Spatiotemporal firing patterns in the cerebellum

Neurons are generally considered to communicate information by increasing or decreasing their firing rate. However, in principle, they could in addition convey messages by using specific spatiotemporal patterns of spiking activities and silent intervals. Here, we review expanding lines of evidence that such spatiotemporal coding occurs in the cerebellum, and that the olivocerebellar system is optimally designed to generate and employ precise patterns of complex spikes and simple spikes during the acquisition and consolidation of motor skills. These spatiotemporal patterns may complement rate coding, thus enabling precise control of motor and cognitive processing at a high spatiotemporal resolution by fine-tuning sensorimotor integration and coordination.     

A hidden Markov model approach to neuron firing patterns.

Analysis and characterization of neuronal discharge patterns are of interest to neurophysiologists and neuropharmacologists. In this paper we present a hidden Markov model approach to modeling single neuron electrical activity. Basically the model assumes that each interspike interval corresponds to one of several possible states of the neuron. Fitting the model to experimental series of interspike intervals by maximum likelihood allows estimation of the number of possible underlying neuron states, the probability density functions of interspike intervals corresponding to each state, and the transition probabilities between states. We present an application to the analysis of recordings of a locus coeruleus neuron under three pharmacological conditions. The model distinguishes two states during halothane anesthesia and during recovery from halothane anesthesia, and four states after administration of clonidine. The transition probabilities yield additional insights into the mechanisms of neuron firing.     

The effects of recurrent inhibition on the cross-correlated firing patterns of motoneurones (and their relation to signal transmission in the spinal cord-muscle channel)

Cross-correlation histograms (CCH) were computed for discharge sequences of pairs of motoneurones which were excited by sinusoidal muscle stretches. These CCH's were compared before and after opening of the recurrent inhibitory loop by Renshaw cell blocking agents. Periodic patterns in the CCH's indicative of specifically timed phase relations between discharges of different motoneurones were enhanced after Renshaw cell blockage. This was confirmed by power spectra computed for the CCH's. They contained power peaks about 50Hz which tended to increase after depression of recurrent inhibition. The correlation was thus due predominantly to line current interference which seemed to act as a common entrainment input at the spinal level. It is concluded that Renshaw cells de-correlate discharge patterns of different motoneurones of the same pool by injecting uncorrelated signals into them. This de-correlation is an important prerequisite for distortion suppression of signal transmission in a multi-channel system, like that of stretch reflex, and for its linearization.     

Mechanisms of firing patterns in fast-spiking cortical interneurons

Cortical fast-spiking (FS) interneurons display highly variable electrophysiological properties. Their spike responses to step currents occur almost immediately following the step onset or after a substantial delay, during which subthreshold oscillations are frequently observed. Their firing patterns include high-frequency tonic firing and rhythmic or irregular bursting (stuttering). What is the origin of this variability? In the present paper, we hypothesize that it emerges naturally if one assumes a continuous distribution of properties in a small set of active channels. To test this hypothesis, we construct a minimal, single-compartment conductance-based model of FS cells that includes transient Na(+), delayed-rectifier K(+), and slowly inactivating d-type K(+) conductances. The model is analyzed using nonlinear dynamical system theory. For small Na(+) window current, the neuron exhibits high-frequency tonic firing. At current threshold, the spike response is almost instantaneous for small d-current conductance, gd, and it is delayed for larger gd. As gd further increases, the neuron stutters. Noise substantially reduces the delay duration and induces subthreshold oscillations. In contrast, when the Na(+) window current is large, the neuron always fires tonically. Near threshold, the firing rates are low, and the delay to firing is only weakly sensitive to noise; subthreshold oscillations are not observed. We propose that the variability in the response of cortical FS neurons is a consequence of heterogeneities in their gd and in the strength of their Na(+) window current. We predict the existence of two types of firing patterns in FS neurons, differing in the sensitivity of the delay duration to noise, in the minimal firing rate of the tonic discharge, and in the existence of subthreshold oscillations. We report experimental results from intracellular recordings supporting this prediction.     

Visual perception: mind and brain see eye to eye

Recent functional imaging studies have identified neural activity that is closely associated with the perception of illusory motion. The mapping of the mind onto the bin appears to be one-to-one: activity in visual 'motion area' MT is highly correlated with perceptual experience.     

Modeling the differentiation of A- and C-type baroreceptor firing patterns

The baroreceptor neurons serve as the primary transducers of blood pressure for the autonomic nervous system and are thus critical in enabling the body to respond effectively to changes in blood pressure. These neurons can be separated into two types (A and C) based on the myelination of their axons and their distinct firing patterns elicited in response to specific pressure stimuli. This study has developed a comprehensive model of the afferent baroreceptor discharge built on physiological knowledge of arterial wall mechanics, firing rate responses to controlled pressure stimuli, and ion channel dynamics within the baroreceptor neurons. With this model, we were able to predict firing rates observed in previously published experiments in both A- and C-type neurons. These results were obtained by adjusting model parameters determining the maximal ion-channel conductances. The observed variation in the model parameters are hypothesized to correspond to physiological differences between A- and C-type neurons. In agreement with published experimental observations, our simulations suggest that a twofold lower potassium conductance in C-type neurons is responsible for the observed sustained basal firing, where as a tenfold higher mechanosensitive conductance is responsible for the greater firing rate observed in A-type neurons. A better understanding of the difference between the two neuron types can potentially be used to gain more insight about pathophysiology and treatment of diseases related to baroreflex function, e.g. in patients with autonomic failure, a syndrome that is difficult to diagnose in terms of its pathophysiology.     

Sequential configuration model for firing patterns in local neural networks

This paper presents a sequential configuration model to represent the coordinated firing patterns of memory traces in groups of neurons in local networks. Computer simulations are used to study the dynamic properties of memory traces selectively retrieved from networks in which multiple memory traces have been embedded according to the sequential configuration model. Distinct memory traces which utilize the same neurons, but differ only in temporal sequencing are selectively retrievable. Firing patterns of constituent neurons of retrieved memory traces exhibit the main properties of neurons observed in multi microelectrode recordings. The paper shows how to adjust relative synaptic weightings so as to control the disruptive influences of cross-talk in multipy-embedded networks. The theoretical distinction between (primarily anatomical) beds and (primarily physiological) realizations underlines the fundamentally stochastic nature of network firing patterns, and allows the definition of 4 degrees of clarity of retrieved memory traces.     

Exponential decay characteristics of the stochastic integer multiple neural firing patterns

Integer multiple neural firing patterns exhibit multi-peaks in inter-spike interval (ISI) histogram (ISIH) and exponential decay in amplitude of peaks, which results from their stochastic mechanisms. But in previous experimental observation that the decay in ISIH frequently shows obvious bias from exponential law. This paper studied three typical cases of the decay, by transforming ISI series of the firing to discrete binary chain and calculating the probabilities or frequencies of symbols over the whole chain. The first case is the exponential decay without bias. An example of this case was discovered on hippocampal CA1 pyramidal neuron stimulated by external signal. Probability calculation shows that this decay without bias results from a stochastic renewal process, in which the successive spikes are independent. The second case is the exponential decay with a higher first peak, while the third case is that with a lower first peak. An example of the second case was discovered in experiment on a neural pacemaker. Simulation and calculation of the second and third cases indicate that the dependency in successive spikes of the firing leads to the bias seen in decay of ISIH peaks. The quantitative expression of the decay slope of three cases of firing patterns, as well as the excitatory effect in the second case of firing pattern and the inhibitory effect in the third case of firing pattern are identified. The results clearly reveal the mechanism of the exponential decay in ISIH peaks of a number of important neural firing patterns and provide new understanding for typical bias from the exponential decay law.     

How much the eye tells the brain

In the classic "What the frog's eye tells the frog's brain," Lettvin and colleagues showed that different types of retinal ganglion cell send specific kinds of information. For example, one type responds best to a dark, convex form moving centripetally (a fly). Here we consider a complementary question: how much information does the retina send and how is it apportioned among different cell types? Recording from guinea pig retina on a multi-electrode array and presenting various types of motion in natural scenes, we measured information rates for seven types of ganglion cell. Mean rates varied across cell types (6-13 bits . s(-1)) more than across stimuli. Sluggish cells transmitted information at lower rates than brisk cells, but because of trade-offs between noise and temporal correlation, all types had the same coding efficiency. Calculating the proportions of each cell type from receptive field size and coverage factor, we conclude (assuming independence) that the approximately 10(5) ganglion cells transmit on the order of 875,000 bits . s(-1). Because sluggish cells are equally efficient but more numerous, they account for most of the information. With approximately 10(6) ganglion cells, the human retina would transmit data at roughly the rate of an Ethernet connection.     

RNA silencing in white petunia flowers creates pigmentation patterns invisible to the human eye

Modern commercial petunias exhibit a wide range of flower colors, which can be observed in gardens. In this study, we present a petunia cultivar that exhibits a floral pattern that is invisible to humans but is possibly visible to pollinating insects. We show that this hidden pattern is established by differentially localized accumulation of flavonols and cinnamic acid derivatives in the corolla limb. This accumulation is caused by a combination of two distinct mechanisms that inhibit anthocyanin biosynthesis: a loss-of-function mutation in the ANTHOCYANIN2, and localized RNA-silencing of CHALCONE SYNTHASE-A.     

Pathways of the early propagation of virulent and avirulent rabies strains from the eye to the brain.

Penetration of the central nervous system of the adult rat by the CVS strain of rabies virus and its two avirulent derivatives Av01 and Av02 has been studied by inoculation of the virus into the anterior chamber of the eye. The primary sites of penetration of CVS were (i) the intraocular parasympathetic oculomotor fibers, (ii) the retinopetal fibers of pretectal origin, and (iii) the intraocular fibers of the ophthalmic nerve. The mutant strains, however, lost the capacity to invade the two former groups of fibers, although their penetration into the trigeminal system was not impaired. Neither strain CVS nor the mutants infected primarily the intraocular adrenergic terminals and the optic nerve. Mutant strains, but not CVS, were able to infect the lens. These results indicate that the cholinergic receptor may not be the only receptor for rabies virus and that rabies virus is conveyed in the nervous system by retrograde axoplasmic flow. Strain CVS spread throughout the brain and propagated eventually back to the retina. The mutants penetrated the brain as well, but the infection was slow, involved different cerebral structures, and cleared up completely in 3 weeks, probably because of an efficient immune response.     

Analysis of clustered firing patterns in synaptically coupled networks of oscillators

Oscillators in networks may display a variety of activity patterns. This paper presents a geometric singular perturbation analysis of clustering, or alternate firing of synchronized subgroups, among synaptically coupled oscillators. We consider oscillators in two types of networks: mutually coupled, with all-to-all inhibitory connections, and globally inhibitory, with one excitatory and one inhibitory population of oscillators, each of arbitrary size. Our analysis yields existence and stability conditions for clustered states, along with formulas for the periods of such firing patterns. By using two different approaches, we derive complementary conditions, the first set stated in terms of time lengths determined by intrinsic and synaptic properties of the oscillators and their coupling and the second set stated in terms of model parameters and phase space structures directly linked to parameters. These results suggest how biological components may interact to produce the spindle sleep rhythm in thalamocortical networks. Received: 9 September 1999 / Revised version: 7 July 2000 / Published online: 24 November 2000     

Channel density regulation of firing patterns in a cortical neuron model

Modifying the density and distribution of ion channels in a neuron (by natural up- and downregulation or by pharmacological intervention or by spontaneous mutations) changes its activity pattern. In this investigation we analyzed how the impulse patterns are regulated by the density of voltage-gated channels in a neuron model based on voltage-clamp measurements of hippocampal interneurons. At least three distinct oscillatory patterns, associated with three distinct regions in the Na-K channel density plane, were found. A stability analysis showed that the different regions are characterized by saddle-node, double-orbit, and Hopf-bifurcation threshold dynamics, respectively. Single, strongly graded action potentials occur in an area outside the oscillatory regions, but less graded action potentials occur together with repetitive firing over a considerable range of channel densities. The relationship found here between channel densities and oscillatory behavior may partly explain the difference between the principal spiking patterns previously described for crab axons (class 1 and 2) and cortical neurons (regular firing and fast spiking).     

Transitions between irregular and rhythmic firing patterns in excitatory-inhibitory neuronal networks

Changes in firing patterns are an important hallmark of the functional status of neuronal networks. We apply dynamical systems methods to understand transitions between irregular and rhythmic firing in an excitatory-inhibitory neuronal network model. Using the geometric theory of singular perturbations, we systematically reduce the full model to a simpler set of equations, one that can be studied analytically. The analytic tools are used to understand how an excitatory-inhibitory network with a fixed architecture can generate both activity patterns for possibly different values of the intrinsic and synaptic parameters. These results are applied to a recently developed model for the subthalamopallidal network of the basal ganglia. The results suggest that an increase in correlated activity, corresponding to a pathological state, may be due to an increased level of inhibition from the striatum to the inhibitory GPe cells along with an increased ability of the excitatory STN neurons to generate rebound bursts. Action Editor: Carson Chow     

Principal component analysis of evoked neuronal firing pattern in the human brain

Evoked firing activity (EFA) in neurons of the human thalamic reticular nucleus (Rt) was recorded by microelectrodes using extracellular recording techniques in the course of stereotaxic surgery for dyskinesia. Activity was induced by functionally significant verbal and sensory stimuli together with performance of goal-directed behavioral actions (BA). Use of the principal component method and construction of peristimulus covariance matrices are suggested in view of the presumably convergent nature of EFA in Rt neurons, taking the form of superposing independent components of response and variability in these in the course of BA testing and performance for the purpose of analyzing EFA and interneuronal correlations. The multivariate pattern of Rt EFA time courses during the action of functionally significant stimuli was revealed; this reflects different stages in performance of BA. The dynamics of components of response are revealed and occurrence of rapidly developing interneuronal correlations in functionally significant stages of goal-directed BA are described. Findings point to the efficacy of the suggested approach applied to analysis of EFA neurons.Institute of Chemical Physics, Academy of Sciences of the USSR, Moscow. Translated from Neirofiziologiya, Vol. 22, No. 6, pp. 811–818, November–December, 1990.     

A G beta protein in the Drosophila compound eye is different from that in the brain

A G protein beta subunit gene (Gbe) is expressed only in the eyes of adult D. melanogaster. This gene was identified by probing a Drosophila head cDNA expression library with monoclonal antibodies to a previously characterized Drosophila G protein beta subunit (Gbb). Immunoblot and Northern analyses demonstrate that Gbe protein and mRNA is not present in Drosophila mutants that lack eyes. Immunocytochemical and in situ hybridization analyses further demonstrate that Gbe is expressed in the eyes but not in the brain, whereas Gbb is abundantly expressed in the brain. The Gbe product is approximately 45% identical to previously identified G beta subunits and defines a new G beta class. Its localization suggests a possible role in phototransduction.