is unnecessary to trigger false memory. Experiment 2 showed that the visible continuation of a launched object’s trajectory is all that is required to trigger filling in, regardless of other occurrences in the second half of the scene. Finally, Experiment 3 found that, using naturalistic videos, this filling-in effect is more heavily affected if the object’s trajectory is discontinuous in space/time compared with if the object undergoes a noticeable transformation. Together, these findings indicate that the spontaneous formation of causal event representations is driven by object representation systems that prioritize spatiotemporal information over other object features