Spike coding during osmotic stimulation of the rat supraoptic nucleus

Oxytocin Neurones: Intrinsic Mechanisms Governing the Regularity of Spiking Activity

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.

Probabilistic identification of cerebellar cortical neurones across species

Despite our fine-grain anatomical knowledge of the cerebellar cortex, electrophysiological studies of circuit information processing over the last fifty years have been hampered by the difficulty of reliably assigning signals to identified cell types. We approached this problem by assessing the spontaneous activity signatures of identified cerebellar cortical neurones. A range of statistics describing firing frequency and irregularity were then used, individually and in combination, to build Gaussian Process Classifiers (GPC) leading to a probabilistic classification of each neurone type and the computation of equi-probable decision boundaries between cell classes. Firing frequency statistics were useful for separating Purkinje cells from granular layer units, whilst firing irregularity measures proved most useful for distinguishing cells within granular layer cell classes. Considered as single statistics, we achieved classification accuracies of 72.5% and 92.7% for granular layer and molecular layer units respectively. Combining statistics to form twin-variate GPC models substantially improved classification accuracies with the combination of mean spike frequency and log-interval entropy offering classification accuracies of 92.7% and 99.2% for our molecular and granular layer models, respectively. A cross-species comparison was performed, using data drawn from anaesthetised mice and decerebrate cats, where our models offered 80% and 100% classification accuracy. We then used our models to assess non-identified data from awake monkeys and rabbits in order to highlight subsets of neurones with the greatest degree of similarity to identified cell classes. In this way, our GPC-based approach for tentatively identifying neurones from their spontaneous activity signatures, in the absence of an established ground-truth, nonetheless affords the experimenter a statistically robust means of grouping cells with properties matching known cell classes. Our approach therefore may have broad application to a variety of future cerebellar cortical investigations, particularly in awake animals where opportunities for definitive cell identification are limited.

Reading between the spikes of the hypothalamic neural code

Reading the spike coding of hypothalamic neurones presents a considerable challenge because they exhibit highly irregular firing patterns. Electrophysiologists working in the motor and sensory systems, in which neurones fire more regularly, have devised satisfactory methods to describe the firing of cells, although the statistical assumptions that underlie the methods do not apply to hypothalamic neurones. Measurement of neural activity is nevertheless vital to characterise the activity of neuroendocrine cells. It has thus become necessary to develop methods suitable for the analysis of the highly irregular spike discharge patterns of both spontaneous and stimulus-evoked firing of hypothalamic neurones. We review techniques used to meet this challenge and demonstrate their considerable capacity to address important physiological questions. We also introduce a novel approach for valid statistical estimation of the information conveyed by the response of a single neurone to a periodic stimulus. The approach demonstrated significant diurnal rhythms of synaptic connectivity between hypothalamic nuclei.

State-dependent plasticity in vasopressin neurones: dehydration-induced changes in activity patterning

Moderate dehydration impairs concentration and co-ordination, whereas severe dehydration can cause seizures, brain damage or death. To slow the progression of dehydration until body fluids can be replenished by drinking, the increased body fluid osmolality associated with dehydration increases vasopressin (antidiuretic hormone) secretion from the posterior pituitary gland. Increased vasopressin secretion reduces water loss in the urine by promoting water reabsorption in the collecting ducts of the kidney. Vasopressin secretion is largely determined by action potential discharge in vasopressin neurones, and depends on both the rate and pattern of discharge. Vasopressin neurone activity depends on intrinsic and extrinsic mechanisms. We review recent advances in our understanding of the physiological regulation of vasopressin neurone activity patterning and the mechanisms by which this is altered to cope with the increased secretory demands of dehydration.

Daily rhythms of spike coding in the rat supraoptic nucleus

Novel measures of coding based on interspike intervals were used to characterise the rhythms of single unit activity in the supraoptic nucleus during the day/night cycle in urethane-anaesthetised rats in vivo. Both continuously firing and phasic cells showed significant (P < 0.001) diurnal rhythms of spike frequency and in the irregularity of firing, as quantified by the log interval entropy (ENT). Comparison of rhythms in log interval ENT showed that the amplitude of the rhythms was greater for the continuously firing cells than for the phasic cells (P = 0.002). Rhythms persisted after hypertonic stimulation or pinealectomy and both treatments reduced the amplitude significantly only for the continuously firing cell group. By contrast, the mesor (i.e. mid-point of the rhythm) was reduced only for the phasic cell group. A similar analysis applied to the activity of cells of the suprachiasmatic nucleus showed that, after pinealectomy, there was a significant rhythm in ENT (P < 0.001) but not firing rate; however, the amplitude of the rhythm in ENT was attenuated (P = 0.047). Diurnal changes in the electrical activity of supraoptic cells are consistent with previously reported circadian changes in magnocellular neuropeptide release. Differences between continuous and phasic cell groups in the effects of osmotic stimulation on rhythmic activity indicate that the two cell types differ in their coding of osmolality and zeitgeber time information. The different effects of pinealectomy on the supraoptic and suprachiasmatic nuclei suggest that removal of endogenous melatonin unmasks a difference in circadian coding between the two nuclei.

Dehydration-induced modulation of kappa-opioid inhibition of vasopressin neurone activity

Dehydration increases vasopressin (antidiuretic hormone) secretion from the posterior pituitary gland to reduce water loss in the urine. Vasopressin secretion is determined by action potential firing in vasopressin neurones, which can exhibit continuous, phasic (alternating periods of activity and silence), or irregular activity. Autocrine kappa-opioid inhibition contributes to the generation of activity patterning of vasopressin neurones under basal conditions and so we used in vivo extracellular single unit recording to test the hypothesis that changes in autocrine kappa-opioid inhibition drive changes in activity patterning of vasopressin neurones during dehydration. Dehydration increased the firing rate of rat vasopressin neurones displaying continuous activity (from 7.1 +/- 0.5 to 9.0 +/- 0.6 spikes s(1)) and phasic activity (from 4.2 +/- 0.7 to 7.8 +/- 0.9 spikes s(1)), but not those displaying irregular activity. The dehydration-induced increase in phasic activity was via an increase in intraburst firing rate. The selective -opioid receptor antagonist nor-binaltorphimine increased the firing rate of phasic neurones in non-dehydrated rats (from 3.4 +/- 0.8 to 5.3 +/- 0.6 spikes s(1)) and dehydrated rats (from 6.4 +/- 0.5 to 9.1 +/- 1.2 spikes s(1)), indicating that kappa-opioid feedback inhibition of phasic bursts is maintained during dehydration. In a separate series of experiments, prodynorphin mRNA expression was increased in vasopressin neurones of hyperosmotic rats, compared to hypo-osmotic rats. Hence, it appears that dynorphin expression in vasopressin neurones undergoes dynamic changes in proportion to the required secretion of vasopressin so that, even under stimulated conditions, autocrine feedback inhibition of vasopressin neurones prevents over-excitation.

Age affects spontaneous activity and depolarizing afterpotentials in isolated gonadotropin-releasing hormone neurons

Neuronal activity underlying the pulsatile secretion of GnRH remains poorly understood, as does the endogenous generation of such activity. It is clear that changes at the level of the hypothalamus are taking place during reproductive aging, yet virtually nothing is known about GnRH neuronal physiology in aging and postreproductive animals. In these studies, we performed cell-attached and whole-cell recordings in GnRH-enhanced green fluorescent protein neurons dissociated from young (3 months), middle-aged (10 months), and old (15-18 months) female mice. All mice were ovariectomized; half were estradiol replaced. Neurons from all ages fired spontaneously, most in a short-burst pattern that is characteristic of GnRH neuronal firing. Membrane characteristics were not affected by age. However, firing frequency was significantly reduced in neurons from old animals, as was spike patterning. The amplitude of the depolarizing afterpotential, evoked by a 200-msec current pulse, was significantly smaller in aged animals. In addition, inward whole-cell currents were reduced in estradiol-treated animals, although they were not significantly affected by age. Because depolarizing afterpotentials have been shown to contribute to prolonged discharges of activity after a very brief excitatory input, a decreased depolarizing afterpotential could lead to attenuated pulses in older animals. In addition, decreases in frequency and pattern generation could lead to improper information coding. Therefore, changes in the GnRH neuron during aging could lead to dysregulated activity, potentially resulting in the attenuated LH pulses observed in the transition to reproductive senescence.

Osmotic modulation of stimulus-evoked responses in the rat supraoptic nucleus

Neural information is conveyed by action potentials along axons to downstream synaptic targets. Synapses permit functionally relevant modulation of the information transmitted by converging inputs. Previous studies have measured the amount of information associated with a given stimulus based either on spike counts or on the relative frequencies of spike sequences represented as binary strings. Here we apply information theory to the phase-interval stimulus histogram (PhISH) to measure the extent of the stimulus-evoked response using the statistical relationship between each interspike interval and its phase within the stimulus cycle. We used the PhISH as a novel approach to investigate how different osmotic states affect the flow of information through the osmoreceptor complex of the hypothalamus. The amount of information conveyed from one (afferent) element of the complex, the anteroventral region of the third ventricle (AV3V), to another (an efferent element), the supraoptic nucleus, was increased by hypertonic stimulation (intravenous mannitol, z = 4.39, P < 0.001) and decreased by hypotonic stimulation (intragastric water, z = -3.37, P < 0.001). Supraoptic responses to AV3V stimulation differed from those that follow stimulation of a hypothalamic element outside the osmoreceptor complex, the suprachiasmatic nucleus (SCN), which also projects to the supraoptic nucleus. Thus osmosensitive gain control mechanisms differentially modulate osmotically dependent and osmotically independent inputs, and enhance the osmoresponsiveness of supraoptic cells within a physiological range. The value of the novel approach is that its use is not limited to the osmoreceptor ensemble but it can be used to investigate the flow of information throughout the central nervous system.