Biophysical neurons, energy, and synapse controllability: a review

Diffusive intracellular and extracellular ions induce a gradient electromagnetic field that regulates membrane potential, and energy injection from external stimuli breaks the energy balance between the magnetic and electric fields in a cell. Indeed, any activation of biophysical function and self-adaption of biological neurons may be dependent on energy flow, and synapse connection is controlled to reach energy balance between neurons. When more neurons are clustered and gathered closely, field energy is exchanged and shape formation is induced to achieve local energy balance. As a result, the coexistence of multiple firing modes in neural activities is fostered to prevent the occurrence of bursting synchronization and seizure. In this review, a variety of biophysical neuron models are presented and explained in terms of their physical aspects, and the controllability of functional synapses, formation of heterogeneity, and defects are clarified for knowing the synchronization stability and cooperation between functional regions. These models and findings are summarized to provide new insights into nonlinear physics and computational neuroscience.

Automated summary

Diffusion of ions inside and outside cells leads to a gradient electromagnetic field that regulates membrane potential. External stimuli inject energy to disrupt the energy balance between the magnetic and electric fields in a cell. Activation of biophysical functions and self-adaptation of biological neurons depend on energy flow, and synapse connection is controlled to achieve energy balance. When more neurons are clustered together, field energy is exchanged and shape formation occurs to achieve local energy balance, preventing bursting synchronization and seizure. This review presents various biophysical neuron models and explains their physical aspects, clarifying the controllability of functional synapses, formation of heterogeneity, and defects to understand synchronization stability and cooperation between functional regions. These models and findings provide new insights into nonlinear physics and computational neuroscience.