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Evidence for two types of firing pattern during the sleep-waking cycle in the reticular thalamic nucleus of the cat
EXPERIMENTAL
NEUROLOGY
72.486-501
(1981)
Evidence for Two Types of Firing Pattern during the Sleep-Waking Cycle in the Reticular Thalamic Nucleus of the Cat G. BARRIONUEVO, 0. BENOIT, AND P. TEMPIER’ Unilh de Recherches Neurophysiologiques
de I’INSERM
(U3). Paris, France
Received June 17, 1980: revision received October 31, 1980 The activity of 23 neurons was recorded extracellularly in the nucleus reticularis thalami (RT) of four chronically implanted cats. Patterns of discharge were studied and their relationship to wakefulness (W), slow-wave sleep (SS), and paradoxical sleep (PS) were examined. The firing pattern was analyzed using zero-order (firing rate), first-order (interspike interval histogram), and second-order (joint interval histogram and autocorrelogram histogram) statistics. The SS bursting pattern was investigated taking into account the duration of the intervals between the bursts, the number of spikes per burst, and the duration of the bursts. Zero- and first-order characterizations during W and PS were found to be comparable. However, the joint interval histogram revealed a state-specific pattern during W for 74% of the cells. This pattern was characterized by a nonrandom occurrence of some categories of adjacent intervals. This was not found during PS. Two-thirds of the cells recorded, called “fast” neurons, exhibited firing rates higher than 15 spikes/s during W and PS. Those remaining, called “slow” neurons, showed a mean discharge rate lower than 10 spikes/s. In SS “fast” neurons fired long-duration bursts with interburst intervals generally shorter than 1 s. Conversely, “slow” neurons discharged shortduration bursts interrupted by long interburst intervals (greater than 1 s). Nevertheless, both types of cells had the same number of spikes within the burst and a similar intraburst pattern. Approximately half of the cells studied depicted a “slow rhythm” in the autocorrelogram histogram. Its periodicity was independent of firing rates and behavioral states. Abbreviations: SS-slow-wa.ve sleep, W-waking, PS-paradoxical sleep, RT-nucleus reticularis thalami, EEGLelectroencephalogram, EOG-electrooculogram, EMG-electromyogram. ’ This research was supported by INSERM (ATP 4-74125). The authors wish to express their appreciation to Ms. C. Guidet and Mr. J. R. Teilhac for their valuable technical help. They also thank Drs. N. Weinberger and P. Rinaldi for their helpful assistance and critical comments in preparing the English manuscript. Dr. Barrionuevo is now at the Department of Psychobiology, University of California, Irvine, CA 927 17. Requests for reprints should be addressed to Dr. 0. Benoit, Unite 3 de I’INSERM, 47 Bd de I’HBpital 75634, Paris Cedex 13, France. 486 00 I4-4886/8 l/050486-16$02.00/O Copyright 0 1981 by Academic Press, Inc. All rights of reproduction in any form reserved
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INTRODUCTION Among the hypotheses proposed to explain the synchronization observed in the thalamus during anesthesia or sleep, a possible role was suggested for the reticular thalamic (RT) nucleus. This hypothesis was first suggested by Scheibel and Scheibel (21). As shown by their Golgi studies (20), the majority of RT neurons project back to the thalamus and have many synaptic contacts with the other thalamic nuclei, including the intralaminar thalamic system. This direct backward projection would be very effective in producing inhibition in the other thalamic neurons (22). A major point of the physiologic data supporting the Scheibels’ hypothesis comes from the striking capacity of the cat’s RT neurons to fire in long, sustained bursts separated by long silent pauses correlated with a decrease of vigilance with anesthesia or spontaneously (10, 13, 15, 17, 18, 24, 28, 29). Earlier, Mukhametov et al. ( 17) found that firing rates and interval histograms of RT neuron activity during wakefulness were similar to those occurring in paradoxical sleep. However, such statistical characterizations are all independent of the observed order of intervals in the actual spike train. A higher level of analysis tests for order dependence and characterizes the temporal organization of the discharge. Therefore, the aim of our study was to analyze the spontaneous activity of single RT neurons, using highorder statistics to complement zero-order (firing rate) and first-order (interval histogram) characterizations of the discharge. In addition, an analysis was designed for precise documentation of the slow-wave sleep bursting pattern. METHODS The data reported here are for 23 neurons obtained from four unanesthetized, unparalyzed cats, whose head were held rigidly fixed to the Horsley Clark apparatus by means of a metal frame. The distribution of cells among the four cats was as follows: 7, 6, 5, 5. The animals had been previously aseptically prepared with a stainless-steel cylinder (Trend Wells system) attached to the skull according to stereotaxic coordinates. Six skull screws were used for conventional bipolar electroencephalogram recording. Bipolar measures of electrooculogram (EOG) and neck electromyogram (EMG) were recorded with silver electrodes. Recording sessions began 10 days after surgery. The animals were placed in a sound-attenuated, TV-monitored chamber. A hydraulic microelectrode carrier was fixed to the previously implanted stainless-steel cylinder. Conventional platinum-iridium glass-insulated microelectrodes were used for unit recording. The neuronal action potentials were amplified by an AC coupled amplifier and fed to an oscilloscope, a loudspeaker, and a window
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discriminator. Simultaneously recordings of the EEG, EOG, EMG, and the output of the discriminator were displayed on a polygraph and stored on magnetic tape. Microelectrode tracks were marked by a small electrolytic lesion made by passing a DC current through the tip ( 15 PA for 15 s). On completion of the experiments, the animals were deeply anesthetized with barbiturate and perfused through the carotid artery with a 10% form01 solution. Histologic verification of the electrode placements (Fig, 1) was carried out in serial reconstruction of cresyl violet-stained frozen sections, (40 pm thick). In addition to anatomic localization, the neurons were further localized to the RT by their peculiar long-sustained bursting pattern present during SS sleep. This typical pattern, first described by Negishi et al. (18), was confirmed in a number of other studies (cf. Introduction). Data Analysis Firing Pattern Analysis. Stable states of wakefulness (W), slow-wave sleep (SS), and paradoxical sleep (PS) were defined according to standard polygraphic criteria. Single-unit activity was sampled in each state according to the following criteria: (i) the stability of the polarity and amplitude and (ii) a signal to noise ratio of at least 2:l. The stability of the sampled unit activity was verified by visual inspection and sequential computation of the number of spikes with a resolution of 1 s. Computations were carried out by an Intertechnique multichannel analyzer. All firing pattern analysis was with a PDP-KL-10 with a time resolution
FIG. I. Localization of the 23 cells recorded during slow-wave sleep in stereotaxic (12). Abbreviations: PUL-pulvinar, LP-lateralis posterior, CL-geniculate body, ventralis lateralis, VA-ventralis anterior, NL-reticular thalamic nucleus.
planes VL-
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of 100 ps. Using a program developed in our laboratory (7), the following analyses were made: (i) interspike interval histogram, (ii) joint interval histogram, and (iii) autocorrelogram histogram. The joint interval histogram was displayed as a three-dimensional plot. The x axis represents the duration of Jl, the first of the pair of intervals; the y axis represents the duration of 52, the second of the pair of intervals; and the z axis the probability of occurrence of the pair, JlJ2. Dependence between adjacent intervals was determined from the relationship, P( Jl, 52) = P(J 1) X p(J2), where p(J1, 52) is the actual probability of the pair and P(J1) X p(J2) is the probability of occurrence of the same intervals computed from the interspike interval histogram, i.e., assuming that there is no serial dependence between adjacent intervals ( 19). Burst Pattern Analysis. Among the 20 neurons analyzed for firing pattern during SS, 10 were selected for burst pattern analysis on the basis of the number of bursts (more than 40) emitted during the SS epoch. The analyses of the bursts were carried out with a Wang 600 computer programmed with criteria based upon first-order (interspike interval histogram) and second-order (joint interval histogram) characterizations of the discharge. The criteria for selecting bursts were (i) the sum of the first five intervals was equal to or less than 40 ms, (ii) the burst was preceded by an interspike interval equal to or greater than 100 ms, and (iii) the end of the burst had an intraburst interval greater than 50 ms. Changing these parameters by +20% made no difference in the outcome of the burst pattern analysis. A periburst histogram (7) (computed by a PDP-KL-10) provided a complete and quantitative relationship between the burst and the spike train in its entirety (Fig. 8). Basically, the measure computes the probability per unit time of observing a spike as a function of time before and after the first spike of a burst. The periburst histograms from individual neurons were pooled by using a comparison expected value (Epv) for each cell. This value was derived as described: Epv = f X b X A%, where f = mean firing rate, b = bin width, Nb = number of bursts analyzed. RESULTS During the analysis it became apparent that two groups of neurons could be distinguished on the basis of firing rates and SS bursting pattern. Table 1 provides a summary of the data for the firing pattern of the two groups of cells and will be referred to throughout this section. Firing Rates: “Fast” and “Slow” Neurons. Figure 2 gives the distribution of the firing rates of 20 neurons for SS, 18 for W, and 12 for PS. In W and PS the neurons could be divided into two separate groups in
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1
Comparison of Firing Pattern between “Fast” and “Slow” Nucleus Reticular Thalami Neurons” Firing rate*
Burst analysis (SS)b
Type cell
W*
ps* (spikes/s)
SS
Fast
22.7 f4
34 f4
19.3 22.7
Slow
7.2 * 0.5
*1
6
a VaheS are means f SD. * Abbreviations: W-waking, preceding burst, IFB-interval iBF-intraburst frequency.
IPB* W)
IFB* (4
BD* (ms)
S/B (spikes)
iBF (spikes/s)
480 * 141
360 f123
198.6 &92
12.3 +2
-62
2424 k 1024
1515 *917
96 +28
14.9 kO.7
2158
PS-paradoxical sleep, SS-slow-wave sleep, IPB-interval following burst, BD-burst duration, S/B-spikes per burst,
* P < 0.05.
terms of firing rate. Most of them (73% in W and 66% in PS) had firing rates higher than 15 spikes/s. Their mean frequency rates ( + SD) were 22.7 + 4 spikes/s for W and 34 + 4 spikes/s for PS. The remaining neu'1. LO 35 30 25 20 15 10 5 0i 25 20 15 10 5 0 25 20 15 10 5 0
W
Nz18
5 10 15 20 25 M 35 40 &5 50 PS
N:lZ
5 10 15 20 25 30 35 LO45
FIG. 2. Distribution of the firing rates (expressed in percentage of the total number of cells) observed in 18 neurons during waking (W), in 20 neurons during slow-wave sleep, (SS), and in 12 neurons during paradoxical sleep (PS).
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rons (27% in W and 34% in PS) had firing rates less than 10 spikes/s (7.2 f 0.5 spikes/s for W and 6 & 1 spike/s for PS). Differences in firing rates in these two groups of neurons, “fast” and “slow,” respectively, within each state were significant (P < 0.05, Mann-Whitney U test) (Table 1). However, no significant differences could be found between the firing rates during W and PS within each group. In SS, neurons were not distinguishable on the basis of rate alone. Their mean firing rate was 19.3 + 2.7 spikes/s (median: 16.8 spikes/s). Sixteen neurons were analyzed in two states (W and SS or SS and PS) and seven in all three stages. Figure 3 shows the changes in firing rates observed as a function of the sleep-waking state. In most cases the firing rate changed according to the state of vigilance, SS being significantly different from W and PS (P < 0.05, Wilcoxon matched pair signed-ranks test). All neurons but one maintained their fast or slow characterization when passing from W to PS. The definition of a neuron as fast or slow depended only on its mean firing rate in W and PS and not on its intraburst firing rate in SS (Table 1). Firing Pattern Analysis in Waking and Paradoxical Sleep. In W and PS the activity of the RT neurons was characterized by a continuous, sustained discharge as shown in Figs. 4 and 5 (Al and B 1 ), and by the unimodal distribution of the interspike interval. Slow and fast neurons differed mainly in the mode of the interspike interval histogram. Joint interval histogram distributions for W are presented in Fig. 4, A2 and B2. The main diagonal, which runs from the front to the rear of the “surface” is of particular interest because identical or nearly identical adjacent in-
FIG. 3. Mean firing rates during waking (W), slow-wave sleep (SS), and paradoxical sleep (I’S) of nine neurons followed in two stages (broken lines) and in seven neurons in three stages (continuous lines).
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A2 % mode.177
82
FIG. 4. Spontaneous discharge pattern of a fast neuron (A) and a slow neuron (B) during waking. Al and Bl-actual spike train (3 s of recording) and interspike interval histograms. A2 and B2-joint interval histograms. The arrows indicate the pairs of adjacent intervals with a highly nonrandom probability of occurrence (see Methods). Time axes of the histograms are on a logarithmic scale. Symbols: x-mean interval, s-standard deviation, W-number of intervals, lrst-first interval, Znd-second interval.
tervals lie along this line. Specifically, adjacent short intervals appear near the front of the surface, and adjacent longer intervals are plotted at successive points toward the rear of the surface. These figures show that fast neurons (short intervals) and slow neurons (long intervals) were found to have similar joint interval histograms, i.e., both were characterized by values grouped around the main diagonal; the peak for fast neurons was closer to the front of the surface (short-short intervals) than the values of peaks for the slow neurons, which were close to the rear (long followed by long). Thus, regardless of the rate of discharge (fast or slow), both groups of neurons were found to have regular discharge patterns during W. Furthermore, an analysis of the joint interval histogram during PS also
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FIG. 5. Spontaneous discharge pattern during paradoxical sleep of a fast (A) and a slow neuron (B). Same neurons as in Fig. 4 (see Fig. 4 for symbols and abbreviations).
revealed regular discharge patterns for each type of neuron (Fig. 5, A2 and B2). Thus, discharge patterns were regular for fast and slow cells during both W and PS. In W a more precise analysis showed that for 14 neurons (74%) there was a strong probability for association between a given interval (frequently in or near the modal value) and another two or three times longer (see arrows in joint interval histograms in Fig. 4, A2 and B2). This probability of association was significantly different from chance (see Methods) (P < 0.01, chi-square test). For other associations of pairs of adjacent intervals in W and for all kinds of pairs in PS a relative serial independence was found. Firing Pattern Analysis in Slow-Wave Sleep. As previously described the firing pattern of RT neurons during SS was discontinuous: the long bursts were separated by very long intervals. The interspike interval histograms (Fig. 6, Al) were asymmetrical with a positive skew. The modal
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N= 737
% mode = 3 6
6
Oms
FIG. 6. Discharge pattern during slow-wave sleep of a fast neuron. Al-the actual spike train shows two long bursts (2.5 s of recording). AZ-the joint interval histogram; two aspects are shown with a 90” shift. a, b, and c-Associations of adjacent short, medium, and long intervals, respectively, of the burst (see test for further explanations). Same symbols as in Fig. 4.
values were between 2.8 and 6.6 ms (median less than 14 ms) and corresponded to the intraburst intervals. There were very few intervals between 60 and 100 ms. The percentage of intervals greater than 1 s was 0.6% for “fast” neurons and 9% for “slow” neurons. Thus, the two groups identified in W and PS were still present in SS. They were more easily distinguished by examination of the intraburst organization or the interburst intervals (Table 1). In the following analysis, “fast” or “slow” neuron denotes fast or slow firing rate in W or in PS. An initial analysis of the SS pattern is given by the joint interval histogram (Fig. 6, Al). The short-, less than 10 ms (37.6%, Fig. 6 A2a), and the medium-range intervals, between 10 and 60 ms (33.4%, Fig. 6, A2b), were regularly dispersed around the diagonal such that each interval was
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followed by the same category of interval. These were the intraburst intervals. The long intervals, greater than 100 ms (Fig. 6, ARC), were very frequently (9 1%) associated with the medium-range intervals, rarely (7.6%) with long intervals, and very rarely (1.4%) with short intervals. Zntraburst Organization. From the study of the interval dependency in the joint interval histogram some common features of the intraburst organization may be deduced. In general, one long interval and one or two medium-range intervals were followed by some short intervals; then, medium intervals of increasing duration occurred, finally followed by one long interval. It appeared as if a firing acceleration (to 400 spikes/s) was followed by a progressive deceleration (to 16 spikes/s). Burst Analysis. During SS, seven fast neurons firing 680 bursts and four slow neurons firing 193 bursts were studied. The durations of the two groups of bursts were significantly different (P < 0.05, Kolmogorov-Smirnov, two-sample test) (Fig. 7 A and B); bursts had a shorter duration in slow neurons (mean 96 f 28 ms; median 90 ms) than in fast neurons (mean 198.6 + 92 ms, median 150 ms). In contrast, the number of spikes within the bursts were very similar: 14.9 f 0.7 spikes/s in slow neurons and 12.3 + 2 spikes/s in fast neurons. Thus, the intraburst firing rates were approximately three times greater in slow neurons than in fast neurons (158 against 62 spikes/s) (Table 1). Distribution of Intervals Preceding and Following the Bursts. Again,
ii = ,986 ms SD = 92ms
FIG. 7. Long and short bursts fired by fast neurons (left) and slow neurons (right) respectively. The actual spike trains are shown on the top (3 s of recording). The histograms of the bursts’ duration were calculated for 680 bursts from seven fast neurons and 193 bursts from four slow neurons.
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when looking at the intervals before and after the bursts, fast and slow neurons behaved differently (Fig. 8). For fast neurons the intervals before and after the bursts were usually shorter than 1 s and the distributions were positively skewed. For intervals preceding bursts (Fig. 8, Al), the median was 400 ms with a mean of 480 f 141 ms. For intervals following bursts, (Fig. 8, A2) the median was 300 ms and the mean 360 f 123 ms. In contrast, for slow neurons, most intervals preceding and following bursts were longer than 1 s. The distribution of intervals preceding bursts (Fig. 8, Bl) was negatively skewed with a mean of 2424 f 152 ms (median, 1500 ms, Fig. 8). The lengths of the intervals following the bursts appeared to be bimodally distributed (Fig. 8, B2) with a short mode (12%) at 118 ms, a long mode (7%) at 4100 ms, and the median at approximately 1 s. This pattern was somewhat influenced by the temporal variability in the spiking at the end of the burst; although typically a few such spikes followed each burst, in some cases it was difficult to ascertain whether they were linked to the burst. The firing probability before or after a burst (periburst histogram, Fig. 8, A3 and B3) confirmed that slow neurons discharged considerably under the comparison expected value (see Methods) for 1 s
Al
A3
FIG. 8. Distribution of the duration of the intervals preceding and following the bursts of fast neurons (A) and slow neurons (B) Al, Bl-histograms of the preceding intervals. A2, BZ-histograms of the following intervals. A3, B3-periburst histograms. The observed probability of firing before or after the first spike of a burst is expressed in percentage of the comparison expected value (EpV) calculated for each cell from the mean rate (see Methods). 0 corresponds to the first spike of the bursts.
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and more. Thus the study of the burst firing pattern in SS confirmed the physiologic heterogeneity of RT neurons: slow and fast neurons observed in W or in PS have different intra- and interburst organization (Table 1). Rhythmicity. Examination of the second-order statistics with the autocorrelogram histogram revealed that approximately half the cells in each state showed rhythmicity (at least three cycles in the sample autocorrelogram histogram) regardless of characteristic fast or slow cell type designation. The incidence of rhythmic cells and mean frequencies for each state were W (8/18) = 2 + 0.6 cycles/s; PS (7/12) = 1.8 f 0.4 cycles/ s; and SS (10/20) = 1.2 -t 0.7 cycles/s. There were no significant differences between states. DISCUSSION Two populations of neurons (“fast” and “slow”) could be readily identified in the RT nucleus during W and PS on the basis of firing rate and interspike interval histogram alone. For SS only a bursting pattern analysis could differentiate fast and slow cells. The view that firing rate and interspike interval histogram analysis do not allow differentiation of the firing pattern between W and PS has been advanced before (17) and is in general agreement with the data reported here. Because such statistical characterizations neglect temporal ordering, we also used joint interval histogram techniques to study the time pattern of the spike trains. The most striking feature that was shown by this technique was a state-specific pattern during W compared with PS. Specifically, in most cells, the joint interval histogram describing W revealed a recurrence of a time interval in or near the modal value followed (and preceded) by one of longer duration, i.e., the location on time of an impulse depended on the time of occurrence of previous impulses; the underlying process differed from a renewal process. At present, the interpretation of this temporal pattern during W, and its relation to physiologic mechanisms, may be somewhat speculative. However, it is permissible to assume that this could be the consequence of inhibitory mechanisms triggered during W and rather inoperational during PS. Relevant to this, perhaps, is the fact that the medial mesencephalic reticular formation which actively maintains waking (16) also inhibits RT neurons (6, 30). The rhythmic activity found in some RT neurons by means of the autocorrelogram histogram is likely to correspond to the “slow rhythm” found in the mesencephalic reticular formation (14). It should not be assumed that RT neurons are pacemaker-like cells for this slow rhythm because there was a considerable difference between the modal interval and the
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periodicity and a lack of variability with the sleep-wakefulness cycle. These rhythms may be related to the activity of the respiratory center, as was suggested for the mesencephalic reticular formation (14). “Fast” and “Slow” Neurons. Fast and slow neurons have not been differentiated previously in the RT nucleus. The population studied by Mukhametov et al. (17) seems to correspond to our fast-type neuron with a mean discharge rate of 35.6 spikes/s during W (range 18 to 72 spikes/s) and 40 spikes/s during PS (range 12 to 80 spikes/s). In SS, they found that the percentage of intervals greater than 1 s is approximately 2%, as in our data. No comparison with Lamarre et al. ( 13) could be made because they did not report firing rates. The rates found by Schlag and Waszak (24) distributed between 0 and 120 spikes/s and thus included slow neurons. The slow neurons recorded in this study are likely to be from the RT because (i) they had the same firing pattern in W and PS as fast neurons, (ii) they exhibited the same dependency among intraburst intervals as shown by the joint interval histogram in SS; and (iii) both slow and fast neurons had at times been recorded from the same electrode tracks within a 200-pm distance. Therefore, the two populations were not segregated in different locations. Histological study of the RT established the heterogeneous character of cell size throughout the RT nucleus. The region from which the recordings for this study were made was shown to be composed mainly of small cells (20). This may account for the predominance of fast cells in our data. The discharges of small neurons were indeed described as faster than those of large neurons (11). This, of course, must remain somewhat speculative until the individual cells recorded are identified. Zntraburst and Znterburst Organization. The general characteristics of the bursting pattern in RT neurons (interburst intervals, spikes per burst, burst duration) as defined by our computer analysis were in agreement with those found by previous investigators (10, 13, 15, 17, 18, 24, 29). Bursting patterns are especially prominent in the thalamic structures. However, the bursts fired by RT neurons differ from those of units recorded in thalamic relay and associative (9) nuclei. RT bursts are characterized by long-lasting, high-frequency discharges in which the number of spikes within bursts is greater than six (18, 24). If we examine the case where the average frequency is the same in both types of bursts, the maximal frequency is at the beginning of the burst (first or second interval) in relay nuclei (3, 27) and in the middle of the burst in the RT (24). The secondorder statistics used in our study dramatically confirm this intraburst organization and allow a more precise categorization. In contrast to W and PS, during SS, zero- and first-order statistics were
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not useful in differentiating fast and slow cells. It was only by the study of burst patterns that the two populations were recognized. Specifically, the neurons of the slow population emitted bursts at a slower rate (slower interburst frequency) than those of the fast population. This was “counterbalanced” by the fact that intraburst frequencies of the slow population cells were two or three times higher than those of fast cells. Nevertheless, with the joint interval histogram both types of cells showed the same pattern of statistical dependence for the intraburst organization. This might suggest a common mechanism of burst production. In many other cortical and thalamic structures (2, 3, 8), fast and slow neurons have been observed in W or PS. These differences were analyzed either according to the size of the cells, or to the change of firing rate throughout the sleep-wakefulness cycle. As far as we know, the slow or fast firing rate characterization in these other structures does not lead to a clearcut prediction concerning the SS pattern as it did in RT neurons. Waszak (28) reported heterogeneity of the neuronal responses to repetitive intralaminar stimulation in the ventral leaf of the RT nucleus. All neurons responded with a depolarization, but in a second group the excitatory postsynaptic potential was followed by large hyperpolarizations. It would be interesting to see if our slow neurons, which exhibit very long interburst intervals and relatively short duration bursts, correspond to the second group of Waszak. If this were so, it would suggest that fast and slow neurons may have different physiologic roles. Burst Mechanism. The mechanism underlying the production of bursting from cells of specific thalamic nuclei was shown to involve a sustained depolarization interrupted by a hyperpolarization (1). Bursts from RT neurons are produced by a similar but longer sustained depolarization (10, 28), probably in combination with some other mechanisms, possibly including the “regenerative mode” discussed by Calvin (4). The latter could explain the sudden acceleration of the discharge in the middle of the burst as described in this study. One of the surprising facts is the capacity of RT cells to fire in bursts from stimulation of a variety of inputs. However, this capacity is related to complex factors. For example, Steriade (25) was able to obtain unitary monosynaptic responses during W, but during EEG synchronization these same cells produced a bursting response to stimulation. Therefore, it is possible to consider that the RT neurons may operate as a “damped oscillator” (5), i.e., due to special properties of the membrane and under certain conditions, the cells fire in burst. Specifically, these conditions are likely to prevail during SS and as a consequence of an increased synchronization of inputs during this period (26). In addition, the likelihood of burst occurrence in RT neurons could be enhanced by the special dendritic pattern described by Scheibel and Scheibel (23).
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CALVIN, W. H. 1975. Generation of spike trains in CNS neurons. Brain Res. 84: l-22. CHALAZONITIS, N. 1977. Introduction to neuronal burst activity. J. Physiol. (Paris) 73: 441-452. DINGLEDINE, R., AND J. S. KELLY. 1977. Brain stem stimulation and the acetylcholineevoked inhibition of neurons in the feline nucleus reticularis thalami. J. Physiol. (London) 271: 135-154. DUFOSSE, M., P. DECANTE, AND A. HANEN. 1975. Systbme d’analyse des processus ponctuels simples et multiples. Application B la neuro-physiologie. Inf. J. Bio-Med. Comput. 6: 249-291. EVARTS, E. V. 1965. Relation of discharge frequency to conduction velocity in pyramidal tract neurons. J. Neurophysiol. 28: 215-228. FOURMENT, A., AND J. C. HIRSCH. 1979. Single-unit discharges in the dorsolateral thalamus of behaving cats: spontaneous activity. Exp. Neural. 65: 1-15. FRIGYSI, T. L. 1972. Intracellular recording from neurons in dorsolateral thalamic reticularis nucleus during capsular, basal ganglia and midline thalamic stimulation. Brain Res. 48: 157-172. HENNEMAN, E., G. SOMJEN, AND D. 0. CARPENTER. 1965. Functional significance of cell size in spinal motoneurons. J. Neurophysiol. 28: 566580. JASPER, H. H., AND C. AJMONE-MARSAN. 1954. AStereotaxic Atlas of the Diencephalon of the Cat, p. 7 1. Natonal Research Council of Canada, Ottawa. LAMARRE, Y., M. FILION, AND J. P. CORDEAU. 1971. Neuronal discharges of the ventrolateral nucleus of the thalamus during sleep and wakefulness in the cat. I. Spontaneous activity. Exp. Brain Res. 12: 48&498. MACGREAGOR, R. J., R. PRIETO DIAZ, S. W. MILLER, AND P. M. GROVES. 1973. Statistical properties of neurons in the rat mesencephalic reticular formation. Brain Res. 64: 167-187. MASSION, J. 1968. Etude d’une Structure Motrice Thalamique. le Noyau VentrolaGral et de sa Regulationpar les Affkrences Sensorielles. Thbe de doctorat d’Etat et sciences naturelles. Facultt de Sciences de Paris. MORUZZI, G. 1972. The sleep-waking cycle. Ergebn. Physiol. 64: I-165. MUKHAMETOV, L. M., G. RIZZOLATTI, AND V. TRADARDI. 1970. Spontaneous activity of neurons of nucleus reticularis thalami in freely moving cats. J. Physiol. (London) 210: 651-667.
18. NEGISHI, K., E. S. LLJ, AND M. VERZEANO. 1962. Neuronal activity in the lateral geniculate body and the nucleus reticularis of the thalamus. Vision Res. 1: 343-353. 19. RODIECK, T. W., N. Y. S. KIANG, ANDG. L. GERSTEIN: 1962. Somequantitative methods for the study of spontaneous activity of single cell. Biophys. J. f: 351-368. 20. SCHEIBEL, M. E., AND A. B. SCHEIBEL. 1966. The organization of the nucleus reticularis thalami: a Golgi study. Brain Res. 1: 43-62. 21. SCHEIBEL, M. E., AND A. B. SCHEIBEL. 1967. Structural organization of non-specific thalamic nuclei and their projection toward cortex. Brain Res. 6: 60-94.
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22. SCHEIBEL, M. E., AND A. B. SCHEIBEL. 1970. Elementary processes in selected thalamic and cortical subsystems-the structural substrates Pages 443-457 in F. SCHMITT, Ed., The Neurosciences Second Study Program. Rockefeller Univ. Press, New York. 23. SCHEIBEL, M. E.. AND A. B. SCHEIBEL. 1972. Specialized organizational pattern within the nucleus reticularis thalami of the cat. Exp. Neural. 34: 316-322. 24. SCHLAG, J., AND M. WASZAK. 1971. Electrophysiological properties of units of the thalamic reticularis complex. Exp. Neural. 32: 79-97. 25. STERIADE, M., AND P. WYZINSKI. 1972. Cortically elicited activities in thalamic reticularis neurons. Brain Res. 42: 5 14-520. 26. STERIADE, M., AND J. A. HOBSON. 1976. Neuronal activity during the sleep-waking cycle. Prog. Neurobiol. 6: 155-376. 27. TEMPIER. P., 0. BENOIT, AND B. GEORGE. 1975. Characteristic of the spontaneous bursting pattern of thalamic neurons during slow wave sleep. Pages 281-284 in P. LEVIN AND W. P. K&LLA, Eds. Karger, Basel. 28. WASZAK, M. 1972. Membrane potentials changes in rostra1 thalamic neurons during spontaneous and triggered spindles. Bruin Res. 41: 47948 1. 29. WASZAK, M. 1974. Firing pattern of neurons in the rostra1 part of the nucleus reticularis thalami during EEG spindles. Exp. Neurol. 43: 38-59. 30. YINGLING, C. D., AND E. J. SKINNER. 1975. Regulation of unit activity in nucleus reticularis thalamic by the mesencephalic reticular formation and the frontal granular cortex. Electroenceph. Clin. Neurophysiol. 39: 635-642.
NEUROLOGY
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Evidence for Two Types of Firing Pattern during the Sleep-Waking Cycle in the Reticular Thalamic Nucleus of the Cat G. BARRIONUEVO, 0. BENOIT, AND P. TEMPIER’ Unilh de Recherches Neurophysiologiques
de I’INSERM
(U3). Paris, France
Received June 17, 1980: revision received October 31, 1980 The activity of 23 neurons was recorded extracellularly in the nucleus reticularis thalami (RT) of four chronically implanted cats. Patterns of discharge were studied and their relationship to wakefulness (W), slow-wave sleep (SS), and paradoxical sleep (PS) were examined. The firing pattern was analyzed using zero-order (firing rate), first-order (interspike interval histogram), and second-order (joint interval histogram and autocorrelogram histogram) statistics. The SS bursting pattern was investigated taking into account the duration of the intervals between the bursts, the number of spikes per burst, and the duration of the bursts. Zero- and first-order characterizations during W and PS were found to be comparable. However, the joint interval histogram revealed a state-specific pattern during W for 74% of the cells. This pattern was characterized by a nonrandom occurrence of some categories of adjacent intervals. This was not found during PS. Two-thirds of the cells recorded, called “fast” neurons, exhibited firing rates higher than 15 spikes/s during W and PS. Those remaining, called “slow” neurons, showed a mean discharge rate lower than 10 spikes/s. In SS “fast” neurons fired long-duration bursts with interburst intervals generally shorter than 1 s. Conversely, “slow” neurons discharged shortduration bursts interrupted by long interburst intervals (greater than 1 s). Nevertheless, both types of cells had the same number of spikes within the burst and a similar intraburst pattern. Approximately half of the cells studied depicted a “slow rhythm” in the autocorrelogram histogram. Its periodicity was independent of firing rates and behavioral states. Abbreviations: SS-slow-wa.ve sleep, W-waking, PS-paradoxical sleep, RT-nucleus reticularis thalami, EEGLelectroencephalogram, EOG-electrooculogram, EMG-electromyogram. ’ This research was supported by INSERM (ATP 4-74125). The authors wish to express their appreciation to Ms. C. Guidet and Mr. J. R. Teilhac for their valuable technical help. They also thank Drs. N. Weinberger and P. Rinaldi for their helpful assistance and critical comments in preparing the English manuscript. Dr. Barrionuevo is now at the Department of Psychobiology, University of California, Irvine, CA 927 17. Requests for reprints should be addressed to Dr. 0. Benoit, Unite 3 de I’INSERM, 47 Bd de I’HBpital 75634, Paris Cedex 13, France. 486 00 I4-4886/8 l/050486-16$02.00/O Copyright 0 1981 by Academic Press, Inc. All rights of reproduction in any form reserved
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INTRODUCTION Among the hypotheses proposed to explain the synchronization observed in the thalamus during anesthesia or sleep, a possible role was suggested for the reticular thalamic (RT) nucleus. This hypothesis was first suggested by Scheibel and Scheibel (21). As shown by their Golgi studies (20), the majority of RT neurons project back to the thalamus and have many synaptic contacts with the other thalamic nuclei, including the intralaminar thalamic system. This direct backward projection would be very effective in producing inhibition in the other thalamic neurons (22). A major point of the physiologic data supporting the Scheibels’ hypothesis comes from the striking capacity of the cat’s RT neurons to fire in long, sustained bursts separated by long silent pauses correlated with a decrease of vigilance with anesthesia or spontaneously (10, 13, 15, 17, 18, 24, 28, 29). Earlier, Mukhametov et al. ( 17) found that firing rates and interval histograms of RT neuron activity during wakefulness were similar to those occurring in paradoxical sleep. However, such statistical characterizations are all independent of the observed order of intervals in the actual spike train. A higher level of analysis tests for order dependence and characterizes the temporal organization of the discharge. Therefore, the aim of our study was to analyze the spontaneous activity of single RT neurons, using highorder statistics to complement zero-order (firing rate) and first-order (interval histogram) characterizations of the discharge. In addition, an analysis was designed for precise documentation of the slow-wave sleep bursting pattern. METHODS The data reported here are for 23 neurons obtained from four unanesthetized, unparalyzed cats, whose head were held rigidly fixed to the Horsley Clark apparatus by means of a metal frame. The distribution of cells among the four cats was as follows: 7, 6, 5, 5. The animals had been previously aseptically prepared with a stainless-steel cylinder (Trend Wells system) attached to the skull according to stereotaxic coordinates. Six skull screws were used for conventional bipolar electroencephalogram recording. Bipolar measures of electrooculogram (EOG) and neck electromyogram (EMG) were recorded with silver electrodes. Recording sessions began 10 days after surgery. The animals were placed in a sound-attenuated, TV-monitored chamber. A hydraulic microelectrode carrier was fixed to the previously implanted stainless-steel cylinder. Conventional platinum-iridium glass-insulated microelectrodes were used for unit recording. The neuronal action potentials were amplified by an AC coupled amplifier and fed to an oscilloscope, a loudspeaker, and a window
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discriminator. Simultaneously recordings of the EEG, EOG, EMG, and the output of the discriminator were displayed on a polygraph and stored on magnetic tape. Microelectrode tracks were marked by a small electrolytic lesion made by passing a DC current through the tip ( 15 PA for 15 s). On completion of the experiments, the animals were deeply anesthetized with barbiturate and perfused through the carotid artery with a 10% form01 solution. Histologic verification of the electrode placements (Fig, 1) was carried out in serial reconstruction of cresyl violet-stained frozen sections, (40 pm thick). In addition to anatomic localization, the neurons were further localized to the RT by their peculiar long-sustained bursting pattern present during SS sleep. This typical pattern, first described by Negishi et al. (18), was confirmed in a number of other studies (cf. Introduction). Data Analysis Firing Pattern Analysis. Stable states of wakefulness (W), slow-wave sleep (SS), and paradoxical sleep (PS) were defined according to standard polygraphic criteria. Single-unit activity was sampled in each state according to the following criteria: (i) the stability of the polarity and amplitude and (ii) a signal to noise ratio of at least 2:l. The stability of the sampled unit activity was verified by visual inspection and sequential computation of the number of spikes with a resolution of 1 s. Computations were carried out by an Intertechnique multichannel analyzer. All firing pattern analysis was with a PDP-KL-10 with a time resolution
FIG. I. Localization of the 23 cells recorded during slow-wave sleep in stereotaxic (12). Abbreviations: PUL-pulvinar, LP-lateralis posterior, CL-geniculate body, ventralis lateralis, VA-ventralis anterior, NL-reticular thalamic nucleus.
planes VL-
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of 100 ps. Using a program developed in our laboratory (7), the following analyses were made: (i) interspike interval histogram, (ii) joint interval histogram, and (iii) autocorrelogram histogram. The joint interval histogram was displayed as a three-dimensional plot. The x axis represents the duration of Jl, the first of the pair of intervals; the y axis represents the duration of 52, the second of the pair of intervals; and the z axis the probability of occurrence of the pair, JlJ2. Dependence between adjacent intervals was determined from the relationship, P( Jl, 52) = P(J 1) X p(J2), where p(J1, 52) is the actual probability of the pair and P(J1) X p(J2) is the probability of occurrence of the same intervals computed from the interspike interval histogram, i.e., assuming that there is no serial dependence between adjacent intervals ( 19). Burst Pattern Analysis. Among the 20 neurons analyzed for firing pattern during SS, 10 were selected for burst pattern analysis on the basis of the number of bursts (more than 40) emitted during the SS epoch. The analyses of the bursts were carried out with a Wang 600 computer programmed with criteria based upon first-order (interspike interval histogram) and second-order (joint interval histogram) characterizations of the discharge. The criteria for selecting bursts were (i) the sum of the first five intervals was equal to or less than 40 ms, (ii) the burst was preceded by an interspike interval equal to or greater than 100 ms, and (iii) the end of the burst had an intraburst interval greater than 50 ms. Changing these parameters by +20% made no difference in the outcome of the burst pattern analysis. A periburst histogram (7) (computed by a PDP-KL-10) provided a complete and quantitative relationship between the burst and the spike train in its entirety (Fig. 8). Basically, the measure computes the probability per unit time of observing a spike as a function of time before and after the first spike of a burst. The periburst histograms from individual neurons were pooled by using a comparison expected value (Epv) for each cell. This value was derived as described: Epv = f X b X A%, where f = mean firing rate, b = bin width, Nb = number of bursts analyzed. RESULTS During the analysis it became apparent that two groups of neurons could be distinguished on the basis of firing rates and SS bursting pattern. Table 1 provides a summary of the data for the firing pattern of the two groups of cells and will be referred to throughout this section. Firing Rates: “Fast” and “Slow” Neurons. Figure 2 gives the distribution of the firing rates of 20 neurons for SS, 18 for W, and 12 for PS. In W and PS the neurons could be divided into two separate groups in
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Comparison of Firing Pattern between “Fast” and “Slow” Nucleus Reticular Thalami Neurons” Firing rate*
Burst analysis (SS)b
Type cell
W*
ps* (spikes/s)
SS
Fast
22.7 f4
34 f4
19.3 22.7
Slow
7.2 * 0.5
*1
6
a VaheS are means f SD. * Abbreviations: W-waking, preceding burst, IFB-interval iBF-intraburst frequency.
IPB* W)
IFB* (4
BD* (ms)
S/B (spikes)
iBF (spikes/s)
480 * 141
360 f123
198.6 &92
12.3 +2
-62
2424 k 1024
1515 *917
96 +28
14.9 kO.7
2158
PS-paradoxical sleep, SS-slow-wave sleep, IPB-interval following burst, BD-burst duration, S/B-spikes per burst,
* P < 0.05.
terms of firing rate. Most of them (73% in W and 66% in PS) had firing rates higher than 15 spikes/s. Their mean frequency rates ( + SD) were 22.7 + 4 spikes/s for W and 34 + 4 spikes/s for PS. The remaining neu'1. LO 35 30 25 20 15 10 5 0i 25 20 15 10 5 0 25 20 15 10 5 0
W
Nz18
5 10 15 20 25 M 35 40 &5 50 PS
N:lZ
5 10 15 20 25 30 35 LO45
FIG. 2. Distribution of the firing rates (expressed in percentage of the total number of cells) observed in 18 neurons during waking (W), in 20 neurons during slow-wave sleep, (SS), and in 12 neurons during paradoxical sleep (PS).
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rons (27% in W and 34% in PS) had firing rates less than 10 spikes/s (7.2 f 0.5 spikes/s for W and 6 & 1 spike/s for PS). Differences in firing rates in these two groups of neurons, “fast” and “slow,” respectively, within each state were significant (P < 0.05, Mann-Whitney U test) (Table 1). However, no significant differences could be found between the firing rates during W and PS within each group. In SS, neurons were not distinguishable on the basis of rate alone. Their mean firing rate was 19.3 + 2.7 spikes/s (median: 16.8 spikes/s). Sixteen neurons were analyzed in two states (W and SS or SS and PS) and seven in all three stages. Figure 3 shows the changes in firing rates observed as a function of the sleep-waking state. In most cases the firing rate changed according to the state of vigilance, SS being significantly different from W and PS (P < 0.05, Wilcoxon matched pair signed-ranks test). All neurons but one maintained their fast or slow characterization when passing from W to PS. The definition of a neuron as fast or slow depended only on its mean firing rate in W and PS and not on its intraburst firing rate in SS (Table 1). Firing Pattern Analysis in Waking and Paradoxical Sleep. In W and PS the activity of the RT neurons was characterized by a continuous, sustained discharge as shown in Figs. 4 and 5 (Al and B 1 ), and by the unimodal distribution of the interspike interval. Slow and fast neurons differed mainly in the mode of the interspike interval histogram. Joint interval histogram distributions for W are presented in Fig. 4, A2 and B2. The main diagonal, which runs from the front to the rear of the “surface” is of particular interest because identical or nearly identical adjacent in-
FIG. 3. Mean firing rates during waking (W), slow-wave sleep (SS), and paradoxical sleep (I’S) of nine neurons followed in two stages (broken lines) and in seven neurons in three stages (continuous lines).
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A2 % mode.177
82
FIG. 4. Spontaneous discharge pattern of a fast neuron (A) and a slow neuron (B) during waking. Al and Bl-actual spike train (3 s of recording) and interspike interval histograms. A2 and B2-joint interval histograms. The arrows indicate the pairs of adjacent intervals with a highly nonrandom probability of occurrence (see Methods). Time axes of the histograms are on a logarithmic scale. Symbols: x-mean interval, s-standard deviation, W-number of intervals, lrst-first interval, Znd-second interval.
tervals lie along this line. Specifically, adjacent short intervals appear near the front of the surface, and adjacent longer intervals are plotted at successive points toward the rear of the surface. These figures show that fast neurons (short intervals) and slow neurons (long intervals) were found to have similar joint interval histograms, i.e., both were characterized by values grouped around the main diagonal; the peak for fast neurons was closer to the front of the surface (short-short intervals) than the values of peaks for the slow neurons, which were close to the rear (long followed by long). Thus, regardless of the rate of discharge (fast or slow), both groups of neurons were found to have regular discharge patterns during W. Furthermore, an analysis of the joint interval histogram during PS also
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FIG. 5. Spontaneous discharge pattern during paradoxical sleep of a fast (A) and a slow neuron (B). Same neurons as in Fig. 4 (see Fig. 4 for symbols and abbreviations).
revealed regular discharge patterns for each type of neuron (Fig. 5, A2 and B2). Thus, discharge patterns were regular for fast and slow cells during both W and PS. In W a more precise analysis showed that for 14 neurons (74%) there was a strong probability for association between a given interval (frequently in or near the modal value) and another two or three times longer (see arrows in joint interval histograms in Fig. 4, A2 and B2). This probability of association was significantly different from chance (see Methods) (P < 0.01, chi-square test). For other associations of pairs of adjacent intervals in W and for all kinds of pairs in PS a relative serial independence was found. Firing Pattern Analysis in Slow-Wave Sleep. As previously described the firing pattern of RT neurons during SS was discontinuous: the long bursts were separated by very long intervals. The interspike interval histograms (Fig. 6, Al) were asymmetrical with a positive skew. The modal
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N= 737
% mode = 3 6
6
Oms
FIG. 6. Discharge pattern during slow-wave sleep of a fast neuron. Al-the actual spike train shows two long bursts (2.5 s of recording). AZ-the joint interval histogram; two aspects are shown with a 90” shift. a, b, and c-Associations of adjacent short, medium, and long intervals, respectively, of the burst (see test for further explanations). Same symbols as in Fig. 4.
values were between 2.8 and 6.6 ms (median less than 14 ms) and corresponded to the intraburst intervals. There were very few intervals between 60 and 100 ms. The percentage of intervals greater than 1 s was 0.6% for “fast” neurons and 9% for “slow” neurons. Thus, the two groups identified in W and PS were still present in SS. They were more easily distinguished by examination of the intraburst organization or the interburst intervals (Table 1). In the following analysis, “fast” or “slow” neuron denotes fast or slow firing rate in W or in PS. An initial analysis of the SS pattern is given by the joint interval histogram (Fig. 6, Al). The short-, less than 10 ms (37.6%, Fig. 6 A2a), and the medium-range intervals, between 10 and 60 ms (33.4%, Fig. 6, A2b), were regularly dispersed around the diagonal such that each interval was
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followed by the same category of interval. These were the intraburst intervals. The long intervals, greater than 100 ms (Fig. 6, ARC), were very frequently (9 1%) associated with the medium-range intervals, rarely (7.6%) with long intervals, and very rarely (1.4%) with short intervals. Zntraburst Organization. From the study of the interval dependency in the joint interval histogram some common features of the intraburst organization may be deduced. In general, one long interval and one or two medium-range intervals were followed by some short intervals; then, medium intervals of increasing duration occurred, finally followed by one long interval. It appeared as if a firing acceleration (to 400 spikes/s) was followed by a progressive deceleration (to 16 spikes/s). Burst Analysis. During SS, seven fast neurons firing 680 bursts and four slow neurons firing 193 bursts were studied. The durations of the two groups of bursts were significantly different (P < 0.05, Kolmogorov-Smirnov, two-sample test) (Fig. 7 A and B); bursts had a shorter duration in slow neurons (mean 96 f 28 ms; median 90 ms) than in fast neurons (mean 198.6 + 92 ms, median 150 ms). In contrast, the number of spikes within the bursts were very similar: 14.9 f 0.7 spikes/s in slow neurons and 12.3 + 2 spikes/s in fast neurons. Thus, the intraburst firing rates were approximately three times greater in slow neurons than in fast neurons (158 against 62 spikes/s) (Table 1). Distribution of Intervals Preceding and Following the Bursts. Again,
ii = ,986 ms SD = 92ms
FIG. 7. Long and short bursts fired by fast neurons (left) and slow neurons (right) respectively. The actual spike trains are shown on the top (3 s of recording). The histograms of the bursts’ duration were calculated for 680 bursts from seven fast neurons and 193 bursts from four slow neurons.
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when looking at the intervals before and after the bursts, fast and slow neurons behaved differently (Fig. 8). For fast neurons the intervals before and after the bursts were usually shorter than 1 s and the distributions were positively skewed. For intervals preceding bursts (Fig. 8, Al), the median was 400 ms with a mean of 480 f 141 ms. For intervals following bursts, (Fig. 8, A2) the median was 300 ms and the mean 360 f 123 ms. In contrast, for slow neurons, most intervals preceding and following bursts were longer than 1 s. The distribution of intervals preceding bursts (Fig. 8, Bl) was negatively skewed with a mean of 2424 f 152 ms (median, 1500 ms, Fig. 8). The lengths of the intervals following the bursts appeared to be bimodally distributed (Fig. 8, B2) with a short mode (12%) at 118 ms, a long mode (7%) at 4100 ms, and the median at approximately 1 s. This pattern was somewhat influenced by the temporal variability in the spiking at the end of the burst; although typically a few such spikes followed each burst, in some cases it was difficult to ascertain whether they were linked to the burst. The firing probability before or after a burst (periburst histogram, Fig. 8, A3 and B3) confirmed that slow neurons discharged considerably under the comparison expected value (see Methods) for 1 s
Al
A3
FIG. 8. Distribution of the duration of the intervals preceding and following the bursts of fast neurons (A) and slow neurons (B) Al, Bl-histograms of the preceding intervals. A2, BZ-histograms of the following intervals. A3, B3-periburst histograms. The observed probability of firing before or after the first spike of a burst is expressed in percentage of the comparison expected value (EpV) calculated for each cell from the mean rate (see Methods). 0 corresponds to the first spike of the bursts.
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and more. Thus the study of the burst firing pattern in SS confirmed the physiologic heterogeneity of RT neurons: slow and fast neurons observed in W or in PS have different intra- and interburst organization (Table 1). Rhythmicity. Examination of the second-order statistics with the autocorrelogram histogram revealed that approximately half the cells in each state showed rhythmicity (at least three cycles in the sample autocorrelogram histogram) regardless of characteristic fast or slow cell type designation. The incidence of rhythmic cells and mean frequencies for each state were W (8/18) = 2 + 0.6 cycles/s; PS (7/12) = 1.8 f 0.4 cycles/ s; and SS (10/20) = 1.2 -t 0.7 cycles/s. There were no significant differences between states. DISCUSSION Two populations of neurons (“fast” and “slow”) could be readily identified in the RT nucleus during W and PS on the basis of firing rate and interspike interval histogram alone. For SS only a bursting pattern analysis could differentiate fast and slow cells. The view that firing rate and interspike interval histogram analysis do not allow differentiation of the firing pattern between W and PS has been advanced before (17) and is in general agreement with the data reported here. Because such statistical characterizations neglect temporal ordering, we also used joint interval histogram techniques to study the time pattern of the spike trains. The most striking feature that was shown by this technique was a state-specific pattern during W compared with PS. Specifically, in most cells, the joint interval histogram describing W revealed a recurrence of a time interval in or near the modal value followed (and preceded) by one of longer duration, i.e., the location on time of an impulse depended on the time of occurrence of previous impulses; the underlying process differed from a renewal process. At present, the interpretation of this temporal pattern during W, and its relation to physiologic mechanisms, may be somewhat speculative. However, it is permissible to assume that this could be the consequence of inhibitory mechanisms triggered during W and rather inoperational during PS. Relevant to this, perhaps, is the fact that the medial mesencephalic reticular formation which actively maintains waking (16) also inhibits RT neurons (6, 30). The rhythmic activity found in some RT neurons by means of the autocorrelogram histogram is likely to correspond to the “slow rhythm” found in the mesencephalic reticular formation (14). It should not be assumed that RT neurons are pacemaker-like cells for this slow rhythm because there was a considerable difference between the modal interval and the
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periodicity and a lack of variability with the sleep-wakefulness cycle. These rhythms may be related to the activity of the respiratory center, as was suggested for the mesencephalic reticular formation (14). “Fast” and “Slow” Neurons. Fast and slow neurons have not been differentiated previously in the RT nucleus. The population studied by Mukhametov et al. (17) seems to correspond to our fast-type neuron with a mean discharge rate of 35.6 spikes/s during W (range 18 to 72 spikes/s) and 40 spikes/s during PS (range 12 to 80 spikes/s). In SS, they found that the percentage of intervals greater than 1 s is approximately 2%, as in our data. No comparison with Lamarre et al. ( 13) could be made because they did not report firing rates. The rates found by Schlag and Waszak (24) distributed between 0 and 120 spikes/s and thus included slow neurons. The slow neurons recorded in this study are likely to be from the RT because (i) they had the same firing pattern in W and PS as fast neurons, (ii) they exhibited the same dependency among intraburst intervals as shown by the joint interval histogram in SS; and (iii) both slow and fast neurons had at times been recorded from the same electrode tracks within a 200-pm distance. Therefore, the two populations were not segregated in different locations. Histological study of the RT established the heterogeneous character of cell size throughout the RT nucleus. The region from which the recordings for this study were made was shown to be composed mainly of small cells (20). This may account for the predominance of fast cells in our data. The discharges of small neurons were indeed described as faster than those of large neurons (11). This, of course, must remain somewhat speculative until the individual cells recorded are identified. Zntraburst and Znterburst Organization. The general characteristics of the bursting pattern in RT neurons (interburst intervals, spikes per burst, burst duration) as defined by our computer analysis were in agreement with those found by previous investigators (10, 13, 15, 17, 18, 24, 29). Bursting patterns are especially prominent in the thalamic structures. However, the bursts fired by RT neurons differ from those of units recorded in thalamic relay and associative (9) nuclei. RT bursts are characterized by long-lasting, high-frequency discharges in which the number of spikes within bursts is greater than six (18, 24). If we examine the case where the average frequency is the same in both types of bursts, the maximal frequency is at the beginning of the burst (first or second interval) in relay nuclei (3, 27) and in the middle of the burst in the RT (24). The secondorder statistics used in our study dramatically confirm this intraburst organization and allow a more precise categorization. In contrast to W and PS, during SS, zero- and first-order statistics were
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not useful in differentiating fast and slow cells. It was only by the study of burst patterns that the two populations were recognized. Specifically, the neurons of the slow population emitted bursts at a slower rate (slower interburst frequency) than those of the fast population. This was “counterbalanced” by the fact that intraburst frequencies of the slow population cells were two or three times higher than those of fast cells. Nevertheless, with the joint interval histogram both types of cells showed the same pattern of statistical dependence for the intraburst organization. This might suggest a common mechanism of burst production. In many other cortical and thalamic structures (2, 3, 8), fast and slow neurons have been observed in W or PS. These differences were analyzed either according to the size of the cells, or to the change of firing rate throughout the sleep-wakefulness cycle. As far as we know, the slow or fast firing rate characterization in these other structures does not lead to a clearcut prediction concerning the SS pattern as it did in RT neurons. Waszak (28) reported heterogeneity of the neuronal responses to repetitive intralaminar stimulation in the ventral leaf of the RT nucleus. All neurons responded with a depolarization, but in a second group the excitatory postsynaptic potential was followed by large hyperpolarizations. It would be interesting to see if our slow neurons, which exhibit very long interburst intervals and relatively short duration bursts, correspond to the second group of Waszak. If this were so, it would suggest that fast and slow neurons may have different physiologic roles. Burst Mechanism. The mechanism underlying the production of bursting from cells of specific thalamic nuclei was shown to involve a sustained depolarization interrupted by a hyperpolarization (1). Bursts from RT neurons are produced by a similar but longer sustained depolarization (10, 28), probably in combination with some other mechanisms, possibly including the “regenerative mode” discussed by Calvin (4). The latter could explain the sudden acceleration of the discharge in the middle of the burst as described in this study. One of the surprising facts is the capacity of RT cells to fire in bursts from stimulation of a variety of inputs. However, this capacity is related to complex factors. For example, Steriade (25) was able to obtain unitary monosynaptic responses during W, but during EEG synchronization these same cells produced a bursting response to stimulation. Therefore, it is possible to consider that the RT neurons may operate as a “damped oscillator” (5), i.e., due to special properties of the membrane and under certain conditions, the cells fire in burst. Specifically, these conditions are likely to prevail during SS and as a consequence of an increased synchronization of inputs during this period (26). In addition, the likelihood of burst occurrence in RT neurons could be enhanced by the special dendritic pattern described by Scheibel and Scheibel (23).
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REFERENCES I. ANDERSEN, P., AND S. V. ANDERSSON. 1968. Physiological Basis ofthe Alpha Rhythm, p. 235. Appleton-Century-Crofts, New York. 2. BAKER, M. A. 1971. Spontaneous and evoked activity of neurons in the somatosensory thalamus of the waking cat. J. Physiol. (London) 271: 359-379. 3. BENOIT, O., AND C. CHATAIGNIER. 1973. Patterns of spontaneous unitary discharge in thalamic ventrobasal complex during wakefulness and sleep. Exp. Brain Res. 17: 34% 363. 4.
5. 6. 7. 8. 9. 10. Il. 12. 13. 14.
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