Xenopus tadpole research projects (2006-present)

Specific brainstem neurons switch each other into pacemaker mode to drive movement by activating NMDARs

Li, W.-C., Roberts, A. and Soffe, S. R. (2010) J Neurosci 30(49):16609 –16620

NMDA transforms firing
NMDA transforms firing of neurons which drive swimming from single firing to pacemaker

Rhythmic activity is central to brain function. In the vertebrate central nervous system, the neuronal circuits for breathing and locomotion involve inhibition and also neurons acting as pacemakers, but identifying the neurons responsible has proven difficult. By studying simple hatchling Xenopus laevis tadpoles, we have already identified a population of electrically coupled hindbrain neurons (dINs) which drive swimming. During rhythm generation dINs release glutamate to excite each other and activate NMDA receptors (NMDARs). The resulting depolarization enables a network mechanism for swimming rhythm generation which depends on reciprocal inhibition between antagonistic right and left sides. Surprisingly, a surgically isolated hemi-CNS without inhibition can still generate swimming-like rhythms. We have now discovered that activation of NMDARs transforms dINs, which normally fire singly to current injection, into pacemakers firing within the normal swimming frequency range (10-25 Hz). When dIN firing is blocked pharmacologically, this NMDAR activation produces 10 Hz membrane potential oscillations which persist when electrical coupling is blocked but not when the voltage-dependent gating of NMDARs by Mg2+ is removed. The NMDA-induced oscillations and pacemaker firing at swimming frequency are unique to the dIN population and do not occur in other spinal neurons. We conclude that NMDAR-mediated self-resetting switches critical neurons which drive swimming into pacemaker mode only during locomotion where it provides an additional, parallel mechanism for rhythm generation. This allows rhythm generation in a half CNS and raises the possibility that such concealed pacemaker properties may be present underlying rhythm generation in other vertebrate brain networks.

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Axon and dendrite geography predict the specificity of synaptic connections in a functioning spinal cord network

Li, W.-C., Cooke, T., Sautois, B., Soffe, S. R., Borisyuk, R., and Roberts, A. (2007)

Histograms summarise dorso-ventral distribution of cell bodies, dendrites and axons of different neuron types expressed as the probability that a neuron will have a soma or dendrite in a particular dorso-ventral position.
Axons generated by a model where growth angle depends on dorso-ventral position, generated aIN axons (red) match real axons (blue) closely.

How specific are the synaptic connections formed as neuronal networks develop and can simple rules account for the formation of functioning circuits? These questions are assessed in the spinal circuits controlling swimming in hatchling frog tadpoles. This is possible because detailed information is now available on the identity and synaptic connections of the main types of neuron. The probabilities of synapses between 7 types of identified spinal neuron were measured directly by making electrical recordings from 500 pairs of neurons. For the same neuron types, the dorso-ventral distributions of axons and dendrites were measured and then used to calculate the probabilities that axons would encounter particular dendrites and so potentially form synaptic connections. Surprisingly, synapses were found between all types of neuron but contact probabilities could be predicted simply by the anatomical overlap of their axons and dendrites. These results suggested that synapse formation may not require axons to recognise specific, correct dendrites. To test the plausibility of simpler hypotheses, we first made computational models which were able to generate longitudinal axon growth paths and reproduce the axon distribution patterns and synaptic contact probabilities found in the spinal cord. To test if probabilistic rules could produce functioning spinal networks, we then made realistic computational models of spinal cord neurons, giving them established cell-specific properties and connecting them into networks using the contact probabilities we had determined. A majority of these networks produced robust swimming activity. Simple factors such as morphogen gradients controlling dorso-ventral soma, dendrite and axon positions may sufficiently constrain the synaptic connections made between different types of neuron as the spinal cord first develops and allow functional networks to form. Our analysis implies that detailed cellular recognition between spinal neuron types may not be necessary for the reliable formation of functional networks to generate early behaviour like swimming.

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Reconfiguration of a Vertebrate Motor Network: Specific Neuron Recruitment and Context-Dependent Synaptic Plasticity

A half-centre model of the struggling network in the caudal hindbrain and rostral spinal cord. A Diagram of the model network. Large squares are the half-centres. Circles represent neurons where S1 and S2 are the sensory driver neurons. Triangles are excitatory synapses and black dots inhibitory synapses made onto all neurons within one half-centre. Motoneurons are coupled by electrical junctions. B Stable bursting activity when cIN synapses show depression (a = ?0.5, ß = 38).

Li, W.-C., Sautois, B., Roberts, A. and Soffe, S. R. (2007)

Motor networks typically generate several related output patterns or gaits where individual neurons may be shared or recruited between patterns. We investigate how a vertebrate locomotor network is reconfigured to produce a second rhythmic motor pattern, defining the detailed pattern of neuronal recruitment and consequent changes in the mechanism for rhythm generation. Hatchling Xenopus tadpoles swim if touched but when held make slower, stronger, struggling movements. In immobilised tadpoles a brief current pulse to the skin initiates swimming, while 40 Hz pulses produce struggling. The classes of neurons active during struggling are defined using whole-cell patch recordings from hindbrain and spinal cord neurons during 40 Hz stimulation of the skin. Some motoneurons and inhibitory interneurons are active in both swimming and struggling, but more neurons are recruited within these classes during struggling. In addition, and in contrast to an earlier study, we describe two new classes of excitatory interneuron specifically recruited during struggling and define their properties and synaptic connections. We then explore mechanisms that generate struggling by building a network model incorporating these new neurons. As well as the recruitment of new neuron classes, we show that reconfiguration of the locomotor network to the struggling CPG reveals a context-dependent synaptic depression of reciprocal inhibition: the result of increased inhibitory neuron firing frequency during struggling. This provides one possible mechanism for burst termination not seen in the swimming CPG. The direct demonstration of depression in reciprocal inhibition confirms a key element of Brown’s 1911 hypothesis for locomotor rhythmogenesis.

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Role of type-specific neuron properties in a spinal cord motor network

Sautois, B., Soffe, S. R., Li, W.-C., and Roberts, A. (2007)

Recent recordings from spinal neurons in hatchling frog tadpoles allow their type-specific properties to be defined. Nine types of neuron form spinal networks that control fast swimming and slower struggling. To investigate the significance of type-specific properties, we build models of each neuron type and assemble them into a network using known connectivity between: sensory neurons, sensory pathway interneurons, central pattern generator (CPG) interneurons and motoneurons. A single stimulus to a sensory neuron initiates swimming where modelled neuronal and network activity parallels physiological activity. Substitution of firing properties between neuron types shows that those of excitatory CPG interneurons are critical for stable swimming; those of other CPG neurons are not. We suggest that type-specific neuronal properties can reflect the requirements for involvement in one particular network response (like swimming), but may also reflect the need to participate in more than one response (like swimming and struggling).

The figure below shows a comparison of model and real activity of 4 different spinal neuron types.

Spinal neuron types

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Hindbrain neurons make reciprocal excitatory connections with each other.
Hindbrain neurons make reciprocal excitatory connections with each other. A, Two hdINs, both with descending (d) and ascending (a) axons. Possible contacts at arrows. B, Intracellular current injection (at arrowheads) shows that each hdIN excites the other. Diagrams summarise the anatomy and interactions between hdIN pairs (triangles represent excitatory synapses).

Persistent responses to brief stimuli: feedback excitation among brainstem neurons driving locomotion.

W.-C. Li, S. R. Soffe, E. S. Wolf and Alan Roberts. J. Neurosci 26:4026-4035

The ability of brief stimuli to trigger prolonged neuronal activity is a fundamental requirement in nervous systems, common to motor responses and short term memory. Bistable membrane properties and network feedback excitation have both been proposed as suitable mechanisms to sustain such persistent responses. There is now good experimental evidence for membrane bistability. In contrast, the long-standing hypotheses based on positive feedback excitation have yet to be supported by direct evidence for mutual excitatory connections between appropriate neurons. In young frog tadpoles, we show that a small region of caudal hindbrain and rostral spinal cord is sufficient to generate prolonged swimming in response to a brief stimulus. We use paired whole-cell patch recordings to identify hindbrain neurons in this region that actively excite spinal neurons to drive sustained swimming. We show directly that some of these hindbrain neurons make reciprocal excitatory connections with each other. We use a population model of the hindbrain network to illustrate how feedback excitation can provide a robust mechanism to generate persistent responses. Our recordings provide direct evidence for feedback excitation among neurons within a network that drives a prolonged response. Its presence in a lower brain region early in development suggests that it is a basic feature of neuronal network design.

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