Pharmacology of currents underlying the different firing patterns of spinal sensory neurons and interneurons identified in vivo using multivariate analysis

Alternative classifications of neurons based on physiological properties and synaptic responses, a computational study

One of the central goals of today's neuroscience is to achieve the conceivably most accurate classification of neuron types in the mammalian brain. As part of this research effort, electrophysiologists commonly utilize current clamp techniques to gain a detailed characterization of the neurons' physiological properties. While this approach has been useful, it is not well understood whether neurons that share physiological properties of a particular phenotype would also operate consistently under the action of natural synaptic inputs. We approached this problem by simulating a biophysically diverse population of model neurons based on 3 generic phenotypes. We exposed the model neurons to two types of stimulation to investigate their voltage responses under conventional current step protocols and under simulated synaptic bombardment. We extracted standard physiological parameters from the voltage responses elicited by current step stimulation and spike arrival times descriptive of the model's firing behavior under synaptic inputs. The biophysical phenotypes could be reliably identified using classification based on the 'static' physiological properties, but not the interspike interval-based parameters. However, the model neurons associated with the biophysically different phenotypes retained cell type specific features in the fine structure of their spike responses that allowed their accurate classification.

Modelling Feedback Excitation, Pacemaker Properties and Sensory Switching of Electrically Coupled Brainstem Neurons Controlling Rhythmic Activity

What cellular and network properties allow reliable neuronal rhythm generation or firing that can be started and stopped by brief synaptic inputs? We investigate rhythmic activity in an electrically-coupled population of brainstem neurons driving swimming locomotion in young frog tadpoles, and how activity is switched on and off by brief sensory stimulation. We build a computational model of 30 electrically-coupled conditional pacemaker neurons on one side of the tadpole hindbrain and spinal cord. Based on experimental estimates for neuron properties, population sizes, synapse strengths and connections, we show that: long-lasting, mutual, glutamatergic excitation between the neurons allows the network to sustain rhythmic pacemaker firing at swimming frequencies following brief synaptic excitation; activity persists but rhythm breaks down without electrical coupling; NMDA voltage-dependency doubles the range of synaptic feedback strengths generating sustained rhythm. The network can be switched on and off at short latency by brief synaptic excitation and inhibition. We demonstrate that a population of generic Hodgkin-Huxley type neurons coupled by glutamatergic excitatory feedback can generate sustained asynchronous firing switched on and off synaptically. We conclude that networks of neurons with NMDAR mediated feedback excitation can generate self-sustained activity following brief synaptic excitation. The frequency of activity is limited by the kinetics of the neuron membrane channels and can be stopped by brief inhibitory input. Network activity can be rhythmic at lower frequencies if the neurons are electrically coupled. Our key finding is that excitatory synaptic feedback within a population of neurons can produce switchable, stable, sustained firing without synaptic inhibition.

Modelling the Effects of Electrical Coupling between Unmyelinated Axons of Brainstem Neurons Controlling Rhythmic Activity

Gap junctions between fine unmyelinated axons can electrically couple groups of brain neurons to synchronise firing and contribute to rhythmic activity. To explore the distribution and significance of electrical coupling, we modelled a well analysed, small population of brainstem neurons which drive swimming in young frog tadpoles. A passive network of 30 multicompartmental neurons with unmyelinated axons was used to infer that: axon-axon gap junctions close to the soma gave the best match to experimentally measured coupling coefficients; axon diameter had a strong influence on coupling; most neurons were coupled indirectly via the axons of other neurons. When active channels were added, gap junctions could make action potential propagation along the thin axons unreliable. Increased sodium and decreased potassium channel densities in the initial axon segment improved action potential propagation. Modelling suggested that the single spike firing to step current injection observed in whole-cell recordings is not a cellular property but a dynamic consequence of shunting resulting from electrical coupling. Without electrical coupling, firing of the population during depolarising current was unsynchronised; with coupling, the population showed synchronous recruitment and rhythmic firing. When activated instead by increasing levels of modelled sensory pathway input, the population without electrical coupling was recruited incrementally to unpatterned activity. However, when coupled, the population was recruited all-or-none at threshold into a rhythmic swimming pattern: the tadpole “decided” to swim. Modelling emphasises uncertainties about fine unmyelinated axon physiology but, when informed by biological data, makes general predictions about gap junctions: locations close to the soma; relatively small numbers; many indirect connections between neurons; cause of action potential propagation failure in fine axons; misleading alteration of intrinsic firing properties. Modelling also indicates that electrical coupling within a population can synchronize recruitment of neurons and their pacemaker firing during rhythmic activity.

Some groups of nerve cells in the brain are connected to each other electrically where their processes make contact and form specialized “gap” junctions. The simplest function of electrical connections is to make activity propagate faster by avoiding the delays resulting from chemical messengers at synaptic connections. In other cases, especially in higher brain regions where more spread out nerve cells may be connected by their axons, the function of electrical coupling is less clear. To understand this type of electrical connection better we have built computer models of a group of electrically coupled nerve cells in the brain which control swimming in very young frog tadpoles. We show that the coupling can be indirect, via other members of the group, and can profoundly influence the properties of the nerve cells which would be recorded during real experiments. The main role of the coupling is to synchronise the firing of the group so they are all recruited together when the tadpole is stimulated and then fire in a rhythm suitable to drive swimming movements. The results from this simple animal raise issues which will help to understand coupling in more complex brains.

Spinal neurons require Islet1 for subtype-specific differentiation of electrical excitability

BACKGROUND

In the spinal cord, stereotypic patterns of transcription factor expression uniquely identify neuronal subtypes. These transcription factors function combinatorially to regulate gene expression. Consequently, a single transcription factor may regulate divergent development programs by participation in different combinatorial codes. One such factor, the LIM-homeodomain transcription factor Islet1, is expressed in the vertebrate spinal cord. In mouse, chick and zebrafish, motor and sensory neurons require Islet1 for specification of biochemical and morphological signatures. Little is known, however, about the role that Islet1 might play for development of electrical membrane properties in vertebrates. Here we test for a role of Islet1 in differentiation of excitable membrane properties of zebrafish spinal neurons.

RESULTS

We focus our studies on the role of Islet1 in two populations of early born zebrafish spinal neurons: ventral caudal primary motor neurons (CaPs) and dorsal sensory Rohon-Beard cells (RBs). We take advantage of transgenic lines that express green fluorescent protein (GFP) to identify CaPs, RBs and several classes of interneurons for electrophysiological study. Upon knock-down of Islet1, cells occupying CaP-like and RB-like positions continue to express GFP. With respect to voltage-dependent currents, CaP-like and RB-like neurons have novel repertoires that distinguish them from control CaPs and RBs, and, in some respects, resemble those of neighboring interneurons. The action potentials fired by CaP-like and RB-like neurons also have significantly different properties compared to those elicited from control CaPs and RBs.

CONCLUSIONS

Overall, our findings suggest that, for both ventral motor and dorsal sensory neurons, Islet1 directs differentiation programs that ultimately specify electrical membrane as well as morphological properties that act together to sculpt neuron identity.

Modeling human neurodevelopmental disorders in the Xenopus tadpole: from mechanisms to therapeutic targets

The Xenopus tadpole model offers many advantages for studying the molecular, cellular and network mechanisms underlying neurodevelopmental disorders. Essentially every stage of normal neural circuit development, from axon outgrowth and guidance to activity-dependent homeostasis and refinement, has been studied in the frog tadpole, making it an ideal model to determine what happens when any of these stages are compromised. Recently, the tadpole model has been used to explore the mechanisms of epilepsy and autism, and there is mounting evidence to suggest that diseases of the nervous system involve deficits in the most fundamental aspects of nervous system function and development. In this Review, we provide an update on how tadpole models are being used to study three distinct types of neurodevelopmental disorders: diseases caused by exposure to environmental toxicants, epilepsy and seizure disorders, and autism.

The firing patterns of spinal neurons: in situ patch-clamp recordings reveal a key role for potassium currents

Neuron firing patterns underpin the detection and processing of stimuli, influence synaptic interactions, and contribute to the function of networks. To understand how intrinsic membrane properties determine firing patterns, we investigated the biophysical basis of single and repetitive firing in spinal neurons of hatchling Xenopus laevis tadpoles, a well-understood vertebrate model; experiments were conducted in situ. Primary sensory Rohon-Beard (RB) neurons fire singly in response to depolarising current, and dorsolateral (DL) interneurons fire repetitively. RB neurons exhibited a large tetrodotoxin-sensitive sodium current; in DL neurons, the sodium current density was significantly lower. High-voltage-activated calcium currents were similar in both neuron types. There was no evidence of persistent sodium currents, low-voltage-activated calcium currents, or hyperpolarisation-activated currents. In RB neurons, the potassium current was dominated by a tetraethylammonium-sensitive slow component (I(Ks) ); a fast component (I(Kf) ), sensitive to 4-aminopyridine, predominated in DL neurons. Sequential current-clamp and voltage-clamp recordings in individual neurons suggest that high densities of I(Ks) prevent repetitive firing; where I(Ks) is small, I(Kf) density determines the frequency of repetitive firing. Intermediate densities of I(Ks) and I(Kf) allow neurons to fire a few additional spikes on strong depolarisation; this property typifies a novel subset of RB neurons, and may activate escape responses. We discuss how this ensemble of currents and firing patterns underpins the operation of the Xenopus locomotor network, and suggest how simple mechanisms might underlie the similar firing patterns seen in the neurons of diverse species.