Computational model of response maps in the dorsal cochlear nucleus

The neurons in the mammalian (gerbil, cat) dorsal cochlear nucleus (DCN) have responses to tones and noise that have been used to classify them into unit types. These types (I–V) are based on excitatory and inhibitory responses to tones organized into plots called response maps (RMs). Type I units show purely excitatory responses, while type V units are primarily inhibited. A computational model of the neural circuitry of the mammalian DCN, based on the MacGregor neuromime, was used to investigate RMs of the principal cells (P-cells) that represent the fusiform and giant cells. In gerbils, fusiform cells have been shown to have primarily type III unit response properties; however, fusiform cells in the cat DCN are thought to have type IV unit response properties. The DCN model is based on a previous computational model of the cat (Hancock and Voigt Ann Biomed Eng 27: 73–87, 1999) and gerbil (Zheng and Voigt Ann Biomed Eng 34: 697–708, 2006) DCN. The basic model for both species is architecturally the same, and to get either type III unit RMs or type IV unit RMs, connection parameters were adjusted. Interestingly, regardless of the RM type, these units in gerbils and cats show spectral notch sensitivity and are thought to play a role in sound localization in the median plane. In this study, further parameter adjustments were made to systematically explore their effect on P-cell RMs. Significantly, type I, type III, type III-i, type IV, type IV-T and type V unit RMs can be created for the modeled P-cells. Thus major RMs observed in the cat and gerbil DCN are recreated by the model. These results suggest that RMs of individual DCN projection neurons are the result of specific assortment of excitatory and inhibitory inputs to that neuron and that subtle differences in the complement of inputs can result in different RM types. Modulation of the efficacy of certain synapses suggests that RM type may change dynamically.     

Modeling inhibition of type II units in the dorsal cochlear nucleus

 Type II units in the dorsal cochlear nucleus (DCN) are characterized by vigorous but nonmonotonic responses to best frequency tones as a function of sound pressure level, and relatively weak responses to noise. A model of DCN neural circuitry was used to explore two hypothetical mechanisms by which neurons may be endowed with type II unit response properties. Both mechanisms assume that type II units receive excitatory input from auditory nerve (AN) fibers and inhibitory input from an unspecified class of cochlear nucleus interneurons that also receive excitatory AN input. The first mechanism, a lateral inhibition (LI) model, supposes that type II units receive inhibitory input from a number of narrowly tuned interneurons whose best frequencies (BFs) flank the BF of the type II unit. Tonal stimuli near BF result in only weak inhibitory input, but broadband stimuli recruit enough lateral inhibitors to greatly weaken the type II unit response. The second mechanism, a wideband inhibition (WBI) model, supposes that type II units receive inhibitory input from interneurons that are broadly tuned so that they respond more vigorously to broadband stimuli than to tones. Physiological and anatomical evidence points to the possible existence of such a class of neurons in the cochlear nucleus. The model extends an earlier computer model of an iso-frequency DCN patch to multiple frequency slices and adds a population of interneurons to provide the inhibition to model type II units (called I2-cells). The results show that both mechanisms accurately simulate responses of type II units to tones and noise. An experimental paradigm for distinguishing the two mechanisms is proposed. Received: 30 December 1996/Accepted in revised form: 13 March 1997     

Neural modeling of the dorsal cochlear nucleus: cross-correlation analysis of short-duration tone-burst responses

A conceptual model of a portion of dorsal cochlear nucleus (DCN) neural circuitry has emerged over the past two decades. This model suggests that the response properties of the DCN’s major projection neurons, called type IV units, are due, in part, to the behavior of local circuit inhibitory interneurons called type II units (Young and Brownell 1976). Cross-correlation studies of simultaneously recorded pairs of DCN units in decerebrate cat derived from 50-s best frequency (BF) stimuli are consistent with and have extended this conceptual model (Voigt and Young 1980, 1985, 1988, 1990). Interestingly, Gochin et al. (1989) found no signs of inhibition in the anesthetized rat DCN in cross-correlograms derived from 55-ms short-duration BF tone bursts. This seemingly contradictory result has motivated this study. Computer simulations were run using our network model of the intrinsic DCN neural circuitry. This model has previously been shown to reproduce the major features of both type II and type IV rate-level curves and the inhibitory trough (IT) observed in cross-correlograms derived from long-duration stimuli (Voigt and Davis 1994). The goal was to study the stimulus-duration-dependent strength of ITs in the cross-correlograms derived from short-duration BF tone-burst stimuli. The results suggest that ITs may not be detectable when the stimulus duration is 50 ms but may be detectable when the stimulus duration is 200 ms or greater. Furthermore, when the ITs are detected in cross-correlograms derived from 200-ms data sets, the strength of the IT, as measured by effectiveness, is comparable to the strength of ITs measured when the stimulus duration is 50 s. Received: 16 March 1994/Accepted in revised form: 31 May 1994     

Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells

Significant inroads have been made to understand cerebellar cortical processing but neural coding at the output stage of the cerebellum in the deep cerebellar nuclei (DCN) remains poorly understood. The DCN are unlikely to just present a relay nucleus because Purkinje cell inhibition has to be turned into an excitatory output signal, and DCN neurons exhibit complex intrinsic properties. In particular, DCN neurons exhibit a range of rebound spiking properties following hyperpolarizing current injection, raising the question how this could contribute to signal processing in behaving animals. Computer modeling presents an ideal tool to investigate how intrinsic voltage-gated conductances in DCN neurons could generate the heterogeneous firing behavior observed, and what input conditions could result in rebound responses. To enable such an investigation we built a compartmental DCN neuron model with a full dendritic morphology and appropriate active conductances. We generated a good match of our simulations with DCN current clamp data we recorded in acute slices, including the heterogeneity in the rebound responses. We then examined how inhibitory and excitatory synaptic input interacted with these intrinsic conductances to control DCN firing. We found that the output spiking of the model reflected the ongoing balance of excitatory and inhibitory input rates and that changing the level of inhibition performed an additive operation. Rebound firing following strong Purkinje cell input bursts was also possible, but only if the chloride reversal potential was more negative than −70 mV to allow de-inactivation of rebound currents. Fast rebound bursts due to T-type calcium current and slow rebounds due to persistent sodium current could be differentially regulated by synaptic input, and the pattern of these rebounds was further influenced by HCN current. Our findings suggest that active properties of DCN neurons could play a crucial role for signal processing in the cerebellum.     

Decorrelation of Neural-Network Activity by Inhibitory Feedback

Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural networks is common presynaptic input to pairs of neurons. Recent studies demonstrate that spike correlations in recurrent neural networks are considerably smaller than expected based on the amount of shared presynaptic input. Here, we explain this observation by means of a linear network model and simulations of networks of leaky integrate-and-fire neurons. We show that inhibitory feedback efficiently suppresses pairwise correlations and, hence, population-rate fluctuations, thereby assigning inhibitory neurons the new role of active decorrelation. We quantify this decorrelation by comparing the responses of the intact recurrent network (feedback system) and systems where the statistics of the feedback channel is perturbed (feedforward system). Manipulations of the feedback statistics can lead to a significant increase in the power and coherence of the population response. In particular, neglecting correlations within the ensemble of feedback channels or between the external stimulus and the feedback amplifies population-rate fluctuations by orders of magnitude. The fluctuation suppression in homogeneous inhibitory networks is explained by a negative feedback loop in the one-dimensional dynamics of the compound activity. Similarly, a change of coordinates exposes an effective negative feedback loop in the compound dynamics of stable excitatory-inhibitory networks. The suppression of input correlations in finite networks is explained by the population averaged correlations in the linear network model: In purely inhibitory networks, shared-input correlations are canceled by negative spike-train correlations. In excitatory-inhibitory networks, spike-train correlations are typically positive. Here, the suppression of input correlations is not a result of the mere existence of correlations between excitatory (E) and inhibitory (I) neurons, but a consequence of a particular structure of correlations among the three possible pairings (EE, EI, II).     

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.     

蛙下丘听觉神经元对双耳强度差检测功能的建模和仿真

建立了蛙下丘听觉神经元对双耳刺激强度差检测功能的一个数学模型。按此模型所作的计算机仿真和相应实验结果比较的一致性支持了下列假设 :下丘中的EO神经元对同侧刺激不产生反应可能是由于接受了来自同侧的强烈抑制性输入 ,从而掩盖了它同时接受到的来自同侧耳的兴奋性输入。而来自同侧的抑制性输入 ,与来自对侧的兴奋性输入可能通过突触前抑制的相互作用 ,则导致了EE神经元的双耳抑制现象。     

In vivo analysis of inhibitory synaptic inputs and rebounds in deep cerebellar nuclear neurons

Neuronal function depends on the properties of the synaptic inputs the neuron receive and on its intrinsic responsive properties. However, the conditions for synaptic integration and activation of intrinsic responses may to a large extent depend on the level of background synaptic input. In this respect, the deep cerebellar nuclear (DCN) neurons are of particular interest: they feature a massive background synaptic input and an intrinsic, postinhibitory rebound depolarization with profound effects on the synaptic integration. Using in vivo whole cell patch clamp recordings from DCN cells in the cat, we find that the background of Purkinje cell input provides a tonic inhibitory synaptic noise in the DCN cell. Under these conditions, individual Purkinje cells appear to have a near negligible influence on the DCN cell and clear-cut rebounds are difficult to induce. Peripheral input that drives the simple spike output of the afferent PCs to the DCN cell generates a relatively strong DCN cell inhibition, but do not induce rebounds. In contrast, synchronized climbing fiber activation, which leads to a synchronized input from a large number of Purkinje cells, can induce profound rebound responses. In light of what is known about climbing fiber activation under behaviour, the present findings suggest that DCN cell rebound responses may be an unusual event. Our results also suggest that cortical modulation of DCN cell output require a substantial co-modulation of a large proportion of the PCs that innervate the cell, which is a possible rationale for the existence of the cerebellar microcomplex.     

Presynaptic GABA(B) receptors modulate synaptic facilitation and depression at distinct synapses in fusiform cells of mouse dorsal cochlear nucleus

The mammalian dorsal cochlear nucleus (DCN) is considered to contribute to the localization of the sound sources. Fusiform cells (FCs), principal projection neurons in the DCN, integrate two excitatory inputs from auditory nerve fibers (ANFs) and parallel fibers (PFs). Although an immunohistochemical study suggested presence of GABA_B receptors at excitatory presynaptic terminals in the DCN, it has not been elucidated how GABA_B receptors modulate the synaptic transmission to FCs. Here, we examined effects of baclofen on the transmission in vitro. Baclofen reduced both PF-EPSC and ANF-EPSC by reducing transmitter releases, and it enhanced the facilitation in PF-FC synapses and prevented the depression in ANF-FC synapses. The enhancement and prevention were prominent during high-frequency (50 Hz) synaptic input, suggesting the activation of presynaptic GABA_B receptors may optimize both PF-FC and ANF-FC synapses for high-frequency transmission. Postsynaptic GABA_B receptors activated GIRK current and would further modulate the activity of FCs.     

Lateral sharpening of cortical frequency tuning by approximately balanced inhibition

Cortical inhibition plays an important role in shaping neuronal processing. The underlying synaptic mechanisms remain controversial. Here, in vivo whole-cell recordings from neurons in the rat primary auditory cortex revealed that the frequency tuning curve of inhibitory input was broader than that of excitatory input. This results in relatively stronger inhibition in frequency domains flanking the preferred frequencies of the cell and a significant sharpening of the frequency tuning of membrane responses. The less selective inhibition can be attributed to a broader bandwidth and lower threshold of spike tonal receptive field of fast-spike inhibitory neurons than nearby excitatory neurons, although both types of neurons receive similar ranges of excitatory input and are organized into the same tonotopic map. Thus, the balance between excitation and inhibition is only approximate, and intracortical inhibition with high sensitivity and low selectivity can laterally sharpen the frequency tuning of neurons, ensuring their highly selective representation.     

Subthreshold aortic nerve inputs to neurons in nucleus of the solitary tract

Subthreshold aortic nerve (AN) inputs to neurons receiving a monosynaptic AN-evoked input (MSNs: respond to each of two AN stimuli separated by 5 ms) and neurons receiving a polysynaptic AN input (PSNs) in the nucleus of the solitary tract (NTS) were identified in anesthetized rats. In extracellular recordings from 24 MSNs and 49 PSNs, 12% of MSNs and 29% of PSNs only responded to AN stimulation during the application of excitatory amino acids. In intracellular recordings from 24 MSNs and 22 PSNs, 12% of MSNs and 14% of PSNs responded to AN stimulation with excitatory postsynaptic potentials that did not evoke action potential discharge. Reductions in arterial pressure produced minimal changes in the spontaneous discharge of suprathreshold AN-evoked neurons, suggesting that these neurons receive excitatory inputs from nonbaroreceptor sources. The results suggest that some baroreflex-related NTS neurons exist in a "reserve state and can be changed to an active state or vice versa. This will change the number of neurons involved in baroreflex circuits and provides a novel mechanism for regulating baroreflex function independently of alterations in peripheral afferent input.     

Spectrotemporal processing in spectral tuning modules of cat primary auditory cortex

Spectral integration properties show topographical order in cat primary auditory cortex (AI). Along the iso-frequency domain, regions with predominantly narrowly tuned (NT) neurons are segregated from regions with more broadly tuned (BT) neurons, forming distinct processing modules. Despite their prominent spatial segregation, spectrotemporal processing has not been compared for these regions. We identified these NT and BT regions with broad-band ripple stimuli and characterized processing differences between them using both spectrotemporal receptive fields (STRFs) and nonlinear stimulus/firing rate transformations. The durations of STRF excitatory and inhibitory subfields were shorter and the best temporal modulation frequencies were higher for BT neurons than for NT neurons. For NT neurons, the bandwidth of excitatory and inhibitory subfields was matched, whereas for BT neurons it was not. Phase locking and feature selectivity were higher for NT neurons. Properties of the nonlinearities showed only slight differences across the bandwidth modules. These results indicate fundamental differences in spectrotemporal preferences--and thus distinct physiological functions--for neurons in BT and NT spectral integration modules. However, some global processing aspects, such as spectrotemporal interactions and nonlinear input/output behavior, appear to be similar for both neuronal subgroups. The findings suggest that spectral integration modules in AI differ in what specific stimulus aspects are processed, but they are similar in the manner in which stimulus information is processed.     

Organization of the Connections between the Parietal Associative Zone and the Primary Sensory Zones in the Cat Neocortex

In acute experiments on cats, we studied the impulse activity of 262 neurons of the parietal associative zone (PAZ, field 5). Among them, 129 cells [100 silent units and 29 units generating background activity (BA)] were identified as output neurons, while 133 cells with the BA were interneurons of the intrinsic cortical neuronal circuits. Electrical stimulation of the primary visual, auditory, or somatosensory cortices evoked no impulse responses in silent output PAZ neurons, while output neurons with the BA and interneurons (more than 65 and 80% of the cell units, respectively) generated clear responses (more frequently, phasic). Stimulation of the auditory and visual cortices exerted mostly inhibitory effects, while stimulation of the somatosensory cortex provided mostly excitatory influences. The ratios of neurons generating primary excitatory and inhibitory responses to stimulation of the visual, auditory, and somatic cortices were 0.3:1, 0.6:1, and 3.2:1, respectively. More than 95% of the field-5 neurons were influenced from the primary sensory zones via di- and/or polysynaptic pathways. Monosynaptic excitatory inputs from the visual cortex were identified for 3.8% of interneurons and 6.9% of output PAZ neurons; for the auditory cortical inputs, the respective figures were 1.7 and 3.5%. Monosynaptic connections with the somatic cortex were found only for 4% of the interneurons under study. It has been concluded that interaction of heteromodal signals coming to the PAZ via the corticopetal and associative inputs occurs on neurons of all the cortical layers.     

Retrograde GABA signaling adjusts sound localization by balancing excitation and inhibition in the brainstem

Central processing of acoustic cues is critically dependent on the balance between excitation and inhibition. This balance is particularly important for auditory neurons in the lateral superior olive, because these compare excitatory inputs from one ear and inhibitory inputs from the other ear to compute sound source location. By applying GABA(B) receptor antagonists during sound stimulation in vivo, it was revealed that these neurons adjust their binaural sensitivity through GABA(B) receptors. Using an in vitro approach, we then demonstrate that these neurons release GABA during spiking activity. Consequently, GABA differentially regulates transmitter release from the excitatory and inhibitory terminals via feedback to presynaptic GABA(B) receptors. Modulation of the synaptic input strength, by putative retrograde release of neurotransmitter, may enable these auditory neurons to rapidly adjust the balance between excitation and inhibition, and thus their binaural sensitivity, which could play an important role as an adaptation to various listening situations.     

Synaptic mechanisms of monaural and binaural processing in the locust

(1) Responses of auditory interneurones were recorded intracellularly within the metathoracic ganglion of the locust when stimulating each tympanic membrane with a piezoelectric transducer. Thus, in contrast to conventional sound stimulation, each of the two ears could be activated independently from the other at variable intensities, duration and stimulus onsets. By means of this ‘earphone-like’ stimulation technique the binaural integration properties of auditory interneurons could be analysed. (2) A minority of units (3 out of 43) was affected by input from one side only. Their synaptic input was purely excitatory and the intensity characteristics reflected those of auditory receptor fibres. (3) Most interneurones received input from both ears, each being excitatory or one excitatory or one excitatory and one inhibitory. In some units the unilateral synaptic response already included both an EPSP and an IPSP. As a result of varying temporal interactions between the EPSP and the IPSP within the unilaterally evoked complex response the intensity characteristics differed widely from unit to unit. (4) With binaural simultaneous stimulation the complexity of the postsynaptic responses of most interneurones increased as the synaptic input from both ears coincided at the level of the recorded interneurone. Although both ears were stimulated symmetrically (at the same time and intensity), units were recorded where the latencies of ipsilateral and contralateral synaptic input were different. Contralateral inhibition could either follow or precede ipsilateral excitation and in some cases both EPSP and IPSP had the same latency. On the basis of these findings the binaural synaptic mechanisms of directional coding are discussed and compared with corresponding results under free field stimulus conditions.     

The Correlation Structure of Local Neuronal Networks Intrinsically Results from Recurrent Dynamics

Correlated neuronal activity is a natural consequence of network connectivity and shared inputs to pairs of neurons, but the task-dependent modulation of correlations in relation to behavior also hints at a functional role. Correlations influence the gain of postsynaptic neurons, the amount of information encoded in the population activity and decoded by readout neurons, and synaptic plasticity. Further, it affects the power and spatial reach of extracellular signals like the local-field potential. A theory of correlated neuronal activity accounting for recurrent connectivity as well as fluctuating external sources is currently lacking. In particular, it is unclear how the recently found mechanism of active decorrelation by negative feedback on the population level affects the network response to externally applied correlated stimuli. Here, we present such an extension of the theory of correlations in stochastic binary networks. We show that (1) for homogeneous external input, the structure of correlations is mainly determined by the local recurrent connectivity, (2) homogeneous external inputs provide an additive, unspecific contribution to the correlations, (3) inhibitory feedback effectively decorrelates neuronal activity, even if neurons receive identical external inputs, and (4) identical synaptic input statistics to excitatory and to inhibitory cells increases intrinsically generated fluctuations and pairwise correlations. We further demonstrate how the accuracy of mean-field predictions can be improved by self-consistently including correlations. As a byproduct, we show that the cancellation of correlations between the summed inputs to pairs of neurons does not originate from the fast tracking of external input, but from the suppression of fluctuations on the population level by the local network. This suppression is a necessary constraint, but not sufficient to determine the structure of correlations; specifically, the structure observed at finite network size differs from the prediction based on perfect tracking, even though perfect tracking implies suppression of population fluctuations.     

Synchronization and sensitivity enhancement of the Hodgkin-Huxley neurons due to inhibitory inputs

Recent experimental results imply that inhibitory postsynaptic potentials can play a functional role in realizing synchronization of neuronal firing in the brain. In order to examine the relation between inhibition and synchronous firing of neurons theoretically, we analyze possible effects of synchronization and sensitivity enhancement caused by inhibitory inputs to neurons with a biologically realistic model of the Hodgkin-Huxley equations. The result shows that, after an inhibitory spike, the firing probability of a single postsynaptic neuron exposed to random excitatory background activity oscillates with time. The oscillation of the firing probability can be related to synchronous firing of neurons receiving an inhibitory spike simultaneously. Further, we show that when an inhibitory spike input precedes an excitatory spike input, the presence of such preceding inhibition raises the firing probability peak of the neuron after the excitatory input. The result indicates that an inhibitory spike input can enhance the sensitivity of the postsynaptic neuron to the following excitatory spike input. Two neural network models based on these effects on postsynaptic neurons caused by inhibitory inputs are proposed to demonstrate possible mechanisms of detecting particular spatiotemporal spike patterns. Received: 15 April 1999 /Accepted in revised form: 25 November 1999     

Integration of ascending and descending inputs in the auditory midbrain of anurans.

In anurans, the midbrain torus semicircularis is involved in auditory processing and audio-motor integration. In this study, we examined the influence of descending forebrain projections on the auditory response properties and hence the audiomotor transmission of mesencephalic interface neurons. In order to investigate response integration, we performed intracellular recordings from torus neurons in an isolated brain preparation of Discoglossus pictus and Bombina orientalis and stimulated the auditory nerve, striatum, and the dorsal thalamus electrically with single pulses. Stimulation of all three sites could evoke responses in torus neurons that were either excitatory, inhibitory, or a mixture of both, with durations of up to several hundred milliseconds. Further, striatum and thalamus were activated by pulse trains (10-20 Hz, 50 pulses) immediately before stimulating the auditory nerve with single pulses. Thus, responses of torus neurons to "auditory" input were facilitated or suppressed for up to 2 min by striatum stimulation or only suppressed by thalamus stimulation. Intracellular labeling of recorded neurons revealed that response modulation by descending input mostly occurred in laminar nucleus neurons. These results suggest that descending forebrain projections to mesencephalic audiomotor interface neurons may play an important role in modifying acoustically guided behavior in anurans.     

Responses of auditory cortex neurons in unanesthetized cats to best-frequency tones

The characteristics of extra- and intracellular responses of neurons in the AI region were studied in experiments with unanesthetized cats. It was established that auditory cortex neurons with similar best frequencies showed different forms of responses to tones of the corresponding frequency. About 40% of the auditory cortex neurons generated on responses to tone presentation. On — off and off responses were found in 27% of the neurons. Cortical neurons (27%) in which stimulation or inhibition of impulse discharge persisted throughout tone action were assigned to the tonic type group of cells. Approximately 6% of neurons in the AI region did not respond to a tone. During intracellular recording about 85% of the neurons responded to the turning on and/or off of a tone by generating an action potential followed by an IPSI. In 96% of the cortical neurons studied the IPSPs were a constant component of the intracellular responses to a tone. It is concluded that the inhibition of the impulse activity of the given neurons is of primarily a postsynaptic origin. Neurons showing one or another form of response differ from one another in the relative intensity and time characteristics of excitatory and inhibitory processes interacting on their postsynaptic membranes. In neurons of the phasic type inhibitory processes are dominant over excitatory, while excitatory processes are predominant in neurons of the tonic type.A. A. Bogomolets Institute of Physiology, Academy of Sciences of the Ukrainian SSR, Kiev. Translated from Neirofiziologiya, Vol. 17, No. 4, pp. 500–508, July–August, 1985.     

Neuronal interaction in the auditory cortex of alert cats

Spontaneous activity of neighboring auditory cortical neurons was derived by glass microelectrodes in chronic experiments on unanesthetized, unimmobilized cats, and the spike trains were subsequently analyzed by computer. Altogether 20 pairs of neurons were tested. The commonest type of interaction (50%) was found to be a common excitatory source, conjectured to be from specific auditory afferents. Interaction of the "common inhibitory source" (5%) and also complex forms of interaction were found. Interaction was absent in only 10% of cases. No direct inhibitory influence of neighboring neurons on one another was observed. The possible causes of absence of a direct inhibitory action are discussed. The most likely cause is absence of marked spontaneous activity in inhibitory auditory cortical neurons.A. A. Bogomolets Institute of Physiology, Academy of Sciences of the Ukrainian SSR, Kiev. Translated from Neirofiziologiya, Vol. 16, No. 2, pp. 161–167, March–April, 1984.