Eve Marder

Variability, compensation and homeostasis in neuron and network function.

Neurons in most animals live a very long time relative to the half-lives of all of the proteins that govern excitability and synaptic transmission. Consequently, homeostatic mechanisms are necessary to ensure stable neuronal and network function over an animals lifetime. To understand how these homeostatic mechanisms might function, it is crucial to understand how tightly regulated synaptic and intrinsic properties must be for adequate network performance, and the extent to which compensatory mechanisms allow for multiple solutions to the production of similar behaviour. Here, we use examples from theoretical and experimental studies of invertebrates and vertebrates to explore several issues relevant to understanding the precision of tuning of synaptic and intrinsic currents for the operation of functional neuronal circuits.

Central pattern generators and the control of rhythmic movements

Central pattern generators are neuronal circuits that when activated can produce rhythmic motor patterns such as walking, breathing, flying, and swimming in the absence of sensory or descending inputs that carry specific timing information. General principles of the organization of these circuits and their control by higher brain centers have come from the study of smaller circuits found in invertebrates. Recent work on vertebrates highlights the importance of neuro-modulatory control pathways in enabling spinal cord and brain stem circuits to generate meaningful motor patterns. Because rhythmic motor patterns are easily quantified and studied, central pattern generators will provide important testing grounds for understanding the effects of numerous genetic mutations on behavior. Moreover, further understanding of the modulation of spinal cord circuitry used in rhythmic behaviors should facilitate the development of new treatments to enhance recovery after spinal cord damage.

Similar network activity from disparate circuit parameters

It is often assumed that cellular and synaptic properties need to be regulated to specific values to allow a neuronal network to function properly. To determine how tightly neuronal properties and synaptic strengths need to be tuned to produce a given network output, we simulated more than 20 million versions of a three-cell model of the pyloric network of the crustacean stomatogastric ganglion using different combinations of synapse strengths and neuron properties. We found that virtually indistinguishable network activity can arise from widely disparate sets of underlying mechanisms, suggesting that there could be considerable animal-to-animal variability in many of the parameters that control network activity, and that many different combinations of synaptic strengths and intrinsic membrane properties can be consistent with appropriate network performance.

Neuromodulation of Neuronal Circuits: Back to the Future

All nervous systems are subject to neuromodulation. Neuromodulators can be delivered as local hormones, as cotransmitters in projection neurons, and through the general circulation. Because neuromodulators can transform the intrinsic firing properties of circuit neurons and alter effective synaptic strength, neuromodulatory substances reconfigure neuronal circuits, often massively altering their output. Thus, the anatomical connectome provides a minimal structure and the neuromodulatory environment constructs and specifies the functional circuits that give rise to behavior.

Variable channel expression in identified single and electrically coupled neurons in different animals

It is often assumed that all neurons of the same cell type have identical intrinsic properties, both within an animal and between animals. We exploited the large size and small number of unambiguously identifiable neurons in the crab stomatogastric ganglion to test this assumption at the level of channel mRNA expression and membrane currents (measured in voltage-clamp experiments). In lateral pyloric (LP) neurons, we saw strong correlations between measured current and the abundance of Shal and BK-KCa mRNAs (encoding the Shal-family voltage-gated potassium channel and large-conductance calcium-activated potassium channel, respectively). We also saw two- to fourfold interanimal variability for three potassium currents and their mRNA expression. Measurements of channel expression in the two electrically coupled pyloric dilator (PD) neurons showed significant interanimal variability, but copy numbers for IH (encoding the hyperpolarization-activated, inward-current channel) and Shal mRNA in the two PD neurons from the same crab were similar, suggesting that the regulation of some currents may be shared in electrically coupled neurons.Note: The PDF version of this article was corrected on 05 February 2006. Please see the PDF for details.

The roles of co-transmission in neural network modulation

Neuromodulation provides considerable flexibility to the output of neural networks. In spite of the extensive literature documenting the presence of modulatory peptide co-transmitters in many neurons, considerably less is known about the specific roles of co-transmission in circuit function. This review describes some of the potential consequences of peptide co-transmission in functional circuits, using specific examples from recent work on the actions of identified peptidergic projection neurons acting on the multifunctional neural network within the crustacean stomatogastric ganglion. This system reveals that co-transmission provides projection neurons with a rich assortment of strategies for eliciting multiple outputs from a multifunctional network.

Global Structure, Robustness, and Modulation of Neuronal Models

The electrical characteristics of many neurons are remarkably robust in the face of changing internal and external conditions. At the same time, neurons can be highly sensitive to neuromodulators. We find correlates of this dual robustness and sensitivity in a global analysis of the structure of a conductance-based model neuron. We vary the maximal conductance parameters of the model neuron and, for each set of parameters tested, characterize the activity pattern generated by the cell as silent, tonically firing, or bursting. Within the parameter space of the five maximal conductances of the model, we find directions, representing concerted changes in multiple conductances, along which the basic pattern of neural activity does not change. In other directions, relatively small concurrent changes in a few conductances can induce transitions between these activity patterns. The global structure of the conductance-space maps implies that neuromodulators that alter a sensitive set of conductances will have powerful, and possibly state-dependent, effects. Other modulators that may have no direct impact on the activity of the neuron may nevertheless change the effects of such direct modulators via this state dependence. Some of the results and predictions arising from the model studies are replicated and verified in recordings of stomatogastric ganglion neurons using the dynamic clamp.

The dynamic clamp : artificial conductances in biological neurons

The dynamic clamp is a novel method that uses computer simulation to introduce conductances into biological neurons. This method can be used to study the role of various conductances in shaping the activity of single neurons, or neurons within networks. The dynamic clamp can also be used to form circuits from previously unconnected neurons. This approach makes computer simulation an interactive experimental tool, and will be useful in many applications where the role of synaptic strengths and intrinsic properties in neuronal and network dynamics is of interest.

Invertebrate Central Pattern Generation Moves along

Central pattern generators (CPGs) are circuits that generate organized and repetitive motor patterns, such as those underlying feeding, locomotion and respiration. We summarize recent work on invertebrate CPGs which has provided new insights into how rhythmic motor patterns are produced and how they are controlled by higher-order command and modulatory interneurons.

The dynamic clamp comes of age

The dynamic clamp uses computer simulation to introduce artificial membrane or synaptic conductances into biological neurons and to create hybrid circuits of real and model neurons. In the ten years since it was first developed, the dynamic clamp has become a widely used tool for the study of neural systems at the cellular and circuit levels. This review describes recent state-of-the-art implementations of the dynamic clamp and summarizes insights gained through its use, ranging from the role of voltage-dependent conductances in shaping neuronal activity to the effects of synaptic dynamics on network behavior and the impact of in vivo-like input on neuronal information processing.