 |
INTRODUCTION |
In the past decade, it has become clear that many pattern-generating networks are not fixed, specialized units that only drive one single motor act, but rather dynamic networks of neurons that can be modified and reconfigured to generate different patterns of output (Weimann et al. 1991
). Hormones, neurotransmitters as well as individual neurons have been shown to be able to modify ("rewire") existing networks of neurons or form entirely new networks (Dickinson et al. 1990
; Hooper and Moulins 1989
). Most of these modifications involve the modulation of membrane and synaptic properties of neurons in the network (Hooper and Moulins 1989
). These mechanisms are thought to enable an animal to control different behaviors (or different aspects of a single behavior) using just a small number of neurons.
It is much less clear, however, if and how the modulation of pattern-generating networks occurs in freely behaving animals. A notable exception is, for example, the endoscopic study of the gastric mill cycle in the crab Cancer pagurus, where Heinzel et al. (1993)
showed that pattern-generating neurons switch their patterns of electrical activity during different movements of the gastric mill cycle. The critical difference between preparations and intact animals is, obviously, that in intact animals, the output of pattern-generating networks depends on sensory input (Barnes and Gladden 1985
). Many pattern-generating networks, however, have been studied in the absence of the normal sensory signals (isolated central nervous systems, reduced preparations). This absence of sensory information makes it very difficult to predict the properties of networks of neurons in intact animals from observations made in vitro.
In this paper, we investigate, in freely behaving animals, the modulation of a central pattern generator (CPG) under conditions where the pattern generator is used during two different behaviors, feeding and egg laying. The system used is the feeding rhythm generator of the snail Lymnaea stagnalis; this generator has been shown to be a useful model in the study the modulation of CPGs by neurotransmitters and higher order neurons (Benjamin and Rose 1979
; Benjamin et al. 1979
, 1985
; Yeoman et al. 1994
). Benjamin and colleagues have described extensively the pattern-generating network that drives motor neurons of the feeding apparatus. This feeding pattern generator is composed of three types of interneurons that can be driven by a slow oscillator neuron. The interneurons fire in sequence to produce a four-phase rhythm (protraction, rasp, swallow, and inactive) (Benjamin et al. 1985
) that drives the motor neurons. The feeding pattern-generating network is modulated by identified higher order neurons that are located in the cerebral ganglia (McCrohan 1984
; McCrohan and Audesirk 1987
; Yeoman et al. 1994
). Among these are the serotonergic cerebral giant cells (CGCs), a pair of neurons that is homologous to the metacerebral neurons that are associated with the feeding systems of other gastropods (Granzow and Kater 1977
).
The CGCs make mono- and polysynaptic connections with interneurons of the CPG as well as with motorneurons and muscles of the buccal mass. The time course of the postsynaptic effects that are caused by firing the CGC range from tens of milliseconds to 10 s (Yeoman et al. 1996
). Similar long-lasting effects are seen after application of the transmitter serotonin. In the past, it has been hypothesized that the CGCs have command neuronlike properties (McCrohan 1984
; McCrohan et al. 1987
), but it recently has been shown that electrical activity of the CGCs does not directly cause feeding movements: experiments in freely behaving animals showed that during feeding, the CGCs fire at a specific minimum rate (Yeoman et al. 1994
). Higher rates of firing of the CGCs than this threshold level are thought to set the rate of the feeding cycle.
The buccal system of Lymnaea is especially interesting because it is not just used to collect food, but it also active during a different behavior, egg laying (Goldschmeding et al. 1983
). During the turning and oviposition phases of egg laying (ter Maat et al. 1986
) the animal makes frequent rasping movements with the buccal mass. As opposed to feeding, however, it does not appear to collect food with this activity (Goldschmeding et al. 1983
). During egg laying on a leafy substrate such as lettuce, only the topmost layer of cells is removed, and it is thought to allow for the proper attachment of the egg mass that is about to be deposited. When the animal is made to lay eggs on a starch covered glass plate, the rasping movements remove the starch only from the location where the egg mass is to be deposited (Goldschmeding et al. 1983
). Egg-laying-related rasping also occurs on a completely clean substrate such as glass. When rasping is prevented by lesions of the cerebrobuccal connective, the egg mass is not attached to the substrate properly and frequently ends up on the bottom of the tank (Ferguson et al. 1993
).
The neural control of this egg-laying-related rasping is also different from that of normal feeding. Egg-laying-related rasping is enabled by neural signals from one of the visceral nerves, the intestinal nerve (Ferguson et al. 1993
). When this nerve is cut, egg-laying-related rasping does not occur but feeding is unaffected (Ferguson et al. 1993
). Egg-laying-related rasping is caused, either directly or indirectly, by peptides released from the neuroendocrine cells in the CNS that trigger egg laying, the caudodorsal cells (CDCs). The CDCs express two CDCH genes (Vreugdenhil et al. 1989) and release a number of different peptides to the blood and to the CNS (Li et al. 1994
) during a discharge of electrical spiking activity that occurs ~2 h before egg laying.
As a first step in the analysis of neural changes caused by these CDC peptides in the feeding network, we investigated the firing pattern of the CGC neurons and the timing relationship between and the electrical activity of the CGC neurons and the patterns of buccal rasping movements.
 |
METHODS |
Animals
All experiments were done in vivo using freely behaving pond snails (Lymnaea stagnalis). Adult specimen age 4-6 mo, shell length 25-35 mm, bred under standard laboratory conditions were used in all experiments. The animals were housed in perforated jars placed in a large tank with running fresh water (20°C) and were kept under a 12 h-12 h light-dark cycle and fed a daily ration of lettuce.
Fine-wire recording of CGC cell bodies and cerebro-buccal connectives
Permanently implanted electrodes were used to monitor electrical activity in connectives and cell bodies in freely behaving animals (Parsons et al. 1983
). The procedures were as described by Hermann et al. (1994)
for nerve and connective recordings and by Yeoman et al. (1994)
for cell body recordings. In short, stainless steel wire electrodes (25 µm diam, California Fine Wire) were implanted to record electrical spiking activity. Animals were anaesthetized by injection of 1.5 ml of MgCl2 (50 µl) into the foot. The head-foot was opened dorsally over a length of 3 mm. In the case of cell body recordings, the outer connective tissue layer that overlies the cell bodies was removed carefully. Next, electrodes were inserted into the body cavity through the body wall and the insulation of the end of the fine wire was removed over a length of ~200 µm. The bare end of the wire was bent into a circle. The plane of the circle then was bent again to make an angle of 90° to the rest of the wire and glued into place by means of superglue (Pattex, Nieuwegein, The Netherlands). In the case of nerve and connective recordings, electrodes were inserted into the body cavity through the body wall and positioned around the nerve or connective. The tissue was dried with a jet of air, and the wire was secured with tissue adhesive (cell bodies) or with dental impression material (Reflect, Kerr) in the case of nerves and connectives.
Analysis of behavior
Buccal rasping was analyzed from videotape and frame-by-frame photographs. The buccal movement has been described by Benjamin (Benjamin et al. 1985
) as the sequence protraction, rasp, swallow, and inactive. In intact animals, the swallowing movement is not visible and we thus used the terms "open," "rasp," and "closed." In this study, open and rasp presumably correspond to protraction and retraction, respectively, of the radula. As mentioned earlier, the swallowing movement is not visible in intact animals and is included in the closed phase.
The occurrences of open, rasp, and closed in the buccal system were registered together with the VITC time code (see later text). This ensured that electrical and behavioral activity could be analyzed separately and realigned during later stages of analysis with single-video frame (40 ms) accuracy.
Egg-laying behavior is composed of behaviors that occur in a fixed sequence. They are termed resting, turning, and oviposition (ter Maat et al. 1986
). The durations of these behaviors are, however, variable. The start of resting phase of egg-laying behavior was identified by the start of the discharge of the CDCs, the neuroendocrine cells that trigger egg laying (ter Maat et al. 1986
). The massed low-frequency electrical activity of the CDCs that marks the start of the CDC discharge of spikes of these neurons in most animals can be made visible in the signal recorded from the electrodes implanted on the CGC neurons by filtering the signal (see further). The onset of the turning and oviposition phases of the egg-laying behavior are determined by the overt behavior of the animals as described earlier (ter Maat et al. 1986
). Interval distributions (Figs. 1 and 2) are shown as quantile plots (Systat, Evanston, IL).

View larger version (21K):
[in this window]
[in a new window]
| FIG. 1.
Interval distributions of the open and the rasp phase of the rasping movement. A: quantile plots of the interval distribution of the open in a feeding animal. Graph shows the open times measured (x axis) plotted against the proportion of the data with that value (y axis). Dashed line, linear regressions of the log-survival data points. B: log-survival plot of the data shown in A. A single exponential with no lag-time would have resulted in a log-survival plot that shows a straight line through the origin. Systematic deviations from a straight line indicate that mixture of multiple exponential distributions is present. When the plot is (nearly) horizontal for small values of x, a lag-time is indicated (see Haccou and Meelis 1992 ). C: quantile plots of rasp in a feeding animal. D: log-survival plot of the data shown in C.
|
|

View larger version (20K):
[in this window]
[in a new window]
| FIG. 2.
Difference in interval distributions of the closed phase between feeding (A and B) and egg-laying (C and D) animals. A: quantile plots of the interval distribution of the closed state in a feeding animal. B: log-survival plot of the data in A. C: quantile plots of the closed times in an egg-laying animal. D: log-survival plot of the data shown in C. Interval distributions of the closed times were single exponentials in 5 of 6 egg-laying animals. In feeding animals, the interval distributions were composed of multiple exponentials (see text for details).
|
|
Recording and analysis of electrical signals
Electrical activity recorded with fine-wire electrodes was fed through a WPI DAM-80 differential amplifier and stored on the hifi-track of the video tape used to store the recording of the animals' behavior. A time-code generator (VITC, Alpermann and Velte, Wuppertal, Germany) was used to provide every video frame with a time code to be able to synchronize the behavior stored on videotape with the digitized electrical activity of nerves, connectives or cell bodies. The electrical activity was digitized using a Cambridge Electronic Design model 1401 or 1401Plus, 12-bit A/D converter that was running a special wavecapture protocol (see Jansen and ter Maat 1992
). During digitization, both the waveform activity as well as the matching VITC signal are read from tape.
In ~50% of the preparations we recorded, in addition to the signal from the CGC neurons small amplitude waveforms that occurred in bursts (Fig. 4). These bursts were associated with the animal breathing at the water surface and were not analyzed further. When the electrode signal was filtered to remove all frequencies >38 Hz, the electrical discharge of the CDCs that precedes egg laying could be detected in most of the animals (see Fig. 4B) (ter Maat et al. 1986
). During this discharge, the CDCs fire in near unison, and the electrical signal of the ~100 CDCs firing in concert is large enough to be picked up at the CGC soma site.

View larger version (41K):
[in this window]
[in a new window]
| FIG. 4.
Electrical activity recorded from the soma of a cerebral giant neuron during egg laying in a freely behaving animal. A: slow runout of the electrical activity recorded from the soma of a cerebral giant cell (CGC). Large spikes stand out against the background. Large arrow on the left indicates the starting point of the faster runout shown in B. B: faster runout of A, indicated by the large arrow in A. Filtering of this signal (see METHODS) reveals the onset of the burst discharge of electrical spiking activity of the caudodorsal cells, also located in the in the cerebral ganglion. This burst discharge marks the start of egg laying. C: histogram of the electrical activity of the CGC before, during, and after egg laying. Note that the histogram in C shows a longer piece of the recording than A does.
|
|
Permutation tests
The correlation between CGC spiking and buccal rasping movements was investigated by means of permutation tests. Permutation tests have been used to investigate patterns in spike trains (Dayhoff and Gerstein 1983
), the relation among spike trains (Lindsey et al. 1992
), and behavioral data (Adams and Anthony 1996
). Similar tests are used in randomization tests for single subject experiments (Edgington 1995
; Edgington and Bland 1993
). True randomization tests, however, rely on the random assignment of treatments to time blocks. In this paper, we are investigating spontaneous behavior, and consequently is it impossible to assign randomly treatments to time blocks.
Randomization techniques applied to single subjects are used to calculate the probability that an experimentally found relation is due to chance, by calculating all (or a large number of) the theoretical possibilities. If the percentage of permutations that yields a result equal to the null hypothesis is smaller then a preset level (5%), then the experimentally obtained data are not considered to be the result of chance, and the null hypothesis is rejected. If the number of theoretical possibilities is finite, the permutation test yields an exact P value. Otherwise, it yields an approximation of the real P value with the accuracy of the approximation depending on the number of permutations.
In this paper, the P values calculated for different animals were tested using Fisher's test for combining probabilities from independent tests of significance. This test uses the fact that
2
ln p of n independent P values follows a
2 distribution with 2n df (Fisher 1932
; Sokal and Rohlf 1995
). All the results of permutation tests presented here are based on 10,000 random permutations. The random number generator used is a long period (>2*1018) generator (Press et al. 1992
).
 |
RESULTS |
Egg-laying-related rasping movements are different from feeding movements
Our first aim was to come to a qualitative and quantitative description of the behavioral output of the buccal system during the two behaviors under investigation, feeding and egg laying. Feeding movements of Lymnaea in the past have been described as a four-phase rhythm (protraction, rasp, swallow, and inactive) (Benjamin et al. 1985
). Although it is debatable whether "inactive" can be called a genuine phase of any pattern generator without the definition becoming self-referential, we include this phase in our description of the behavior.
The rasping movements of the buccal mass were scored in such a way that a continuous time-record of behavior was obtained. Of the four phases that were distinguished by Benjamin, swallow happens after the animal's mouth has closed and is, therefore, invisible in intact animals. This movement was consequently not scored separately but is included in the phase closed. The open phase started when the mouth started opening, rasp started when the radula started moving forward, and closed started when the mouth was closed fully again. As is the case with any continuous time record, the onset of one phase of the behavior always ended the previous one, and a normal rasping movement thus consisted of the sequence closed-open-rasp-closed and occasionally of closed-open-closed.
The composition of the feeding movements was measured by determining the lengths of these three phases from videotape, frame by frame (see METHODS). Both the interval distributions of bout lengths and the average lengths of the phases were calculated from these data. The interval distributions are shown as quantile plots (see METHODS). The bout lengths of the phases open and rasp both showed a mixed exponential distribution with a time-lag during feeding as well as during egg laying. Figure 1 shows an example of the distributions of open and rasp in a feeding animal. Although the shape of the distributions of open and rasp intervals were not different during feeding and egg laying, changes in the average lengths of the rasping movement did occur. The average length of the open phases were significantly shorter in feeding animals (0.81 ± 0.04 s; mean ± SD) than in egg-laying animals (1.72 ± 0.24 s, P = 0.005, Fig. 3). In contrast, the average lengths of the rasp phases were not different during feeding and egg laying (1.75 ± 0.2 s vs. 1.42 ± 0.05 s, P = 0.254, Fig. 3). The distribution of the closed bouts was more complicated (Fig. 2). The distribution of the shorter intervals appeared to be a single exponential distribution, but in some animals, the longest intervals showed a marked deviation from this single exponent. To test if the closed distribution contained multiple exponents, we applied Darlings test against a mixture of exponentials (cf. Haccou and Meelis 1992
). The result was significant (P < 0.05) for all feeding animals and one of six egg-laying animals. This shows that in five of six egg-laying animals the closed bouts had a single exponential distribution. This indicates that the likelihood that an egg-laying animal ended a closed bout (by starting a rasping movement) was constant and thus can be considered as one single behavioral process. The closed bouts in feeding animals were composed of a mixture of exponentials. Also, the closed bouts were much shorter during feeding than during egg laying.

View larger version (23K):
[in this window]
[in a new window]
| FIG. 3.
Average lengths of the open and rasp phases of the rasping movement in egg-laying (left) and feeding animals (right). Duration of the open phase was significantly shorter in feeding animals (*).
|
|
This distribution of the bout lengths shows the differences in the time-structure of rasping movement between feeding and egg-laying animals. These data show that the timing of the rasping movement made with the buccal mass during egg laying is different from the rasping movement seen during feeding.
CGC neurons are electrically active during spontaneous egg laying
It has been shown that the differences in firing pattern and frequency between CGCs recorded neurons in freely behaving animals and in isolated central nervous systems are appreciable. In the intact animals, for example, firing rates are 10-fold lower than in the isolated CNS (Yeoman et al. 1994
). To investigate the role that the CGCs play in modulating the buccal system during egg laying, we therefore first needed to establish whether or not the CGCs are active at all during egg laying.
To investigate this, we recorded the electrical spiking activity of the CGCs during normal, spontaneous egg laying in freely behaving animals. All experiments were done using fine-wire electrodes glued onto the connective tissue overlying the soma of one CGC or onto the cerebrobuccal connective. Each of the two CGCs has a large axon in the cerebrobuccal connective that generates a large and easily identifiable signal (Goldschmeding et al. 1981
; Jansen et al. 1996
). The cell bodies of CGC neurons also are identified easily because they are the largest ones on the ventral side of the anterior part of the cerebral ganglion (diameter 100-200 µm).
Figure 4 shows an example of the activity of the CGC during egg laying. The average firing rates of five egg-laying animals are shown in Fig. 5, A and B. Before the onset of egg-laying behavior, the average firing rate of the CGCs was ~8 spikes/min. This low rate of firing is typical of the CGCs recorded in freely behaving animals (see Yeoman et al. 1994
). At the start of the resting phase, no immediate changes in the firing rate of the CGC occurred, but in most animals, the firing rate of the CGCs slowly decreased during the course of 5-10 min. In the example shown, the onset of egg laying was determined by the start of the discharge of the CDCs (see METHODS and Fig. 4B). About 10 min after the start of the resting phase, the average firing rate of the CGC dropped to ~20 spikes/5 min (Fig. 5, A and B). When counted as the total number of spikes that occurred in the 20-min periods just before and after the start of the resting phase, the firing rate of the CGCs rate was significantly lower after the start of the resting phase (square root transformed, t-test, P = 0.027, n = 5).

View larger version (35K):
[in this window]
[in a new window]
| FIG. 5.
Average spiking activity of the CGCs of 5 animals. A: recordings were aligned around the end of the oviposition phase of the egg-laying behavior. Average onset ± SE of each of the 3 phases of egg-laying behavior (resting, turning, and oviposition) are shown. B: spiking of the CGCs around different transition moments in the egg-laying behavior. Spiking activity was counted as the total number of spikes in 20 before and after a transition. Both at start of resting and at the end of oviposition, a significant drop in the electrical activity of the CGCs was seen.
|
|
After the resting phase of egg-laying behavior, the animals enter the turning phase. The firing rate of the CGCs increased again after the onset of the turning phase, and this increase (because the definition of the start of the turning phase) coincided with an increase in the rate rasping movements. The test statistic, however, was marginal (Fig. 5, P = 0.054). Aligning the recordings at the end of Oviposition revealed a decrease in the electrical activity of the CGCs from 11.25 ± 1.64 per minute during turning/oviposition to 1.40 ± 0.60 per minute within minutes after the end of oviposition (P = 0.032). This decrease in CGC activity coincided with the drop in the rate of rasping that occurs at the end of the oviposition phase (ter Maat et al. 1986
). This shows that the CGC neurons are active during the turning phase, when egg-laying-related rasping occurs.
Firing pattern of the CGCs during egg laying is different from that during feeding
On the basis of behavioral experiments, a firing rate of 6.7 action potentials/min has been proposed to be the minimum rate of CGC firing that still allows the feeding pattern generator to work in freely behaving animals (Yeoman et al. 1994
). The current data show that during the last 20 min of the turning/oviposition phases of egg laying, the firing rate of the CGCs was 6.45 spikes/min (129 spikes/20 ± 33.7 min, Fig. 5B). This would be just below the rate needed to enable the feeding rhythm generator to oscillate. Because the animals make frequent rasping movements during this phase of egg-laying behavior, this suggests that alternative mechanisms may play a role. However, because the overall firing rate of a neuron gives no information about its firing pattern, we investigated the firing patterns of the CGCs during feeding and egg laying as well as the patterns of buccal activity during both behaviors.
The timing of the feeding movements of the buccal mass of four animals as well as the egg-laying-related rasping movements of six different animals were quantified frame by frame as described in the preceding text. The presence of the food in the tank gave rise to a fourth category in the behavioral plot of feeding animals. This category, termed "invisible," was used to indicate the time that the animal's mouth was obscured completely by the food (Fig. 6, bottom). Frequently feeding activity was observed during this period, but an accurate assessment of the movements was not possible. In all the analyses, the invisible periods were not used, and in behavioral analyses, bouts that immediately precede or follow an invisible period were not used because their lengths could not be determined accurately.

View larger version (41K):
[in this window]
[in a new window]
| FIG. 6.
Interval- and autocorrelation plots of buccal rasping and CGC spiking during feeding. A: interval histograms of rasping (top) and CGC spiking (bottom) are shown on the left, the autocorrelation histograms on the right top and bottom. B: chart recorder output of CGC spiking (top) and the buccal rasping. Behavioral categories, from top to bottom, are closed, open, rasp, and invisible. Latter is not a part of the rasping movement per se, but is used to indicate the periods that the mouth of the animal is obscured by food.
|
|
The average duration of the feeding period recorded was 7.63 ± 2.5 min, the average number of feeding movements recorded per animal was 78.25 ± 23.5. During egg laying, the spiketrains of the CGCs as well as the animals' behavior were recorded during as much of the turning/oviposition phase as the animal was visible (average duration 36.6 ± 9.61 min). The average number of rasping movements recorded per animal was 109.7 ± 24.1. Electrical activity of the CGCs as well as buccal rasping was characterized by means of interval histograms and autocorrelation histograms (Perkel et al. 1967
). In the case of rasping, the moment of the transition closed-open (the start of the feeding movement) was used to construct the histograms. The results are shown in Figs. 6 and 7.

View larger version (43K):
[in this window]
[in a new window]
| FIG. 7.
Interval- and autocorrelation plots of buccal rasping and CGC spiking during egg laying. A: interval histograms of rasping (top) and CGC spiking (bottom) are shown on the left, the autocorrelation histograms on the right top and bottom. B: chart recorder output of CGC spiking (top) and the buccal rasping (feeding animal). Behavioral categories, from top to bottom, are closed, open, and rasp. Invisible did not occur during egg laying.
|
|
During feeding, the interval histogram of the CGC spikes was double-peaked with an early peak at 0.5 s and a secondary peak at 2-3 s (Fig. 6). In addition, there was a small number of much longer intervals (duration 10-30 s). The mode was 0.25-7.5 s (bin size = 0.25 s), the average mode in the feeding animals was 1.5 s. The average overall firing rate of the CGCs during feeding was 16.7 ± 3.2 spikes/min. The autocorrelation histograms of the CGCs showed a much decreased spiking probability 1-2 s after a spike. This was also visible in the autocorrelation plots of the rasping activity itself.
During egg laying, the interval histogram of the CGCs showed a single, broad peak with the mode close to 10 s (Fig. 7). The average mode in six animals was 7.5 s. The average overall firing rate of was 4.3 ± 0.7 spikes/min. The autocorrelation histograms of the CGCs were characterized by a strong decline in the spiking probability in the first 5-7 s after a spike. This pattern was also visible in the autocorrelation histogram of the rasping activity itself. This shows that the short, 0.25- to 7.5-s intervals in the CGC spiking that are seen in feeding animals do not (or very seldom) occur in egg-laying animals.
There were similar differences between the interval histograms and autocorrelation histograms of feeding and egg laying animals: where the feeding animals show an increased rasping probability during the first few seconds after a rasping movement (Fig. 6), the egg-laying animals show a decreased rasping probability (Fig. 7). These experiments reveal that there are large differences between the rasping behaviors during feeding and during egg laying and between the electrical activity in the CGCs recorded during these periods.
CGC firing is suppressed during the rasp phase of
egg-laying-related rasping movement
Although there obviously is no one-for-one relationship between CGC spikes and rasping movements of the buccal mass in feeding animals (Figs. 6 and 7), Yeoman et al. (1994)
describe that in feeding animals CGC spikes were "phase locked to the feeding movements of the animal" and that no CGC spikes occur during the bite itself. However, no quantitative data are available.
The fact that the autocorrelation histograms of CGC spikes and rasping movements have several features in common suggests that there may be a direct relation between CGC firing and the rasping cycle itself. This relation could be due to direct (synaptic) interactions or due to common input form other sources. Previously, Yeoman et al. (1996)
have shown that the CGCs make monosynaptic connections with neurons in the buccal ganglia, with postsynaptic effects in the buccal neurons ranging from tens of milliseconds to 10 s. We therefore investigated quantitatively whether a relation exists between the firing of the CGCs and the rasping cycle of the buccal system in feeding and egg-laying animals.
First, the relation between feeding movements and CGC firing was investigated by means of cross-correlation histograms. The sequences of CGC spikes were aligned at the onset of a rasping movement (transition closed-open) and the occurrences of CGC spikes around these a transitions were plotted in a raster diagram as well as in a histogram. Figure 8 shows that in both feeding (A and B) and in egg-laying animals (C and D), the onset of a buccal movement coincided with a peak in the spiking activity of the CGCs.

View larger version (35K):
[in this window]
[in a new window]
| FIG. 8.
Cross-correlation plots of buccal rasping and CGC spiking during feeding (A and B) and egg laying (C and D). A: records of CGC spiking in a feeding animal were aligned at the occurrences of the behavioral transition from closed to open. Each CGC spike within the 20 + 20 s window is marked by a vertical line within the horizontal lane that indicates that particular transition. B: individual CGC spikes are added across transitions and are shown in a histogram (bin size = 0.4 s). Transition closed-open coincided with high CGC spiking activity. C: as in A but now for an egg-laying animal. D: histogram of the data shown in D. Although the overall spiking activity is lower than in feeding animals, the transition closed-open also coincided with (relatively) high CGC spiking activity.
|
|
To investigate if these changes in the rates of CGC firing around the onset of a buccal movement were statistically significant, the spiking and rasping data of egg-laying and feeding animals were analyzed further using data permutation tests. If the original sequences of CGC spikes and rasping behavior were unrelated, then the spike count during each of the phases of the rasp movement was due to chance and should not be lower than a random sequence of behaviors (null hypothesis). If, on the other hand, CGC spiking is suppressed during any of the phases of the rasping movement, then this correlation is destroyed by permuting the behavior sequence, and the original count should be lower than that of the permuted run. Thus a large number of permutation runs yields an estimate of the different possible outcomes of random alignment of rasping behavior and CGC spikes. This then is used to calculate an exact P value.
To perform this test, in each individual animal, we first counted the total number of CGC spikes that occurred during each of the three phases closed, open, and rasp. This total count for each of the three phases could be especially low just by chance or be because of the preferential firing during one or more phases of the rasping movement. To distinguish between these possibilities, a permutation test was done. The blocks representing the start and stop times of the different behaviors were shuffled at random (Fig. 9A). This resulted in a behavioral sequence different from the original one, while the sequence of CGC spikes was kept the same. The CGC spikes that occurred during each phase of the new sequence again were counted. This procedure, referred to as a "random" run, was repeated a large number of times (10,000).

View larger version (23K):
[in this window]
[in a new window]
| FIG. 9.
Permutation test of the relation between CGC spikes and the closed, open, and rasp phases of the rasping movement. A: top 2 traces (marked CGC spikes and Original behavior) show the original arrangement of CGC spikes and rasping behavior. CGC spikes that occur during each of the phases are counted. Bottom 2 traces show 2 examples of permuted sequences. B: result of the permutation test for the rasp phase. Almost all of the 10,000 randomly permuted sequences result in a CGC spike count higher than that of the original sequence, indicating that it is unlikely that is was obtained by chance.
|
|
The results are shown in Fig. 9 and Table 1. Figure 9B shows an example of the result of a permutation run. During the rasp movement of this animal, the CGC fired a total of four times. The histogram shows the distribution of the counts of the CGC spikes from the permutation runs. Of the 10,000 permutations, 99.52% had a spike count higher than the experimentally obtained count, 0.14% was lower, and there were 0.34% ties. Thus in this animal, the null hypothesis that the distribution of CGC spikes over the rasp phase of rasping movement was due to chance had to be rejected. The results of the test of the combined probabilities of the different animals (see METHODS) are shown in Table 1. In both feeding and egg-laying animals, there was a significantly decreased spiking probability during the rasp phase of the rasping movement.
The permutation test used in the preceding text gives information about the number of spikes during phases of the behavior in their entirety. It does not give information about parts of a behavior. If, for example, the CGCs would fire preferentially a few seconds before the opening of the mouth, then we would not be able to detect that. As mentioned above, Yeoman et al. (1994)
describe that CGC spikes occur "just before the opening of the mouth" in feeding animals. To investigate this quantitatively in feeding and egg-laying animals, a second permutation test was done.
First, the number of spikes that occur within a given period around a behavioral transition (e.g., 1 s before or 1 s after closed-open) was counted for each individual animal. To that end, this time "window" was aligned at all occurrences of that particular behavioral transition and the number of CGC spikes that occurred within the window was counted. This was done for all the transitions in the record. To answer the question whether the data so obtained represented a rare (statistically significant) event or an event that also could have been obtained by sampling from the data at random moments rather than at behavioral transitions, spikes were counted in exactly the same way as above but now at randomly chosen moments in the recording rather than at behavioral transitions (Fig. 10A). The number of samples within a run was the same as the number behavioral transitions that occurred in the recording: when a recording yielded 150 transitions closed-open, spiking data were collected within the chosen window at 150 randomly chosen moments. Again, these random runs were repeated a large number of times (10,000) and yielded a probability distribution for the parameter in question (the number of CGC spikes within a period before and after a transition). This probability distribution was used to calculate a P value, which was used in Fisher's test for combining probabilities as described above. The null hypothesis was that the CGCs spikes are distributed randomly.

View larger version (24K):
[in this window]
[in a new window]
| FIG. 10.
Permutation test of the relation between CGC spikes and specific parts of the rasping movement. A: top 2 traces show the original arrangement of CGC spikes and rasping behavior. CGC spikes that occur a period that precedes the transition closed-open are counted. Bottom 2 traces show 2 of the 10,000 permuted runs, where the counting periods are arranged at random. B: result for a counting period of 3 s before the transition closed-open. Large majority of the 10,000 permuted runs had a total spike count lower than the original period. This indicates that it is unlikely that that the original count was high by chance.
|
|
We investigated three different lengths of periods: 10, 3, and 0.24 s (6 video frames of 40 ms) before the onset of the open phase of the rasping movement. An example of data obtained from an egg-laying animal is shown in Fig. 10B. The total number of spikes counted in 3-s periods before the closed-open transition was 104. The permutation test yielded the distribution shown. Of the 10,000 permuted runs, 0.54% had a total spike count higher than 104 with 0.23% tied observations. This means that with alpha = 0.05, the experimentally obtained total count of 104 is not likely to be the result of chance. The results of the combined probabilities for the feeding and egg-laying animals are shown in Table 2.
In the feeding animals, there were significantly more spikes before the onset of the feeding movement in all periods investigated than could be expected if they were distributed at random. In egg-laying animals this was true for the 3- and 10-s period but not for the 0.24-s period. These data show that in both feeding and egg-laying animals more CGC occurred 3-10 s before the opening of the mouth then chance predicts and that during the rasp movement, the CGC is silent more than chance predicts. These data suggest that both during feeding and egg laying, the CGCs show the tendency to fire "in phase" with the rasping movement. However, in all of the above it should be noted that the absolute spiking frequencies of the CGCs are very low during both feeding and egg laying and that frequently just one CGC spike precedes a rasping movement (Figs. 6 and 7). Conversely, many CGC spikes are not immediately followed by a rasping movement.
 |
DISCUSSION |
In this paper, we have investigated the activities of the CPG and a pair of associated higher order interneurons (CGCs) during two unrelated behaviors (feeding and egg laying). We have found that there are differences between the motor patterns expressed during the two behaviors. The results show that the CGCs are involved in the modulation of the buccal pattern-generator system during feeding and during egg laying. However, the timing relation between the CGC spikes and the cycle of the buccal CPG changes little, and additional modulating factors are needed to explain the observed differences in motor patterns.
After the onset of the CDC discharge, the firing rate of the CGCs was shown to drop significantly. Interestingly, this phase of egg-laying behavior (resting) is characterized by a lack of rasping activity (ter Maat et al. 1986
). Possibly this low spontaneous firing rate of the CGCs helps to suppress the buccal CPG during the resting phase. During the turning and oviposition phases, CGCs are active, and it is during this phase that the animal shows buccal rasping activity (ter Maat et al. 1986
). This correlation suggests that the activity of the CGCs may be necessary for the expression of the buccal CPG during egg laying. The latter also is borne out by the fact that CGC activity drops off significantly at the end of oviposition.
The neural circuitry in the buccal ganglia of Lymnaea exclusively drives the muscles of the buccal mass and related structures such as the oesophagus. The rasping movement that this circuitry produces has both been described as a four- and a three-phase rhythm. However, in all studies inactive was used to indicate the time the oscillator is inactive between two rasping movements, and there is a consensus that in vitro the movements protraction, retraction, and swallow correspond to the three phases of the CPG rhythm. These three phases also are referred to as N1, N2, and N3. They occur in this sequence and are named after the neurons of the CPG that are active during these phases. In our study, open and rasp presumably correspond to protraction and retraction, respectively, of the radula. As mentioned earlier, the swallowing movement is not visible in intact animals and is included in the closed phase.
The rasping behavior was described as a continuous time record to be able to apply some of the tests for multi-exponentiality such as described for the analysis of continuous Markov chain models (Haccou and Meelis 1992
). The distributions of the duration of all three elements of the rasping movement (open, rasp, and closed) all had a lag-time that was greater than the time-resolution of the measurement. This indicates that all three have a certain minimum duration that probably represents the minimum time the animals needs to make the movement. The duration of both open and rasp followed a distribution that was characterized by multiple exponentials. This indicates that open and rasp are composed of multiple acts that each are distributed exponentially (Haccou and Meelis 1992
). The distributions of closed bouts in egg-laying animals were distributed as a single exponential, which indicates that in these animals, closed can be considered as one single act that has a constant chance of being terminated (by a rasping movement). In all feeding animals, the distribution of the closed bouts contained multiple exponents, and this suggests that, in feeding animals, closed cannot be considered as a single act, but that it is composed of multiple components.
Because the neural organization of the feeding network has only been studied extensively in vitro, we can at this moment only speculate about the nature of the multiple components of rasping movements. The buccal mass is a complex structure, and rasping movements involve the coordinated contraction of the 46 muscles of the buccal mass. The exact composition of individual rasping movements most likely depends on the nature of the substrate and probably involves sensory signals from mechanosensory structures such as mechanosensory neurons found in the buccal system of the related mollusc Aplysia (Miller et al. 1994
).
There were considerable differences between feeding and egg-laying animals in the distributions of the lengths of closed and open. The open phases were on average ~50% shorter in feeding animals, but the shape of the distribution was the same. The closed phases were distributed exponentially in both feeding and egg-laying animals, but there was a large difference in the absolute lengths of the closed phases. The longer open phase seen during egg laying is in line with the observation that electromyograms show an increase in the duration of the contraction of the anterior jugalis muscle of the buccal mass during egg laying (ter Maat, unpublished observations).
The timing of the rasping movement in vitro has been studied by Elliott and Andrew (1991)
. These authors investigated fictive feeding in starved animals that were fed just before the experiment, and they distinguished two different feeding rhythms: spontaneous and slow oscillator (SO) driven. The SO is an unpaired identified neuron, which on depolarization starts the buccal pattern generator (Rose and Benjamin 1981
). These two rhythms were different with regard to the sources of the variability of the relative timing of the generated rhythm. In the spontaneous rhythm, the N3 phase (swallow) was the only variable phase, whereas in the SO-driven rhythm, both the N1 phase (protraction) and N3 were variable. In all cases, the N2 phase (rasp) was relatively fixed. The open phase most likely corresponds with the protraction movement of the radula, which is driven by the N1 neurons of the CPG. Because the length of the open phase was increased by ~50% during egg laying, it is possible that this is caused by circulating or locally released CDC peptides. These N1 neurons have bursting properties, and it is tempting to speculate that the longer open phase seen during egg laying is caused by CDC-peptides changing the bursting properties of these N1 neurons.
In the isolated CNS, the buccal pattern generator is modulated by different interneurons. Activation of the cerebral ventral 1 cells triggers the buccal motor program (McCrohan 1984
; McCrohan and Kyriakides 1989
), but also the unpaired buccal SO neuron can trigger the motor program (Rose and Benjamin 1981
). Firing the CGCs at very high rates also can trigger the motor program, but these rates have never been seen in the intact animal (Yeoman et al. 1994
; this study). Instead, the CGCs now are thought to play a modulatory role: firing rates >6.7/min enable the feeding motor program, and rates between 6.7 and 20/min influence the rate of the motor program cycle (Yeoman et al. 1994
).
During the turning phase of egg laying, the rate of firing of the CGCs was below (4.3/min) the frequency that enables the buccal pattern generator. Because the animals make frequent rasping movements during this behavior, this suggests that the buccal pattern generator receives additional input from an alternate source. Two earlier findings suggest that sensory input from the female tract may provide, directly or indirectly, this alternate source of input. First, the length of the phase of egg-laying behavior during which rasping occurs is correlated highly with the size of the egg mass (ter Maat et al. 1986
). Second, one of the visceral nerves that innervates the female tract (the intestinal nerve) is necessary and sufficient for the buccal rasping (but not feeding itself) to occur during egg laying. Furthermore, recordings from the intestinal nerve in freely behaving animals have shown electrical activity correlated with rasping activity (Jansen and ter Maat, unpublished data). An alternate additional source of excitation of the buccal pattern generator could be peptides from the CDCH gene (which also encodes for the ovulation hormone itself). Van Minnen et al. (1988)
have shown that neurons that stain positive with a monoclonal anti-CDCH antibody are found in the buccal ganglia. This shows that the CDCH-1 gene is expressed in neurons in the buccal ganglia and suggests that local release of peptides encoded on this gene may play a role in the modulation of the buccal pattern generator during egg laying.
The autocorrelation data of the rasping activity and the electrical activity of the CGCs show that there is an intimate involvement of the CGCs with both feeding-related and egg-laying-related rasping activity. The period during which there is a decreased likelihood that either a rasping event or a CGC spike occurs before or after the current event increases for both events during egg laying. This suggests that the timing relationship between CGC spikes and the CPG activity does not change as the animal switches from feeding to egg laying. The timing relationship between CGC spikes and buccal rasping was investigated more closely in the permutation tests. These cross-correlation tests show that this relationship is essentially identical during feeding and egg laying. During both behaviors, there was a reduced probability of the CGC spiking during the rasp movement and an increased probability of spiking 3-10 s before a rasping movement. The main differences between feeding and egg-laying-related rasping, therefore, are the rate at which the CGC neurons fire, the rate at which rasping movements occur, and the length of the open phase of the rasping movement.
The permutation tests used in this paper are particularly useful when investigating the relation between spontaneous behavior and ongoing spiking activity. In these cases, it is difficult and often impossible to define a set of suitable control circumstances. In the case of spontaneous feeding, for example, nonfeeding animals are not a good control if one's aim is to investigate the relation between CGC spikes and buccal movements. Therefore, permutation tests have been used to investigate whether the correlation between event trains is likely to be the result of chance (Adams and Anthony 1996
; Dayhoff and Gerstein 1983
; Lindsey et al. 1992
). Translating the effects measured in individual tests to effects at the population level was done by using a statistical method (Fishers test for multiple independent P values) from the field of meta-analysis (Hedges and Olkin 1985
).