Department of Biology, National Science Foundation Center for Biological Timing, University of Virginia, Charlottesville, Virginia 22903-2477
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ABSTRACT |
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Friesen, W. O. and C. G. Hocker. Functional Analyses of the Leech Swim Oscillator. J. Neurophysiol. 86: 824-835, 2001. The oscillations that underlie swimming movements in the leech arise from a series of identified concatenated circuits within the ventral nerve cord. In the intact nerve cord, ascending and descending intersegmental interactions via axons within the lateral connectives function both to generate robust oscillations throughout the cord and to establish an anterior-to-posterior phase delay among segmental oscillators. We addressed two questions about this system. First, do the intrasegmental swim circuits in each ganglion function as a single oscillator or do they comprise a pair of coupled oscillators? Second, what are the relative strengths of the ascending and descending intersegmental interactions between the segmental oscillators? Experiments were carried out on semi-intact leeches (Hirudo medicinalis) and on isolated leech nerve cords in which "Z-cut" ganglia were generated by cutting one lateral connective nerve anterior and the contralateral connective nerve posterior to the target ganglion. In these Z-cut ganglia, all rhythmic ascending intersegmental input is conveyed via one lateral connective while rhythmic descending input is conveyed via the contralateral connective. We found that rhythmic bursting recorded from the left and right sides of Z-cut ganglia had identical cycle periods with no phase difference, despite strong intersegmental inputs with differing periods from the two swimming ends of the preparations. We conclude that the swim circuits within individual leech ganglia act as single units. Moreover, we determined through correlation and Fourier spectral analyses, that the functional strengths of ascending and descending intersegmental inputs to Z-cut ganglia located in the middle of the nerve cord are approximately equal.
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INTRODUCTION |
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A fundamental question
concerning the nature of the neuronal circuits that generate rhythmic
movement, namely whether such circuits lie within the CNS or whether
they are critically dependent on phasic sensory information, was
already clearly defined at the beginning of the 20th century. Although
caveats concerning the importance of sensory feedback for shaping fully
expressed movement rhythms are appropriate (Pearson and Ramirez
1990; Pearson et al. 1983
), the overwhelming
evidence demonstrates that CNS circuits generate the oscillations at
the center of all rhythmic animal movements (Delcomyn
1980
). For animals in which rhythmic movements involve several
appendages or the entire body, such as swimmeret movement of
crustaceans or swim undulations of elongated animals (for example
lamprey, Xenopus, and leech), a further refinement of the
initial research problem is to determine the specific locus of the
oscillator circuit. That is, do individual segments in these
vertebrates and invertebrates have independent functional circuits or
is the rhythm-generating system distributed along the neuroaxis? The
answer is that individual segments of the spinal cord in crayfish and
leeches (Hocker et al. 2000
; Murchison et al.
1993
) and a few segments in lamprey have such capability
(Buchanan and Grillner 1987
). Another question is
whether there are two bilateral oscillators or a single one within each ganglion.
Our initial identification of the swim oscillator circuits in the leech
revealed primarily interactions within hemiganglia; except for
electrotonic coupling between homologue pairs, only the inhibitory
connection of cells 123 and 27 crossed the ganglion midline
(Friesen et al. 1978). Given this circuit morphology, it
was natural to view the fundamental swim oscillator as consisting of
bilateral circuits whose output maintained synchrony via the electrical
interactions. Further research led to identification of a midline
neuron, cell 208 (Weeks 1982
), and its strong chemical and electronic coupling to a bilateral pair of INs, cell 60 (Friesen 1985
). More recently, additional connections
between the two sides of segmental ganglia that are mediated by the
inhibitory motor neurons (MNs) have come to light (Friesen
1989a
,b
). Given these crossed connections, it seems quite
likely that each ganglion contains only one oscillator; that is, left
and right sides of the ganglion may not be able to generate
oscillations independently. If the circuit in each ganglion indeed
functions as a unitary oscillator, we are justified in collapsing the
swim circuit diagram of Fig.
1A into the form shown in Fig.
1B, wherein laterality of cells and interactions is lost.
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The circuit schematics shown in Fig. 1, together with the finding that
individual segments generate at least the rudiments of swimming
activity (Brodfuehrer et al. 1995;
Hashemzadeh-Gargari and Friesen 1989
; Hocker et
al. 2000
) leads to a model in which the leech swim system is a
chain of coupled oscillators (Fig. 2A). In this model, each
ganglion comprises two coupled unit oscillators. These oscillators are
coupled to many others along the nerve cord not merely to nearest
neighbors (Fig. 1C). The experiments we describe here were
designed to test and explore the functional strength of interactions
between the oscillatory neurons within ganglia. Specifically, we
addressed the question "are the neuronal interactions between the two
sides (Figs. 1A and 2A) of leech ganglia
sufficiently strong to force left and right sides to function as a
unit?" Alternatively, are these crossed connections functionally weak
enough to permit the two sides to oscillate independently? Our
experimental approach was to subject the two sides of a midbody ganglion to differing rhythmic inputs, with one side driven by the
anterior nerve cord and the other by the posterior end (Fig. 2B). We also investigated the functional strengths of
intersegmental coupling to determine whether ascending or descending
intersegmental connections are dominant. Our results demonstrate that
oscillator circuits within individual ganglia act as a unit and that
ascending and descending intersegmental interactions between these
oscillators are of approximately equal strengths.
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METHODS |
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Preparations
Medicinal leeches, Hirudo medicinalis, were obtained from Leeches USA (New York) and were maintained in aquaria at about 20°C.
The leech CNS comprises head and tail ganglia linked by a chain of 21 serially homologous segmental ganglia. Large, paired nerve cord
connectives are conduits for the axons of oscillatory intersegmental
interneurons (INs). In addition, Faivre's nerve, a small median nerve,
carries, the axons of swim gating neurons. The nomenclature for
identifying the ganglia and their associated peripheral nerves was
devised by Kristan and coworkers (1974) and modified by
O'Gara and Friesen (1995)
. The number "M1"
is assigned to the first segmental (noncephalic) ganglion of the ventral nerve cord. The large, most caudal ganglion, also known as the
tail ganglion, is designated by "T." The remaining ganglia of the
nerve cord are numbered consecutively, in a rostrocaudal direction,
ganglia M2 through M21.
Dissections were performed as described earlier (Mangan et al.
1994), with the animals immersed in, and hence
anesthetized by, cold physiological saline containing (in mmol/l) 115 NaCl, 4 KCl, 1.8 CaCl2, 2 MgCl2, and 10 HEPES buffer, pH 7.4 (Friesen 1981
). Following dissection, the preparation
was pinned to the bottom of a glass dish to permit cell visualization
by dark-field illumination. Preparations were perfused with saline at a
rate of 1-2 ml/min. If preparations did not generate swimming activity in normal saline, we added serotonin (50 µM) to the saline to enhance
swim expression. [Recordings from preparations exposed to serotonin
are qualitatively identical to those when only saline is used
(Willard 1981
).] Additionally, for several preparations we perfused with saline containing elevated concentrations of divalent
ions to reduce spontaneous neuronal activity: composition (in mmol/l)
91 NaCl, 4 KCl, 10 CaCl2, 10 MgCl2, and 10 HEPES buffer, pH 7.4.
We performed experiments on two types of Hirudo
preparations. One consisted of the isolated ventral nerve cord, with
the maximum length extending from midbody ganglion 2 (M2) to the tail
ganglion (T). Because of the disruption of IN interactions in Z-cut
preparations (see following text), it was often difficult to obtain
strong swimming in both ends of the isolated nerve cord. To obtain the strong, prolonged swimming activity required for detailed quantitative analyses, we employed another type of preparation: semi-intact leeches
(Kristan et al. 1974), in which sensory feedback from the body wall increases the robustness of swimming activity.
Semi-intact preparations consisted of nearly intact anterior and
posterior ends of the leech, with head ganglia, M1, M20, M21, and tail
ganglia either removed or disconnected from the body wall. We removed the body wall in the middle of the animal to expose five nerve-cord ganglia for extracellular recording (diagram, Fig. 4A). To
generate a Z-cut ganglion in either preparation, we cut two of the
lateral intersegmental connectives: one cut severed the left
intersegmental connective adjacent to one end of the designated Z-cut
ganglion; the other severed the right lateral intersegmental connective at the other end (Fig. 2C). In most preparations, Faivre's
nerve remained intact following the procedure to cut lateral
connectives. The presence or absence of Faivre's nerve alters the
excitability of the preparation but has at most only very weak effects
on intersegmental coordination (Hocker et al. 2000
;
Weeks 1981
). We found that swimming activity in the two
ends of a Z-cut preparation often have differing cycle periods, with
the posterior ends exhibiting the shorter period. In some preparations,
we enhanced or reversed these period disparities by partitioning the
recording chamber and perfusing the two ends of the nerve cord with
salines at different temperatures (Pearce and Friesen
1985a
). The results presented in the following text are based
on 23 Z-cut preparations. In 13 of these preparations, we obtained
bilateral recordings from the Z-cut ganglia, in the remainder the
recordings were unilateral; the data from 10 (of the 23) preparations
were subjected to quantitative analyses.
Electrophysiological recordings
The neuronal oscillations underlying swimming movements are
detectable as MN impulse bursts in extracellular recordings from peripheral nerves. The most useful recording site is the dorsal posterior (DP) nerve, which exhibits bursts from a single large axon,
that of the dorsal excitatory MN (cell DE-3). In each segment, the
median impulse of DP nerve bursts provides a convenient phase reference
point for swim oscillations (Kristan et al. 1974). Motor neuron output is a reliable indicator of the period and phase of
individual segmental oscillators (Friesen et al. 1978
;
Poon et al. 1978
).
For intracellular recordings, MNs were identified on the basis of their
positions within the ganglion, inherent electrical properties and
activity, and synaptic connections with other MNs. Glass capillary
microelectrodes were filled with 3 M potassium chloride; electrode
resistances ranged from 20 to 40 M. Neuronal signals were visualized
on an oscilloscope (Tektronix 5111), and recorded with an FM tape
recorder (Vetter Model A) or a PCM recorder (Vetter 3000).
Transcription from tape to paper was via a penwriter (Gould 2400).
Data analyses
Extracellular records were digitized at a sampling rate of 1 or
5 kHz per channel using a DAS-8 (Metrabyte) A/D converter. Digitized
records were sampled for the occurrence of cell DE-3 impulses with a
simple threshold routine and converted to files listing the temporal
occurrence of each impulse. These temporal files were then converted to
instantaneous frequency by calculating the interspike intervals, at
10-ms intervals. We performed linear unbiased autocorrelations and
cross-correlations on the frequency files to find the period of the
bursting and examine phase relationships. We used discrete Fourier
analyses to calculate the power spectrum of the frequency data. Some of
the analyses were carried out with the rhythm analysis system [RAS, a
MatLab (MathWorks) version of our LAS analysis system] (Friesen
1989a) to digitize extracellular records, to detect nerve
impulses, and to compute cycle periods. Numerical values in the text
are given as means ± SE.
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RESULTS |
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Our conceptual model for the system of neuronal circuits that
control swimming movements in the leech (Fig. 2A) rests on
the fact that swim-related INs have extensive interactions both within and between segmental ganglia. This model requires that some of the
interneuronal interactions within ganglia cross the midline but that
intersegmental interactions are uncrossed. Previous experiments (Friesen 1989c) demonstrated that there are numerous
intrasegmental interactions between contralateral INs; hence the first
requirement is met (Fig. 1A). We show in the following text
that the second requirement also is met.
Oscillator INs do not cross the midline
Except for cell 208, the soma of oscillatory INs lie within one of
the lateral packets of nerve cord ganglia. Neurites from these INs
either lie ipsilateral to the soma and give rise to an axon in the
ipsilateral intersegmental connective nerve (e.g., cell 33)
(Friesen et al. 1978) or cross the midline within
ganglia to give rise to an axon contralateral to the cell body (e.g., cell 115) (Friesen 1989b
). We tested whether the axons
of the oscillatory INs cross the midline in a series of experiments in which we cut one lateral connective and the median Faivre's nerve anterior to a nerve cord ganglion and the contralateral connective and
Faivre's nerve posterior to that ganglion, generating a Z-cut preparation (Fig. 3). We then positioned
a stimulating suction electrode, which stimulated axons in all three
connectives, and recorded activity in all three via a suction electrode
at several positions along this preparation. First, we positioned the
stimulating electrode between the ganglion and the lesion and recorded
impulse activity at the end of the nerve cord. With this configuration, we recorded a barrage of impulses with a short and constant latency, as
well as individual delayed impulses with no fixed latency (Fig. 3A). The short-latency impulses are those conveyed by the
uninterrupted axons of one lateral nerve cord. Next we relocated the
stimulating electrode to the end of the nerve cord beyond the lesion
(Fig. 3B). Now, although all three connectives were again
stimulated, the right lesion interrupted impulses traveling through one
lateral connective and Faivre's nerve. At the same time the second
lesion, to the left of the ganglion, interrupted all impulses in the
contralateral connective. Because no constant-latency impulses appear
at the recording electrode with this configuration, it is clear that no
axons cross from one side to the other between the two lesioned sites.
More specifically, no intersegmental axons cross within ganglion M11.
Finally, as a control, we relocated the recording electrode to a point
right of the anterior lesion, between the right lesion and the ganglion
(Fig. 3C). Once again, we detected a constant-latency volley
of impulses after each stimulus, demonstrating that both lateral
connectives were undamaged and capable of conveying impulses.
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We performed similar experiments with both long and short chains of ganglia between the lesions and in preparations bathed either in normal saline or in saline with elevated divalent cations. In all experiments, the double lesions interrupted short-latency impulse traffic between the ends of the nerve cord. We conclude that intersegmental axons of INs within the lateral connectives do not cross the midline to continue in the contralateral connective nerve. Thus any interactions between the two ends of a Z-cut preparation (as modeled in Fig. 2B) must be via chemical or electronic synaptic interactions within the Z-cut ganglion.
Leech midbody ganglia comprise a single swim oscillator
When intact, the full-length isolated nerve cord acts as a unitary
oscillator for swimming, with left-right symmetry and with motor output
that is phase-delayed along the nerve cord. Although there exists some
variation in the intersegmental phase lags, segmental swim circuits in
the intact cord express the same period of MN activity (Fig.
4A). Because of bilateral
symmetry in the oscillator circuits (Fig. 1A), the left and
right intersegmental connectives carry identical information. However,
the oscillator circuits are not functionally identical in all parts of
the nerve cord. Instead, cycle periods generated by anterior ganglia in isolated nerve cords are usually longer than those generated by more
posterior ganglia (Pearce and Friesen 1985a,b
). Our
approach for testing the hypothesis that individual ganglia comprise a unit swim oscillator was to subject the left and right sides of segmental ganglia to rhythmic inputs with differing cycle periods either in isolated nerve cord or in semi-intact preparations. In either
case, our preparations consisted of long chains of ganglia with a
lateral connective cut on one side of a targeted "Z-cut" ganglion
and the contralateral connective cut on the other side (Fig.
2C). The Z-cut ganglion thus receives unilateral input from rostral ganglia on one side and unilateral input from caudal ganglia on
the contralateral side. Because of the nonuniformity of cycle periods
in the nerve cord, the cycle period of ascending inputs to Z-cut
ganglia was usually longer than the descending ones. (It is important
to note that the cuts to the lateral connectives allow descending axons
in the intact anterior connective nerve and ascending INs from the
contralateral posterior nerve cord to impinge without diminution onto
neurons of the Z-cut ganglion.)
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BURSTING IN Z-CUT PREPARATIONS IS NOT PHASE-LOCKED. The physiological consequences of the Z-cut procedure are illustrated in Fig. 4. In the control preparation, prior to lesioning, the entire preparation generates a unified swimming pattern with a single cycle period (0.64 ± 0.02 s) as shown in the extracellular records (Fig. 4A) and observed in movements of the innervated ends. When the two cuts are made (Fig. 4B), the unity of the system is disrupted. Now the phase-locked swimming rhythm that existed before the lesions were imposed is divided into two rhythms. The cycle period in the anterior nerve cord as measured in DP(R,7) bursts is 1.24 ± 0.07 s, whereas the period of the swim oscillations in the posterior end of the cord, recorded from DP(L,9), is 0.69 ± 0.04 s (Fig. 4B). The coupling between anterior and posterior ends of the cord, via synaptic interactions within Z-cut ganglion M8, is too weak to phase-lock oscillations with the two very different periods.
Neuronal oscillations within the Z-cut ganglion result from the summed actions of its intrinsic (relatively weak) oscillator circuit and the relatively strong rhythmic inputs from the two ends of the nerve cord. Consequently, the MN activity in the Z-cut ganglion reflects both the long-period oscillations of the anterior nerve cord sector, the shorter period bursting in the posterior end of the preparation, and the intrinsic rhythmicity of the Z-cut ganglion. Thus it is useful to view the Z-cut preparation as comprising three oscillators: one in each end of the preparation and a third within the Z-cut ganglion. Quantitative analyses of such oscillations in a long swim episode are described in the following text.LEFT/RIGHT RECORDINGS FROM Z-CUT GANGLIA SHOW SYNCHRONOUS BURSTS. To determine whether the differing periods of two ends of the nerve cord can drive the left and right sides of the Z-cut ganglion at two frequencies, we recorded MN activity on both sides of Z-cut ganglia. In the sample swim episode illustrated (Fig. 5A), the differences in cycle period between the two ends of the preparation were small (anterior, 0.81 ± 0.02 s; posterior, 0.72 ± 0.03 s), and hence the phase relationship between the oscillations in the anterior and posterior ends changed gradually. These phase changes cause variations in the intensity of bursts (impulse frequency) recorded from the Z-cut ganglion [DP(R,10) and DP(L,10)]. These bursts are strong at the beginning and end of the record but weak in the middle as the phase of the posterior ganglia first lags, then leads, and finally again lags that of the anterior one. Despite these changing phase relationships between the two ends of the preparation, the two DP records from M10 were synchronous throughout the episode.
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BURSTING IN Z-CUT GANGLIA IS MODULATED BY ACTIVITY IN THE ANTERIOR AND POSTERIOR NERVE CORDS. The bursting activity in Z-cut ganglia results from the mixing of rhythmic drives from anterior and posterior sectors of the nerve cord. Perhaps not surprisingly, when the periods of these two inputs differ slightly beating is observed (isolated CNS preparation, Fig. 6A; anterior period, 0.69 ± 0.01 s, posterior period, 0.76 ± 0.02 s). Figure 6A illustrates clearly this beating phenomenon as the waxing and waning in the intensity of the impulse bursts in the DP recordings obtained from the Z-cut ganglion (M10). At the beginning of the illustrated swim episode, posterior bursts follow the anterior ones with a nearly appropriate phase lag, leading to strong constructive interference during the first three bursts. As the swim bursts in the posterior ends become more phase delayed because of their longer cycle period, destructive interference causes the successive weakening and finally cessation of bursting in the Z-cut ganglion (similar to data shown in Fig. 5). Near the end of this episode, the phase relationship between the anterior and posterior oscillators once more has the appropriate delay and strong bursting resumes in the Z-cut ganglion. Please note that when strong bursts occur in the Z-cut ganglion, the phase of this activity is between that of the anterior oscillators, strongly implying that activity in the Z-cut ganglion is the normal "swim-like" bursting of the system rather than simply activity driven by intersegmental input. Also note that bursts on the two sides of the Z-cut ganglion are synchronized; the two sides do not independently follow activity in the anterior and posterior chains. Thus similar phase-locked beating rhythms occur in isolated CNS and semi-intact Z-cut preparations.
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BURSTING IN Z-CUT GANGLIA DEPENDS ON THE LENGTHS OF THE ANTERIOR AND POSTERIOR SECTORS. In the preparation illustrated in Fig. 6A, there are eight midbody ganglia anterior to the Z-cut ganglion and 11 at the posterior end. Thus two nearly equal long chains of oscillators are imparting their input to the Z-cut ganglion. We examined the effects of changing the inputs to the Z-cut ganglion by progressively shortening the anterior chain of ganglia both to reduce the robustness of swimming in the anterior oscillator and to decrease the number of INs interacting with M10. The consequence was that the cycle period of the anterior oscillator increased until, with only two ganglia in the chain, the cycle period of the anterior chain nearly doubled (anterior period, 1.43 ± 0.12 s, Fig. 6B). With swim activity in the anterior cord thus weakened, activity in the two ends of the cords assumed a 1-to-2 relative coordination during most of the episode (posterior period, 0.76 ± 0.05 s). Bursts in the Z-cut ganglion were phase-locked to activity in the posterior cord and much more regular than when anterior and posterior chains were of equal lengths (cf. Fig. 6, A and B). Nevertheless, these bursts were strongest during alternate posterior bursts [in DP(R,15)] when these bursts were preceded by ones in the anterior sector of the preparation [in DP(L,9)]. Thus the posterior chain comprising 11 midbody ganglia clearly had a much greater influence on bursting in the Z-cut ganglion than the two-ganglion anterior chain.
PHASE RELATIONSHIP BETWEEN LEFT AND RIGHT SIDES OF Z-CUT GANGLIA. We digitized records from the preparation used in Fig. 6 to examine the phase relationship between bursting on the two sides of Z-cut ganglia. We found that MN activities on the two sides of Z-cut ganglia are always very nearly in phase, at 0°. As illustrated in Fig. 7, there are small differences in the characteristics of bursts on the two sides. Often the two sides will undergo small modulations in burst duration and frequency, which reflect their differing inputs from the anterior and posterior nerve cord. Such small differences can be seen in Fig. 7A, 2 and 4. In addition, the phase relationships between the two sides sometimes reveal small deviations from 0°. These deviations are not greater than the normal variance in ganglia that have not been Z-cut. We observed no large fluctuations in phase that would be present if there were two oscillators were cycling at differing periods (Fig. 7B1) in the Z-cut ganglia.
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MEMBRANE POTENTIAL OSCILLATIONS IN Z-CUT GANGLIA ARE SYNCHRONOUS. To investigate whether synchronous activity recorded from excitatory MN on the two sides of Z-cut ganglion accurately reflects that of deeper levels, we penetrated dorsal inhibitor cells (DI-1) on both sides of a Z-cut ganglion. We found that just as at the level of excitatory MNs, bilateral inhibitor homologs remained phase-locked when the subjected to inputs of differing periods from the anterior (period, 1.11 ± 0.7 s) and posterior (period, 0.94 ± 0.08 s) ganglion chains (Fig. 8). We conclude that also at the level of the inhibitory MNs, which participate in generating the swim rhythm, Z-cut ganglia comprise a unitary oscillator.
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Relative strengths of ascending and descending input to the Z-cut ganglion
PROLONGED SWIM EPISODE FOR QUANTITATIVE ANALYSES.
With the unity of segmental swim oscillators established, we were
interested in assessing the relative strengths of ascending and
descending interactions among the segmental swim circuits. We know that
intersegmental interactions play a critical role in generating not only
the progressive phase delays of bursting along the nerve cord but also
in generating the cord-wide rhythm itself. Our recent findings (Hocker
et al. 2000) demonstrate that there is a greater heterogeneity in the
ability of nerve cord ganglia to generate stable swim-like oscillations
than we had previously understood. In fact, only ganglia in the middle
of the nerve cord are individually capable of generating stable, constant-period oscillations. Oscillations generated by the anterior ganglia are weak and irregular; ganglia posterior to ganglion M13
appear incapable of individually generating any swim-like oscillations
without sensory feedback from the body wall. To evaluate the functional
strength of ascending and descending intersegmental interactions
between ganglia, we again employed Z-cut preparations. We describe here
in some detail the quantitative analyses of one particularly prolonged
swim episode. Similar analyses were performed on nine other
preparations that exhibited briefer swim episodes.
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CONVERSION OF INTER-SPIKE-INTERVALS TO INSTANTANEOUS FREQUENCIES.
We digitized the swim records in Z-cut ganglia using an a/d converter
(Metrabyte DAS 8 and LAS and RAS software) (Friesen 1989a; Hocker, unpublished data) and then analyzed those
temporal files to detect the occurrence of cell 3 impulses with a
simple threshold algorithm. Further data reduction included the
conversion of the temporal data into instantaneous frequency by taking
the reciprocals of the inter-impulse intervals and plotting the
resulting values at 10-ms intervals. This conversion generates graphs
in which the impulse bursts of extracellular recordings are represented as bouts of high-frequency activity with low-frequency interburst intervals (Fig. 10).
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CORRELATION ANALYSIS.
To determine the average period of the impulse bursts in the prolonged
swim episodes, we performed autocorrelation analyses on records of the
instantaneous impulse frequencies. The correlation graph for the
anterior sector has large, symmetrical peaks that repeat with at
multiples of a 1.37 s time lag (Fig.
11, top). Thus the cycle
period in the anterior cord is long and constant. The corresponding
cycle frequency is 0.73 Hz. Similarly, the correlation diagram for the
posterior sector (Fig. 11, bottom) exhibits repeated peaks
at multiples of 0.85 s (corresponding to 1.18 Hz). The lower amplitude of these peaks, together with their decreasing amplitude at
greater time lags, indicates that the swim oscillations in this sector
are less constant than in the anterior sector of the preparation. The
occurrence of peaks at both 1.53 and 0.96 s time lags in the
autocorrelation graph for the Z-cut ganglion (Fig. 11,
middle) is most interesting. These peaks occur at period
values corresponding closely to those in the anterior and posterior
sectors. Although both anterior and posterior sectors of the nerve cord strongly influence the oscillations in the Z-cut ganglion, the effect
of the anterior sector, which gives rise to the larger peak (at
1.53 s), is clearly stronger. We observed clear double peaks in
autocorrelations of impulse bursts recorded from Z-cut ganglia in two
other preparations. Thus ascending and descending inputs are both
functionally importanteach is effective in setting the frequency of
the oscillations in Z-cut ganglia.
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POWER SPECTRAL ANALYSIS. We applied a second metric to these swim data, power spectral density analyses, to learn more about the relative strengths of the ascending and descending inputs to Z-cut ganglia. For these analyses, we determined the power spectral densities in the frequency records (Fig. 12). Plotted on a linear scale, we found peak values at 0.74 Hz (anterior sector) and 1.08 Hz (posterior sector) and two peaks at very similar frequency values, 0.72 and 1.11 Hz, in the Z-cut ganglion. Thus by this metric as well, anterior and posterior sectors of the nerve cord provide functionally significant input to Z-cut ganglia.
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DISCUSSION |
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Our aim in performing these experiments was to determine two
system-level properties of the leech swim oscillator circuits. First,
our results demonstrate that the segmental circuits of bilateral INs
and MNs function as a single oscillator rather than as two independent
units. We also showed that ascending or descending interactions between
these segmental oscillators are of approximately equal strength. This
latter conclusion is based on our observation that oscillations in
Z-cut ganglia exhibit strong periodicities from both the anterior and
posterior sectors of the nerve cord. The strengths of the periodicity
conveyed depend on the specific configuration of the preparationa
very short chain of ganglia conveys very little period information to
the Z-cut ganglion, whereas longer chains have much stronger effects.
For a ganglion located in the middle of the nerve cord, the
intersegmental inputs from anterior and posterior ganglia are about equal.
Span of intersegmental projections
Individual ganglia from M2 through M12 include oscillatory
circuits that can generate the rudiments of swimming activity
(Hashemzadeh-Gargari and Friesen 1989; Hocker et
al. 2000
; Weeks 1981
). The complete set of
circuits that generate swimming activity in the leech is complex; that
is, the segmental circuits are highly interconnected. Not only are
there numerous interactions within segmental ganglia (Fig. 1,
A and B), but all of these INs project also to
more anterior or more posterior ganglia (Fig. 1C). The span
of the projections for some of these IN is at least five segments
(Poon et al. 1978
; Weeks 1982
). In
experiments not presented in detail here (Friesen, unpublished data),
we examined the projections of cells 115 and 28. The maximal extent of
the intersegmental projections, measured physiologically via detection
of extracellularly recorded impulses in intersegmental connective
nerves, was no more than seven segments. In the absence of precise data
for the span of every oscillatory IN in all ganglia, we employed this
new information about cells 115 and 28 to make the approximation that
the projection span of an inhibitory IN is five or six segments but not
more than seven segments. In a topological sense, then, the functional
oscillator unit in the middle segments of the nerve cord comprises
about 12 segments and more than 150 oscillatory INs (13 INs per
ganglion × 12 ganglia).
How many oscillators per segment?
Experiments in other preparations show that individual CNS
segments may comprise one or two oscillators. In the lamprey, for example, the swim circuits appear to function as a single bilateral unit. Intracellular recordings from lamprey interneurons by Buchanan and coworkers (Buchanan 1982; Buchanan and Cohen
1982
) revealed reciprocal inhibitory synaptic interactions
between contralateral interneurons, the CCIN. Extensive modeling
experiments carried out on the lamprey swim circuit, which rely on
these data, are based explicitly on the assumption that reciprocal
inhibition between contralateral inhibitory neurons contributes to the
generation of swim oscillations (Kotaleski et al. 1999
;
Ullström 1998
; Wadden et al. 1997
).
The experiments by Cohen and Harris-Warrick (1984)
do
suggest that lamprey spinal segments may comprise two oscillators. In
their study, crossed inhibitory synaptic connections in lamprey spinal
cords were blocked with strychnine, revealing that rhythmic activity
can occur independently on the two sides of the cord. However, motor
neuron output on the two sides of the cords was nearly synchronous
rather than antiphasic, hence the oscillations observed probably were
not generated by the same mechanisms as the normal antiphasic swim
rhythm. In vertebrate studies on the generation of rhythmic movements,
the evidence points to separate left-right oscillators. Thus in low
spinal cats, the two hindlimbs could walk with differing periods
(Forssberg et al. 1980
). Experiments on turtles
similarly indicate that left and right sides of the spinal cord have
some independence in generating scratch reflexes (Stein et al.
1995
, 1998a
,b
). In this latter context, it is interesting to
note that the authors stress repeatedly that the central pattern generator is bilaterally distributed
as it is in the leech swim oscillator.
Recent work on the swimmeret system in the crayfish demonstrates that
the beating movements of each swimmeret can be generated within
hemiganglia of the nerve cord. In these experiments, the abdominal
ganglia of the nerve cord were cut down the midline or interactions
were blocked with TTX. Such preparations were sometimes capable of
generating weak, antiphasic oscillations between MN antagonists
(Murchison et al. 1993). Because of the massive
disruption of intrasegmental interactions, these experiments do not
answer the functional question of whether the swimmeret pairs operate
as a unit in the intact system. [Similar bisections of leech ganglia
destroy all rhythmic activity in the cut ganglia (Friesen, unpublished
data).]
Our experiments demonstrate that swim circuits within midbody ganglia
functionally comprise a single, unitary oscillator. Even very disparate
intersegmental inputs from anterior versus posterior ganglia cannot
drive the two sides at differing periods nor cause significant
differences, except for one preparation, in left-right phases in swim
bursts (Fig. 5B). Although the strong intrasegmental
interactions across the midline of leech ganglia (Fig. 1A)
were strongly suggestive of this unity, only a functional test could
provide the conclusive answer to the question posed in the
introduction. It is interesting to note that the neuronal circuits
generating the rhythmic contractions of the bilateral heart tubes in
leeches also comprise a single unit within individual ganglia. In this
system, as in the lamprey and leech swim circuits, there are strong
inhibitory synaptic interactions across the midline (Calabrese
and Arbas 1989).
What is the relative strength of ascending and descending interactions?
Two important questions regarding intersegmental coordination are
whether the ascending or descending interactions between segmental
oscillators are symmetric and whether one of them dominates to generate
normal phase relationships in multisegmental motor systems
(Skinner and Mulloney 1998b). The ascending and
descending interactions are asymmetric in three diverse species:
leeches (Friesen 1989c
), lamprey (Buchanan 1982
,
1996
), and crayfish (Braun and Mulloney 1995
;
Skinner and Mulloney 1998a
), suggesting that such
asymmetry is ubiquitous. These interactions, together with the
intrinsic cycle periods of segmental circuits, determine the intersegmental phase relationships. In crayfish, where there appears to
be no gradient in cycle period along the swimmeret neuroaxis (Mulloney 1997
), the functional intersegmental
interaction strength appears to be strongest in the posterior direction
(Braun and Mulloney 1995
). The issue of whether
intersegmental interaction strengths are functionally polarized in the
lamprey is still unresolved (Hagevik and McClellan
1999
). One possibility is that ascending coupling dominates for
entrainment and setting intersegmental phase lags, and descending
coupling dominates for setting the cycle period (Sigvardt and
Williams 1996
).
In leeches, the INs that generate the swimming rhythm have either long
rostral or caudal intersegmental projections. In the currently
identified set, there are five neurons that project caudallytwo cells
115, two cells 123, and cell 208, and eight that project in the rostral
directions
two each of cells 27, 28, 33, and 60. The experiments
presented here now provide one quantitative measure of the
effectiveness of these INs and of any that remain undiscovered. At
least in the middle of the nerve cord, where the differences in the
amplitudes of correlation peaks (Fig. 11) and power spectral peaks
(Fig. 12) in Z-cut ganglia are small, neither the rostral nor the
caudal projections dominate. It should be noted that in our experiments
to determine the relative strength of intersegmental coupling, the
length of the intact anterior cord comprised either six or seven
ganglia, whereas the posterior cord comprised between 10 and 14 ganglia. Because the span of intersegmental interactions in the leech
is only about six segments (Pearce and Friesen 1985b
),
equal numbers of segments provided input to the Z-cut ganglion from
both anterior and posterior ends of the cord. We propose that
intersegmental phase lags in the leech nerve cord result from the
specificity of the interconnections
that is from the specific
postsynaptic target neurons and sign (inhibitory or excitatory) of the
synaptic interactions
not from differences in synaptic strength. These
currently identified intersegmental interactions between INs can
account qualitatively for the anterior to posterior phase lags
(Friesen and Pearce 1993
).
Overview of the leech swim oscillator system
Leech swim oscillator INs are, to the extent
examinedM2-M18
found in all ganglia of the leech ventral cord.
However, we now view the system as a concatenation of functionally
dissimilar units. Ganglia in the middle third of the nerve cord,
M7-M12, can individually generate moderately strong, swim-like
oscillations with a cycle period of about 1.0 s. The anterior
ganglia generate at best weak, irregular swim-like bursts. Those
posterior to M12 are incapable of oscillations in isolation
(Hocker et al. 2000
; Pearce 1985a
).
Coupling between swim IN is strong, not only within ganglia as we have
demonstrated here, but also between ganglia (Friesen et al.
1978
). Thus despite segmental heterogeneity, the intact leech
nerve cord is a functional unit, generating a common cycle period with
progressive rostrocaudal phase lags when the animal, or reduced
preparation, is swimming. We conclude that the leech swim circuit
cannot be viewed as a chain of weakly coupled robust segmental
oscillators. Rather it is a system of individually weak unit
oscillators that are strongly coupled into a single functional unit by
powerful intra- and intersegmental interactions.
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ACKNOWLEDGMENTS |
---|
We gratefully acknowledge Dr. Martin Straume, Center for Biological Timing, for expert assistance with data analyses. Thanks to Dr. Gisele Oda, X. Yu, and J. Cang for stimulating discussions and K. Dame for editorial assistance.
This work was supported by National Science Foundation Grants IBN94-10779, IBN97-23320, and DIR89-20162.
Present address of C. G. Hocker: Div. of Neuroscience S-603,
HHMIBaylor College of Medicine, One Baylor Plaza, Houston, TX 77030-3498.
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FOOTNOTES |
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Address for reprint requests: W. O. Friesen, Dept. of Biology, University of Virginia, Charlottesville, VA 22903-2477 (E-mail: wof{at}virginia.edu).
Received 7 June 2000; accepted in final form 2 April 2001.
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REFERENCES |
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