TY  - JOUR
AU  - Xu, Ying
AU  - Li, Xiaodi
PY  - 2025
TI  - The pattern dynamics of interneuronal networks with inhibitory synaptic coupling
JO  - AIMS Mathematics
SP  - 10976
EP  - 10993
VL  - 10
IS  - 5
AB  - Interneurons modulate the excitability of neural networks and maintain neural activity balance via inhibitory or excitatory synaptic connections. Here, we studied the formation of patterns of interneuronal networks with inhibitory synaptic coupling. We found that both electrical synaptic coupling and inhibitory synaptic coupling play a crucial role in the formation of neural network patterns. In addition, delayed inhibitory synapses can also affect the transition of target waves to chaotic states. As the strength of electrical synaptic coupling increases, the firing behavior of neurons gradually becomes highly ordered. When the inhibitory synaptic delay reaches a critical value, we observe a transition in oscillatory patterns from an ordered state to a synchronized state. We further investigated how inhibitory synaptic conductance influences the formation of oscillatory patterns in the network. The study reveals that increasing synaptic conductance disrupts the structure of target waves, inducing chaotic states such as spiral wave fragmentation, while simultaneously elevating neuronal firing rates.
UR  - https://doi.org/10.3934/math.2025498
DO  - 10.3934/math.2025498