Dirk M. Bucher - US grants

[unreadable] DESCRIPTION (provided by applicant): Plasticity is the mechanism for development and learning, as much as a cause of pathology. The neural circuits in the brain that are responsible for specific functions have to be both flexible to allow learning and adaptive behavior, and stable to ensure constant function and endurance of learned behaviors. In order to reconcile the need to change synaptic connections and intrinsic neuronal properties with the need to maintain long-term stability, regulatory mechanisms have to be employed that keep plastic changes within functional boundaries. This proposal focuses on how the nervous system can produce stable output activity, both over time, and across individuals. Homeostatic mechanisms that maintain stable neuronal activity over time are relatively well described at the level of single neurons and pairs of synaptic partners, but little is known about how this translates into the stable performance of and entire network of neurons. Network activity is relatively straightforward to monitor in small circuits that produce rhythmic motor behaviors, like the crustacean stomatogastric ganglion. Across individuals, the rhythmic patterns produced by these circuits are very consistent in the relative timing between different groups of neurons, even though the network architecture is variable, as some neuron types exist in different numbers of copies. The goal of the experiments proposed here is to identify which parameters of the synaptic interactions and intrinsic neuronal properties are regulated to compensate for the different network architectures. Individual neurons may adjust their firing patterns to achieve stable network performance. The strength of the synaptic connections onto postsynaptic partners, or the response properties of the postsynaptic neurons may be adjusted in a way that ensures similar total synaptic efficacy. This may also be reflected at the level of neuronal morphology and the abundance of synaptic contacts. Finally, it will be tested if experimental changes of the circuit architecture that result in acute changes of network activity can be compensated over time. It is of fundamental importance to understand the balance of homeostasis and plasticity in the brain, because this balance is lost in neurodegenerative diseases like Alzheimer's and epilepsy, with devastating consequences. In addition, unbalanced plasticity can hinder recovery from stroke or CNS injury. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): Homeostatic processes are involved in the maintenance of unique neuronal phenotypes and circuit function in the face of plastic changes or injury. Neuronal homeostasis is a result of orchestrated activity of multiple gene products and, evidently, some of these can be neuron-specific. Here, we propose to use one of the best described "simple" neural circuits, the pyloric central pattern generator (CPG) in the stomatogastric ganglion of the crab (Cancer borealis), to address how gene expression patterns differ across different neuron types and how changes in gene expression maintain circuit function in response to changes in activity and modulatory state. We will start with two synaptically coupled, unambiguously identifiable neuron types that are known to be crucial for the production of rhythmic motor patterns controlling foregut movements. We propose 2 conceptually overlapping aims that will lead to the unbiased genome-wide view of neuron identity and function: Aim 1) Using sequencing-by-ligation &pyrosequencing platforms adapted to the single cell level, we will tag and quantify the majority of gene products expressed in both cholinergic (PD) and glutamatergic (LP) motoneurons, and identify which genes are differentially expressed between them, and which genes are relevant to neuronal excitability and rhythmic properties of the CPG circuit. Aim 2) We will determine which genes are involved in homeostatic regulation and functional recovery of the stereotypic rhythmic properties of the circuit. The decentralization of the stomatogastric ganglion by deprivation of descending modulatory inputs results in silencing of pyloric motor activity. However, the isolated circuit is able to restore its excitability and rhythmic properties within 2-3 days. This recovery requires changes in gene expression that can be both cell-specific and "universal". We will profile the gene expression patterns at different time points during circuit silencing and recovery of functional activity. As a result, we will identify candidate genes crucial for such functional rescue of the endogenous motor rhythms. We also hypothesize that there are evolutionarily conserved subsets of genes involved in these recovery/homeostatic mechanisms that can be shared between arthropods and mammals. PUBLIC HEALTH RELEVANCE: Here, we will characterize molecular mechanisms of how individual neurons maintain their specific properties and connections to meet the functional demands in a neural circuit controlling rhythmic foregut movements. Specifically we will describe homeostatic processes underlying functional recovery in a neural circuit following silencing and deprivation of modulatory inputs. Although we mainly develop these approaches in a model Cancer preparation where identifiable and experimentally accessible neurons allow such a proof of principle, the methods and related biological questions are of broad, general importance and their applicability to mammals will be tested as the project develops.

DESCRIPTION (provided by applicant): The neural code is expressed as either the rate or the timing of action potentials (spikes). Yet, spike patterns can be affected by changes in the speed and precision of axonal spike propagation, by spike failures or generation of ectopic spikes in the axon. These phenomena depend on the axon morphology, passive membrane properties, and the complement and properties of voltage-gated ion channels. Although axons are often presumed to faithfully transmit spikes with uniform velocity, conduction velocity often depends on the history of axonal activity on both fast and slow time scales. Thus, spike patterns generated at one end of the axon can change dramatically during propagation to the other end, potentially affecting neural coding. In addition, the degree to which axons contribute to the shaping of activity can depend on neuromodulators like dopamine or serotonin. Additionally, changes in axon excitability and propagation are widely used as diagnostic tools for peripheral neuropathies, commonly associated with dysregulation of ion channels. Yet, these measurements do not take into account how the natural temporal patterns of spikes are changed as they propagate along the axon. In sensorimotor systems, highly repetitive spiking is prevalent. During ongoing repetitive activity, history-dependence can occur with large time scales and, in turn, have distinct effects on shorter time scale dynamics like the frequency-dependence of propagation speed. Here, for the first time, we propose to develop a conceptual description of the history-dependence of axonal propagation, its modification by modulators and its influence on the neural code. Crustacean axons provide several experimental advantages to this end: they allow for multiple long-lasting electrophysiological recordings from different sites are amenable to voltage-clamp measurements, have a well-described range of natural activity patterns, readily follow artificially imposed patterns and share with mammalian axons in their constituent ion channels and activity-dependent dynamics of propagation. Furthermore, the motor patterns they are involved in are well defined and straightforward to monitor. Biophysical and pharmacological methods will be used to establish the types and properties of different ionic currents in these axons. Multiple-site electrophysiological recordings and imposed stimulation patterns will be used to establish the history- and frequency-dependence of propagation over multiple time scales, and their dependence on different ionic mechanisms and neuromodulators. Computational models will be constructed to aid in understanding the non-linear interactions between different ionic mechanisms. A mathematical decoding framework will be developed to produce a description of history- dependence that can be generalized for comparison between different axons, treatments and pathological conditions. Finally, a combination of experimental and theoretical methods will be used to characterize how axon dynamics affect neural coding, specifically how they change motor output and muscle dynamics.

Neuromodulators provide flexibility for neural circuit operation and behavior. Yet, at any given time, neural circuits are subject to modulation by multiple neurotransmitters and neurohormones. Each modulator elicits its own specific activity pattern, and presumably, co-modulation by multiple substances increases the degree of circuit flexibility. Despite the multitude of possible combinations and relative concentrations, the output of any neural circuit has low variability across individuals under baseline conditions. Even under identical modulatory conditions this would not be obvious, given that the expression levels of the molecular targets of modulators, for example ion channels, can vary substantially across the population. Numerous studies show that multiple modulators can target the same voltage-gated ion channel type or the same synapse. We propose, somewhat counterintuitively, that the presence of multiple convergent neuromodulators at low concentrations in fact reduces population variability of circuit activity, a hypothesis that is supported by preliminary data. We further propose that consistent circuit activity can occur in the presence of different sets of convergent modulators. We examine these hypotheses in the oscillatory pyloric circuit of the crab stomatogastric ganglion (STG), one of the premier systems for the study of neuromodulation. We propose to combine detailed quantitative measurements of circuit output, as well as underlying synaptic and voltage-gated ionic currents, at different concentrations of 5 neuropeptide modulators and a muscarinic agonist. The modulators of interest are known to target the same fast low-threshold voltage-gated inward current, which increases excitability of STG neurons. A subset of the peptide modulators are known to enhance the same synaptic connections, while others have unknown actions on the synapses, which we plan to explore. Electrical coupling conductances also appear to be modulated by the peptides, potentially with nonlinear interactions. We propose experiments to examine the interactions of modulators at these component levels, with a detailed focus on two well studied neuropeptide modulators, proctolin and the crustacean cardioactive peptide. We will use evolutionary algorithm optimization techniques to produce populations of computational models of the pyloric neurons and synapses, based on these data, where each single model produces the same responses, but different models in the population have different levels of ionic conductances, as observed in the biological system. Component models will be used to build circuit models that produce appropriate activity and correct (co-)modulatory responses. These models would allow us to explore how circuit-level population variability may be changed by co-modulation and by component variability. Additionally, the models will enable us to predict how modulation of components gives rise to circuit patterns of activity specific to that modulator. This work would provide a basic framework for understanding the interactions between different convergent neuromodulators, which can help elucidate drug interaction mechanisms in pharmaceutical therapies.