Consequences of converting graded to action potentials upon neural information coding and energy efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ~50% in generator potentials, to ~3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation

Central synapses release a resource-efficient amount of glutamate.

Why synapses release a certain amount of neurotransmitter is poorly understood. We combined patch-clamp electrophysiology with computer simulations to estimate how much glutamate is discharged at two distinct central synapses of the rat. We found that, regardless of some uncertainty over synaptic microenvironment, synapses generate the maximal current per released glutamate molecule while maximizing signal information content. Our result suggests that synapses operate on a principle of resource optimization

Cellular and synaptic diversity of layer 2-3 pyramidal neurons in human individuals

Understanding the functional principles of the human brain requires deep insight into the neuronal and network physiology. To what extent such principles of cellular physiology and synaptic interactions are common across different human individuals is unknown. We characterized the physiology of ~1200 pyramidal neurons and ~1400 monosynaptic connections using advanced multineuron patch-clamp recordings in slices from human temporal cortex. To disentangle within and between individual sources of heterogeneity, we recorded up to 100 neurons per single subject. We found that neuronal, but not synaptic physiology varied with laminar depth. Connection probability was ~15% throughout layer 2-3. Synaptic amplitudes exhibited heavy-tailed distributions with an inverse power law relationship to short term plasticity. Neurons could be classified into four functional subtypes. These general principles of microcircuit physiology were common across individuals. Our study advances the understanding of human neuron and synaptic diversity from an individual and phenotypic perspective