Cholecystokinin activates both A- and C-type vagal afferent neurons

Patch-clamp electrophysiological methods were used on dissociated rat nodose neurons maintained in culture to determine whether responses to cholecystokinin (CCK) were associated with capsaicin-resistant (A type) or capsaicin-sensitive (C type) neurons. Nodose neurons were classified as A or C type on the basis of the characteristics of the Na+ current, a hyperpolarization-activated current, and sensitivity to a low concentration of capsaicin to ascertain the presence of vanilloid receptor 1 that has been associated with C-type neurons in sensory ganglia. It was expected that only capsaicin-sensitive C-type neurons would respond to CCK, because most vagally mediated actions of CCK are blocked by capsaicin treatment. However, we found that subpopulations of both A- and C-type neurons responded to CCK (24 and 38%, respectively). Thus some vagally mediated actions of CCK may be mediated by capsaicin insensitive A-type neurons.     

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.     

Direct and indirect assessment of gamma-motor firing patterns

The study of the patterns of gamma-motor activity which accompany natural contractions has been long and difficult, and has not as yet led to general agreement. In this review we have simplified matters by considering the case of locomotion in the cat only, and we have avoided discussion of the various hypotheses which have been advanced to provide general schemes of gamma control for a wide range of movements. The development of the subject is shown to depend very much on devising ingenious methods applicable to reduced and intact animals. Direct recording from gamma-motoneurones has only been possible in reduced preparations, whereas indirect assessment of gamma activity from spindle afferent recordings was used in these and in intact animals. At this point in time, we still have no direct recordings from gamma-motoneurones in normally behaving animals, but those obtained in decerebrate animals show distinct patterns of modulation for static and dynamic types with particular temporal relation to the stepping movements. The spindle recordings in intact animals potentially provide the most important information, and the problems of interpretation, which have previously caused difficulties, are beginning to be solved through the insights obtained from the reduced preparations.     

Discharge patterns of tonically firing human motoneurones

We have attempted to reconcile the different patterns of distribution of interspike intervals that are found in motoneurones made to discharge by intracellular injection of constant current in reduced animal preparations and by voluntary control in human subjects. We recorded long spike trains from single motor units in three human muscles made to discharge at constant mean frequencies with the help of auditory and visual feedback. The distribution of interspike intervals in each spike train was analysed quantitatively. We found that the different pattern of discharge of the human motor units could be accounted for when due allowance was made for the variability of the drive to the human motoneurone which arose because of the feedback process used to maintain the target frequency. A model testing this hypothesis gave results that were qualitatively consistent with the human data.     

Afferent modulation of dopamine neuron firing patterns

In recent studies examining the modulation of dopamine (DA) cell firing patterns, particular emphasis has been placed on excitatory afferents from the prefrontal cortex and the subthalamic nucleus. A number of inconsistencies in recently published reports, however, do not support the contention that tonic activation of NMDA receptors is the sole determinate of DA neuronal firing patterns. The results of work on the basic mechanism of DA firing and the action of apamin suggest that excitatory projections to DA neurons from cholinergic and glutamatergic neurons in the tegmental pedunculopontine nucleus, and/or inhibitory GABAergic projections, are also involved in modulating DA neuron firing behavior.     

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.     

Multineuronal firing patterns in the signal from eye to brain

Population codes in the brain have generally been characterized by recording responses from one neuron at a time. This approach will miss codes that rely on concerted patterns of action potentials from many cells. Here we analyze visual signaling in populations of ganglion cells recorded from the isolated salamander retina. These neurons tend to fire synchronously far more frequently than expected by chance. We present an efficient algorithm to identify what groups of cells cooperate in this way. Such groups can include up to seven or more neurons and may account for more than 50% of all the spikes recorded from the retina. These firing patterns represent specific messages about the visual stimulus that differ significantly from what one would derive by single-cell analysis.     

Genomic structural differentiation in Solanum: comparative mapping of the A- and E-genomes

 A genetic map was constructed from an F₂ population of 76 individuals for the purpose of comparing the arrangement of loci in the A and E Solanum genomes. This progeny was derived from an interspecific cross between the species Solanum palustre×Solanum etuberosum, both of which are E-genome species. Two hundred and eighty one probes previously mapped in tomato and potato (A-genome, as postulated for diploid cultivated potato species by Matsubayashi 1991) disclosed 109 segregating loci in this population. Of these, 80 loci were linked in 19 linkage groups covering a total of 720.4 cM, with an average of 9 cM between markers. Although the genetic map of the E-genome showed conservation for most linkage groups with those of tomato and the A-genome, various translocations and possible inversions and transpositions were detected. It is evident that the accumulation of these structural changes in the E-genome is sufficient to cause the observed hybrid sterility. The major rearrangements in the E-genome included multiple translocations involving mosly linkage groups 2 and 8. Also a transposition was detected on group 9, with the same group-10 inversion distinguishing potato from tomato. Definitively groups 2, 8, 9 and 10, and possibly groups 1, 4 and 12, in the E-genome are structurally different from their homologues in the A-genome. In general, recombination values were larger in the E- than in the A-genome. The extensive structural differentiation of the E-genome with respect to that of potato and tomato justifies its present designation as a different genome, which is supported by previous chromosome-pairing studies. The difficult introgression of desirable traits from the Etuberosum species into potato can be explained by these structural differences. Received: 1 February 1998 / Accepted: 8 October 1998     

Modeling the variability of firing rate of retinal ganglion cells.

Impulse trains simulating the maintained discharges of retinal ganglion cells were generated by digital realizations of the integrate-and-fire model. If the mean rate were set by a "bias" level added to "noise," the variability of firing would be related to the mean firing rate as an inverse square root law; the maintained discharges of retinal ganglion cells deviate systematically from such a relationship. A more realistic relationship can be obtained if the integrate-and-fire mechanism is "leaky"; with this refinement, the integrate-and-fire model captures the essential features of the data. However, the model shows that the distribution of intervals is insensitive to that of the underlying variability. The leakage time constant, threshold, and distribution of the noise are confounded, rendering the model unspecifiable. Another aspect of variability is presented by the variance of responses to repeated discrete stimuli. The variance of response rate increases with the mean response amplitude; the nature of that relationship depends on the duration of the periods in which the response is sampled. These results have defied explanation. But if it is assumed that variability depends on mean rate in the way observed for maintained discharges, the variability of responses to abrupt changes in lighting can be predicted from the observed mean responses. The parameters that provide the best fits for the variability of responses also provide a reasonable fit to the variability of maintained discharges.     

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.     

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.     

A model of cell firing patterns during epileptic seizures

A simplified model is presented of the dynamics of excitatory and inhibitory neurons in the cerebral cortex. A key feature of the model is that neurons may cease to fire when strongly depolarized (spike inactivation). Computer simulations for different parameters reveal five classes of solutons: a) steady states in which neither excitatory nor inhibitory cells are active, b) steady states in which one or both types of cells fire repetitively, c) states in which one type of cell fluctuates rapidly between bursts of action potentials and inactivity due to strong depolarization, d) rhythmic activity in which both types of cells fire in unison followed by a period of spike inactivation and e) states similar to d but in which the inhibitory cells never produce action potentials. Solutions b, c, d, and e qualitatively resemble the different firing patterns observed during experimental seizures. It is shown that changes in those parameters that are functions of potassium concentration can induce changes in the type of solution. It is therefore proposed that the increase in extracellular potassium concentration during seizures may be responsible for the progressive changes observed in firing patterns and particularly for the transition from tonic to clonic patterns. A method is also outlined for testing the predictions of the model.     

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     

Modeling motoneuron firing properties: dependency on size and calcium dynamics

The origin of functional differences between motoneurons of varying size was investigated by employing a one-compartmental motoneuron model containing a slow conductance dependent on the intracellular calcium concentration. The size of the cell was included as an explicit parameter. Simulations show that motoneurons of varying size cannot be regarded as simple `scaled' versions of each other. Rather, they are expected to have intrinsic properties that vary with cell size. These intrinsic properties refer to the membrane conductances per unit area and the dynamics of the intracellular calcium concentration. Received: 18 March 1994 / Accepted in revised form: 29 July 1994     

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     

Identifying type I excitability using dynamics of stochastic neural firing patterns

The stochastic firing patterns are simulated near saddle-node bifurcation on an invariant cycle corresponding to type I excitability in stochastic Morris–Lecar model. In absence of external periodic signal, the stochastic firing manifests continuous distribution in ISI histogram (ISIH), whose amplitude at first increases sharply and then decreases exponentially. In presence of the external periodic signal, stochastic firing patterns appear as two cases of integer multiple firing with multiple discrete peaks in ISIH. One manifests perfect exponential decay in all peaks and the other imperfect exponential decay except a lower first peak. These stochastic firing patterns simulated with or without external periodic signal can be demonstrated in the experiments on rat hippocampal CA1 pyramidal neurons. The exponential decay laws in the multiple peaks are also acquired using probability analysis method. The perfect decay law is determined by the independent characteristic within the firing while the imperfect decay law is from the inhibitory effect. In addition, the stochastic firing patterns corresponding to type I excitability are compared to those of type II excitability. The results not only reveal the dynamics of stochastic firing patterns with or without external signal corresponding to type I excitability, but also provide practical indicators to availably identify type I excitability.