Optimal responsiveness and collective oscillations emerging from the heterogeneity of inhibitory neurons
arXiv:2005.05596 · doi:10.1038/s41598-021-96745-2
Abstract
The brain is characterized by a strong heterogeneity of inhibitory neurons. We report that spiking neural networks display a resonance to the heterogeneity of inhibitory neurons, with optimal input/output responsiveness occurring for levels of heterogeneity similar to that found experimentally in cerebral cortex. A heterogeneous mean-field model predicts such optimal responsiveness. Moreover, we show that new dynamical regimes emerge from heterogeneity that were not present in the equivalent homogeneous system, such as sparsely synchronous collective oscillations.
References in corpus (12)
- Diversity-induced resonance
- Dynamical Entropy Production in Spiking Neuron Networks in the Balanced State
- Breaking Synchrony by Heterogeneity in Complex Networks
- Phase-locking in weakly heterogeneous neuronal networks
- Non-universal results induced by diversity distribution in coupled excitable systems
- Dynamics of a large system of spiking neurons with synaptic delay
- Nonlocal mechanism for cluster synchronization in neural circuits
- Neuronal Response Impedance Mechanism Implementing Cooperative Networks with Low Firing Rates and Microseconds Precision
- Heterogeneous Mean Field for neural networks with short term plasticity
- Neural networks with excitatory and inhibitory components: direct and inverse problems by a mean-field approach
- Neural Activity of Heterogeneous Inhibitory Spiking Networks with Delay
- Sudden synchrony leaps accompanied by frequency multiplications in neuronal activity