Energy encoding in a biophysical neuron and adaptive energy balance under field coupling

We discuss the biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons. We compare their applicability to large-scale simulations of cortical neural networks.

Bifurcation mechanisms involved in the generation of action potentials (spikes) by neurons are reviewed here. We show how the type of bifurcation determines the neuro-computational properties of the cells. For example, when the rest state is near a saddle-node bifurcation, the cell can fire all-or-none spikes with an arbitrary low frequency, it has a well-defined threshold manifold, and it acts as an integrator; i.e. the higher the frequency of incoming pulses, the sooner it fires. In contrast, when the rest state is near an Andronov–Hopf bifurcation, the cell fires in a certain frequency range, its spikes are not all-or-none, it does not have a well-defined threshold manifold, it can fire in response to an inhibitory pulse, and it acts as a resonator; i.e. it responds preferentially to a certain (resonant) frequency of the input. Increasing the input frequency may actually delay or terminate its firing. We also describe the phenomenon of neural bursting, and we use geometric bifurcation theory to extend the existing classification of bursters, including many new types. We discuss how the type of burster defines its neuro-computational properties, and we show that different bursters can interact, synchronize and process information differently.

Brain function relies on the ability of neurons to communicate with each other. Interneuronal communication primarily takes place at synapses, where information from one neuron is rapidly conveyed to a second neuron. There are two main modalities of synaptic transmission: chemical and electrical. Far from functioning independently and serving unrelated functions, mounting evidence indicates that these two modalities of synaptic transmission closely interact, both during development and in the adult brain. Rather than conceiving synaptic transmission as either chemical or electrical, this article emphasizes the notion that synaptic transmission is both chemical and electrical, and that interactions between these two forms of interneuronal communication might be required for normal brain development and function.