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Some neural representations gradually change across multiple timescales. Here we argue that modeling this “drift” could help explain the spacing effect (the long-term benefit of distributed learning),whereby differences between stored and current temporal context activity patterns produce greater error-driven learning. We trained a neurobiologically realistic model of the entorhinal cortex and hippocampus to learn paired associates alongside temporal context vectors that drifted between learning episodes and/or before final retention intervals. In line with spacing effects, greater drift led to better model recall after longer retention intervals. Dissecting model mechanisms revealed that greater drift increased error-driven learning, strengthened weights in slower drifting temporal context neurons (temporal abstraction), and improved direct cue–target associations (decontextualization). Intriguingly, these results suggest that decontextualization—generally ascribed only to the neocortex—can occur within the hippocampus itself. Altogether, our findings provide a mechanistic formalization for established learning concepts such as spacing effects and errors during learning. 

Abstract The atmospheric effects of precipitating electrons are not fully understood, and uncertainties are large for electrons with energies greater than ~30 keV. These electrons are underrepresented in modeling studies today, primarily because valid measurements of their precipitating spectral energy fluxes are lacking. This paper compares simulations from the Whole Atmosphere Community Climate Model (WACCM) that incorporated two different estimates of precipitating electron fluxes for electrons with energies greater than 30 keV. The estimates are both based on data from the Polar Orbiting Environmental Satellite Medium Energy Proton and Electron Detector (MEPED) instruments but differ in several significant ways. Most importantly, only one of the estimates includes both the 0° and 90° telescopes from the MEPED instrument. Comparisons are presented between the WACCM results and satellite observations poleward of 30°S during the austral winter of 2003, a period of significant energetic electron precipitation. Both of the model simulations forced with precipitating electrons with energies >30 keV match the observed descent of reactive odd nitrogen better than a baseline simulation that included auroral electrons, but no higher energy electrons. However, the simulation that included both telescopes shows substantially better agreement with observations, particularly at midlatitudes. The results indicate that including energies >30 keV and the full range of pitch angles to calculate precipitating electron fluxes is necessary for improving simulations of the atmospheric effects of energetic electron precipitation.