Minute-Scale Oscillations in Sparse Neural Networks

Abstract

Neurons linked to spatial navigation and toroidal dynamics in the mouse medial entorhinal cortex (MEC) show unexpected minute-scale (< 0.01 Hz) oscillatory sequences without neural organization or clear relation to behavior. However, the conditions sustaining these’ ultraslow' equences remain uncertain. Since dopaminergic modulation of spike-timing-dependent plasticity (STDP) enables infraslow (< 0.1 Hz) oscillations in sparse neural networks (SNN), we hypothesize that SNN might sustain minute-scale (ultraslow) oscillatory sequences when bypassing the modulation. Using computational simulations through detailed numerical investigations, the conditions that enable the MEC-like ultraslow rhythms are characterized in an Izhikevich's SNN with dopaminergic STDP modulation. To induce the ultraslow sequences, a few active neurons are defined at each simulation step following a toroid-like trajectory. The results indicate that even when disrupting the dopamine-based STDP learning, the ultraslow oscillations require a second-scale resetting of the membrane potential to keep the sequential firing. Interestingly, separate oscillations on synapses that do not contribute to the firing rate at a specific time step (silent synaptic connections) are observed in the presence of the sequences. Since the mechanisms underlying the experimental finding are unknown, the present manuscript generates hypotheses on the conditions that sustain minute-scale sequences, which will be relevant for the community studying population dynamics in the MEC.