Homeostatic synaptic depression is achieved through a regulated decrease in presynaptic calcium channel abundance.

Homeostatic signaling stabilizes synaptic transmission at the neuromuscular junction (NMJ) of Drosophila, mice, and human. It is believed that homeostatic signaling at the NMJ is bi-directional and considerable progress has been made identifying mechanisms underlying the homeostatic potentiation of neurotransmitter release. However, very little is understood mechanistically about the opposing process, homeostatic depression, and how bi-directional plasticity is achieved. Here, we show that homeostatic potentiation and depression can be simultaneously induced, demonstrating true bi-directional plasticity. Next, we show that mutations that block homeostatic potentiation do not alter homeostatic depression, demonstrating that these are genetically separable processes. Finally, we show that homeostatic depression is achieved by decreased presynaptic calcium channel abundance and calcium influx, changes that are independent of the presynaptic action potential waveform. Thus, we identify a novel mechanism of homeostatic synaptic plasticity and propose a model that can account for the observed bi-directional, homeostatic control of presynaptic neurotransmitter release.

Phase response theory extended to nonoscillatory network components.

New tools for analysis of oscillatory networks using phase response theory (PRT) under the assumption of pulsatile coupling have been developed steadily since the 1980s, but none have yet allowed for analysis of mixed systems containing nonoscillatory elements. This caveat has excluded the application of PRT to most real systems, which are often mixed. We show that a recently developed tool, the functional phase resetting curve (fPRC), provides a serendipitous benefit: it allows incorporation of nonoscillatory elements into systems of oscillators where PRT can be applied. We validate this method in a model system of neural oscillators and a biological system, the pyloric network of crustacean decapods.

Co-variation of ionic conductances supports phase maintenance in stomatogastric neurons.

Neuronal networks produce reliable functional output throughout the lifespan of an animal despite ceaseless molecular turnover and a constantly changing environment. Central pattern generators, such as those of the crustacean stomatogastric ganglion (STG), are able to robustly maintain their functionality over a wide range of burst periods. Previous experimental work involving extracellular recordings of the pyloric pattern of the STG has demonstrated that as the burst period varies, the inter-neuronal delays are altered proportionally, resulting in burst phases that are roughly invariant. The question whether spike delays within bursts are also proportional to pyloric period has not been explored in detail. The mechanism by which the pyloric neurons accomplish phase maintenance is currently not obvious. Previous studies suggest that the co-regulation of certain ion channel properties may play a role in governing neuronal activity. Here, we observed in long-term recordings of the pyloric rhythm that spike delays can vary proportionally with burst period, so that spike phase is maintained. We then used a conductance-based model neuron to determine whether co-varying ionic membrane conductances results in neural output that emulates the experimentally observed phenomenon of spike phase maintenance. Next, we utilized a model neuron database to determine whether conductance correlations exist in model neuron populations with highly maintained spike phases. We found that co-varying certain conductances, including the sodium and transient calcium conductance pair, causes the model neuron to maintain a specific spike phase pattern. Results indicate a possible relationship between conductance co-regulation and phase maintenance in STG neurons.

Identifiable cells in the crustacean stomatogastric ganglion.

Neural circuits rely on slight physiological differences between the component cells for proper function. When any circuit is analyzed, it is important to characterize the features that distinguish one cell type from another. This review describes the methods used to identify the neurons of the crustacean stomatogastric ganglion.