Two-neurons network

The behavior of two pacemakers simulated by integrate and fire oscillators reciprocally connected by synapses is studied. The activation of each synapse produces a sudden potential shift in the post-synaptic neuron. Two sorts of behaviour may occur when at least one synapse is excitatory. Phase-locking occurs for almost every set of parameters, and given certain initial conditions. Repetitive patterns in indifferent equilibrium appear in the presence of a given set of parameters and certain other initial conditions. Quasi-periodic behaviour corresponds to almost every set of parameters when both synapses are inhibitory, although repetitive patterns of firing in indifferent equilibrium occassionally occur.     

Local and global synchronization transitions induced by time delays in small-world neuronal networks with chemical synapses

Effects of time delay on the local and global synchronization in small-world neuronal networks with chemical synapses are investigated in this paper. Numerical results show that, for both excitatory and inhibitory coupling types, the information transmission delay can always induce synchronization transitions of spiking neurons in small-world networks. In particular, regions of in-phase and out-of-phase synchronization of connected neurons emerge intermittently as the synaptic delay increases. For excitatory coupling, all transitions to spiking synchronization occur approximately at integer multiples of the firing period of individual neurons; while for inhibitory coupling, these transitions appear at the odd multiples of the half of the firing period of neurons. More importantly, the local synchronization transition is more profound than the global synchronization transition, depending on the type of coupling synapse. For excitatory synapses, the local in-phase synchronization observed for some values of the delay also occur at a global scale; while for inhibitory ones, this synchronization, observed at the local scale, disappears at a global scale. Furthermore, the small-world structure can also affect the phase synchronization of neuronal networks. It is demonstrated that increasing the rewiring probability can always improve the global synchronization of neuronal activity, but has little effect on the local synchronization of neighboring neurons.     

When inhibition not excitation synchronizes neural firing

Excitatory and inhibitory synaptic coupling can have counter-intuitive effects on the synchronization of neuronal firing. While it might appear that excitatory coupling would lead to synchronization, we show that frequently inhibition rather than excitation synchronizes firing. We study two identical neurons described by integrate-and-fire models, general phase-coupled models or the Hodgkin-Huxley model with mutual, non-instantaneous excitatory or inhibitory synapses between them. We find that if the rise time of the synapse is longer than the duration of an action potential, inhibition not excitation leads to synchronized firing.     

Noise-tolerant stimulus discrimination by synchronization with depressing synapses

 Some synapses between cortical pyramidal neurons exhibit a rapid depression of excitatory postsynaptic potentials for successive presynaptic spikes. Since depressing synapses do not transmit information on sustained presynaptic firing rates, it has been speculated that they are favorable for temporal coding. In this paper, we study the dynamical effects of depressing synapses on stimulus-induced transient synchronization in a simple network of inhibitory interneurons and excitatory neurons, assuming that the recurrent excitation is mediated by depressing synapses. This synchronization occurs in a temporal pattern which depends on a given stimulus. Since the presence of noise is always a potential hazard in temporal coding, we investigate the extent to which noise in stimuli influences the synchronization phenomena. It is demonstrated that depressing synapses greatly contribute to suppressing the influences of noise on the stimulus-specific temporal patterns of synchronous firing. The timing-based Hebbian learning revealed by physiological experiments is shown to stabilize the temporal patterns in cooperation with synaptic depression. Thus, the times at which synchronous firing occurs provides a reliable information representation in the presence of synaptic depression. Received: 5 July 2000 / Accepted in revised form: 12 January 2001     

Synaptic dendritic activity modulates the single synaptic event

Synaptic transmission is the key system for the information transfer and elaboration among neurons. Nevertheless, a synapse is not a standing alone structure but it is a part of a population of synapses inputting the information from several neurons on a specific area of the dendritic tree of a single neuron. This population consists of excitatory and inhibitory synapses the inputs of which drive the postsynaptic membrane potential in the depolarizing (excitatory synapses) or depolarizing (inhibitory synapses) direction modulating in such a way the postsynaptic membrane potential. The postsynaptic response of a single synapse depends on several biophysical factors the most important of which is the value of the membrane potential at which the response occurs. The concurrence in a specific time window of inputs by several synapses located in a specific area of the dendritic tree can, consequently, modulate the membrane potential such to severely influence the single postsynaptic response. The degree of modulation operated by the synaptic population depends on the number of synapses active, on the relative proportion between excitatory and inbibitory synapses belonging to the population and on their specific mean firing frequencies. In the present paper we show results obtained by the simulation of the activity of a single Glutamatergic excitatory synapse under the influence of two different populations composed of the same proportion of excitatory and inhibitory synapses but having two different sizes (total number of synapses). The most relevant conclusion of the present simulations is that the information transferred by the single synapse is not and independent simple transition between a pre- and a postsynaptic neuron but is the result of the cooperation of all the synapses which concurrently try to transfer the information to the postsynaptic neuron in a given time window. This cooperativeness is mainly operated by a simple mechanism of modulation of the postsynaptic membrane potential which influences the amplitude of the different components forming the postsynaptic excitatory response.     

Stabilization of Hebbian neural nets by inhibitory learning

In Hebbian neural models synaptic reinforcement occurs when the pre- and post-synaptic neurons are simultaneously active. This causes an instability toward unlimited growth of excitatory synapses. The system can be stabilized by recurrent inhibition via modifiable inhibitory synapses. When this process is included, it is possible to dispense with the non-linear normalization or cut-off conditions which were necessary for stability in previous models. The present formulation is response-linear if synaptic changes are slow. It is self-consistent because the stabilizing effects will tend to keep most neural activity in the middle range, where neural response is approximately linear. The linearized equations are tensor invariant under a class of rotations of the state space. Using this, the response to stimulation may be derived as a set of independent modes of activity distributed over the net, which may be identified with cell assemblies. A continuously infinite set of equivalent solutions exists.     

LTS and FS inhibitory interneurons, short-term synaptic plasticity, and cortical circuit dynamics

Somatostatin-expressing, low threshold-spiking (LTS) cells and fast-spiking (FS) cells are two common subtypes of inhibitory neocortical interneuron. Excitatory synapses from regular-spiking (RS) pyramidal neurons to LTS cells strongly facilitate when activated repetitively, whereas RS-to-FS synapses depress. This suggests that LTS neurons may be especially relevant at high rate regimes and protect cortical circuits against over-excitation and seizures. However, the inhibitory synapses from LTS cells usually depress, which may reduce their effectiveness at high rates. We ask: by which mechanisms and at what firing rates do LTS neurons control the activity of cortical circuits responding to thalamic input, and how is control by LTS neurons different from that of FS neurons? We study rate models of circuits that include RS cells and LTS and FS inhibitory cells with short-term synaptic plasticity. LTS neurons shift the RS firing-rate vs. current curve to the right at high rates and reduce its slope at low rates; the LTS effect is delayed and prolonged. FS neurons always shift the curve to the right and affect RS firing transiently. In an RS-LTS-FS network, FS neurons reach a quiescent state if they receive weak input, LTS neurons are quiescent if RS neurons receive weak input, and both FS and RS populations are active if they both receive large inputs. In general, FS neurons tend to follow the spiking of RS neurons much more closely than LTS neurons. A novel type of facilitation-induced slow oscillations is observed above the LTS firing threshold with a frequency determined by the time scale of recovery from facilitation. To conclude, contrary to earlier proposals, LTS neurons affect the transient and steady state responses of cortical circuits over a range of firing rates, not only during the high rate regime; LTS neurons protect against over-activation about as well as FS neurons.     

Synaptic integration in spinal motoneurones.

Spinal motoneurones receive thousands of presynaptic excitatory and inhibitory synaptic contacts distributed throughout their dendritic trees. Despite this extensive convergence, there have been very few studies of how synaptic inputs interact in mammalian motoneurones when they are activated concurrently. In the experiments reported here, we measured the effective synaptic currents and the changes in firing rate evoked in cat spinal motoneurones by concurrent repetitive activation of two separate sets of presynaptic neurons. We compared these effects to those predicted by a linear sum of the effects produced by activating each set of presynaptic neurons separately. We generally found that when two inputs were activated concurrently, both the effective synaptic currents and the synaptically-evoked changes in firing rate they produced in motoneurones were generally linear, or slightly less than the linear sum of the effects produced by activating each input alone. The results suggest that the spatial distribution synaptic terminals on the dendritic trees of motoneurones may help isolate synapses from one another, minimizing non-linear interactions.     

Cortical network modeling: analytical methods for firing rates and some properties of networks of LIF neurons.

The circuitry of cortical networks involves interacting populations of excitatory (E) and inhibitory (I) neurons whose relationships are now known to a large extent. Inputs to E- and I-cells may have their origins in remote or local cortical areas. We consider a rudimentary model involving E- and I-cells. One of our goals is to test an analytic approach to finding firing rates in neural networks without using a diffusion approximation and to this end we consider in detail networks of excitatory neurons with leaky integrate-and-fire (LIF) dynamics. A simple measure of synchronization, denoted by S(q), where q is between 0 and 100 is introduced. Fully connected E-networks have a large tendency to become dominated by synchronously firing groups of cells, except when inputs are relatively weak. We observed random or asynchronous firing in such networks with diverse sets of parameter values. When such firing patterns were found, the analytical approach was often able to accurately predict average neuronal firing rates. We also considered several properties of E-E networks, distinguishing several kinds of firing pattern. Included were those with silences before or after periods of intense activity or with periodic synchronization. We investigated the occurrence of synchronized firing with respect to changes in the internal excitatory postsynaptic potential (EPSP) magnitude in a network of 100 neurons with fixed values of the remaining parameters. When the internal EPSP size was less than a certain value, synchronization was absent. The amount of synchronization then increased slowly as the EPSP amplitude increased until at a particular EPSP size the amount of synchronization abruptly increased, with S(5) attaining the maximum value of 100%. We also found network frequency transfer characteristics for various network sizes and found a linear dependence of firing frequency over wide ranges of the external afferent frequency, with non-linear effects at lower input frequencies. The theory may also be applied to sparsely connected networks, whose firing behaviour was found to change abruptly as the probability of a connection passed through a critical value. The analytical method was also found to be useful for a feed-forward excitatory network and a network of excitatory and inhibitory neurons.     

The self-tuning neuron: synaptic scaling of excitatory synapses

Homeostatic synaptic scaling is a form of synaptic plasticity that adjusts the strength of all of a neuron's excitatory synapses up or down to stabilize firing. Current evidence suggests that neurons detect changes in their own firing rates through a set of calcium-dependent sensors that then regulate receptor trafficking to increase or decrease the accumulation of glutamate receptors at synaptic sites. Additional mechanisms may allow local or network-wide changes in activity to be sensed through parallel pathways, generating a nested set of homeostatic mechanisms that operate over different temporal and spatial scales.     

Immunocytochemistry of glycine in small neurons of the granule cell areas of the guinea pig dorsal cochlear nucleus: a post-embedding ultrastructural study

The axon terminals of the acoustic nerve contact different part of the cochlear nucleus including granule cell areas. Little is known of the cell composition and neural circuits of granule cell areas present in the fusiform and upper polymorphic layers of the dorsal cochlear nucleus in the guinea pig. The present ultrastructural immunocytochemical study exploits the technique of post-embedding immunogold and silver intensification to reveal the characteristics of small neurons in granule cell areas. Few neurons (Golgi-stellate cells) use glycine as inhibitory neurotransmitter which is present in symmetric synaptic boutons with pleomorphic and flat vesicles. In contrast, most neurons (granule and unipolar brush cells) are not glycine-positive, and presumably not excitatory. Most of the large axons (mossy fibres) in granule areas are probably excitatory (glycine-negative and storing round synaptic vesicles) and contact unipolar brush cells forming large synapses or granule cell dendrites by small synapses. A few large glycinergic boutons (inhibitory) also contact unipolar brush cells. The excitatory circuit of mossy fibre-unipolar brush and granule cells may be inhibited by the glycinergic terminals from the few glycinergic cells (Golgi-stellate neurons) present within the granule cell areas. The latter are not contacted by large mossy-like glycine terminals.     

Different extrinsic trophic factors regulate neurite outgrowth and synapse formation between identified Lymnaea neurons

The requirement for trophic factors in neurite outgrowth is well established, though their role in synapse formation is yet to be determined. Moreover, the issue of whether the trophic factors mediating neurite outgrowth are also responsible for synapse specification has not yet been resolved. To test whether trophic factors mediating neurite outgrowth and synapse formation between identified neurons are conserved in two molluscan species and whether these developmental processes are differentially regulated by different trophic factors, we used soma-soma and neurite-neurite synapses between identified Lymnaea neurons. We demonstrate here that the trophic factors present in Aplysia hemolymph, although sufficient to induce neurite outgrowth from Lymnaea neurons, do not promote specific synapse formation between excitatory partners. Specifically, the identified presynaptic neuron visceral dorsal 4 (VD4) and postsynaptic neuron left pedal dorsal 1 (LPeD1) were either paired in a soma-soma configuration or plated individually to allow neuritic contacts. Cells were cultured in either Lymnaea brain-conditioned medium (CM) or on poly-L-lysine dishes that were pretreated with Aplysia hemolymph (ApHM), but contained only Lymnaea defined medium (DM; does not promote neurite outgrowth). In ApHM-coated dishes containing DM, Lymnaea neurons exhibited extensive neurite outgrowth, but appropriate excitatory synapses failed to develop between the cells. Instead, inappropriate reciprocal inhibitory synapses formed between VD4 and LPeD1. Similar inappropriate inhibitory synapses were observed in Aplysia hemolymph-pretreated dishes that contained dialyzed Aplysia hemolymph. These inhibitory synapses were novel and inappropriate, because they do not exist in vivo. A receptor tyrosine kinase inhibitor (Lavendustin A) blocked neurite outgrowth induced by both Lymnaea CM and ApHM. However, it did not affect inappropriate inhibitory synapse formation between the neurons. These data demonstrate that neurite outgrowth but not inappropriate inhibitory synapse formation involves receptor tyrosine kinases. Together, our data provide direct evidence that trophic factors required for neurite outgrowth are conserved among two different molluscan species, and that neurite extension and synapse specification between excitatory partners are likely mediated by different trophic factors.     

Longitudinal neuronal organization and coordination in a simple vertebrate: a continuous,semi-quantitative computer model of the central pattern generator for swimming in young frog tadpoles

When frog tadpoles hatch their swimming requires co-ordinated contractions of trunk muscles, driven by motoneurons and controlled by a Central Pattern Generator (CPG). To study this co-ordination we used a 3.5 mm long population model of the young tadpole CPG with continuous distributions of neurons and axon lengths as estimated anatomically. We found that: (1) alternating swimming-type activity fails to self-sustain unless some excitatory interneurons have ascending axons, (2) a rostro-caudal (R-C) gradient in the distribution of excitatory premotor interneurons with short axons is required to obtain the R-C gradient in excitation and resulting progression of motoneuron firing necessary for forward swimming, (3) R-C delays in motoneuron firing decrease if excitatory motoneuron to premotor interneuron synapses are present, (4) these feedback connections and the electrical synapses between motoneurons synchronise motoneuron discharges locally, (5) the above findings are independent of the detailed membrane properties of neurons.     

Inhibitory Contribution to Suprathreshold Corticostriatal Responses: An Experimental and Modeling Study

Neostriatal neurons may undergo events of spontaneous synchronization as those observed in recurrent networks of excitatory neurons, even when cortical afferents are transected. It is necessary to explain these events because the neostriatum is a recurrent network of inhibitory neurons. Synchronization of neuronal activity may be caused by plateau-like depolarizations. Plateau-like orthodromic depolarizations that resemble up-states in medium spiny neostriatal neurons (MSNs) may be induced by a single corticostriatal suprathreshold stimulus. Slow synaptic depolarizations may last hundreds of milliseconds, decay slower than the monosynaptic glutamatergic synaptic potentials that induce them, and sustain repetitive firing. Because inhibitory inputs impinging onto MSNs have a reversal potential above the resting membrane potential but below the threshold for firing, they conform a type of “shunting inhibition”. This work asks if shunting GABAergic inputs onto MSNs arrive asynchronously enough as to help in sustaining the plateau-like corticostriatal response after a single cortical stimulus. This may help to begin explaining autonomous processing in the striatal micro-circuitry in the presence of a tonic excitatory drive and independently of spatio-temporally organized inputs. It is shown here that besides synaptic currents from AMPA/KA- and NMDA-receptors, as well as L-type intrinsic Ca²⁺- currents, inhibitory synapses help in maintaining the slow depolarization, although they accomplish the role of depressing firing at the beginning of the response. We then used a NEURON model of spiny cells to show that inhibitory synapses arriving asynchronously on the dendrites can help to simulate a plateau potential similar to that observed experimentally. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Diffusion barriers constrain receptors at synapses

The flux of neurotransmitter receptors in and out of synapses depends on receptor interaction with scaffolding molecules. However, the crowd of transmembrane proteins and the rich cytoskeletal environment may constitute obstacles to the diffusion of receptors within the synapse. To address this question, we studied the membrane diffusion of the γ-aminobutyric acid type A receptor (GABA(A)R) subunits clustered (γ2) or not (α5) at inhibitory synapses in rat hippocampal dissociated neurons. Relative to the extrasynaptic region, γ2 and α5 showed reduced diffusion and increased confinement at both inhibitory and excitatory synapses but they dwelled for a short time at excitatory synapses. In contrast, γ2 was ～3-fold more confined and dwelled ～3-fold longer in inhibitory synapses than α5, indicating faster synaptic escape of α5. Furthermore, using a gephyrin dominant-negative approach, we showed that the increased residency time of γ2 at inhibitory synapses was due to receptor-scaffold interactions. As shown for GABA(A)R, the excitatory glutamate receptor 2 subunit (GluA2) of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) had lower mobility in both excitatory and inhibitory synapses but a higher residency time at excitatory synapses. Therefore barriers impose significant diffusion constraints onto receptors at synapses where they accumulate or not. Our data further reveal that the confinement and the dwell time but not the diffusion coefficient report on the synapse specific sorting, trapping and accumulation of receptors.     

Signal propagation in feedforward neuronal networks with unreliable synapses

In this paper, we systematically investigate both the synfire propagation and firing rate propagation in feedforward neuronal network coupled in an all-to-all fashion. In contrast to most earlier work, where only reliable synaptic connections are considered, we mainly examine the effects of unreliable synapses on both types of neural activity propagation in this work. We first study networks composed of purely excitatory neurons. Our results show that both the successful transmission probability and excitatory synaptic strength largely influence the propagation of these two types of neural activities, and better tuning of these synaptic parameters makes the considered network support stable signal propagation. It is also found that noise has significant but different impacts on these two types of propagation. The additive Gaussian white noise has the tendency to reduce the precision of the synfire activity, whereas noise with appropriate intensity can enhance the performance of firing rate propagation. Further simulations indicate that the propagation dynamics of the considered neuronal network is not simply determined by the average amount of received neurotransmitter for each neuron in a time instant, but also largely influenced by the stochastic effect of neurotransmitter release. Second, we compare our results with those obtained in corresponding feedforward neuronal networks connected with reliable synapses but in a random coupling fashion. We confirm that some differences can be observed in these two different feedforward neuronal network models. Finally, we study the signal propagation in feedforward neuronal networks consisting of both excitatory and inhibitory neurons, and demonstrate that inhibition also plays an important role in signal propagation in the considered networks.     

Relationship between applicability of current-based synapses and uniformity of firing patterns

The purpose of this paper is to identify situations in neural network modeling where current-based synapses are applicable. The applicability of current-based synapse model for studying post-transient behavior of neural networks is discussed in terms of average synaptic current strength induced by per spike during one firing cycle of a neuron (or briefly per spike synaptic current strength). It was found that current-based synapse models are applicable in both situations where both the interspike intervals of the neurons and the distribution of firing times of the neurons are uniform, and where the firing of all neurons is synchronized. If neither the interspike intervals nor the distribution of firing times of the neurons is uniform or the reversal potential is between the rest and threshold potentials, current-based synapse models may be oversimplified.     

Inhibitory neurons exhibit high controlling ability in the cortical microconnectome

The brain is a network system in which excitatory and inhibitory neurons keep activity balanced in the highly non-random connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons in the cortex. So, in general, how inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question. There is much accumulated knowledge about this fundamental question. This study quantitatively evaluated the relatively higher functional contribution of inhibitory neurons in terms of not only properties of individual neurons, such as firing rate, but also in terms of topological mechanisms and controlling ability on other excitatory neurons. We combined simultaneous electrical recording (~2.5 hours) of ~1000 neurons in vitro, and quantitative evaluation of neuronal interactions including excitatory-inhibitory categorization. This study accurately defined recording brain anatomical targets, such as brain regions and cortical layers, by inter-referring MRI and immunostaining recordings. The interaction networks enabled us to quantify topological influence of individual neurons, in terms of controlling ability to other neurons. Especially, the result indicated that highly influential inhibitory neurons show higher controlling ability of other neurons than excitatory neurons, and are relatively often distributed in deeper layers of the cortex. Furthermore, the neurons having high controlling ability are more effectively limited in number than central nodes of k-cores, and these neurons also participate in more clustered motifs. In summary, this study suggested that the high controlling ability of inhibitory neurons is a key mechanism to keep balance with a large number of other excitatory neurons beyond simple higher firing rate. Application of the selection method of limited important neurons would be also applicable for the ability to effectively and selectively stimulate E/I imbalanced disease states.     

The suprachiasmatic nucleus exhibits diurnal variations in spontaneous excitatory postsynaptic activity

A most prominent feature of neurons in the suprachiasmatic nucleus (SCN) is the circadian rhythm in spontaneous firing frequency. To disclose synaptic mechanisms associated with the rhythmic activity, the spontaneous postsynaptic activity was studied using whole-cell, patch clamp recordings in the ventral region of the SCN in slice preparations from rats. The synaptic events were compared between two time intervals corresponding to the highest and lowest electrical activity within the SCN during subjective daytime and nighttime, respectively. The gamma-aminobutyric acid (GABA)-mediated spontaneous inhibitory activity showed no diurnal variations, but the excitatory activity was markedly higher in frequency, without differences in amplitude, during the subjective day compared to the subjective night. Spontaneous and evoked inhibitory synaptic events were blocked by the GABA(A) receptor antagonist bicuculline. The alpha-amino-hydroxy-5-methylisoxazole-4-propionic acid (AMPA/kainate) receptor antagonist 6-cyano-7-nitroquinoxaline-2, 3-dione (CNQX) blocked most of the excitatory activity. In addition, CNQX reduced the spontaneous inhibitory activity. The N-methyl-D-aspartate antagonist D-2-amino-5-phosphonopentanoic acid reduced the inhibitory activity to a lesser degree, and there was no significant difference in amplitude or frequency of synaptic events in control and Mg2+-free solutions, indicating that the AMPA receptor plays an important role in regulating the inhibitory release of GABA within the SCN. Ipsi- and contralateral stimulation of the SCN consistently evoked excitatory synaptic responses. Inhibitory synaptic responses occurred in some neurons upon increasing stimulus strength. In conclusion, this study shows that there is a substantial influence from spontaneous glutamatergic synapses on the ventral part of the SCN and that these exhibit daily variations in activity. Diurnal fluctuations in spontaneous excitatory postsynaptic activity within this network may contribute to the mechanisms for synchronization of rhythms between individual SCN neurons and may underlie the daily variations in the spontaneous firing frequency of SCN neurons.     

Coexistence of inhibitory dopamine D-1 and excitatory D-2 receptors on the same caudate nucleus neurons

Microiontophoretic studies using cats anesthetized with alpha-chloralose were performed to determine whether or not dopamine D-1 and D-2 receptors co-exist in the same caudate nucleus (CN) neurons that receive inputs from the substantia nigra (SN), and in which spikes elicited by SN stimulation were blocked by domperidone, a selective D-2 antagonist. Iontophoretic application of dopamine produced a dose-dependent inhibition of spontaneous firing in 2 of 4 spontaneously active CN neurons and an increase in firing in the remaining 2 neurons. However, dopamine inhibited the glutamate-induced firing in 31 of 32 CN neurons that were not spontaneously active. Similar inhibition with iontophoretically applied SKF 38393, a selective D-1 agonist, was observed in 33 of 34 spontaneously inactive neurons tested. When the effects of dopamine, SKF 38393 and bromocriptine (D-2 agonist) were examined on the same CN neurons, the inhibitory effects of both dopamine and SKF 38393 were seen in 14 of 15 neurons, and both an inhibition by SKF 38393 and an excitation by bromocriptine were observed in 15 of 17 neurons. The inhibitory effects of dopamine and SKF 38393 were antagonized by haloperidol and SCH 23390 (D-1 antagonist) without being affected by domperidone. Furthermore, the dopamine-induced inhibition was converted to an excitation during simultaneous application of SCH 23390 in 6 of 10 CN neurons, and this excitation was antagonized by domperidone. These results strongly suggest that the inhibitory D-1 and excitatory D-2 receptors co-exist on the same CN neurons receiving inputs from the SN.