SEARCH

SEARCH BY CITATION

Abstract

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements
  • 1
    The influence of stimulus trains applied to single I a axons on the firing behaviour of single motoneurones was assessed in anaesthetized cats. The change in motoneurone firing probability associated with a single I a afferent spike was measured from short-latency peaks in peristimulus time histograms or cross-correlograms. Some synapses showed frequency-dependent depression of the short-latency peak, which is consonant with the frequency-dependent depression reported for the I a-motoneurone excitatory postsynaptic potential (EPSP).
  • 2
    Where they could be measured, EPSPs superimposed on the depolarizing ramps of potential recorded from motoneurones as they fired repetitively showed frequency-dependent changes in amplitude that parallelled those of the simultaneously recorded histograms.
  • 3
    Thus it appears that at synapses with small EPSPs, which are typical in the mammalian CNS, modulation of the EPSP should result in similar modulation of cell firing.

Extensive effort has been devoted to studying the modulation of synaptic strength in the mammalian CNS. Many studies have focussed on the influence of presynaptic firing rate, and both enhancement and depression of the amplitude of postsynaptic potentials (PSPs) have been found when the presynaptic rate was increased (Magleby, 1987; Zucker, 1989). These and other forms of synaptic modulation are considered to be important mechanisms governing the operation of neural circuits (Churchland & Sejnowski, 1992).

Surprisingly, the effect of modulation of synaptic potentials on the spike train output of postsynaptic neurons has not been tested directly. Various authors (Fetz & Gustafsson, 1983; Gustafsson & McCrea, 1984; Cope et al. 1987) provide indirect evidence using pooled data from synapses made with motoneurones: they report positive correlations between the primary peak of the cross-correlogram (computed from I a afferent and motoneurone spike trains) and the amplitude of the corresponding excitatory postsynaptic potential (EPSP). From those relationships (e.g. Fig. 7 of Cope et al. 1987) it could be inferred that modulation of a single EPSP should yield a proportional modulation of the correlogram. However, the observed relationships showed substantial scatter, due to uncontrolled sources of variation such as synaptic noise (e.g. Gustafsson & McCrea, 1984; Polyakov, 1991), so confidence in this inference must be limited.

Given the importance of synaptic potentials in determining postsynaptic firing behaviour it seemed critical to us to test whether modulation of PSPs at single synapses is sufficient to influence spike train output. We chose to examine this problem using the synaptic connection between muscle spindle primary afferents and spinal motoneurones (the I a- motoneurone synapse), in part because of its experimental tractability and in part because of the well documented frequency dependence of the EPSPs generated there (e.g. Curtis & Eccles, 1960; Honig et al. 1983). Our principal finding was that statistical measures of interaction between firing cells do change with presynaptic firing rate, consistent with predictions based on EPSP modulation. In the instances where they could be resolved, EPSPs measured on the ramps of depolarization in firing motoneurones showed the same rate dependence as the corresponding spike train measures. These data suggest that modulation of small individual PSPs at other synapses might reasonably be expected to influence postsynaptic spike trains.

Portions of this work have appeared previously in abstract form (Clark & Cope, 1995).

METHODS

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements

Surgery and recording

All experiments were conducted in accordance with local and federal guidelines for the care and use of laboratory animals. Adult male cats (2.6–4.2 kg) were anaesthetized with pentobarbitone sodium (35 mg kg−1i.p.). Anaesthetic depth was judged from the absence of limb withdrawal reflexes and from mean arterial blood pressure, which was monitored via a cannula in the carotid artery. Standard Ringer solution and supplementary pentobarbitone were administered via a second cannula in the external jugular vein. A cannula was placed in the trachea to facilitate artificial ventilation. Throughout surgery and subsequent recording, blood pressure was maintained > 60 mmHg by administering fluid i.v., body temperature was maintained between 35 and 37°C using radiant heat, and end-tidal PCO2 was maintained around 3.5 % by adjusting tidal volume. At the end of the recording session, the animal was killed using an overdose of pentobarbitone.

A laminectomy was performed from segments L7 to L4, exposing spinal roots carrying axons supplying the triceps surae. The left hindlimb was completely denervated with the exception of the nerve supplying the medial gastrocnemius muscle. The medial gastrocnemius was freed of its insertion and surrounding tissues, and a cord was tied to its tendon. The animal was mounted in a rigid recording apparatus, and skin flaps were fashioned to hold mineral oil pools bathing the spinal cord and left leg. The medial gastrocnemius (MG) nerve was mounted on a hook electrode to permit stimulation.

Dorsal root filaments from segments L7 and S1 were tested for the presence of stretch-sensitive afferents by elevating them on bipolar hook electrodes and monitoring electrical activity in them while gently pulling on a cord attached to the medial gastrocnemius tendon. Once a filament with a significant number of afferents was found, all other dorsal root filaments from S1 to L6 were cut in order to minimize synaptic noise in motoneurones. For most recordings, the animal was paralysed with gallamine triethiodide (Flaxedil), and artificially ventilated. During the epochs of paralysis, adequacy of anaesthesia was assured by monitoring end-tidal PCO2 and blood pressure; anaesthetic level was adjusted so that mean levels of these measures were kept near pre-paralysis values, and transient changes in response to paw pinch or electrical stimulation of muscle nerves were absent.

Two microelectrodes (filled with 2 m potassium acetate) were employed. The first (10–20 MΩ) was driven into medial gastrocnemius group I a afferent axons (identified by orthodromic stimulation latency and high sensitivity to stretch) in the dorsal root filament. This electrode both recorded spontaneous action potentials and delivered depolarizing pulse trains that elicited action potentials. The second electrode (5–10 MΩ) was driven into antidromically-identified motoneurones (supplying the medial gastrocnemius or synergists) in the spinal cord. This electrode was used both to record membrane potential at rest (for measurement of I a-triggered EPSPs) and to pass steady depolarizing current sufficient to cause the motoneurone to fire at a steady average rate, usually 10–15 spikes s−1 Data were accepted for further analysis when the amplitude of action potentials in the motoneurone exceeded 65 mV.

Data acquisition and analysis

Once a I a afferent and a motoneurone were simultaneously isolated, they were tested for a synaptic connection by spike-triggered averaging (STA) the motoneurone membrane potential (sampled at 100–133 kHz). If the averaged EPSP was ca. 100 μV or greater, steady depolarizing current was injected into the motoneurone to induce it to fire. Trains of brief (0.5 ms) depolarizing pulses were injected into the I a axon at stimulation frequencies (20–60 or 50–100 pulses s−1) below the range where temporal summation was expected to be significant (Honig et al. 1983). At least 2000 stimuli were delivered to the I a axon, and 400–2500 action potentials were recorded from the motoneurone for each frequency. For seven cases in which it was permitted by stable conditions, additional STA EPSPs were recorded after the period of motoneurone firing to test for stationarity. All trials involving motoneurone activation were recorded on magnetic tape (DC, −11 kHz) for subsequent analysis.

From real-time or tape-recorded trials, the times of motoneurone spikes as well as of spontaneous or driven I a spikes were recorded after band-pass filtering the signals and presenting them to Schmidt triggers coupled to TTL pulse generators. The times of onset of the TTL pulses were recorded to the nearest 10 μs.

For each bout of I a activation, a histogram (cross-correlogram or peristimulus time histogram (PSTH), depending on whether the I a activity was spontaneous or driven) describing the times of firing of the motoneurone with respect to the I a was constructed using 100 μs bins, as described in Cope et al. (1987) (cf. Moore et al. 1966). The cusum (Ellaway, 1978) was constructed in order to facilitate identification of the limits of the primary correlogram peak, which is associated with the increase in firing probability caused by the I a EPSP (Moore et al. 1970; Kirkwood, 1979). The mean percentage increase (MPI) of the primary correlogram peak above the pre-trigger baseline was computed as described by Cope et al. (1987).

Following Cope et al. (1987) and Garnett & Stephens (1980), the significance of the primary correlogram peak was first assessed from the z-statistic (Cox & Lewis, 1966) for comparison of two Poisson processes:

  • image

where n1 and n2 are the numbers of events in two histogram bins and t1 and t2 are the associated bin durations. In our application, the two bins correspond to the duration of the correlogram peak and a 5 ms pre-trigger baseline interval. For two independent Poisson processes, z follows a standard normal distribution (Cox & Lewis, 1966), so the primary correlogram peak could be considered significant at the 5 % level if |z| > 1.96 (two-tailed test).

In addition, because neither the trains of stimuli nor the trains of motoneurone action potentials fit the assumptions of a Poisson process (Perkel et al. 1967), significance of the correlogram peaks was assessed using the non-parametric bootstrap technique (Efron & Tibshirani, 1993), which sidesteps assumptions about the statistical distributions involved. Using the BCα method of Efron & Tibshirani, 95 % confidence intervals for primary correlogram peaks were computed from the distributions of 1000 bootstrap estimates drawn from the samples of first cross-intervals between I a and motoneurone firing times. A peak was considered significant if its 95 % confidence interval did not span 0 impulses s−1. Confidence intervals estimated from the bootstrap agreed well with those derived from the z-statistic; the size of the lower confidence interval showed only a 1 % to 12 % difference (either positive or negative) for the two methods, and enlarging the bootstrap sample to 10 000 for a subset of the trials decreased that discrepancy to a maximum of 8 %. For the relatively strong I a-motoneurone synapses evaluated in this study, the two methods led to the same conclusions as to the significance of all twenty-six correlograms tested. Thus it appears that the normal approximation given by Cox & Lewis (1966) would be adequate, despite the regularity of the spike trains studied.

The bootstrap was also used in the analysis of MPI statistics. First, BCα 95 % confidence intervals were constructed for each MPI from the sample of waiting times. An MPI was considered significant if its confidence interval did not span 0 %. Second, MPIs from a single synapse stimulated at different rates were compared by evaluating the confidence interval for the difference between MPI values at successive test frequencies, again derived from a bootstrapped sample.

Frequency-dependent changes in EPSPs were estimated from tape records of the membrane potentials of motoneurones firing repetitively. As described by Cope et al. (1987), we performed STA of motoneurone membrane potential using as triggers only those I a spikes that occurred within a fixed interval (in this case, 10–14 ms) prior to a motoneurone spike (the ‘ramp EPSPs’ of Cope et al. 1987). These triggers were selected using an analog delay line (CWE ADL-832; DC −10 kHz) and custom circuitry that generated TTL-level trigger pulses when the timing criteria were met. Motoneurone potential was also delayed (10 ms more than the I a triggering train) prior to sampling (12-bit, 100 kHz) to permit examination of the pre-trigger ramp. In most cases, at least fifty sweeps were averaged to estimate the ramp EPSP. Ramp EPSP amplitude was measured after subtracting a straight line fit to 3–5 ms of the pre-trigger baseline of each average.

RESULTS

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements

Representative EPSPs and PSTHs are shown in Fig. 1. The records shown in Fig. 1A and B were taken shortly after locating an MG I a afferent that made a relatively strong (673 μV) synaptic connection with an MG motoneurone. In the 150 s separating the recordings made for Fig. 1B and D, the motoneurone was activated continuously, and the I a afferent was driven to fire continuously at 40 and 60 pulses s−1. The EPSP shown in Fig. 1C was measured shortly thereafter. Little change was seen in EPSP amplitude (673 vs. 690 μV), EPSP rise time (0.56 vs. 0.53 ms) or MPI of the histogram peak (323 %vs. 301 %). Although few other synapses were held long enough to gather comparable data, whenever replicate EPSPs, cross-correlograms or PSTHs could be obtained from a synapse (n= 14, 9 and 9, respectively), they generally agreed well with one another.

image

Figure 1. Spike-triggered average EPSPs (A and C) and PSTHs (B and D) from a single synapse recorded early (A and B) and late (C and D) in an experimental run

The PSTHs were obtained using 20 pulses s−1 stimulation of the I a afferent in 2 epochs that were separated by 2.5 min of continuous stimulation at 40 and 60 pulses s−1. The spike-triggered averages (256 sweeps in A, 1024 sweeps in C) were taken during periods of spontaneous I a firing at roughly 20 pulses s−1, which occurred at the beginning and end of the sequence. MPI, mean percentage increase.

Download figure to PowerPoint

The relationships between features of the EPSP and MPI measured from spontaneous I a action potentials (or occasionally from constant-frequency I a activation at 20 pulses s−1) are described in Fig. 2, which combines data from the present study (n= 29) with thirteen comparable values from Cope et al. (1987). As shown by those authors, the amplitude of the EPSP appears to be positively related to MPI. The present data overlap those of Cope et al. (1987) but span a greater range of amplitudes. In addition, they appear slightly shifted upwards on the MPI axis, i.e. for a given EPSP size, on average a greater MPI was recorded in the present than in the earlier study. This difference probably reflects greater levels of noise (see below) in the Cope et al. (1987) study, where dorsal roots were left intact and I a stimulation was achieved by muscle stretch. As reported by Cope et al. (1987) there was little indication of a relationship between EPSP rise time and MPI (Fig. 2B).

image

Figure 2. Relationships between mean percentage increase (MPI) and EPSP amplitude (A) and rise time (B)

•, present study, data collected using spontaneous I a activity (usually 15–20 pulses s−1) or electrical stimulation of the I a fibre at 20 pulses s−1. ○, equivalent data from Cope et al. (1987).

Download figure to PowerPoint

For some synapses, PSTH primary peaks appeared to remain fairly constant as stimulation frequency increased, whereas at others, PSTH peaks were clearly related to stimulation frequency. Figure 3A–C shows histograms for a 137 μV synapse stimulated at 20 (A), 40 (B) and 100 pulses s−1 (C). The PSTH peaks in these plots are roughly equivalent, given the variation inherent in these histograms (Moore et al. 1966). In contrast, Fig. 3D–F shows histograms for a 358 μV synapse driven at 20 (D), 40 (E) and 60 pulses s−1 (F). For this synapse the amplitude of the primary PSTH peak clearly decreases with stimulation frequency, as shown below.

image

Figure 3. PSTHs from two synapses stimulated at multiple frequencies

A–C, records from a synapse having a 137 μV EPSP at rest. D–F, records from a synapse having a 358 μV EPSP at rest. A and D, 20 pulses s−1 stimulation. B and E, 40 pulses s−1 stimulation. C, 100 pulses s−1 stimulation. F, 60 pulses s−1 stimulation. The second peak in C results from a second I a trigger at 10 ms.

Download figure to PowerPoint

The MPI values from these two synapses, as well as six others tested at multiple stimulation frequencies, are shown in Fig. 4. The error bars represent 95 % confidence intervals computed with the bootstrap technique. All but one of the illustrated MPI values were significant, i.e. the confidence intervals did not span 0 % (dotted line). The asterisks denote MPI values that were significantly different from the MPI obtained at the next lowest frequency. Even though the confidence intervals were fairly large, several of the synapses showed frequency dependence of the MPI. For the 137 μV synapse illustrated in Fig. 3 (□ in Fig. 4) there were no significant differences between frequencies, whereas for the 358 μV synapse (▪ in Fig. 4), the MPI at 60 pulses s−1 was significantly lower than the MPI at 40 pulses s−1. All significant changes in MPI were in the direction of decreasing magnitude as stimulation frequency increased.

image

Figure 4. Changes in mean percentage increase (MPI) in histogram peaks as a function of stimulation frequency

Each symbol denotes a different synapse. Values are shown with bootstrapped BCα 95 % confidence intervals. Asterisks indicate values found to be significantly different from the next lower frequency (see Methods). Although they are displaced horizontally to increase visibility on the plot, synapses were stimulated at nominal frequencies of 20, 40, 60 etc. pulses s−1. The dotted line indicates 0 %.

Download figure to PowerPoint

By evaluating the ramps of membrane depolarization, it was possible to determine whether the frequency dependence of MPI was also seen in the EPSP. For six of the recordings, it was possible to average enough ramps to evaluate the EPSPs falling in a fixed time window prior to a postsynaptic action potential. Figure 5 shows sample recordings taken from a motoneurone firing steadily at about 9 impulses s−1, while a single I a was driven at either 20 (Fig. 5A) or 60 pulses s−1 (Fig. 5B). The EPSP is smaller at the higher frequency, as can be seen from the superimposed records (after subtracting the respective ramps) shown in Fig. 5C. The corresponding PSTHs (Fig. 5D and E; 20 and 60 pulses s−1, respectively) showed a decline in MPI of the primary peak from 496 % to 329 %. Of the six synapses, the four with the largest EPSP amplitudes (300 μV at the lowest measured frequency) were depressed by 15–58 % as afferent frequency increased, whereas the two synapses for which EPSP amplitude was < 200 μV at the lowest frequency were facilitated, or showed little change (Fig. 6A) with frequency. Ramp EPSPs are plotted against the corresponding MPI in Fig. 6B along with the geometric mean regression line fit to the data on rest EPSPs. Generally, MPI and EPSP amplitude appear to co-vary within synapses much as they do among synapses (Fig. 2 and Cope et al. 1987), although the data are too sparse to warrant a rigorous statistical comparison.

image

Figure 5. EPSPs and PSTHs from a single synapse stimulated at two different frequencies

EPSPs were recorded on the depolarizing ramp of a repetitively firing motoneurone, with the I a afferent stimulated at 20 pulses s−1 (A) or 60 pulses s−1 (B). C, data from A and B superimposed after the lines fitted to the pre-trigger ramps of membrane potential were subtracted from all points. D, PSTH from the same recording as A (20 pulses s−1). E, PSTH from the same recording as B (60 pulses s−1) shown on the same vertical scale as D. This synapse is the same one shown in Fig. 1, and is represented by ○ in Figs 4 and 6. Arrows indicate stimulus onset.

Download figure to PowerPoint

image

Figure 6. Modulation of EPSP and MPI

A, ramp EPSP amplitude as a function of afferent frequency. B, MPI as a function of ramp EPSP amplitude. Each symbol represents a different synapse, and matches the equivalent synapse shown in Fig. 4. Dashed line, geometric mean regression (Y= 0.95X–45.4) fitted to data for single synapses (Fig. 2A, •).

Download figure to PowerPoint

Potential influence of other factors on histogram peaks

In addition to afferent stimulation frequency, the PSTH primary peaks could be affected by other factors, such as synaptic noise (Kirkwood, 1979; Fetz & Gustafsson, 1983; Gustafsson & McCrea, 1984; Poliakov et al. 1996 and references therein) or the discharge rate of the postsynaptic cell. Models (e.g. Kirkwood, 1979; Midroni & Ashby, 1989; Polyakov, 1991) predict that the sharpness and height of PSTH primary peaks (and thus the MPI) should vary inversely with synaptic noise. In this study, noise did not appear to change greatly over the periods of study of a single synapse. For example, estimates of root mean square noise (1 Hz to 10 kHz) taken from the depolarizing ramps of discharging motoneurones (after subtracting the linear trend) varied from 78 to 250 μV among experiments, amounting to 2–37 % of EPSP amplitude. For single synapses, estimated noise varied by 9–48 μV, or 6–19 % of maximum over a trial. Considering only the five cases where a significant difference was found between MPIs (Fig. 4), the largest change in synaptic noise was a drop of 48 μV (○, shift from 40 to 60 pulses s−1). This drop was accompanied by a decline in MPI from 491 % to 329 %, which is in the direction opposite to that predicted from modelling. The four remaining significant changes in MPI with stimulation frequency were accompanied by small (9 μV maximum) changes in noise. We conclude that our results cannot be explained by fluctuations in synaptic noise.

Mean discharge rate of the postsynaptic cell was also examined for its effect on the PSTH, because the rate could not be tightly regulated over a trial. The motoneurone firing rate has been shown to affect various probabilistic measures of motoneurone discharge, such as the shape of interspike interval (ISI) histograms (Person & Kudina, 1972; Matthews, 1995), the area of synchronous peaks in cross-correlograms between homonymous motoneurones (Nordstrom et al. 1992) and the size of short-latency peaks in PSTHs between I a afferents and motoneurones (Jones & Bawa, 1995). It is thus important to consider whether some of the variation in MPI with stimulation frequency found in the present study might have resulted in fact from uncontrolled drift in the motoneurone rate.

In this study, the level of injected current was adjusted gradually during an experiment in an attempt to hold the motoneurone rate roughly constant, but it was not always possible to induce a motoneurone to fire at a steady mean rate. In the worst case, the mean motoneurone rate varied by 3.1 impulses s−1 among the I a trials, but typically the motoneurone rate varied by less than 1 impulse s−1. Again considering only the five significant differences between MPIs shown in Fig. 4, the greatest change in motoneurone rate was −1.8 impulses s−1 (again ○, changing from 40 to 60 pulses s−1), whereas the four remaining differences were accompanied by changes of +0.4 to −0.6 impulses s−1 in the motoneurone rate. The small span of these changes reinforces the interpretation that the observed MPI differences did indeed result from changes in the frequency of afferent stimulation. Although frequency-dependent properties of the postsynaptic cell may influence PSTH peaks, we conclude that they probably did not affect the present experiments to any great extent.

DISCUSSION

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements

This study provides the first evidence that PSTH primary peaks for single I a-motoneurone synapses change with stimulation frequency, and that this modulation parallels that of the corresponding synaptic potentials. Although prior workers demonstrated a frequency dependence of the amplitude of EPSPs at the I a-motoneurone synapse (Curtis & Eccles, 1960; Hirst et al. 1981; Honig et al. 1983; Grimwood & Appenteng, 1995), they measured only resting membranes, leaving open the question of whether the observed modulation was sufficient to alter motoneurone discharge. Although other workers found dependence of motoneurone discharge rate on the frequency of intracellular current pulses (Powers & Binder, 1996) or of group I stimulation (Redman et al. 1968; Chaplain & Schaupp, 1973), they do not identify the possible contributions of frequency-dependent changes in the synaptic potentials. The present study spans the gap between these two areas of investigation by showing that frequency-dependent synaptic depression translates into changes in the output of the postsynaptic cell.

Relationship to other studies of synaptic modulation at I a-motoneurone synapses

The frequency-dependent depression of I a EPSPs observed here is similar to that described before (Curtis & Eccles, 1960; Hirst et al. 1981; Honig et al. 1983; Collins et al. 1984; Grimwood & Appenteng, 1995). Most relevant are the studies by Mendell and colleagues (reviewed in Mendell et al. 1990) of frequency-dependent changes in EPSPs produced by single I a afferents in motoneurones. Those investigators found that some large EPSPs (100 μV) exhibit a decline in amplitude in a frequency range of 50–100 Hz, which is comparable to the frequency range in which we found clear-cut depression in larger EPSPs (Fig. 6A) and the associated MPIs (Fig. 4). The order of magnitude of EPSP depression they report (e.g. 21 % in Honig et al. 1983) is within the range of depression we found for ramp EPSPs. The single synapse that showed facilitation as afferent frequency increased from 8.6 to 40 pulses s−1 had a resting EPSP amplitude of 195 μV, which is greater than most of the facilitating I a synapses reported previously (Mendell et al. 1990). Although EPSPs smaller than 100 μV (the median value for MG homonymous I a-motoneurone connections) tend to facilitate with increased stimulation frequency, they were not studied here because the correlograms they make are difficult to resolve (see Cope et al. 1987).

Our study of synaptic modulation at single I a-motoneurone synapses differs from others in two respects. First, unlike studies in which I a-motoneurone connections were tested using short bursts of stimulation (tens of seconds at most), we employed continuous afferent stimulation for periods of up to 3 min in order to obtain sufficient numbers of spikes to resolve primary peaks in histograms. We found no indication, however, that such prolonged stimulation (at rates up to 100 pulses s−1) introduced long-term changes in synaptic efficacy (Fig. 1). Thus the longer-term changes observed for many minutes following high-frequency tetanic stimulation (500 pulses s−1 in Curtis & Eccles, 1960) were not apparent in our study. Second, whereas previous studies evaluated changes in synaptic strength only in quiescent motoneurones, we were able to extend those observations to repetitively firing motoneurones, and we confirmed that frequency-dependent depression is similar in the two conditions.

Relationship to other studies of neuronal output

Many studies compare the statistical dependence between neuronal spike trains under different conditions. Our findings bear on various conjectures concerning the modifiability of that dependence. Ghose et al. (1994) interpreted shifts in the area of short-latency peaks in correlograms between two neurones of the visual cortex as indicating ‘transient strengthenings of monosynaptic efficacy.’ Other authors report that discharge probabilities or the size of correlogram peaks vary with the length of the previous presynaptic interspike interval, an effect they ascribe to temporal summation or interactions (facilitation or depression) between PSPs (Segundo et al. 1963; Glantz & Nudelman, 1988; Lemon & Mantel, 1989). Conway et al. (1993) offer similar explanations for some features of third-order cumulant densities between I a and motoneurone spike trains. Even though the constant-frequency afferent stimulation employed in the present study sets it apart, our demonstration of co-modulation of PSTH peak with EPSP amplitude proves that shifts within the physiological range of single-fibre PSPs can be detected in probabilistic measures of spike-train interaction.

Implications for neural circuits

Our findings support suggestions (e.g. Abbott et al. 1997) that the magnitude of change observed in EPSPs at weak synapses can be sufficient to have measurable consequences for the input-output operation of neural circuits. While not yet demonstrated for other synapses, these consequences may appear widely in the mammalian nervous system, given the ubiquity of synaptic modulation. Of course, the actual consequence will be determined by functional properties of synapses and by firing behaviour of postsynaptic cells, both of which are widely divergent among cell types. Our results are most relevant to I a-motoneurone synaptic connections. Compared with the results of the present study, the changes in EPSP size associated with facilitation, depression and potentiation at single I a-motoneurone connections are sufficient to cause detectable alterations in motoneurone firing. In addition to depending on frequency, EPSPs also change in response to injury and inactivity in I a afferents and motoneurones as well as to injury of the spinal cord (Mendell, 1984). Our results confirm that these changes are also substantial enough to cause changes in the input-output relationship of the monosynaptic reflex circuit.

  • Abbott, L. F., Varela J. A., Sen K. & Nelson, S. B. (1997). Synaptic depression and cortical gain control. Science 275, 220224.
  • Chaplain, R. A. & Schaupp, V. (1973). The frequency transfer characteristics of cat soleus motoneurone during suppression of excitatory synaptic activity by ‘direct’ and Ib-type inhibition. Pflügers Archiv 345, 311316.
  • Churchland, P. S. & Sejnowski, T. J. (1992). The Computational Brain. MIT Press, Cambridge , MA , USA .
  • Clark, B. D. & Cope, T. C. (1995). Modulation of motoneuron firing by high and low Ia afferent rates. Society for Neuroscience Abstracts 21, 144.
  • Collins, W. F. III, Honig, M. G. & Mendell, L. M. (1984). Heterogeneity of group Ia synapses on homonymous α-motoneurons as revealed by high frequency stimulation of Ia afferent fibers. Journal of Neurophysiology 52, 980983.
  • Conway, B. A., Halliday, D. M. & Rosenberg, J. R. (1993). Detection of weak synaptic interactions between single Ia afferent and motor-unit spike trains in the decerebrate cat. The Journal of Physiology 471, 379409.
  • Cope, T. C., Fetz, E. E. & Matsumura, M. (1987). Cross-correlation assessment of synaptic strength of single I a fibre connections with triceps surae motoneurones in cats. The Journal of Physiology 390, 161188.
  • Cox, D. R. & Lewis, P. A. W. (1966). The Statistical Analysis of Series of Events. John Wiley & Sons, Inc., New York .
  • Curtis, D. R. & Eccles, J. C. (1960). Synaptic action during and after repetitive stimulation. The Journal of Physiology 150, 374398.
  • Efron, B. & Tibshirani, R. (1993). An Introduction to the Bootstrap. Chapman & Hall, New York .
  • Ellaway, P. H. (1978). Cumulative sum technique and its application to the analysis of peri-stimulus time histograms. Electroencephalography and Clinical Neurophysiology 45, 302304.
  • Fetz, E. E. & Gustafsson, B. (1983). Relation between shapes of post-synaptic potentials and changes in firing probability of cat motoneurons. The Journal of Physiology 341, 387410.
  • Garnett, R. & Stephens, J. A. (1980). The reflex responses of single motor units in human first dorsal interosseous muscle following cutaneous afferent stimulation. The Journal of Physiology 303, 35136.
  • Glantz, R. M. & Nudelman, H. B. (1988). Interval coding and band-pass filtering at oculomotor synapses in crayfish. Journal of Neurophysiology 59, 5676.
  • Ghose, G. M., Freeman. R. D. & Ohzawa, I. (1994). Local intracortical connections in the cat's visual cortex: postnatal development and plasticity. Journal of Neurophysiology 72, 12901303.
  • Grimwood, P. & Appenteng, K. (1995). Effects of afferent firing frequency on the amplitude of the monosynaptic EPSP elicited by trigeminal spindle afferents on trigeminal motoneurones. Brain Research 689, 299303.
  • Gustafsson, B. & McCrea, D. (1984). Influence of stretch-evoked synaptic potentials on firing probability of cat spinal motoneurons. The Journal of Physiology 347, 431451.
  • Hirst, G. D. S., Redman, S. J. & Wong, K. (1981). Post-tetanic potentiation and facilitation of synaptic potentials evoked in cat spinal motoneurones. The Journal of Physiology 321, 97109.
  • Honig, M., Collins, W. F. III & Mendell, L. M. (1983). α-Motoneuron EPSPs exhibit different sensitivities to single Ia-afferent fiber stimulation. Journal of Neurophysiology 49, 886901.
  • Jones, K. E. & Bawa, P. (1995). Responses of human motoneurons to Ia inputs: effects of background firing rate. Canadian Journal of Physiology and Pharmacology 73, 12241234.
  • Kirkwood, P. A. (1979). On the use and interpretation of cross-correlation measurements in the mammalian central nervous system. Journal of Neuroscience Methods 1, 107132.
  • Lemon, R. N. & Mantel, G. W. H. (1989). The influence of changes in discharge frequency of corticospinal neurones on hand muscles in the monkey. The Journal of Physiology 413, 351378.
  • Magleby, K. L. (1987). Short-term changes in synaptic efficacy. In Synaptic Function, ed. Edelman, G. M., Gall, W. E. & Cowan, W. M., pp. 2156. John Wiley & Sons, New York .
  • Matthews, P. B. C. (1995). Relationship of firing intervals of human motor units to the trajectory of post-spike after-hyperpolarization and synaptic noise. The Journal of Physiology 492, 597628.
  • Mendell, L. M. (1984). Modifiability of spinal synapses. Physiological Reviews 64, 260324.
  • Mendell, L. M., Collins, W. F. III & Koerber, H. R. (1990). How are Ia synapses distributed on spinal motoneurons to permit orderly recruitment? In The Segmental Motor System, ed. Binder, M. D. & Mendell, L. M., pp. 308327. Oxford University Press, New York .
  • Midroni, G. & Ashby, P. (1989). How synaptic noise may affect cross-correlations. Journal of Neuroscience Methods 27, 112.
  • Moore, G. P., Perkel, D. H. & Segundo, J. P. (1966). Statistical analysis and functional interpretation of neuronal spike data. Annual Review of Physiology 28, 493522.
  • Moore, G. P., Segundo, J. P., Perkel, D. H. & Levitan, H. (1970). Statistical signs of synaptic interaction in neurons. Biophysical Journal 10, 876900.
  • Nordstrom, M. A., Fuglevand, A. J. & Enoka, R. M. (1992). Estimating the strength of common input to human motoneurons from the cross-correlogram. The Journal of Physiology 453, 547574.
  • Perkel, D. H., Gerstein, G. L. & Moore, G. P. (1967). Neuronal spike trains and stochastic point processes II. Simultaneous spike trains. Biophysical Journal 7, 419440.
  • Person, R. S. & Kudina, L. P. (1972). Discharge frequency and discharge pattern of human motor units during voluntary contraction of muscle. Electroencephalography and Clinical Neurophysiology 32, 471483.
  • Poliakov, A. V., Powers, R. K., Sawczuk, A. & Binder, M. D. (1996). Effects of background noise on the response of rat and cat motoneurones to excitatory current transients. The Journal of Physiology 495, 143157.
  • Polyakov, A. V. (1991). Synaptic noise and the cross-correlation between motoneuron discharges and stimuli. NeuroReport 2, 489492.
  • Powers, R. K. D. B. & Binder, M. D. (1996). Experimental evaluation of input-output models of motoneuron discharge. Journal of Neurophysiology 75, 367379.
  • Redman, S. J., Lampard, D. G. & Annal, P. (1968). Monosynaptic stochastic stimulation of cat spinal motoneurons. II. Frequency transfer characteristics of tonically discharging motoneurons. Journal of Neurophysiology 31, 499508.
  • Segundo, J. P., Moore, G. P., Stensaas, L. J. & Bullock, T. H. (1963). Sensitivity of neurones in Aplysia to temporal pattern of arriving impulses. Journal of Experimental Biology 40, 643667.
  • Zucker, R. S. (1989). Short-term synaptic plasticity. Annual Review of Neuroscience 12, 1331.

Acknowledgements

  1. Top of page
  2. Abstract
  3. METHODS
  4. RESULTS
  5. DISCUSSION
  6. Acknowledgements

This study was supported by NSF IBN-9208649 and NSF IBN-9596117. We are grateful to M. D. Binder, E. E. Fetz and R. K. Powers for comments on the manuscript.