Oscillating neurons in the cochlear nucleus: I. Experimental basis of a simulation paradigm

Anatomical and physiological auditory data and pitch measurements are presented including some additional analysis. The data provide the basis for a new computer model of sustained chopper neurons in the ventral cochlear nucleus. New and old evidence indicating a preference for multiples of 0.4 ms in oscillations of chopper neurons in the cochlear nucleus of different species such as man, cats, and Guinea fowls, is summarized. Our hypothesis is that the time constant of 0.4 ms is due to the minimum synaptic delay of chopper neuron connections. Anatomical findings show that chopper neurons are indeed connected and can excite each other; a model of a circular network of neurons that are connected via synapses with a delay of 0.4 ms is thus plausible. Results concerning frequency tuning and dynamical properties of periodicity encoding of chopper neurons are reviewed. It is concluded that chopper neurons receive input both from auditory nerve fibres and onset neurons.     

Oscillating neurons in the cochlear nucleus: II. Simulation results

A computer model of sustained chopper neurons in the ventral cochlear nucleus is presented and investigated. In the companion paper, the underlying neurophysiological and neuroanatomical data are demonstrated. To explain the preference of chopper neurons for oscillations with periods which are multiples of a 0.4 ms synaptic delay, we suggest a model of circularly connected chopper neurons. In order to simulate chopper neurons within a physiological dynamic range for periodicity encoding, it is necessary to assume that they receive an input from onset neurons. Our computer analysis of the resulting simple neuronal network shows that it can produce stable oscillations. The chopping can be triggered by an amplitude-modulated signal (AM). The dynamic range and the synchronous response of the simulated chopper neurons to AM are enhanced significantly by an additional input from onset neurons. Physiological properties of chopper neurons in the cat, such as mean, standard deviation, and coefficient of variation of the interspike interval are matched precisely by our simulations.     

Leader neurons in leaky integrate and fire neural network simulations

In this paper, we highlight the topological properties of leader neurons whose existence is an experimental fact. Several experimental studies show the existence of leader neurons in population bursts of activity in 2D living neural networks (Eytan and Marom, J Neurosci 26(33):8465–8476, 2006; Eckmann et al., New J Phys 10(015011), 2008). A leader neuron is defined as a neuron which fires at the beginning of a burst (respectively network spike) more often than we expect by chance considering its mean firing rate. This means that leader neurons have some burst triggering power beyond a chance-level statistical effect. In this study, we characterize these leader neuron properties. This naturally leads us to simulate neural 2D networks. To build our simulations, we choose the leaky integrate and fire (lIF) neuron model (Gerstner and Kistler 2002; Cessac, J Math Biol 56(3):311–345, 2008), which allows fast simulations (Izhikevich, IEEE Trans Neural Netw 15(5):1063–1070, 2004; Gerstner and Naud, Science 326:379–380, 2009). The dynamics of our lIF model has got stable leader neurons in the burst population that we simulate. These leader neurons are excitatory neurons and have a low membrane potential firing threshold. Except for these two first properties, the conditions required for a neuron to be a leader neuron are difficult to identify and seem to depend on several parameters involved in the simulations themselves. However, a detailed linear analysis shows a trend of the properties required for a neuron to be a leader neuron. Our main finding is: A leader neuron sends signals to many excitatory neurons as well as to few inhibitory neurons and a leader neuron receives only signals from few other excitatory neurons. Our linear analysis exhibits five essential properties of leader neurons each with different relative importance. This means that considering a given neural network with a fixed mean number of connections per neuron, our analysis gives us a way of predicting which neuron is a good leader neuron and which is not. Our prediction formula correctly assesses leadership for at least ninety percent of neurons.     

Background impulse activity of neurons of the fastigial cerebellar nucleus of intact and labyrinthectomized rats under conditions of vibration

In acute experiments on nembutal-anesthetized (40 mg/kg, i.p.) albino rats, we recorded extracellularly and analyzed the background impulse activity (BIA) of neurons of the fastigial nucleus of the cerebellum. Experiments were carried out on intact and labyrinthectomized rats in the norm and after long-lasting (up to 15 days) influence of general vertical vibration (60 Hz, 0.4 mm, 2-h-long everyday sessions). Distributions of the neurons according to the level of regularity of BIA, dynamics of spike trains, pattern of histograms of interspike intervals (ISIs), and different frequency ranges of BIA were plotted; the mean frequency of this activity and the coefficient of variation of ISIs were also calculated. Possible mechanisms of the effects of long-lasting vibration of different durations on the BIA generated by neurons of the fastigial cerebellar nucleus in intact animals and after switching off of labyrinth afferent inputs are discussed. Neirofiziologiya/Neurophysiology, Vol. 38, No. 1, pp. 32–39, January–February, 2006.     

Frequency sensitivity in Hodgkin–Huxley systems

 The frequency sensitivity of weak periodic signal detection has been studied via numerical simulations for both a single neuron and a neuronal network. The dependence of the critical amplitude of the signal upon its frequency and a resonance between the intrinsic oscillations of a neuron and the signal could account for the frequency sensitivity. In the presence of both a subthreshold periodic signal and noise, the signal-to-noise ratio (SNR) of the output of either a single neuron or a neuronal network present the typical characteristics of stochastic resonance. In particular, there exists a frequency-sensitive range of 30–100 Hz, and for signals with frequencies within this range the SNRs have large values. This implies that the system under consideration (a single neuron or a neuronal network) is more sensitive to the detection of periodic signals, and the frequency sensitivity may be of a functional significance to signal processing. Received: 26 October 1999 / Accepted in revised form: 25 July 2000     

Discharge patterns in human motor units during fatiguing arm movements

The purpose of this study was to determinewhether short interspike intervals (ISIs of <20 ms) would occurnaturally during voluntary movement and would increase in number withfatigue. Thirty-four triceps brachii motor units from ninesubjects were assessed during a fatigue task consisting of fiftyextension and fifty flexion elbow movements against a constant-loadopposing extension. Nineteen motor units were recorded from thebeginning of the fatigue task; the number of short ISIs was 7.1 ± 4.1% of the total number of ISIs in the first one-third of the task(unfatigued state). This value increased to 11.8 ± 5.9% for thelast one-third of the task (fatigued state). Fifteen motor units wererecruited during the fatigue task and discharged, with 16.4 ± 6.0%of short ISIs in the fatigued state. For all motor units, the number of short ISIs was positively correlated(r² = 0.85) withthe recruitment threshold torque. Short ISIs occurred most frequentlyat movement initiation but also occurred throughout the movement. Theseresults document the presence of short ISIs during voluntary movementand their increase in number during fatigue.

     

Spike timing dependent plasticity promotes synchrony of inhibitory networks in the presence of heterogeneity

Recently Haas et al. (J Neurophysiol 96: 3305–3313, 2006), observed a novel form of spike timing dependent plasticity (iSTDP) in GABAergic synaptic couplings in layer II of the entorhinal cortex. Depending on the relative timings of the presynaptic input at time t _pre and the postsynaptic excitation at time t _post, the synapse is strengthened (Δt = t _post − t _pre > 0) or weakened (Δt < 0). The temporal dynamic range of the observed STDP rule was found to lie in the higher gamma frequency band (≥40 Hz), a frequency range important for several vital neuronal tasks. In this paper we study the function of this novel form of iSTDP in the synchronization of the inhibitory neuronal network. In particular we consider a network of two unidirectionally coupled interneurons (UCI) and two mutually coupled interneurons (MCI), in the presence of heterogeneity in the intrinsic firing rates of each coupled neuron. Using the method of spike time response curve (STRC), we show how iSTDP influences the dynamics of the coupled neurons, such that the pair synchronizes under moderately large heterogeneity in the firing rates. Using the general properties of the STRC for a Type-1 neuron model (Ermentrout, Neural Comput 8:979–1001, 1996) and the observed iSTDP we determine conditions on the initial configuration of the UCI network that would result in 1:1 in-phase synchrony between the two coupled neurons. We then demonstrate a similar enhancement of synchrony in the MCI with dynamic synaptic modulation. For the MCI we also consider heterogeneity introduced in the network through the synaptic parameters: the synaptic decay time of mutual inhibition and the self inhibition synaptic strength. We show that the MCI exhibits enhanced synchrony in the presence of all the above mentioned sources of heterogeneity and the mechanism for this enhanced synchrony is similar to the case of the UCI.     

Structure of Neuronal Impulse Trains of the Rat Inferior Olive under Conditions of Long-Lasting Vibrational Influence

In acute experiments on albino rats anesthetized with Nembutal (40 mg/kg, i.p.), we recorded the background impulse activity (BIA) generated by neurons of the inferior olive in the norm and after 5-, 10-, and 15-daylong vibrational influence (60 Hz, 2 h, daily). We characterized the distributions of neurons according to the regularity of impulse successions, their dynamics, and pattern of histograms of interspike intervals (ISIs); we also calculated the mean frequency of impulsation and the coefficient of variation of ISIs. It was demonstrated that the most significant shifts of the characteristics of BIA generated by neurons of the inferior olive were formed within the first 10 days of the vibrational influence. These shifts were observed mainly in the mean discharge frequency (increased within the initial period) and, to a lesser extent, in the intrinsic structure of impulse trains. Such shifts in the background activity of the inferior olive caused by long-lasting vibrational influence result, perhaps, from intensification of the influences of excitatory cerebellar/mesodiencephalic inputs to olivary neurons within the early periods of action of the above factor and prevalence of GABAergic influences within the later periods. It seems possible that, under such conditions, the characteristics of electrical synapses of the olivary neurons are also subjected to modification. Neirofiziologiya/Neurophysiology, Vol. 40, No. 4, pp. 340–347, July–August, 2008.     

Schema design and implementation of the grasp-related mirror neuron system

 Mirror neurons within a monkey's premotor area F5 fire not only when the monkey performs a certain class of actions but also when the monkey observes another monkey (or the experimenter) perform a similar action. It has thus been argued that these neurons are crucial for understanding of actions by others. We offer the hand-state hypothesis as a new explanation of the evolution of this capability: the basic functionality of the F5 mirror system is to elaborate the appropriate feedback – what we call the hand state– for opposition-space based control of manual grasping of an object. Given this functionality, the social role of the F5 mirror system in understanding the actions of others may be seen as an exaptation gained by generalizing from one's own hand to an other's hand. In other words, mirror neurons first evolved to augment the “canonical” F5 neurons (active during self-movement based on observation of an object) by providing visual feedback on “hand state,” relating the shape of the hand to the shape of the object. We then introduce the MNS1 (mirror neuron system 1) model of F5 and related brain regions. The existing Fagg–Arbib–Rizzolatti–Sakata model represents circuitry for visually guided grasping of objects, linking the anterior intraparietal area (AIP) with F5 canonical neurons. The MNS1 model extends the AIP visual pathway by also modeling pathways, directed toward F5 mirror neurons, which match arm–hand trajectories to the affordances and location of a potential target object. We present the basic schemas for the MNS1 model, then aggregate them into three “grand schemas”– visual analysis of hand state, reach and grasp, and the core mirror circuit – for each of which we present a useful implementation (a non-neural visual processing system, a multijoint 3-D kinematics simulator, and a learning neural network, respectively). With this implementation we show how the mirror system may learnto recognize actions already in the repertoire of the F5 canonical neurons. We show that the connectivity pattern of mirror neuron circuitry can be established through training, and that the resultant network can exhibit a range of novel, physiologically interesting behaviors during the process of action recognition. We train the system on the basis of final grasp but then observe the whole time course of mirror neuron activity, yielding predictions for neurophysiological experiments under conditions of spatial perturbation, altered kinematics, and ambiguous grasp execution which highlight the importance of the timingof mirror neuron activity. Received: 6 August 2001 / Accepted in revised form: 5 February 2002     

Effects of phase on homeostatic spike rates

Recent experimental results by Talathi et al. (Neurosci Lett 455:145–149, 2009) showed a divergence in the spike rates of two types of population spike events, representing the putative activity of the excitatory and inhibitory neurons in the CA1 area of an animal model for temporal lobe epilepsy. The divergence in the spike rate was accompanied by a shift in the phase of oscillations between these spike rates leading to a spontaneous epileptic seizure. In this study, we propose a model of homeostatic synaptic plasticity which assumes that the target spike rate of populations of excitatory and inhibitory neurons in the brain is a function of the phase difference between the excitatory and inhibitory spike rates. With this model of homeostatic synaptic plasticity, we are able to simulate the spike rate dynamics seen experimentally by Talathi et al. in a large network of interacting excitatory and inhibitory neurons using two different spiking neuron models. A drift analysis of the spike rates resulting from the homeostatic synaptic plasticity update rule allowed us to determine the type of synapse that may be primarily involved in the spike rate imbalance in the experimental observation by Talathi et al. We find excitatory neurons, particularly those in which the excitatory neuron is presynaptic, have the most influence in producing the diverging spike rates and causing the spike rates to be anti-phase. Our analysis suggests that the excitatory neuronal population, more specifically the excitatory to excitatory synaptic connections, could be implicated in a methodology designed to control epileptic seizures.     

Bats and frogs and animals in between: evidence for a common central timing mechanism to extract periodicity pitch

Widely divergent vertebrates share a common central temporal mechanism for representing periodicities of acoustic waveform events. In the auditory nerve, periodicities corresponding to frequencies or rates from about 10 Hz to over 1,000 Hz are extracted from pure tones, from low-frequency complex sounds (e.g., 1st harmonic in bullfrog calls), from mid-frequency sounds with low-frequency modulations (e.g., amplitude modulation rates in cat vocalizations), and from time intervals between high-frequency transients (e.g., pulse-echo delay in bat sonar). Time locking of neuronal responses to periodicities from about 50 ms down to 4 ms or less (about 20–300 Hz) is preserved in the auditory midbrain, where responses are dispersed across many neurons with different onset latencies from 4–5 to 20–50 ms. Midbrain latency distributions are wide enough to encompass two or more repetitions of successive acoustic events, so that responses to multiple, successive periods are ongoing simultaneously in different midbrain neurons. These latencies have a previously unnoticed periodic temporal pattern that determines the specific times for the dispersed on-responses.     

Using interspike intervals to quantify noise effects on spike trains in temperature encoding neurons

This paper examines how noise interacts with the non-linear dynamical mechanisms of neuronal stimulus. We study the spike trains generated by a minimal Hodgkin-Huxley type model of a cold receptor neuron. The distributions of interspike intervals(ISIs) of purely deterministic simulations exhibit considerable differences compared to the noisy ones. We quantify the effect of noise using ISI return plots and the ISI-distance recently proposed by Kreuz et al. (J Neurosci Meth, 165:151–161, 2007). It is shown that the spike trains of a cold receptor neuron are more strongly affected by noise for low temperatures than for high temperatures. This trend is also observed in both regimes of cold receptors: tonic firing(which occurs for low and high temperatures) and bursting (which occurs for intermediate temperatures).     

Modifications of neuronal activity in the rat hypothalamic supraoptic nucleus after long-lasting vibrational stimulation

We analyzed the background impulse activity (BIA) generated by neurons of the rat hypothalamic supraoptic nucleus in the norm and under conditions of long-lasting vibrational stimulation (exposure 5, 10, or 15 days). Distributions of neurons by the level of regularity, dynamics of discharge trains, form of histograms of interspike intervals (ISIs), as well as distributions of neurons by the BIA frequency ranges, were studied. We also calculated the mean frequency of impulsation of the neurons under study and the coefficient of variation of ISIs. After vibrational influences, we found modifications of both the internal structure of the recorded spike trains and the mean frequency of impulsation within the entire studied group and different frequency subgroups. Neirofiziologiya/Neurophysiology, Vol. 38, No. 3, pp. 224–230, May–June, 2006.     

Relative spike timing in stochastic oscillator networks of the Hermissenda eye

The role of relative spike timing on sensory coding and stochastic dynamics of small pulse-coupled oscillator networks is investigated physiologically and mathematically, based on the small biological eye network of the marine invertebrate Hermissenda. Without network interactions, the five inhibitory photoreceptors of the eye network exhibit quasi-regular rhythmic spiking; in contrast, within the active network, they display more irregular spiking but collective network rhythmicity. We investigate the source of this emergent network behavior first analyzing the role of relative input to spike–timing relationships in individual cells. We use a stochastic phase oscillator equation to model photoreceptor spike sequences in response to sequences of inhibitory current pulses. Although spike sequences can be complex and irregular in response to inputs, we show that spike timing is better predicted if relative timing of spikes to inputs is accounted for in the model. Further, we establish that greater noise levels in the model serve to destroy network phase-locked states that induce non-monotonic stimulus rate-coding, as predicted in Butson and Clark (J Neurophysiol 99:146–154, 2008a; J Neurophysiol 99:155–165, 2008b). Hence, rate-coding can function better in noisy spiking cells relative to non-noisy cells. We then study how relative input to spike–timing dynamics of single oscillators contribute to network-level dynamics. Relative timing interactions in the network sharpen the stimulus window that can trigger a spike, affecting stimulus encoding. Also, we derive analytical inter-spike interval distributions of cells in the model network, revealing that irregular Poisson-like spike emission and collective network rhythmicity are emergent properties of network dynamics, consistent with experimental observations. Our theoretical results generate experimental predictions about the nature of spike patterns in the Hermissenda eye.     

The response of a classical Hodgkin–Huxley neuron to an inhibitory input pulse

A population of uncoupled neurons can often be brought close to synchrony by a single strong inhibitory input pulse affecting all neurons equally. This mechanism is thought to underlie some brain rhythms, in particular gamma frequency (30–80 Hz) oscillations in the hippocampus and neocortex. Here we show that synchronization by an inhibitory input pulse often fails for populations of classical Hodgkin–Huxley neurons. Our reasoning suggests that in general, synchronization by inhibitory input pulses can fail when the transition of the target neurons from rest to spiking involves a Hopf bifurcation, especially when inhibition is shunting, not hyperpolarizing. Surprisingly, synchronization is more likely to fail when the inhibitory pulse is stronger or longer-lasting. These findings have potential implications for the question which neurons participate in brain rhythms, in particular in gamma oscillations.     

<Emphasis Type="Italic">Brn-3a</Emphasis> Deficiency Transiently Increases Expression of Calbindin D-28 k and Calretinin in the Trigeminal Ganglion During Embryonic Development

Immunohistochemistry for neuron-specific nuclear protein (NeuN), caspase-3, calcitonin gene-related peptide (CGRP), and calcium-binding proteins was performed on the trigeminal ganglion (TG) in wild type and Brn-3a knockout mice at embryonic days 12.5–16.5 (E12.5–E16.5). In Brn-3a knockout mice, the number of NeuN-immunoreactive (ir) neuron profiles increased at E14.5 (40.0% increase) and decreased at E16.5 (28.3% reduction) compared to wild type mice. Caspase-3-ir neuron profiles were abundant in the TG of wild type mice at E12.5–E16.5. However, the loss of Brn-3a decreased the number of caspase-3-ir neuron profiles at E12.5 (69.7% reduction) and E14.5 (51.7% reduction). At E16.5, the distribution of caspase-3-ir neuron profiles was barely affected by the deficiency. CGRP-ir neuron profiles were observed in the TG of wild type mice but not knockout mice at E12.5. At E14.5 and E16.5, CGRP-ir neuron profiles were abundant in both wild type and knockout mice. Calbindin D-28 k (CB)-ir neuron profiles decreased in the TG of mutant mice at E12.5 compared to wild type mice (56.4% reduction). At E14.5, however, Brn-3a deficiency transiently increased CB-ir neuron profiles (169.4% increase as compared to wild type mice). Calretinin (CR)-ir neuron profiles could not be detected in the TG of wild type mice at E12.5–16.5. However, numerous CR-ir neuron profiles transiently appeared in the knockout mouse at E14.5. Parvalbumin (PV)-ir neurons appeared in wild type and knockout mice at E14.5. At this stage, the number of large (>50 μm²) PV-ir neuron profiles in knockout mice was fewer than that in wild type mice. The number and cell size of PV-ir neuron profiles were barely affected by the deficiency at E16.5. The present study indicates that the loss of Brn-3a causes increase of TG neurons at E14.5 and decrease of TG neurons at E16.5. It is also suggested that Brn-3a deficiency affects the number and cell size of CGRP- and calcium-binding protein-containing neurons at E12.5 and E14.5. Caspase-3-dependent cell death of CB- and CR-ir neurons may be suppressed by the deficiency at E14.5.     

Dynamics of two electrically coupled chaotic neurons: Experimental observations and model analysis

Conductance-based models of neurons from the lobster stomatogastric ganglion (STG) have been developed to understand the observed chaotic behavior of individual STG neurons. These models identify an additional slow dynamical process – calcium exchange and storage in the endoplasmic reticulum – as a biologically plausible source for the observed chaos in the oscillations of these cells. In this paper we test these ideas further by exploring the dynamical behavior when two model neurons are coupled by electrical or gap junction connections. We compare in detail the model results to the laboratory measurements of electrically-coupled neurons that we reported earlier. The experiments on the biological neurons varied the strength of the effective coupling by applying a parallel, artificial synapse, which changed both the magnitude and polarity of the conductance between the neurons. We observed a sequence of bifurcations that took the neurons from strongly synchronized in-phase behavior, through uncorrelated chaotic oscillations to strongly synchronized – and now regular – out-of-phase behavior. The model calculations reproduce these observations quantitatively, indicating that slow subcellular processes could account for the mechanisms involved in the synchronization and regularization of the otherwise individual chaotic activities. Received: 28 June 1999 / Accepted in revised form: 30 June 2000     

Impact of gamma-oscillatory inhibition on the signal transmission of a cortical pyramidal neuron

Networks of synchronized fast-spiking interneurons are thought to be key elements in the generation of gamma (γ) oscillations (30–80 Hz) in the brain. We examined how such γ-oscillatory inhibition regulates the output of a cortical pyramidal cell. Specifically, we modeled a situation where a pyramidal cell receives inputs from γ-synchronized fast-spiking inhibitory interneurons. This model successfully reproduced several important aspects of a recent experimental result regarding the γ-inhibitory regulation of pyramidal cellular firing that is presumably associated with the sensation of whisker stimuli. Through an in-depth analysis of this model system, we show that there is an obvious rhythmic gating effect of the γ-oscillated interneuron networks on the pyramidal neuron’s signal transmission. This effect is further illustrated by the interactions of this interneuron network and the pyramidal neuron. Prominent power in the γ frequency range can emerge provided that there are appropriate delays on the excitatory connections and inhibitory synaptic conductance between interneurons. These results indicate that interactions between excitation and inhibition are critical for the modulation of coherence and oscillation frequency of network activities.     

Cross-trial correlation analysis of evoked potentials reveals arousal-related attenuation of thalamo-cortical coupling

We describe a computational method for assessing functional connectivity in sensory neuronal networks. The method, which we term cross-trial correlation, can be applied to signals representing local field potentials (LFPs) evoked by sensory stimulations and utilizes their trial-to-trial variability. A set of single trial samples of a given post-stimulus latency from consecutive evoked potentials (EPs) recorded at a given site is correlated with such sets for all other latencies and recording sites. The results of this computation reveal how neuronal activities at various sites and latencies correspond to activation of other sites at other latencies. The method was used to investigate the functional connectivity of thalamo-cortical network of somatosensory system in behaving rats at two levels of alertness: habituated and aroused. We analyzed potentials evoked by vibrissal deflections recorded simultaneously from the ventrobasal thalamus and barrel cortex. The cross-trial correlation analysis applied to the early post-stimulus period (<25 ms) showed that the magnitude of the population spike recorded in the thalamus at 5 ms post-stimulus correlated with the cortical activation at 6–13 ms post-stimulus. This correlation value was reduced at 6–9 ms, i.e. at early postsynaptic cortical response, with increased level of the animals’ arousal. Similarly, the aroused state diminished positive thalamo-cortical correlation for subsequent early EP waves, whereas the efficacy of an indirect cortico-fugal inhibition (over 15 ms) did not change significantly. Thus we were able to characterize the state related changes of functional connections within the thalamo-cortical network of behaving animals.     

Differential channeling of sensory stimuli onto a motor neuron in the leech

We studied a specific sensory-motor pathway in the isolated leech ganglia. Pressure-sensitive mechanosensory neurons were stimulated with trains of action potentials at 5–20 Hz while recording the responses of the annulus erector motorneurons that control annuli erection. The response of the annulus erector neurons was a succession of excitatory postsynaptic potentials followed by inhibitory postsynaptic potentials. The excitatory postsynaptic potentials had a brief time-course while the inhibitory postsynaptic potentials had a prolonged time-course that enabled their temporal summation. Thus, the net effect of pressure-sensitive neuron stimulation on the annulus erector neurons was inhibitory. Both phases of the response were mediated by chemical transmission; the excitatory postsynaptic potentials were transmitted via a monosynaptic pathway, and the inhibitory postsynaptic potentials via a polysynaptic one. The pattern of expression of this dual response depended on the field of innervation of the sensory neuron and it was under the influence of cell 151, a non-spiking interneuron, that could regulate the expression of the hyperpolarization. The interaction between pressure-sensitive neurons and annulus erector neuron reveals how sensory specificity, connectivity pattern and regulatory elements interplay in a specific sensory-motor network. Accepted: 6 November 1998