Oxytocin Neurones: Intrinsic Mechanisms Governing the Regularity of Spiking Activity

Abstract

Oxytocin neurones of the rat supraoptic nucleus are osmoresponsive and, with all other things being equal, they fire at a mean rate that is proportional to the plasma sodium concentration. However, individual spike times are governed by highly stochastic events, namely the random occurrences of excitatory synaptic inputs, the probability of which is increased by increasing extracellular osmotic pressure. Accordingly, interspike intervals (ISIs) are very irregular. In the present study, we show, by statistical analyses of firing patterns in oxytocin neurones, that the mean firing rate as measured in bins of a few seconds is more regular than expected from the variability of ISIs. This is consistent with an intrinsic activity‐dependent negative‐feedback mechanism. To test this, we compared observed neuronal firing patterns with firing patterns generated by a leaky integrate‐and‐fire model neurone, modified to exhibit activity‐dependent mechanisms known to be present in oxytocin neurones. The presence of a prolonged afterhyperpolarisation (AHP) was critical for the ability to mimic the observed regularisation of mean firing rate, although we also had to add a depolarising afterpotential (DAP; sometimes called an afterdepolarisation) to the model to match the observed ISI distributions. We tested this model by comparing its behaviour with the behaviour of oxytocin neurones exposed to apamin, a blocker of the medium AHP. Good fits indicate that the medium AHP actively contributes to the firing patterns of oxytocin neurones during non‐bursting activity, and that oxytocin neurones generally express a DAP, even though this is usually masked by superposition of a larger AHP.

Spike patterning in oxytocin neurons: Capturing physiological behaviour with Hodgkin-Huxley and integrate-and-fire models

“…The parameters found are consistent with previous fits to the HAP and AHP [15], with an AHP that most closely matches the time course of the apamin-sensitive medium AHP [25]. We have no good experimental evidence for the true proportion of excitatory and inhibitory synaptic input in vivo , so we repeated the fitting for different balances of excitatory and inhibitory synaptic input ( I ratio = 0, 0.5, and 1), but found no consistent difference in fit scores or fitted parameters.…”

The determinants of food choice

“…These neurons respond to signals from the gut that control meal size, and how these neurons respond to some of these appetite-related stimuli has been analysed at the single-cell level. Their behavior can be captured in detail by biophysical (Hodgkin-Huxley style) models, that can then be well approximated by simpler integrate-and fire models that capture the essential behavior while being better suited for modelling networks of neurons (98). Decision making at the level of the neuron networks that oxytocin engages can be well-modelled by biologically realistic "winner-takes-all" networks, which provide predictive models of how continuous variables lead to categorical decision making, and such network models can be fit to human brain imaging data by "mean field approximation" (99).…”

Sex differences in the effects of social defeat on brain and behavior in the California mouse: Insights from a monogamous rodent

“…For example, phasic but not tonic activity of dopamine neurons in the ventral tegmental area is linked with reduced social interaction behavior [103–105]. Although the electrophysiological properties of OT neurons have been studied [106], they have not been linked to variation in social behavior. Regardless, it is clear that additional knowledge on the electrophysiological properties of OT neurons as well as their projections will be important for understanding the varied behavioral effects of OT.…”