Hippocampal replay

…present computational models in which hippocampal-like representations emerge in recurrent neural networks trained to predict sequences of sensory observations. While spatially tuned units reliably arise, they are not sufficient to form a cognitive map. Instead, map-like representations emerge when recurrent dynamics support multi-step prediction, yielding a population-level encoding of environmental geometry. On

There is a fundamental tension between storing discrete traces of individual experiences, which allows recall of particular moments in our past without interference, and extracting regularities across these experiences, which supports generalization and prediction in similar situations in the future. One influential proposal for how the brain resolves this tension is that it separates the processes anatomically into Complementary Learning Systems, with the hippocampus rapidly encoding individual episodes and the neocortex slowly extracting regularities over days, months, and years. But this do

Memory consolidation is assumed to rely on fine-tuned communication within and between hippocampal and cortical neuronal circuits during offline brain states. Sharp-wave ripples (SWRs) have been proposed as the pivotal signature for consolidation, triggering hippocampal replay and information transfer to cortical sites. Critically, although SWRs are precisely coupled to the cardinal NREM sleep-related mesoscopic brain rhythms (i.e., cortical slow oscillations and thalamo-cortical spindles), evidence for a link between SWRs and directed information transfer is scarce. Here, we leveraged the rar

Humans have the ability to quickly adapt to new tasks and generalise what they learned to improve the learning process itself. At the core of this capacity for meta-learning lies a difficult credit assignment problem. After a learning episode, the system needs to determine how to change the components of plasticity such that the next time a similar task is encountered, a better learning outcome can be arrived at more quickly. In machine learning, this problem is often approached by storing the entire learning trajectory and revisiting it in reverse-time order, a process that places large deman

Hippocampal replay, the sequential reactivation of place cells, is postulated to be a mechanism central to memory consolidation. Commonly studied using highly repeated stereotyped behaviours (e.g. running back and forth on a linear track), we don’t understand how such memories are formed in more naturalistic settings, with a single or limited exposure, and the effect on subsequent replay. To further investigate this, we trained rats to run back on forth on two novel linear tracks each day, each track limited to a fixed but different number of laps. Following a post-behaviour sleep session, rat

…Awake hippocampal replay, when hippocampal neural ensembles briefly reactivate a representation related to prior experience, has been proposed to critically contribute to these memory-related processes. However, it remains unclear whether awake replay contributes to memory function by promoting the storage of past experiences, facilitating planning based on evaluation of those experiences, or both. We designed a dynamic spatial task that promotes replay befo