PT - JOURNAL ARTICLE AU - Jacopo Bono AU - Sara Zannone AU - Victor Pedrosa AU - Claudia Clopath TI - Learning predictive cognitive maps with spiking neurons during behaviour and replays AID - 10.1101/2021.08.16.456545 DP - 2021 Jan 01 TA - bioRxiv PG - 2021.08.16.456545 4099 - http://biorxiv.org/content/early/2021/08/17/2021.08.16.456545.1.short 4100 - http://biorxiv.org/content/early/2021/08/17/2021.08.16.456545.1.full AB - We describe a framework where a biologically plausible spiking neural network mimicking hippocampal layers learns a cognitive map known as the successor representation. We show analytically how, on the algorithmic level, the learning follows the TD(λ) algorithm, which emerges from the underlying spike-timing dependent plasticity rule. We then analyze the implications of this framework, uncovering how behavioural activity and experience replays can play complementary roles when learning the representation of the environment, how we can learn relations over behavioural timescales with synaptic plasticity acting on the range of milliseconds, and how the learned representation can be flexibly encoded by allowing state-dependent delay discounting through neuromodulation and altered firing rates.Competing Interest StatementThe authors have declared no competing interest.