Fred H Sieling

Predictions of phase-locking in excitatory hybrid networks: excitation does not promote phase-locking in pattern-generating networks as reliably as inhibition.

Phase-locked activity is thought to underlie many high-level functions of the nervous system, the simplest of which are produced by central pattern generators (CPGs). It is not known whether we can define a theoretical framework that is sufficiently general to predict phase-locking in actual biological CPGs, nor is it known why the CPGs that have been characterized are dominated by inhibition. Previously, we applied a method based on phase response curves measured using inputs of biologically realistic amplitude and duration to predict the existence and stability of 1:1 phase-locked modes in hybrid networks of one biological and one model bursting neuron reciprocally connected with artificial inhibitory synapses. Here we extend this analysis to excitatory coupling. Using the pyloric dilator neuron from the stomatogastric ganglion of the American lobster as our biological cell, we experimentally prepared 86 networks using five biological neurons, four model neurons, and heterogeneous synapse strengths between 1 and 10,000 nS. In 77% of networks, our method was robust to biological noise and accurately predicted the phasic relationships. In 3%, our method was inaccurate. The remaining 20% were not amenable to analysis because our theoretical assumptions were violated. The high failure rate for excitation compared with inhibition was due to differential effects of noise and feedback on excitatory versus inhibitory coupling and suggests that CPGs dominated by excitatory synapses would require precise tuning to function, which may explain why CPGs rely primarily on inhibitory synapses.

Differential Roles of Nonsynaptic and Synaptic Plasticity in Operant Reward Learning-Induced Compulsive Behavior

BACKGROUND Rewarding stimuli in associative learning can transform the irregularly and infrequently generated motor patterns underlying motivated behaviors into output for accelerated and stereotyped repetitive action. This transition to compulsive behavioral expression is associated with modified synaptic and membrane properties of central neurons, but establishing the causal relationships between cellular plasticity and motor adaptation has remained a challenge. RESULTS We found previously that changes in the intrinsic excitability and electrical synapses of identified neurons in Aplysias central pattern-generating network for feeding are correlated with a switch to compulsive-like motor output expression induced by in vivo operant conditioning. Here, we used specific computer-simulated ionic currents in vitro to selectively replicate or suppress the membrane and synaptic plasticity resulting from this learning. In naive in vitro preparations, such experimental manipulation of neuronal membrane properties alone increased the frequency but not the regularity of feeding motor output found in preparations from operantly trained animals. On the other hand, changes in synaptic strength alone switched the regularity but not the frequency of feeding output from naive to trained states. However, simultaneously imposed changes in both membrane and synaptic properties reproduced both major aspects of the motor plasticity. Conversely, in preparations from trained animals, experimental suppression of the membrane and synaptic plasticity abolished the increase in frequency and regularity of the learned motor output expression. CONCLUSIONS These data establish direct causality for the contributions of distinct synaptic and nonsynaptic adaptive processes to complementary facets of a compulsive behavior resulting from operant reward learning.

Responses of a bursting pacemaker to excitation reveal spatial segregation between bursting and spiking mechanisms

Central pattern generators (CPGs) frequently include bursting neurons that serve as pacemakers for rhythm generation. Phase resetting curves (PRCs) can provide insight into mechanisms underlying phase locking in such circuits. PRCs were constructed for a pacemaker bursting complex in the pyloric circuit in the stomatogastric ganglion of the lobster and crab. This complex is comprised of the Anterior Burster (AB) neuron and two Pyloric Dilator (PD) neurons that are all electrically coupled. Artificial excitatory synaptic conductance pulses of different strengths and durations were injected into one of the AB or PD somata using the Dynamic Clamp. Previously, we characterized the inhibitory PRCs by assuming a single slow process that enabled synaptic inputs to trigger switches between an up state in which spiking occurs and a down state in which it does not. Excitation produced five different PRC shapes, which could not be explained with such a simple model. A separate dendritic compartment was required to separate the mechanism that generates the up and down phases of the bursting envelope (1) from synaptic inputs applied at the soma, (2) from axonal spike generation and (3) from a slow process with a slower time scale than burst generation. This study reveals that due to the nonlinear properties and compartmentalization of ionic channels, the response to excitation is more complex than inhibition.

Distal spike initiation zone location estimation by morphological simulation of ionic current filtering demonstrated in a novel model of an identified Drosophila motoneuron.

Studying ion channel currents generated distally from the recording site is difficult because of artifacts caused by poor space clamp and membrane filtering. A computational model can quantify artifact parameters for correction by simulating the currents only if their exact anatomical location is known. We propose that the same artifacts that confound current recordings can help pinpoint the source of those currents by providing a signature of the neuron’s morphology. This method can improve the recording quality of currents initiated at the spike initiation zone (SIZ) that are often distal to the soma in invertebrate neurons. Drosophila being a valuable tool for characterizing ion currents, we estimated the SIZ location and quantified artifacts in an identified motoneuron, aCC/MN1-Ib, by constructing a novel multicompartmental model. Initial simulation of the measured biophysical channel properties in an isopotential Hodgkin-Huxley type neuron model partially replicated firing characteristics. Adding a second distal compartment, which contained spike-generating Na+ and K+ currents, was sufficient to simulate aCC’s in vivo activity signature. Matching this signature using a reconstructed morphology predicted that the SIZ is on aCC’s primary axon, 70 μm after the most distal dendritic branching point. From SIZ to soma, we observed and quantified selective morphological filtering of fast activating currents. Non-inactivating K+ currents are filtered ∼3 times less and despite their large magnitude at the soma they could be as distal as Na+ currents. The peak of transient component (NaT) of the voltage-activated Na+ current is also filtered more than the magnitude of slower persistent component (NaP), which can contribute to seizures. The corrected NaP/NaT ratio explains the previously observed discrepancy when the same channel is expressed in different cells. In summary, we used an in vivo signature to estimate ion channel location and recording artifacts, which can be applied to other neurons.

A novel model of an identified Drosophila crawl motoneuron for investigating functional effects of ion channel type across larval developmental stages

Drosophila is a powerful genetic model system for investigating neuronal function. Most of the important membrane ion channel genes, such as voltage-gated sodium and potassium channels, were first identified and isolated in the fruit fly. Technical advances have now made possible direct electrophysiological recording of channels in central neurons, allowing the genetic advantages of this system to be applied to analysis of cellular and circuit function and homeostasis. An important open question is the functional effect of channel splice variants that has recently been found in Drosophila neurons. Because of the experimental difficulties in the isolated expression of these splice variants, computational modeling becomes essential. In this work, we aim at assessing effects of Na channel splice variants [1] on neuronal activity by first building a full model neuron. For this full model neuron, parameters for individual ion channels are required. Previous literature on Drosophila ion channel parameters are highly variable. Taking an average of such disparate neuronal parameter values have been shown to be unideal [2]. Furthermore in our case, these data were collected from different neuronal types and preparations. We are thus focusing on identified larval aCC and RP2 abdominal dorsomedial motoneurons, which innervate the dorsal muscles [3], for building a novel full motoneuron model. We obtain their channel parameters by fitting models to experimental voltage-clamp data. We first present a minimal, isopotential spiking model neuron with transient and persistent sodium, delayed-rectifier, and A-type potassium channels. This model allows us to investigate the contributions of the two major types of A-type currents Shal and Shaker that are different in spatial expression over the neuron and in terms of electrophysiological and activity-related characteristics. We show how the Shal channel properties change between the larval stages of 1st and 3rd instar, and we show the effect of this change on neuronal activity characteristics. We then aim to add the calcium channel and potassium channels that are dependent on it. Overall, this neuron model will enable us to investigate the effect Na channel splice variants by varying half-activation and inactivation voltages and ratio of a persistent component.

Changes in electrical coupling via dynamic clamp produces correlates of operant conditioning in the feeding CPG networks of Aplysia

Appetitive operant conditioning, a form of associative learning, produces a long-lasting switch in the mollusk Aplysia’s food-seeking behavior from irregular, impulsive-like radula biting movements into stereotyped, compulsive-like recurrences of this cyclic act [1]. Three bilateral pairs of neurons (B63, B65, and B30) in the feeding central pattern generator (CPG) circuit, found in the buccal ganglia, are initiators of each radula bite motor pattern. Using isolated ganglia from naive and operantly conditioned animals, it was previously found that learning increased both the frequency and regularity of spontaneous bursting activity in these three pairs of neurons. This plasticity was correlated with an increase in electrical coupling among these cells, together with an increased excitability and a change in their intrinsic oscillatory membrane properties [2]. In the present study, we explored the role that changes in electrical coupling between the 6 neurons might play in the operant learning-induced regularization and acceleration of biting motor pattern genesis. In isolated buccal ganglia, we implemented a dynamic clamp procedure during fictive biting activity to artificially increase the electrical coupling among the identified motor pattern initiating neurons. In preparations which spontaneously generated irregular biting motor patterns, artificially increasing the coupling among groups of any 3-4 (out of the 6) neurons immediately switched the network from an irregular to a regular burst pattern. Conversely, in preparations in which the motor pattern-initiating cells spontaneously generated rhythmic motor output, a decrease in their electrical coupling switched the cell’s bursting activity and radula motor pattern genesis from a rhythmic to an arrhythmic mode. These changes were not correlated to a change either in resting membrane potential of the recorded cells or in the frequency of their impulse bursts. These data therefore suggest a causal relationship between the strength of electrical coupling and the temporal regularity of motor pattern genesis underlying each radula cycle, while a separate mechanism is likely to account for the changes in motor pattern frequency. Plasticity induced by operant learning in electrical connectivity within a subset of CPG neurons, may thereby provide a cellular substrate for the behavioral switch between impulsive to compulsive motor actions in Aplysia as well as in more complex animals.

Predicting phase-locking in excitatory hybrid circuits

Introduction Phase-locked activity is thought to be an underlying mechanism controlling aspects of memory, recognition, circadian rhythms, and epileptic seizures, yet no general theoretical framework has been shown to predict the existence of a simple form of phase-locked activity, phaselocking between 2 reciprocally coupled endogenously oscillating neurons. Here, we investigate a general method for predicting the behavior of coupled bursting neurons.

A compartmental model of an identified Drosophila larval motoneuron for investigating functional effects of ion channel parameters

Drosophila is a powerful genetic model system for investigating neuronal function. Several important membrane ion channel genes, such as voltage-gated sodium and potassium channels, were first identified and isolated in the fruit fly. Technical advances in experimental methods have recently made possible direct electrophysiological recording of ionic currents in central neurons, allowing the genetic advantages of this system to be applied to analysis of cellular and circuit function and homeostasis. An important open question is the functional effect of channel splice variants, which have recently been found in Drosophila neurons [1]. The composition of splice variants, which result in the observed sodium current, changes in an activity-dependent manner in seizure mutant Drosophila (personal communication with W-H Lin, R Marley, and RA Baines) and may be the underlying cause of the increase of the persistent component of the sodium current [2]. Because of experimental limitations, computational modeling is essential for understanding the functional implications of this change. We previously presented a computational approach to determine the full set of biophysical parameters of the sodium channel splice variants [3]. We then replicated combinations of these splice variants observed in flies and inserted them into a minimal, isopotential spiking model neuron with transient and persistent sodium, delayed-rectifier, and A-type potassium channels. This isopotential model was limited to reproducing only some firing properties of real neurons because of the morphological distribution of ion channels in these neurons. Specifically, sodium channels that are responsible for action potential initiation are located far from the soma where the recordings are made. In the present work, we improve this model neuron by including morphological details. We take the morphological information from identified larval aCC abdominal dorsomedial motoneurons, which innervate the dorsal muscles [4]. A two-compartment version of the model is used to assess effects of changing sodium channel properties. This neuron model allows investigating the effect of sodium channel splice variants by varying half-activation and inactivation voltages and ratio of a persistent component to mimic changes observed in sodium channel current properties in seizure mutants. We further analyze the effect that changes in synaptic input observed in seizure mutants have on the output neuronal activity.

Predicting excitatory phase resetting curves in bursting neurons

Background The phase resetting curves (PRCs) of neural oscillators can predict the phase locking within a network [1], but for bursting neurons the duration and shape of the burst may change as a result of the feedback within a network, thus it would be useful to understand how these changes impact the resetting. A previous study [2] characterized the responses of bursting neurons to inhibitory pulses as that of a relaxation oscillator whose limit cycle had a depolarized (bursting) and hyperpolarized (silent) branch. Inhibitions applied during the burst produced a switch to the hyperpolarized branch and prevented a from Seventeenth Annual Computational Neuroscience Meeting: CNS*2008 Portland, OR, USA. 19–24 July 2008

Dynamic-Clamp-Constructed Hybrid Circuits for the Study of Synchronization Phenomena in Networks of Bursting Neurons

Hybrid circuits comprised of one biological bursting neuron and one model bursting neuron were constructed using the dynamic clamp to create artificial synaptic conductances in both neurons. The strength and duration of reciprocal inhibitory and excitatory synaptic inputs were varied in a number of such circuits. The phase resetting curves (PRCs) for each component neuron were constructed for each isolated neuron using a pulse in postsynaptic conductance elicited by a single burst in the other neuron. The PRCs from the two component neurons were then used to predict whether a one to one phase-locked mode would be observed in the hybrid network, and if so, to predict the phase angle and network period. The predictions were qualitatively correct for 161 of 164 inhibitory networks and for 64 of 86 excitatory networks. The failures in the case of inhibition resulted from very weak coupling and in the case of excitation from two special cases, one in which the coupling becomes effectively continuous and another in which complex behavior results from a discontinuous PRC. The firing intervals and network period predictions were generally accurate within 10% of the values actually observed in the hybrid networks, a level similar to the level of variability observed in the measurement of the PRC and of the intrinsic period in the biological neuron.