2026-09-30

To support flexible behavior, animals need to learn map like representations of environments from limited experiences, but the underlying neural mechanisms remain unclear. Here, we propose that theta sweeps, a prominent feature in the activities of grid and place cells during active movement, can broadcast acquired sensory information to swept unvisited regions, accelerating cognitive map learning. To test this idea, we built a network of direction, grid, and place cell modules, in which theta modulation and firing rate adaptation generate theta sweeps, while Hebbian plasticity enables place cells to bind environmental observations. Simulations and ablations showed that the dorsal ventral grid organization produces multiscale, independent sweeps broadcasting acquired sensory information to a broad, fan shaped unvisited area, enabling unvisited regions to build place environment associations. The model further suggests that declining theta power as the environment becomes familiar acts as an annealing process, shifting from learning general information about the environment to making local refinements. The model makes three testable predictions: strong theta modulation accelerates early learning, environments with broader spatial correlations favor longer theta sweeps, and theta sweeps progressively shorten as environments become familiar. Together, our results support theta sweeps as a mechanism for accelerating cognitive map learning from limited explorations, and it sheds light on developing brain inspired algorithms for building world models.

During non-rapid-eye-movement (NREM) sleep, the temporal coupling of cortical slow oscillations (SOs), thalamic spindles, and hippocampal sharp wave ripples drives the consolidation of declarative memories. This coupling degrades in ageing and Alzheimers disease (AD), and although A{beta} and tau leave dissociable signatures in human sleep, the mechanisms by which progressive pathology dismantles the consolidation machinery are difficult to isolate experimentally, and have not to our knowledge been reproduced in a model that can be perturbed directly. We built a systems-level model in which cortical SOs and thalamic spindles are generated by reduced oscillators, hippocampal ripples replay encoded spike sequences, and the measured per-event SO-spindle timing alignment causally gates spike-timing dependent plasticity on cortical sequence synapses. A post-sleep cued-recall test reads out consolidation. Five neurodegeneration parameters (amyloid, tau, synaptic density, GABAergic inhibition, cholinergic tone) map to dis tinct mechanisms grounded in the human and animal literature. The model reproduces graded healthy consolidation and a progressive collapse in which coupling, slow-wave power, spindle power and recall fall monotonically and the overnight memory effect flips from consolidation to net forgetting, with weak memories failing first. Scrambling SO-spindle timing while holding oscillation power fixed abolishes consolidation, establishing that coupling timing, rather than oscillation power, is what the plasticity gate depends on within the model. A{beta} and tau impair memory through orthogonal signatures (A{beta} collapses slow-wave power while sparing replay order, tau the reverse) and this orthogonality holds across the entire A{beta} x tau plane and survives simultaneous {+/-}50% resampling of every mapping coefficient (40/40 samples), so it is not an artefact of a single calibration point. The model yields a falsifiable clinical prediction: closed-loop slow-oscillation enhancement rescues memory only when the deficit is amplitude/coupling-dominated, not when it is replay(tau)-dominated, despite normalising slow-wave power in both cases. Because the therapy arms dissociate coupling from memory benefit, the model also cautions against adopting SO-spindle coupling as a standalone surrogate endpoint.