Dynamics of a minimal model of interlocked positive and negative feedback loops of transcriptional regulation by cAMP-response element binding proteins

cAMP-response element binding (CREB) proteins are involved in transcriptional regulation in a number of cellular processes (e.g., neural plasticity and circadian rhythms). The CREB family contains activators and repressors that may interact through positive and negative feedback loops. These loops can be generated by auto- and cross-regulation of expression of CREB proteins, via CRE elements in or near their genes. Experiments suggest that such feedback loops may operate in several systems (e.g., Aplysia and rat). To understand the functional implications of such feedback loops, which are interlocked via cross-regulation of transcription, a minimal model with a positive and negative loop was developed and investigated using bifurcation analysis. Bifurcation analysis revealed diverse nonlinear dynamics (e.g., bistability and oscillations). The stability of steady states or oscillations could be changed by time delays in the synthesis of the activator (CREB1) or the repressor (CREB2). Investigation of stochastic fluctuations due to small numbers of molecules of CREB1 and CREB2 revealed a bimodal distribution of CREB molecules in the bistability region. The robustness of the stable HIGH and LOW states of CREB expression to stochastic noise differs, and a critical number of molecules was required to sustain the HIGH state for days or longer. Increasing positive feedback or decreasing negative feedback also increased the lifetime of the HIGH state, and persistence of this state may correlate with long-term memory formation. A critical number of molecules was also required to sustain robust oscillations of CREB expression. If a steady state was near a deterministic Hopf bifurcation point, stochastic resonance could induce oscillations. This comparative analysis of deterministic and stochastic dynamics not only provides insights into the possible dynamics of CREB regulatory motifs, but also demonstrates a framework for understanding other regulatory processes with similar network architecture.

Feeding behavior of Aplysia: a model system for comparing cellular mechanisms of classical and operant conditioning

Feeding behavior of Aplysia provides an excellent model system for analyzing and comparing mechanisms underlying appetitive classical conditioning and reward operant conditioning. Behavioral protocols have been developed for both forms of associative learning, both of which increase the occurrence of biting following training. Because the neural circuitry that mediates the behavior is well characterized and amenable to detailed cellular analyses, substantial progress has been made toward a comparative analysis of the cellular mechanisms underlying these two forms of associative learning. Both forms of associative learning use the same reinforcement pathway (the esophageal nerve, En) and the same reinforcement transmitter (dopamine, DA). In addition, at least one cellular locus of plasticity (cell B51) is modified by both forms of associative learning. However, the two forms of associative learning have opposite effects on B51. Classical conditioning decreases the excitability of B51, whereas operant conditioning increases the excitability of B51. Thus, the approach of using two forms of associative learning to modify a single behavior, which is mediated by an analytically tractable neural circuit, is revealing similarities and differences in the mechanisms that underlie classical and operant conditioning.

Simulator for neural networks and action potentials

A key challenge for neuroinformatics is to devise methods for representing, accessing, and integrating vast amounts of diverse and complex data. A useful approach to represent and integrate complex data sets is to develop mathematical models [Arbib (The Handbook of Brain Theory and Neural Networks, pp. 741-745, 2003); Arbib and Grethe (Computing the Brain: A Guide to Neuroinformatics, 2001); Ascoli (Computational Neuroanatomy: Principles and Methods, 2002); Bower and Bolouri (Computational Modeling of Genetic and Biochemical Networks, 2001); Hines et al. (J. Comput. Neurosci. 17, 7-11, 2004); Shepherd et al. (Trends Neurosci. 21, 460-468, 1998); Sivakumaran et al. (Bioinformatics 19, 408-415, 2003); Smolen et al. (Neuron 26, 567-580, 2000); Vadigepalli et al. (OMICS 7, 235-252, 2003)]. Models of neural systems provide quantitative and modifiable frameworks for representing data and analyzing neural function. These models can be developed and solved using neurosimulators. One such neurosimulator is simulator for neural networks and action potentials (SNNAP) [Ziv (J. Neurophysiol. 71, 294-308, 1994)]. SNNAP is a versatile and user-friendly tool for developing and simulating models of neurons and neural networks. SNNAP simulates many features of neuronal function, including ionic currents and their modulation by intracellular ions and/or second messengers, and synaptic transmission and synaptic plasticity. SNNAP is written in Java and runs on most computers. Moreover, SNNAP provides a graphical user interface (GUI) and does not require programming skills. This chapter describes several capabilities of SNNAP and illustrates methods for simulating neurons and neural networks. SNNAP is available at http://snnap.uth.tmc.edu .

Teaching basic principles of neuroscience with computer simulations

It is generally believed that students learn best through activities that require their direct participation. By using simulations as a tool for learning neuroscience, students are directly engaged in the activity and obtain immediate feedback and reinforcement. This paper describes a series of biophysical models and computer simulations that can be used by educators and students to explore a variety of basic principles in neuroscience. The paper also suggests 'virtual laboratory' exercises that students may conduct to further examine biophysical processes underlying neural function. First, the Hodgkin and Huxley (HH) model is presented. The HH model is used to illustrate the action potential, threshold phenomena, and nonlinear dynamical properties of neurons (e.g., oscillations, postinhibitory rebound excitation). Second, the Morris-Lecar (ML) model is presented. The ML model is used to develop a model of a bursting neuron and to illustrate modulation of neuronal activity by intracellular ions. Lastly, principles of synaptic transmission are presented in small neural networks, which illustrate oscillatory behavior, excitatory and inhibitory postsynaptic potentials, and temporal summation.

Role of A-type K+ channels in spike broadening observed in soma and axon of Hermissenda type-B photoreceptors: a simulation study

In Hermissenda type-B photoreceptors, the spike is generated in the axon and back-propagated to the soma, resulting in smaller somatic spikes. Experimentally, blocking the A-type K+ current (IK,A) results in broadening of somatic spikes. Similarly, in a compartmental model of the photoreceptor, reducing the maximum A-type K+ conductance (gK,Amax) results in broadening of somatic spikes. However, simulations predict that little or no broadening of axonal spikes occurs when gK,Amax is reduced. The results can be explained by the voltage-dependent properties of IK,A and the different potential ranges that the somatic and axonal spike traverse. Because of the steeper I-V curve and faster activation of the K+ channels at higher potentials, the recruitment of additional K+ channels in the axon is able to compensate for the decrease in K+ conductance, yielding less spike broadening. These results also support the idea that spike duration in the axon may not be reliably inferred based upon recordings collected from the soma.

Bifurcation and singularity analysis of a molecular network for the induction of long-term memory

Withdrawal reflexes of the mollusk Aplysia exhibit sensitization, a simple form of long-term memory (LTM). Sensitization is due, in part, to long-term facilitation (LTF) of sensorimotor neuron synapses. LTF is induced by the modulatory actions of serotonin (5-HT). Pettigrew et al. developed a computational model of the nonlinear intracellular signaling and gene network that underlies the induction of 5-HT-induced LTF. The model simulated empirical observations that repeated applications of 5-HT induce persistent activation of protein kinase A (PKA) and that this persistent activation requires a suprathreshold exposure of 5-HT. This study extends the analysis of the Pettigrew model by applying bifurcation analysis, singularity theory, and numerical simulation. Using singularity theory, classification diagrams of parameter space were constructed, identifying regions with qualitatively different steady-state behaviors. The graphical representation of these regions illustrates the robustness of these regions to changes in model parameters. Because persistent protein kinase A (PKA) activity correlates with Aplysia LTM, the analysis focuses on a positive feedback loop in the model that tends to maintain PKA activity. In this loop, PKA phosphorylates a transcription factor (TF-1), thereby increasing the expression of an ubiquitin hydrolase (Ap-Uch). Ap-Uch then acts to increase PKA activity, closing the loop. This positive feedback loop manifests multiple, coexisting steady states, or multiplicity, which provides a mechanism for a bistable switch in PKA activity. After the removal of 5-HT, the PKA activity either returns to its basal level (reversible switch) or remains at a high level (irreversible switch). Such an irreversible switch might be a mechanism that contributes to the persistence of LTM. The classification diagrams also identify parameters and processes that might be manipulated, perhaps pharmacologically, to enhance the induction of memory. Rational drug design, to affect complex processes such as memory formation, can benefit from this type of analysis.

A model of the roles of essential kinases in the induction and expression of late long-term potentiation

The induction of late long-term potentiation (L-LTP) involves complex interactions among second-messenger cascades. To gain insights into these interactions, a mathematical model was developed for L-LTP induction in the CA1 region of the hippocampus. The differential equation-based model represents actions of protein kinase A (PKA), MAP kinase (MAPK), and CaM kinase II (CAMKII) in the vicinity of the synapse, and activation of transcription by CaM kinase IV (CAMKIV) and MAPK. L-LTP is represented by increases in a synaptic weight. Simulations suggest that steep, supralinear stimulus-response relationships between stimuli (e.g., elevations in [Ca(2+)]) and kinase activation are essential for translating brief stimuli into long-lasting gene activation and synaptic weight increases. Convergence of multiple kinase activities to induce L-LTP helps to generate a threshold whereby the amount of L-LTP varies steeply with the number of brief (tetanic) electrical stimuli. The model simulates tetanic, -burst, pairing-induced, and chemical L-LTP, as well as L-LTP due to synaptic tagging. The model also simulates inhibition of L-LTP by inhibition of MAPK, CAMKII, PKA, or CAMKIV. The model predicts results of experiments to delineate mechanisms underlying L-LTP induction and expression. For example, the cAMP antagonist RpcAMPs, which inhibits L-LTP induction, is predicted to inhibit ERK activation. The model also appears useful to clarify similarities and differences between hippocampal L-LTP and long-term synaptic strengthening in other systems.

Classical and operant conditioning differentially modify the intrinsic properties of an identified neuron

A long-standing debate in neuroscience is whether classical and operant conditioning are mechanistically similar or distinct. The feeding behavior of Aplysia provides a model system suitable for addressing this question. Here we report that classical and operant conditioning of feeding behavior differentially modify the intrinsic excitability of neuron B51, a critical element for the expression of the feeding response, thus revealing that these two forms of associative learning differ at the cellular level.

Reinforcement in an in vitro analog of appetitive classical conditioning of feeding behavior in Aplysia: blockade by a dopamine antagonist

In a recently developed in vitro analog of appetitive classical conditioning of feeding in Aplysia, the unconditioned stimulus (US) was electrical stimulation of the esophageal nerve (En). This nerve is rich in dopamine (DA)-containing processes, which suggests that DA mediates reinforcement during appetitive conditioning. To test this possibility, methylergonovine was used to antagonize DA receptors. Methylergonovine (1 nM) blocked the pairing-specific increase in fictive feeding that is usually induced by in vitro classical conditioning. The present results and previous observation that methylergonovine also blocks the effects of contingent reinforcement in an in vitro analog of appetitive operant conditioning suggest that DA mediates reinforcement for appetitive associative conditioning of feeding in Aplysia.

Dynamic properties of regulatory motifs associated with induction of three temporal domains of memory in aplysia

A model was developed to examine dynamical properties of regulatory motifs correlated with different temporal domains of memory. The model represents short-, intermediate-, and long-term phases of protein kinase A (PKA) activation, which appear related to corresponding phases of facilitation of the Aplysia sensorimotor synapse. The model also represents phosphorylation of the transcription factor CREB1 by PKA and consequent induction of the immediate-early gene Aplysia ubiquitin hydrolase (Ap-uch), which is essential for long-term synaptic facilitation (LTF). Simulations suggest mechanisms responsible for differing profiles of synaptic facilitation following massed vs. spaced exposures to 5-HT, and suggest a novel regulatory motif (gated positive feedback) is important for LTF. Simulations suggest zero-order ultrasensitivity may underlie a requirement of a threshold number of exposures to 5-HT for LTF induction. The model makes predictions for the dynamics of PKA activation and Ap-uch induction when MAP kinase is activated, or when repression of Ap-uch is relieved by inhibiting the transcription factor CREB2. This model may therefore be useful for understanding processes underlying memory formation in Aplysia and other systems.

Voltage-clamp analysis and computational model of dopaminergic neurons from mouse retina

Isolated dopaminergic amacrine (DA) cells in mouse retina fire rhythmic, spontaneous action potentials and respond to depolarizing current with trains of low-frequency action potentials. To investigate the roles of voltage-gated ion channels in these processes, the transient A-type K+ current (IK,A) and Ca2+ current (ICa) in isolated mouse DA cells were analyzed by voltage clamp. The IK,A activated at −60 mV and inactivated rapidly. ICa activated at around −30 mV and reached a peak at 10 mV without apparent inactivation. We also extended our previous computational model of the mouse DA cell to include the new electrophysiological data. The model consisted of a membrane capacitance in parallel with eight currents: Na+ transient (INa,T), Na+ persistent (INa,P), delayed rectifier potassium (IKdr), IK,A, calcium-dependent potassium (IK,Ca), L-type Ca2+ ICa, hyperpolarization-activated cation current (Ih), and a leak current (IL). Hodgkin-Huxley type equations were used to define the voltage- and time-dependent activation and inactivation. The simulations were implemented using the neurosimulator SNNAP. The model DA cell was spontaneously active from a wide range of initial membrane potentials. The spontaneous action potentials reached 35 mV at the peak and hyperpolarized to −76 mV between spikes. The spontaneous firing frequency in the model was 6 Hz. The model DA cell responded to prolonged depolarizing current injection by increasing its spiking frequency and eventually reaching a depolarization block at membrane potentials greater than −10 mV. The most important current for determining the firing rate was IK,A. When the amplitude of IK,A was decreased, the firing rate increased. ICa and IK,Ca also affected the width of action potentials but had only minor effects on the firing rate. Ih affected the firing rate slightly but did not change the waveform of the action potentials.

Computational Model of Touch Sensory Cells (T Cells) of the Leech: Role of the Afterhyperpolarization (AHP) in Activity-Dependent Conduction Failure

Bursts of spikes in T cells produce an AHP, which results from activation of a Na+/K+ pump and a Ca2+-dependent K+ current. Activity-dependent increases in the AHP are believed to induce conduction block of spikes in several regions of the neuron, which in turn, may decrease presynaptic invasion of spikes and thereby decrease transmitter release. To explore this possibility, we used the neurosimulator SNNAP to develop a multi-compartmental model of the T cell. The model incorporated empirical data that describe the geometry of the cell and activity-dependent changes of the AHP. Simulations indicated that at some branching points, activity-dependent increases of the AHP reduced the number of spikes transmitted from the minor receptive fields to the soma and beyond. More importantly, simulations also suggest that the AHP could modulate, under some circumstances, transmission from the soma to the synaptic terminals, suggesting that the AHP can regulate spike conduction within the presynaptic arborizations of the cell and could in principle contribute to the synaptic depression that is correlated with increases in the AHP.

Simulation of Drosophila circadian oscillations, mutations, and light responses by a model with VRI, PDP-1, and CLK

A model of Drosophila circadian rhythm generation was developed to represent feedback loops based on transcriptional regulation of per, Clk (dclock), Pdp-1, and vri (vrille). The model postulates that histone acetylation kinetics make transcriptional activation a nonlinear function of [CLK]. Such a nonlinearity is essential to simulate robust circadian oscillations of transcription in our model and in previous models. Simulations suggest that two positive feedback loops involving Clk are not essential for oscillations, because oscillations of [PER] were preserved when Clk, vri, or Pdp-1 expression was fixed. However, eliminating positive feedback by fixing vri expression altered the oscillation period. Eliminating the negative feedback loop in which PER represses per expression abolished oscillations. Simulations of per or Clk null mutations, of per overexpression, and of vri, Clk, or Pdp-1 heterozygous null mutations altered model behavior in ways similar to experimental data. The model simulated a photic phase-response curve resembling experimental curves, and oscillations entrained to simulated light-dark cycles. Temperature compensation of oscillation period could be simulated if temperature elevation slowed PER nuclear entry or PER phosphorylation. The model makes experimental predictions, some of which could be tested in transgenic Drosophila.

Current- and Voltage-Clamp Recordings and Computer Simulations of Kenyon Cells in the Honeybee

The mushroom body of the insect brain is an important locus for olfactory information processing and associative learning. The present study investigated the biophysical properties of Kenyon cells, which form the mushroom body. Current- and voltage-clamp analyses were performed on cultured Kenyon cells from honeybees. Current-clamp analyses indicated that Kenyon cells did not spike spontaneously in vitro. However, spikes could be elicited by current injection in approximately 85% of the cells. Of the cells that produced spikes during a 1-s depolarizing current pulse, approximately 60% exhibited repetitive spiking, whereas the remaining approximately 40% fired a single spike. Cells that spiked repetitively showed little frequency adaptation. However, spikes consistently became broader and smaller during repetitive activity. Voltage-clamp analyses characterized a fast transient Na+current ( INa), a delayed rectifier K+current ( IK,V), and a fast transient K+current ( IK,A). Using the neurosimulator SNNAP, a Hodgkin–Huxley-type model was developed and used to investigate the roles of the different currents during spiking. The model led to the prediction of a slow transient outward current ( IK,ST) that was subsequently identified by reevaluating the voltage-clamp data. Simulations indicated that the primary currents that underlie spiking are INaand IK,V, whereas IK,Aand IK,STprimarily determined the responsiveness of the model to stimuli such as constant or oscillatory injections of current.

Extending in vitro conditioning in Aplysia to analyze operant and classical processes in the same preparation

Operant and classical conditioning are major processes shaping behavioral responses in all animals. Although the understanding of the mechanisms of classical conditioning has expanded significantly, the understanding of the mechanisms of operant conditioning is more limited. Recent developments in Aplysia are helping to narrow the gap in the level of understanding between operant and classical conditioning, and have raised the possibility of studying the neuronal processes underlying the interaction of operant and classical components in a relatively complex learning task. In the present study, we describe a first step toward realizing this goal, by developing a single in vitro preparation in which both operant and classical conditioning can be studied concurrently. The new paradigm reproduced previously published results, even under more conservative and homogenous selection criteria and tonic stimulation regime. Moreover, the observed learning was resistant to delay, shortening, and signaling of reinforcement.

Spontaneous activity of dopaminergic retinal neurons

Dopaminergic local circuit neurons in the retina (DA cells) show robust, spontaneous, tetrodotoxin-sensitive pacemaking. To investigate the mechanism underlying this behavior, we characterized the sodium current and a subset of the potassium currents in the cells in voltage-clamp experiments. We found that there is a persistent component of the sodium current in DA cells which activates at more depolarized potentials than the transient component of the current. The transient component was completely inactivated at -50 mV, but DA cells remained able to fire spontaneous action potentials when potassium channels were partially blocked and the membrane potential remained above -40 mV. Based on these electrophysiological data, we developed a reduced computer model that reproduced the major features of DA cells. In simulations at the physiological resting potential, the persistent component of the sodium current was both necessary and sufficient to account for spontaneous activity, and the major contribution of the transient component of the sodium current was to initiate the depolarization of the model cell during the interspike interval. When tonic inhibition was simulated by lowering the input impedance of the model cell, the transient component played a larger role.

Multimodal behavior in a four neuron ring circuit: mode switching

We study a four-neuron ring circuit comprised of oscillating burst-type neurons unidirectionally coupled via inhibitory synapses. Simple circuits of this type have been used previously to study gait patterns. The ring circuit itself is a variant of the basic reciprocal inhibition network, and it exhibits the property of multistability (multiple stable modes of behavior). That is, different gait modes can be achieved via appropriate initialization of and parameterization of this self-excited oscillatory network. We demonstrate three common gait modes with this circuit: the walk, the bound, and a slightly rotated trot mode. Attention is focused mainly on the mechanisms of rapidly and effectively switching between these modes. Our simulations suggest that neuron membrane dynamics, as well as synaptic junctional properties, strongly influence phase sensitivity in the network; each synapse is a combination of both and can be characterized by a transient phase response curve (PRC). We use the same bursting neuron model to characterize all network neurons, and shape different transient PRCs by using different synaptic properties. The characteristics of these PRCs determine the gait modes sustained in any network configuration, as well as, the ability to switch between modes. The mechanisms explored in this simple circuit, may find application in the switching of more complicated gait pattern networks, as well as, in the design of neuromorphic gait pattern circuits.

In vitro analog of classical conditioning of feeding behavior in aplysia

The feeding behavior of Aplysia californica can be classically conditioned using tactile stimulation of the lips as a conditioned stimulus (CS) and food as an unconditioned stimulus (US). Moreover, several neural correlates of classical conditioning have been identified. The present study extended previous work by developing an in vitro analog of classical conditioning and by investigating pairing-specific changes in neuronal and synaptic properties. The preparation consisted of the isolated cerebral and buccal ganglia. Electrical stimulation of a lip nerve (AT4) and a branch of the esophageal nerve (En2) served as the CS and US, respectively. Three protocols were used: paired, unpaired, and US alone. Only the paired protocol produced a significant increase in CS-evoked fictive feeding. At the cellular level, classical conditioning enhanced the magnitude of the CS-evoked synaptic input to pattern-initiating neuron B31/32. In addition, paired training enhanced both the magnitude of the CS-evoked synaptic input and the CS-evoked spike activity in command-like neuron CBI-2. The in vitro analog of classical conditioning reproduced all of the cellular changes that previously were identified following behavioral conditioning and has led to the identification of several new learning-related neural changes. In addition, the pairing-specific enhancement of the CS response in CBI-2 indicates that some aspects of associative plasticity may occur at the level of the cerebral sensory neurons.

Modeling interactions between electrical activity and second-messenger cascades in Aplysia neuron R15

The biophysical properties of neuron R15 in Aplysia endow it with the ability to express multiple modes of oscillatory electrical activity, such as beating and bursting. Previous modeling studies examined the ways in which membrane conductances contribute to the electrical activity of R15 and the ways in which extrinsic modulatory inputs alter the membrane conductances by biochemical cascades and influence the electrical activity. The goals of the present study were to examine the ways in which electrical activity influences the biochemical cascades and what dynamical properties emerge from the ongoing interactions between electrical activity and these cascades. The model proposed by Butera et al. in 1995 was extended to include equations for the binding of Ca(2+) to calmodulin (CaM) and the actions of Ca(2+)/CaM on both adenylyl cyclase and phosphodiesterase. Simulations indicated that levels of cAMP oscillated during bursting and that these oscillations were approximately antiphasic to the oscillations of Ca(2+). In the presence of cAMP oscillations, brief perturbations could switch the electrical activity between bursting and beating (bistability). Compared with a constant-cAMP model, oscillations of cAMP substantially expanded the range of bistability. Moreover, the integrated electrical/biochemical model simulated some early experimental results such as activity-dependent inactivation of the anomalous rectifier. The results of the present study suggest that the endogenous activity of R15 depends, in part, on interactions between electrical activity and biochemical cascades.

Desensitization of postsynaptic glutamate receptors contributes to high-frequency homosynaptic depression of aplysia sensorimotor connections

Withdrawal reflexes of Aplysia are mediated in part by a monosynaptic circuit of sensory (SN) and motor (MN) neurons. A brief high-frequency burst of spikes in the SN produces excitatory postsynaptic potentials (EPSPs) that rapidly decrease in amplitude during the burst of activity. It is generally believed that this and other (i.e., low-frequency) forms of homosynaptic depression are entirely caused by presynaptic mechanisms (e.g., depletion of releasable transmitter). The present study examines the contribution that desensitization of postsynaptic glutamate receptors makes to homosynaptic depression. Bath application of cyclothiazide, an agent that reduces desensitization of non-NMDA glutamate receptors, reduced high-, but not low-frequency synaptic depression. Thus, a postsynaptic mechanism, desensitization of glutamate receptors, can also contribute to homosynaptic depression of sensorimotor synapses.

Reduced Models of the Circadian Oscillators in Neurospora crassa and Drosophila melanogaster Illustrate Mechanistic Similarities

We have developed a reduced model representing feedback loops of transcriptional regulation underlying circadian rhythms in Neurospora crassa. The model contains two delay differential equations that describe the dynamics of two core gene products, FRQ and WCC. In a negative feedback loop, FRQ protein represses frq transcription by binding the white-collar complex (WCC), which consists of the WC-1 and WC-2 proteins. In a positive feedback loop, WCC indirectly enhances its own formation. The model simulates circadian oscillations, light entrainment, and a phase-response curve (PRC) similar to experimental PRCs. The Neurospora model is virtually identical to a model describing Drosophila circadian rhythm generation, illustrating that rhythm generation in these divergent organisms shares important mechanistic elements. Significant dynamic differences were found when the parameter spaces of both models were explored to analyze changes in oscillations and bifurcations to steady states. Stochastic fluctuations in molecule numbers were simulated with the Gillespie algorithm. Circadian oscillations and entrainment to light were simulated with <80 molecules of FRQ and WCC present on average. Simulations suggest that in both Neurospora and Drosophila, only the negative feedback loop is essential for circadian oscillations. Similar models may aid understanding of circadian mechanisms in mammals and other organisms.

Burst-induced synaptic depression and its modulation contribute to information transfer at Aplysia sensorimotor synapses: empirical and computational analyses

The Aplysia sensorimotor synapse is a key site of plasticity for several simple forms of learning. Plasticity of this synapse has been extensively studied, albeit primarily with individual action potentials elicited at low frequencies. Yet, the mechanosensory neurons fire high-frequency bursts in response to even moderate tactile stimuli delivered to the skin. In the present study, we extend this analysis to show that sensory neurons also fire bursts in the range of 1-60 Hz in response to electrical stimuli similar to those used in behavioral studies of sensitization. Intracellular stimulation of sensory neurons to fire a burst of action potentials at 10 Hz for 1 sec led to significant homosynaptic depression of postsynaptic responses. The depression was transient and fully recovered within 10 min. During the burst, the steady-state depressed phase of the postsynaptic response, which was only 20% of the initial EPSP of the burst, still contributed to firing the motor neuron. To explore the functional contribution of transient homosynaptic depression to the response of the motor neuron, computer simulations of the sensorimotor synapse with and without depression were compared. Depression allowed the motor neuron to produce graded responses over a wide range of presynaptic input strength. In addition, enhancement of synaptic transmission throughout a burst increased motor neuron output substantially more than did preferential enhancement of the initial phase of a burst. Thus, synaptic depression increased the dynamic range of the sensorimotor synapse and can, in principle, have a profound effect on information processing.

A computational study of the role of spike broadening in synaptic facilitation of Hermissenda

Pavlovian conditioning in Hermissenda produces a decrease in voltage-dependent (I(K,A) and I(Ca)) and Ca2+-dependent (I(K,Ca)) currents, and an increase in the action potential (AP) duration in type B-photoreceptors. In addition, synaptic connections between B and A photoreceptors and B photoreceptor and type I interneurons are facilitated. The increase in AP duration, produced by decreasing one or more K+ currents, may account for synaptic facilitation. The present study examined this issue by using a mathematical model of the B-photoreceptor and the neurosimulator SNNAP. In the model, decreasing g(K,A) by 70% increased the duration of the AP in the terminal by 41% and Ca2+ influx by 30%. However, if the decrease in g(K,A) was combined with a decrease in g(Ca), similar to what has been reported experimentally, the Ca2+ influx decreased by 54%. Therefore, the concomitant change in I(Ca) counter-acted the broadening-induced increase in Ca2+ influx in the synaptic terminal. This result suggests that a spike-duration independent process must contribute to the synaptic facilitation observed following Pavlovian conditioning.

Computational study of enhanced excitability in Hermissenda: membrane conductances modulated by 5-HT

Serotonin (5-HT) applied to the exposed but otherwise intact nervous system results in enhanced excitability of Hermissenda type-B photoreceptors. Several ion currents in the type-B photoreceptors are modulated by 5-HT, including the A-type K+ current (I(K,A)), sustained Ca2+ current (I(Ca,S)), Ca-dependent K+ current (I(K,Ca)), and a hyperpolarization-activated inward rectifier current (I(h)). In this study, we developed a computational model that reproduces physiological characteristics of type B photoreceptors, e.g. resting membrane potential, dark-adapted spike activity, spike width, and the amplitude difference between somatic and axonal spikes. We then used the model to investigate the contribution of different ion currents modulated by 5-HT to the magnitudes of enhanced excitability produced by 5-HT. Ion currents were systematically varied within limits observed experimentally, both individually and in combinations. A reduction of I(K,A) or I(K,Ca), or an increase in I(h) enhanced excitability by 20-50%. Decreasing I(Ca,S) produced a dramatic decrease in excitability. Reductions of I(K,V) produced only minimal increases in excitability, suggesting that I(K,V) probably plays a minor role in 5-HT induced enhanced excitability. Combinations of changes in I(K,A), I(K,Ca), I(h) and I(Ca,S) produced increases in excitability comparable to experimental observations. After 5-HT application, the cell's depolarization force is shifted from the I(h)-I(Ca,S) combination to predominantly I(h).