Theoretical and Computational Neuroscience
Author: Jose A. Fernandez-Leon | Email: jafernandez@intia.exa.unicen.edu.ar
Jose A. Fernandez-Leon1°2°3°
1° CIFICEN (CONICET–CICPBA-UNCPBA), CCT-Tandil, Buenos Aires, Argentina
2° Fac. Cs. Exactas-INTIA, Universidad Nacional del Centro de la Provincia de Buenos Aires (UNCPBA), Tandil, Buenos Aires, Argentina
3° Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
Neurons in the mouse medial entorhinal cortex (MEC) related to spatial navigation and toroid dynamics exhibit unexpected minute-scale (ultraslow, <0.01 Hz) oscillatory firing patterns without clear behavioral correlates. While the mechanisms underlying slow rhythms remain elusive, their potential link to dopaminergic modulation of spike-timing-dependent plasticity (STDP) has been suggested. It is hypothesized that sparse neural networks (SNN) might sustain minute-scale oscillatory sequences when overpassing such modulation; otherwise, the sequences would be disrupted. A computational model based on Izhikevich’s SNN with dopaminergic STDP modulation is used to investigate the conditions supporting ultraslow oscillations. Our results demonstrate that minute-scale sequences emerge in the SNN when a small subset of neurons is sequentially activated along a toroid-like trajectory. Detailed analytical descriptions show that second-scale synaptic resettings are crucial for sustaining these oscillations. Interestingly, the sequential firing patterns induce oscillations that resonate in silent synapses. The balance between long-term synaptic strengthening and wakening during sequential firing explains the relationship between STDP modulation and slow oscillations. This work provides theoretical evidence indicating that minute-scale oscillations can be sustained in a sparse network without imposing severe topological restrictions at the synaptic level.