Neural correlates of retrieval-based enhancement of autobiographical memory in older adults

Investigation of the support constraint effect and failure instability law of tunnels constructed using the New Austrian tunneling method

The application of a reasonable numerical calculation method is the key to accurately analyzing tunnel rock-support interactions. In this paper, we address the support constraint effect of tunnels and analyze the influence of related factors based on the confinement convergence method. Rupturable support models are developed using FLAC^3D to intuitively show the numerical calculation results of tunnels. The results imply that the virtual supporting force generated by the support constraint effect should be considered in two-dimensional rock tunnel model calculations, and that the supporting force of the support should be increased by 2–3% of the maximum supporting force. Boundary effects should be considered in the three-dimensional tunnel model calculations, in which the influence range of the model boundary effect is nearly 1.5 times the tunnel span. A comparison of the field monitoring data and numerical calculations of the Baoshan tunnel project shows that the numerical results that consider the support constraint effect are in better agreement with the actual project situation. The rupturable support models can also reflect the stress and failure evolution law of supports, and provide support for the accurate evaluation of tunnel engineering stability.

Behavioural and neurophysiological signatures in the retrieval of individual memories of recent and remote real-life routine episodic events

Autobiographical memory (AM) has been largely investigated as the ability to recollect specific events that belong to an individual's past. However, how we retrieve real-life routine episodes and how the retrieval of these episodes changes with the passage of time remain unclear. Here, we asked participants to use a wearable camera that automatically captured pictures to record instances during a week of their routine life and implemented a deep neural network-based algorithm to identify picture sequences that represented episodic events. We then asked each participant to return to the lab to retrieve AMs for single episodes cued by the selected pictures 1 week, 2 weeks and 6-14 months after encoding while scalp electroencephalographic (EEG) activity was recorded. We found that participants were more accurate in recognizing pictured scenes depicting their own past than pictured scenes encoded in the lab, and that memory recollection of personally experienced events rapidly decreased with the passing of time. We also found that the retrieval of real-life picture cues elicited a strong and positive 'ERP old/new effect' over frontal regions and that the magnitude of this ERP effect was similar throughout memory tests over time. However, we observed that recognition memory induced a frontal theta power decrease and that this effect was mostly seen when memories were tested after 1 and 2 weeks but not after 6-14 months from encoding. Altogether, we discuss the implications for neuroscientific accounts of episodic retrieval and the potential benefits of developing individual-based AM exploration strategies at the clinical level.