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

Determination of reference intervals for urinary steroid profiling using a newly validated GC-MS/MS method

Background: Urinary steroid profiling (USP) is a powerful diagnostic tool to asses disorders of steroidogenesis. Preanalytical factors such as age, sex and use of oral contraceptive pills (OCP) may affect steroid hormone synthesis and metabolism. In general, USP reference intervals are not adjusted for these variables. In this study we aimed to establish such reference intervals using a newly-developed and validated gas chromatography with tandem mass spectrometry detection method (GC-MS/MS). Methods: Two hundred and forty healthy subjects aged 20-79 years, stratified into six consecutive decade groups each containing 20 males and 20 females, were included. None of the subjects used medications. In addition, 40 women aged 20-39 years using OCP were selected. A GC-MS/MS assay, using hydrolysis, solid phase extraction and double derivatization, was extensively validated and applied for determining USP reference intervals. Results: Androgen metabolite excretion declined with age in both men and women. Cortisol metabolite excretion remained constant during life in both sexes but increased in women 70-79 years of age. Progesterone metabolite excretion peaked in 30-39-year-old women and declined afterwards. Women using OCP had lower excretions of androgen metabolites, progesterone metabolites and cortisol metabolites. Method validation results met prerequisites and revealed the robustness of the GC-MS/ MS method. Conclusions: We developed a new GC-MS/MS method for USP which is applicable for high throughput analysis. Widely applicable age and sex specific reference intervals for 33 metabolites and their diagnostic ratios have been defined. In addition to age and gender, USP reference intervals should be adjusted for OCP use