Phase maintenance in a rhythmic motor pattern during temperature changes in vivo.

Central-pattern-generating neural circuits function reliably throughout an animal's life, despite constant molecular turnover and environmental perturbations. Fluctuations in temperature pose a problem to the nervous systems of poikilotherms because their body temperature follows the ambient temperature, thus affecting the temperature-dependent dynamics of various subcellular components that constitute neuronal circuits. In the crustacean stomatogastric nervous system, the pyloric circuit produces a triphasic rhythm comprising the output of the pyloric dilator, lateral pyloric, and pyloric constrictor neurons. In vitro, the phase relationships of these neurons are maintained over a fourfold change in pyloric frequency as temperature increases from 7°C to 23°C. To determine whether these temperature effects are also found in intact crabs, in the presence of sensory feedback and neuromodulator-rich environments, we measured the temperature dependence of the pyloric frequency and phases in vivo by implanting extracellular electrodes into Cancer borealis and Cancer pagurus and shifting tank water temperature from 11°C to 26°C. Pyloric frequency in the intact crab increased significantly with temperature (Q10 = 2-2.5), while pyloric phases were generally conserved. For a subset of the C. borealis experiments, animals were subsequently dissected and the stomatogastric ganglion subjected to a similar temperature ramp in vitro. We found that the maximal frequency attained at high temperatures in vivo is lower than it is under in vitro conditions. Our results demonstrate that, over a wide temperature range, the phases of the pyloric rhythm in vivo are generally preserved, but that the frequency range is more restricted than it is in vitro.

Increase in sodium conductance decreases firing rate and gain in model neurons.

We studied the effects of increased sodium conductance on firing rate and gain in two populations of conductance-based, single-compartment model neurons. The first population consisted of 1000 model neurons with differing values of seven voltage-dependent conductances. In many of these models, increasing the sodium conductance threefold unexpectedly reduced the firing rate and divisively scaled the gain at high input current. In the second population, consisting of 1000 simplified model neurons, we found that enhanced sodium conductance changed the frequency-current (FI) curve in two computationally distinct ways, depending on the firing rate. In these models, increased sodium conductance produced a subtractive shift in the FI curve at low firing rates because the additional sodium conductance allowed the neuron to respond more strongly to equivalent input current. In contrast, at high input current, the increase in sodium conductance resulted in a divisive change in the gain because the increased conductance produced a proportionally larger activation of the delayed rectifier potassium conductance. The control and sodium-enhanced FI curves intersect at a point that delimits two regions in which the same biophysical manipulation produces two fundamentally different changes to the model neuron's computational properties. This suggests a potentially difficult problem for homeostatic regulation of intrinsic excitability.

Spike resonance properties in hippocampal O-LM cells are dependent on refractory dynamics.

During a wide variety of behaviors, hippocampal field potentials show significant power in the theta (4-12 Hz) frequency range and individual neurons commonly phase-lock with the 4-12 Hz field potential. The underlying cellular and network mechanisms that generate the theta rhythm, however, are poorly understood. Oriens-lacunosum moleculare (O-LM) interneurons have been implicated as crucial contributors to generating theta in local hippocampal circuits because of their unique axonal projections, slow synaptic kinetics and the fact that spikes are phase-locked to theta field potentials in vivo. We performed experiments in brain slice preparations from Long-Evans rats to investigate the ability of O-LM cells to generate phase-locked spike output in response to artificial synaptic inputs. We find that O-LM cells do not respond with any preference in spike output at theta frequencies when injected with broadband artificial synaptic inputs. However, when presented with frequency-modulated inputs, O-LM spike output shows the ability to phase-lock well to theta-modulated inputs, despite their strong low-pass profiles of subthreshold membrane impedance. This result was dependent on spike refractory dynamics and could be controlled by real-time manipulation of the postspike afterhyperpolarization. Finally, we show that the ability of O-LM cells to phase-lock well to theta-rich inputs is independent of the h-current, a membrane mechanism often implicated in the generation of theta frequency activity.

GenNet: A Platform for Hybrid Network Experiments.

We describe General Network (GenNet), a software plugin for the real time experimental interface (RTXI) dynamic clamp system that allows for straightforward and flexible implementation of hybrid network experiments. This extension to RTXI allows for hybrid networks that contain an arbitrary number of simulated and real neurons, significantly improving upon previous solutions that were limited, particularly by the number of cells supported. The benefits of this system include the ability to rapidly and easily set up and perform scalable experiments with hybrid networks and the ability to scan through ranges of parameters. We present instructions for installing, running and using GenNet for hybrid network experiments and provide several example uses of the system.

Mechanisms of coherent activity in hippocampus and entorhinal cortex.

We consider the mechanisms by which coherent activity arises in the hippocampus and entorhinal cortex, two brain areas that are associated with episodic memory in humans and similar forms of memory in animal models. Our approach relies upon techniques from the theory of coupled oscillators. We show that such techniques can yield accurate predictions of the behavior of synaptically coupled neurons. Future work will expand upon these techniques to include real-world complications that better mimic the in vivo state.