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The Journal of Neuroscience, April 1, 1999, 19(7):2765-2779
Network Oscillations Generated by Balancing Graded Asymmetric
Reciprocal Inhibition in Passive Neurons
Yair
Manor1,
Farzan
Nadim1,
Steven
Epstein2, 3,
Jason
Ritt3,
Eve
Marder1, and
Nancy
Kopell3
1 Volen Center, Brandeis University, Waltham,
Massachusetts 02454, 2 Department of Mathematical Sciences,
Rensselaer Polytechnic Institute, Troy, New York 12180, and
3 Department of Mathematics and Center for BioDynamics,
Boston University, Boston, Massachusetts 02215
 |
ABSTRACT |
We describe a novel mechanism by which network oscillations can
arise from reciprocal inhibitory connections between two entirely passive neurons. The model was inspired by the activation of the gastric mill rhythm in the crab stomatogastric ganglion by the modulatory commissural ganglion neuron 1 (MCN1), but it is studied here
in general terms. One model neuron has a linear current-voltage (I-V) curve with a low (L) resting potential, and the
second model neuron has a linear current-voltage curve with a high (H)
resting potential. The inhibitory connections between them are graded. There is an extrinsic modulatory excitatory input to the L neuron, and
the L neuron presynaptically inhibits the modulatory neuron. Activation
of the extrinsic modulatory neuron elicits stable network oscillations
in which the L and H neurons are active in alternation. The
oscillations arise because the graded reciprocal synapses create the
equivalent of a negative-slope conductance region in the
I-V curves for the cells. Geometrical methods are used
to analyze the properties of and the mechanism underlying these network oscillations.
Key words:
neural oscillators; central pattern generators; crustaceans; coupled oscillators; phase plane analysis, mathematical
model
 |
INTRODUCTION |
The mechanisms by which reciprocal
inhibition among neurons give rise to network oscillations have been
studied extensively both experimentally and theoretically (Marder and
Calabrese, 1996
; Stein et al., 1997
). This network module has long been
thought to be critical in the generation of rhythmic motor patterns
(Brown, 1914
; Perkel and Mulloney, 1974
; Miller and Selverston,
1982a
,b
; Satterlie, 1985
; Friesen, 1994
; Calabrese, 1995
). In some
cases, the reciprocally inhibitory connections are thought to occur
between neurons that are nearly identical, as in bilateral circuits
that subserve left-right alternation (Arbas and Calabrese, 1987
). In other cases, reciprocally inhibitory connections occur between functional antagonists such as flexors and extensors (Brown, 1914
; Pearson and Ramirez, 1990
) or other kinds of nonidentical neurons (Miller and Selverston, 1982b
).
There has been a significant amount of theoretical work on half-center
oscillators in which the neurons are essentially identical and the
connections symmetric (Perkel and Mulloney, 1974
; Wang and Rinzel,
1992
, 1993
; Skinner et al., 1994
; Van Vreeswijk et al., 1994
; Nadim et
al., 1995
; Olsen et al., 1995
; Sharp et al., 1996
; Rowat and
Selverston, 1997
). In the cases studied, the component neurons had some
intrinsic excitability, either because they were themselves oscillatory
or had properties such as post-inhibitory rebound that were important
in the production of the oscillation. In this paper we demonstrate that
two reciprocally inhibitory, entirely passive and nonidentical neurons
can produce stable network oscillations, provided that the synaptic
connections between them are graded, and that they receive an
asymmetric extrinsic drive. This work is an outcome of our interest in
providing a heuristic simplification and mathematical understanding of
a recent detailed compartmental model (Nadim et al., 1998
) of the
activation of the gastric mill rhythm of the crab Cancer
borealis by the modulatory commissural neuron 1 (MCN1).
At the center of the MCN1-activated gastric mill rhythm (Coleman et
al., 1995
) are two neurons: the lateral gastric (LG) neuron and
interneuron 1 (Int1). These two neurons reciprocally inhibit each
other. In the absence of MCN1 stimulation, the LG neuron is not active
but maintains a relatively hyperpolarized membrane potential, whereas
Int1 is spontaneously active. MCN1 provides a slow, modulatory,
excitatory drive to the LG neuron, which helps to depolarize it to
threshold. When LG fires, it inhibits Int1, which then stops firing.
The LG neuron also presynaptically inhibits the terminals of MCN1, so
that when LG is active, the excitatory modulatory drive is removed
until LG falls below its threshold, thus releasing both Int1 and the
presynaptic terminals of MCN1 and completing the cycle. In this
scenario, MCN1 plays the role of "balancing the asymmetry" of the
half-center composed of the reciprocally coupled LG and Int1 neurons.
To understand better the operation of this circuit, Nadim et al. (1998)
constructed a detailed compartmental model. This model suggested that
the asymmetric half-center oscillation between LG and Int1 is
controlled by the properties of both the slow modulatory excitation
from MCN1 to LG and the fast rhythmic inhibition from anterior burster
(AB) to Int1 (Marder et al., 1998
; Nadim et al., 1998
). The model used
in Nadim et al. (1998)
is 60-dimensional, with each neuron having
several compartments. It provided significant new insights into the
role of a fast oscillator in controlling the period of a slower network
oscillator (Nadim et al., 1998
) and gave rise to a series of
experiments that essentially confirmed the major findings of the
detailed model (Marder et al., 1999
; M. Bartos, Y. Manor, F. Nadim, E. Marder, M. Nusbaum, unpublished observations). In this paper we
show that the key features of the detailed model are captured in a
three-dimensional model that allows mathematical analysis of the
mechanisms that give rise to the slow oscillations.
 |
MATERIALS AND METHODS |
In this paper we describe a reduced version of the LG/Int1/MCN1
network that retains the essential features of the compartmental model
of Nadim et al. (1998)
. These features include the reciprocally inhibitory connections of LG and Int1, the MCN1 excitation of LG, the
LG presynaptic inhibition of MCN1, and the AB inhibition of
Int1. Figure 1A shows a
detailed schematic circuit of the compartmental model, together with
voltage traces of LG and Int1 during a gastric mill rhythm.

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Figure 1.
Simplifying a compartmental model of the
MCN1-elicited gastric mill rhythm. A, Schematic
representation showing the compartmental model (left)
and voltage traces of the model Int1 and the LG neuron when the model
MCN1 is stimulated at 15 Hz. [Adapted from Nadim et al. (1998) .])
B, The circuit in A is simplified to a
pair of passive neurons L and H connected
via graded reciprocal inhibition. L has a low resting potential and H
has a high resting potential. L receives a slow modulatory excitation
s that is presynaptically gated by L. Also shown are the
voltage traces of L and H. C, Same circuit as in
B, but with an additional periodic inhibition P
(representing the AB neuron in A) to
H.
|
|
To simplify the circuit, we model LG and Int1 as two passive neurons,
one neuron with a low (L) resting membrane potential (
60 mV) and the
other with high (H) resting membrane potential (+10 mV). The modulatory
neuron provides a slow excitation (s) to L. This slow
excitation is controlled by the membrane potential of L via presynaptic
inhibition. This circuit and the resulting oscillation are shown in
Figure 1B. The mechanism that we describe depends
only on graded, not spike-mediated, synaptic transmission. Therefore we
consider only the slow envelopes of the LG and Int1 oscillations shown
in Figure 1A, not the fast spiking activity of these
cells. The electrical coupling between MCN1 and LG that helps sustain
the LG burst (Coleman et al., 1995
) is ignored. In the reduced model
presented in this paper, the LG burst duration is accounted for by the
interaction between L and s. We also assume that the fast
excitatory input from MCN1 to Int1 is not significant.
Our model is a three-dimensional dynamical system. The three variables
are VL, the membrane potential of L,
VH, the membrane potential of H, and
s, the strength of the excitatory input to L. The effect of
AB is added to the circuit as a periodic input (P), and the
consequences are discussed. Figure 1C shows a schematic drawing of the circuit and the voltage traces when P is added.
Equations describing the reciprocally inhibitory pair. We
first consider the subcircuit formed by L and H, leaving out the M
excitation and the periodic input from P. The membrane potentials of L
and H are given by first-order differential equations, each with a
unique equilibrium point. For simplicity, the membrane capacitances of
the two cells are set to 1. The equations of the coupled L/H circuit
have the form:
|
(1)
|
|
(2)
|
The parameters of the reciprocally inhibitory synapses are
EH
L and EL
H (the
reversal potentials);
H
L and
L
H (the maximal conductances); and
mH
L and mL
H (the
gating functions). Because these synapses are relatively fast, we
define mH
L and mL
H
as instantaneous functions of the membrane potential:
|
(3)
|
|
(4)
|
These functions are plotted in Figure 2B,C.
The functions fH
(VH) and fL
(VL) represent the intrinsic properties
of H and L, respectively. We assume that the intrinsic dynamics of H
and L are purely passive:
|
(5)
|
where gleak,L,
gleak,H,
Eleak,L, and
Eleak,H are the conductances and reversal
potentials of the leak currents in L and H, respectively. In the
biological MCN1-elicited gastric mill circuit, without the slow
excitation, L rests at a low potential whereas H fires tonically with a
high baseline potential (Coleman et al., 1995
). We model this asymmetry
by setting Eleak,L to a low value, e.g.,
60
mV, and Eleak,H at a high value, e.g., +10 mV.
Setting the right-hand side of Equation 1 to 0 and solving for
VL, we obtain the following formula for
the L nullcline:
|
(6)
|
L is a sigmoidal function of
VH: when VH is low,
mH
L(VH) is
close to 0 and
L saturates to
Eleak,L. When VH is
large, mH
L(VH)
is close to 1 and
L saturates at an
average between Eleak,L and
EH
L, weighted by the respective leak and
synaptic conductances. The slope between these two saturated portions
of the nullcline is proportional to the degree of gradation of the H to
L synapse. Setting the right-hand side of Equation 2 to 0 and solving
for VH, we obtain the following formula
for the H nullcline:
|
(7)
|
NH is a sigmoidal function of
VL.
Adding the slow modulatory excitation. We now introduce the
slow chemical excitation (s) of L. In our model, this
excitation is completely controlled by the voltage of L: when
VL is above some threshold
VT, the excitation decays, and when
VL is below VT,
the excitation grows. The slow excitation s is therefore
governed by the following equation:
|
(8)
|
where
r,
f > 0. When
VL < VT,
s builds up toward 1 with time constant
r.
When VL > VT,
s decays toward 0 with time constant
f. The
excitation produces an additional term in Equation 1, so that now the
network is described by Equations 2, 8, and:
|
(9)
|
where
s is the maximal conductance
and Es is the reversal potential of the
excitatory input. Setting the right-hand side of Equation 9 to 0 and
solving for VL, we obtain a new formula for the L nullcline:
|
(10)
|
Adding the fast input from P. When P is added to the
circuit, the network is described by Equations 8, 9 and:
|
(11)
|
where the conductance of the P to H synapse
gP
H is a non-negative periodic function of
t, and EP
H is the reversal potential of the P to H synapse. At the peak of the P input
(
P
H), the H nullcline is given by the
formula:
|
(12)
|
We will sometimes use NH,
NL, or ÑH to
denote the graphs of the respective formulae in the
VL-VH space.
The physiological interpretation of nullclines in the
VL-VH phase plane.
In the absence of periodic input P, and for a fixed value of
s, the VL-VH
phase plane is used to describe the relationship between the membrane
potentials of H and L at any time. The L and H nullclines are the sets
of points in the phase plane where
dVL/dt and
dVH/dt, respectively, are zero. Another view, more intuitive to some physiologists, is that the H
nullcline at any value of VL is where
VH would settle if L were voltage-clamped at
that value of VL. When H is at a membrane potential higher than the H nullcline, VH decays
toward NH. VH rises
toward NH when H is at a membrane potential
lower than the H nullcline. NH thus divides the
VL-VH phase plane into
two parts: above NH, where
dVH/dt < 0, and below
NH, where
dVH/dt > 0. Similarly, the L nullcline at any value of VH is where
VL would settle if H were voltage-clamped at
that VH value. NL divides
the VL-VH phase plane
into two parts: to the left of NL, where
dVL/dt > 0, and to the
right of NL, where
dVH/dt < 0.
The intersections of the two nullclines are equilibrium points at which
both dVL/dt and
dVH/dt are zero. An
equilibrium point may be stable
after any local perturbation, the
membrane potential of the perturbed cell will return toward the same
equilibrium point; or the equilibrium point may be unstable
in this
case, a small perturbation results in a large change in the membrane potential. In the phase plane, the stability of these equilibrium points can be determined by direction of the vectors
(dVH/dt, dVL/dt) in the vicinity of
that point. In some figures we show this vector field using small arrows.
By solving the differential equations for VH and
VL we obtain
VH(t) and
VL(t). The trajectory in
the VH-VL phase plane is obtained by plotting the (VH,
VL) values for all times t.
For fixed s, the nullclines NH and
NL are fixed curves in the
VH-VL plane. In the full
system (given by Equations 2, 8, and 9), s changes slowly,
producing a family of curves NL that change
slowly (NH is independent of s).
Thus, the intersections of these curves also change slowly in time,
creating "quasi-static" equilibrium points.
Construction of the current-voltage curves of the
reciprocally inhibitory pair. One can get additional information
from the current-voltage (I-V) relationships of the
neurons H and L. We first describe the derivation of the
I-V curve for L. For simplicity, we consider the case
without the fast periodic input. The total current
IL flowing into L is given by
dVL/dt. From Equation 9, this quantity depends on two fast variables, namely the membrane potentials of both cells, VL and
VH. We view the slow variable s as a
parameter. To construct the I-V curve of L, we must reduce the two-variable expression in Equation 9 to a single-variable function
of VL. Because the reciprocal synaptic currents
between H and L are relatively fast, we can assume, for each value of VL and s, that
VH adjusts quickly to its steady state. At
steady state, NH (the H nullcline) gives an
expression for VH in terms of
VL (see Equation 7). In Equation 9, we can
substitute NH for VH and
obtain a term that depends on VL only:
|
|
The negative of the right-hand side of this expression gives
IL as a function of VL
and is used to plot the family of I-V curves of L,
dependent on s. Using similar arguments, we can derive an
expression for the family of I-V curves of H. In this case, we use Equation 10 instead of Equation 9.
All numerical simulations were performed with the software XPPAUT by B. Ermentrout (available at ftp://ftp.math.pitt.edu/pub/bardware).
Model parameters. The simulations for Figures
1B, 2, 5, 7, and 8 were performed using the following
parameter values:
H
L = 5 mS/cm2,
L
H = 2 mS/cm2, EH
L =
80 mV,
EL
H =
80 mV, vH
L =
30 mV, vL
H =
30 mV,
kH
L = 4 mV, kL
H = 4 mV, Eleak,L =
60 mV,
Eleak,H = 10 mV, gleak,L = 1 mS/cm2, gleak,H = 0.75 mS/cm2, VT =
30 mV,
s = 3 mS/cm2,
Es =
30 mV,
r =
f = 4 sec. The simulations for Figures 1C and
11 used the additional parameters
P
H = 0.9 mS/cm2 and EP
H =
60
mV, and gP
H(t) is a half-sine
function of t with period = 1 sec and duty-cycle = 0.5.
 |
RESULTS |
Figure 2 illustrates oscillations
that result from reciprocal inhibition between two passive neurons with
different resting membrane potentials, provided that the L cell
receives a slow excitation. Figure 2A shows the
voltage traces of the two cells, L and H, together with s
(the slow excitation of L), mL
H (the
activation of the L to H inhibition), and mH
L
(the activation of the H to L inhibition). Figure
2B,C plots the synaptic transfer functions (Eq. 3, 4)
of the L to H and H to L synapses, respectively. When the two cells are
uncoupled (left section), they remain at their respective resting
potentials: L at a low potential and H at a high potential. In the
middle section, L receives an excitatory input. This input depolarizes
L but does not produce oscillations. In the right section, the
reciprocal synapses between L and H are introduced and the two cells
oscillate in antiphase. At the onset of the H plateau,
mH
L increases rapidly to 1, and
mL
H decreases rapidly to 0. At the onset of
the L plateau, the reverse happens. During the H plateau s grows slowly, and during the L plateau s decays slowly. It
is the rates of growth and decay of s that determine the
durations of the plateaus, and therefore the period of the
oscillations.

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Figure 2.
Slow modulatory excitation can balance an
asymmetric half-center to produce oscillations. A, The
top two traces are the voltages of the two cells
H and L. Also shown are the slow
modulatory excitation s to L, the activation of the L to
H inhibition mL H, and the activation of
the H to L inhibition mH L. These
traces start on the left with the two
cells isolated, and s is held at 0. At the time
indicated by the first arrow, s is
activated. At the time indicated by the second arrow,
the reciprocal inhibitory synapses are activated. Shown in the
VL trace is the threshold voltage
VT for presynaptic inhibition of
s by L. B, The synaptic transfer function
for the H to L inhibition. C, The synaptic transfer
function for the L to H inhibition. The vertical dotted
line shows the threshold voltage VT
for presynaptic inhibition of s by L.
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|
We first describe how graded reciprocal inhibition gives rise to a
state equivalent to excitability. Two complementary methods are used.
The first method uses the I-V curves in the pair of neurons, because these are more familiar to many electrophysiologists. Subsequently we use phase plane analysis, because this is a
mathematically compact formalism to elucidate the mechanism of
oscillation in this system.
Reciprocally inhibitory graded synapses produce excitability:
I-V curves
In this section we use the I-V curves of the pair of
neurons to show how inhibitory graded synapses between two passive
cells can produce a state equivalent to excitability. The inhibitory graded synapses create a region of negative slope conductance in the
I-V curves of the two cells. In physiological terms, the negative slope in the I-V curves is tantamount to membrane
excitability. For either cell, this region of negative slope
conductance can produce regenerative dynamics, provided that the
membrane potential is brought into this region. We show that this shift
in the membrane potential can be obtained by an excitatory input to one
of the cells. We treat the excitatory input s as a
parameter: the effects of the reciprocal synapses on the
I-V curves at three representative values of s
are discussed.
We start by describing the I-V curves of the two passive
cells when uncoupled. In Figure
3A the I-V curves
of the L neuron and H are plotted for three different values of
excitatory input into L (s = 0, 0.5, and 1) when there
are no synaptic connections between L and H. The two I-V
curves are plotted together. The zero points on the I-V
curves are the resting potentials of the cells. Because both cells are
passive, the I-V curves are linear. Without the excitatory
input s, the resting potential of the L neuron (marked by
) is low, whereas the resting potential of H (marked by
) is high
(Fig. 3A, left panel). With a larger excitatory input
s, the I-V curve of L becomes steeper, and the
resting potential of L becomes larger (Fig. 3A, middle and
right panels). Because there is no slow excitation to H, the
I-V curve of H is not affected.

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Figure 3.
Reciprocal graded inhibition produces a region of
negative slope conductance in the I-V curves. To obtain
steady-state I-V curves, s was treated
as a parameter. The I-V curves of L
(solid line) and H (dashed
line) are shown for three values of s (0, 0.5, and 1) in the absence (A) and presence
(B) of the reciprocal inhibitory synapses. The
resting potentials of L (marked by ) and H (marked by ) are shown
in A.
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|
Figure 3B shows the I-V curves of L and H when
the reciprocally inhibitory synaptic connections between these two
cells are included. We first describe the case in which there is no
excitatory input to L (Fig. 3B, left panel). At rest,
H is at a voltage greater than its threshold for transmitter release.
When L is at low membrane potentials, H will release transmitter, so
the L I-V curve has a steeper slope, reflecting this
additional conductance. When L is at a higher membrane potential, where
it inhibits H, the H to L synapse is turned off, so the L conductance
is identical to its value in Figure 3A (left
panel). The transition between the two regions of the
I-V curves creates the negative slope conductance. Both
reciprocally inhibitory synapses are therefore responsible for
producing the cubic shape, or negative slope conductance region, in the
I-V curve of L. In contrast with the I-V curve
of L, the I-V curve of H is not affected by the reciprocal
synapses and remains linear. This linearity comes from the fact that in
the absence of excitatory input, L is never at a membrane potential where it can inhibit H. This will be clarified in the discussion of
Figure 4B (left
panel) below.

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Figure 4.
Graded inhibition produces sigmoidal nullclines in
the VL-VH phase
plane. To plot the L nullcline (NL)
and the H nullcline (NH) in the
VL-VH phase
plane, s was treated as a parameter.
NL (solid line) and
NH (dashed line) are shown
for three values of s (0, 0.5, and 1) in the
absence (A) and presence
(B) of the reciprocal inhibitory
synapses. The resting potentials of L (marked by )
and H (marked by ) are shown in A. The
intersections of NL and
NH are steady states, and the
arrows indicate the vector fields in the vicinity of
these steady states. The direction of the vector field indicates
whether the steady state is stable ( ) or unstable ( ).
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|
With a larger s, the excitatory (inward) current into L
shifts the I-V curve of L downward (Fig. 3B,
middle and right traces). When
VH is low, this excitatory drive may allow L to
depolarize enough to activate the L to H synapse. The activation of the
L to H synapse generates an inhibitory (outward) synaptic current from
L to H that causes the I-V curve of H to shift upward. The L to H synapse affects only a portion of the I-V curve of
H, namely the portion where VH is small enough
to allow the L to H synapse to be active. Therefore, when s
is large enough, the I-V curve of H assumes a cubic shape.
Excitability in terms of nullclines
In Figure 4A, we show the
VL-VH phase planes
corresponding to the panels of Figure 3A. The nullclines
NL and NH are obtained from Equations 7 and 10 by setting the right-hand side to 0 when the
maximal conductances of the reciprocal synapses are also set to 0. Because H receives no synaptic input from L, NH
is independent of VL and is a horizontal line at
the H resting potential. Similarly, NL is
independent of VH and is a vertical line. This
vertical line is the average of the resting potential of L and the
reversal potential (Es) of the excitatory
input s, weighted by their respective conductances. When
s = 0, the vertical line is at the L resting potential
(Fig. 4A, left panel). With larger values of
s, the vertical line shifts to the right toward
Es (Fig. 4A, middle and right panels). At the intersection of
NL and NH, both
VL and VH are at steady
state. The steady-state points (
) shown in Figure 4A are stable, as schematically indicated by the
directions of the vector fields (arrows) around the fixed
points (see figure legend for explanation).
In Figure 4B, we plot the H and L nullclines (from
Equations 7 and 10) in the
VL-VH phase plane, for
the cases corresponding to the I-V curves plotted in Figure
3B. We first describe the shape of NH
(same in all three panels of Fig. 4B). At any value of VL, NH depends
on the H resting potential, the reversal potential of the L to H
synapse, and their corresponding conductances. When VL is small, the L to H synapse is off, and
NH lies at H resting potential. As
VL increases, the L to H synapse activates, and NH gets closer to the reversal potential of the
L to H synapse. The sigmoidal shape of NH
reflects the shape of the gating function of the L to H synapse.
Similarly NL assumes a sigmoidal shape lying
between the resting potential of L and the reversal potential of the H
to L synapse. NL depends on s, and
changes are shown in Figure 4B.
Now consider the case where there is no excitatory input into L (Fig.
4B, left panel). Because the resting potential
of L is close to the reversal potential of the H to L synapse,
NL spans a small range of
VL. As a consequence, at steady state
VL is restricted to values for which
NH lies near its maximum, the resting potential of H. Hence, for the whole range of VH,
the synapse from L to H is off. This explains the linearity of the
I-V curve of H in Figure 3B (left
panel).
From Equation 10, NL depends on the conductances
and reversal potentials of L and the inputs to L. When s
becomes larger, the relative "weight" of the reversal potential of
the excitatory input increases. Because this reversal potential is more
positive than both the L resting potential and the reversal potential
of the H to L synapse, NL moves to the right.
Moreover, when VH is low (and therefore the
inhibitory input from the H to L synapse is small), s has a
larger relative contribution, and NL is
stretched more to the right.
The intersections of NL and
NH represent steady states for a fixed value of
s. When s = 0 (no excitation to L), the two
nullclines intersect at a high VH and a low
VL (Fig. 4B, left
panel). When s is at its maximal possible value
of 1 (maximal excitation to L), the two nullclines intersect at a low
VH and a high VL (Fig. 4B, right panel). The intermediate case
s = 0.5 is shown in Figure 4B
(middle panel). In this case, the two nullclines
intersect at three points. In such a case, the middle intersection
(
) is an unstable steady state (saddle point). All other
intersections (
) are stable. The stability of the steady states can
be seen from the local vector field, as shown schematically in Figure 4B (arrows in the panels).
Dynamics of the L/H/s oscillation when L and H
are passive
The oscillation in the L/H/s system comes about because
s, gated by the voltage of L, varies slowly. The analysis of
the oscillation can be performed using either the I-V
curves or the nullclines in the
VH-VL phase plane.
Although reasoning with the I-V curves is more intuitive to
some physiologists, constructing the I-V curves requires an
extra step in which one voltage is computed in terms of the other and
the current value of s (see Materials and Methods). An
advantage of nullclines is that they are directly computable from
Equations 2 and 9. Thus, with nullclines, it is easier to be explicit
about the effect of changing parameters such as degree of gradation of
synapses and ionic conductances. Moreover, the I-V curves
describe the behavior of the cells in steady state based on the
assumption that VH adjusts instantaneously as
VL changes and vice versa. This assumption is
only an approximation to the full dynamics of VH
and VL captured in the phase-plane analysis. For
these reasons, we shall use the phase-plane analysis to describe the
oscillations in the full system.
We start by describing one cycle of the model oscillation in the case
where L and H have passive intrinsic properties. Figure 5A shows
VH, VL, and
s in the time domain. The presynaptic inhibition of
s by L is all-or-none. The white line denotes the threshold VT for presynaptic inhibition of s by
L. The slow excitatory input s grows when
VL is below VT and decays
otherwise (Equation 8). Figure 5B-G illustrates the phase
plane at six representative times during the oscillation. These times
are marked in Figure 5A. In each of the panels
(B-G), we show the L nullcline (solid curve) and the H nullcline (dashed curve). We also show
the complete trajectory of the oscillation (dotted curve;
same in all panels) in the
VL-VH phase plane. In
each of the panels (B-G) the white circle marks the
point on the trajectory at the correspondingly labeled time in
A. We refer to this point in B-G as the
phase point. The gray circle marks the phase point at the
next indicated time. A single arrow indicates the motion of the phase
point along the trajectory from the white to the gray circle. Double
arrows in D and G indicate fast transitions
between L plateau and H plateau. The vertical white line denotes the
threshold VT.

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Figure 5.
Analysis of one cycle of the oscillation using
phase planes. A, Top, middle, and
bottom traces show the voltage traces of H and L and the
modulatory excitation s. The dotted line
superimposed on the voltage trace of L is the threshold
VT for presynaptic inhibition of the
excitatory input. B-G show the
VL-VH phase
plane at the six representative times marked in A. The
corresponding values of s are marked in each panel. The
intersection of the L nullcline (solid line) and H
nullcline (dashed line) is the quasi-steady state ( )
for the indicated value of s. In each panel, the
arrow pointing toward the quasi-steady state of the next
representative time ( )
indicates the movement of the phase point along the trajectory
(dotted line; same in B-G).
Vertical white line indicates the threshold
VT.
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In Figure 5B,C, the phase point follows the quasi-steady
state, with VH decreasing from a high value and
VL increasing from a low value. The slow
movement of the phase point corresponds to the H plateau. In panels
B-D, VL is below
VT and s increases, causing the L
nullcline to shift to the right. In D, the L nullcline separates from the H nullcline at the phase point. At this time the
quasi-steady state is lost through a saddle-node bifurcation. Immediately after this time, the phase point jumps to the only remaining quasi-steady state (D, bottom right). This is the
beginning of the L plateau and the termination of the H plateau. This
fast transition occurs because, away from the quasi-steady states, dVL/dt and
dVH/dt are large in magnitude.
During this transition VL jumps above
VT, and L turns the modulatory excitation
off. At this time s starts to decay, causing the L nullcline
to shift to the left (E-G). The slow movement
through the quasi-steady state shown in E corresponds to the
movement along the L plateau. In G, the L nullcline
separates from the H nullcline, and the bottom right quasi-steady state
is lost through a saddle-node bifurcation. The phase point jumps to the
top left quasi-steady state. This is the beginning of the H plateau and
the termination of the L plateau. During this transition
VL falls below VT and turns the modulatory excitation on. The L nullcline configuration returns to that of B, and the cycle repeats.
A necessary condition for sustained oscillations
For the oscillation mechanism described above to work, the slow
modulatory excitation s must grow during the H plateau and decay during the L plateau. During the H plateau,
VL must be below VT, otherwise s will stop
growing. Similarly, during the L plateau, VL
must be above VT, otherwise s
will stop decaying. Therefore, the threshold VT
for presynaptic inhibition of s by L must lie between the
two values of VL, just before the onset
and just before the termination of the L plateau. This condition can be
formulated as a geometrical condition on the nullclines in the
VL-VH phase plane.
In the VL-VH phase plane
there are two values of s (Fig. 5,D,G) for which
the L nullcline is tangent to the H nullcline. These two values of
s define the two saddle-node bifurcation points. The two
corresponding phase planes are shown again in Figure
6. VBLeft and
VBRight (marked by dotted drop lines)
are the values of VL at the two bifurcation
points. These two values are, respectively, the voltages of L just
before the onset and just before the termination of the L plateau. The
top left quasi-steady state (Fig. 5D) may be lost only when
VBLeft is below VT.
Otherwise the voltage of L reaches VT,
where s stops growing, and the L plateau does not occur. The
bottom right quasi-steady state (Fig. 5G) may be lost only
when VBRight is above VT.
Otherwise the voltage of L reaches VT where
s stops decaying, and the L plateau does not terminate. Therefore, oscillations occur only if VT
(indicated by the white line in Fig. 6) is strictly between
VBLeft and VBRight. Note
that this is the only restriction on VT. As long
as this requirement is satisfied, the exact location of
VT with respect to other voltage-related factors
(such as the synaptic transfer functions) does not affect the
oscillations.

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Figure 6.
The L nullcline (solid line) and H
nullcline (dashed line) are tangent at two distinct
values of VL. A, The tangency
on the top left branch of the H nullcline defines the
saddle-node bifurcation point that corresponds to the onset of the L
burst. B, The tangency on the bottom right
branch of the H nullcline defines the saddle-node bifurcation
point that corresponds to the termination of the L burst. A necessary
condition for oscillations is that the threshold
VT (white line) for
presynaptic inhibition lies strictly between the
VL values (VBLeft
and VBRight) at these two tangency
points.
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We now discuss how several parameters affect the generation of oscillations.
The effect of graded synaptic transmission
In this model, the reciprocally inhibitory synapses are graded.
The graded nature of these synapses gives rise to the sigmoidal shape
of the L and H nullclines (Fig. 4), and the cubic shape of the
I-V curves (Fig. 3). As discussed below, the sigmoidal shapes of both nullclines are essential to the existence of
oscillations. Below, we discuss the effect of the slope
(kH
L from Equation 3) of the activation curve
of the H to L graded synapse. There is a similar effect for the slope
(kL
H from Equation 4) of the activation curve
of the L to H synapse.
If the activation curve of the H to L synapse is too steep,
oscillations will not occur. Figure
7A shows how the voltage
traces of H and L are affected when the H to L synapse is abruptly
changed from graded to all-or-none. Shortly after the beginning of an H
plateau, at the time indicated by the vertical arrow, the H to L
synapse is made all-or-none by changing its activation curve to a step
function. As a result, the plateau of H is prolonged, and as it
terminates L starts its plateau. The L plateau, however, does not
terminate; instead, VL settles at
VT and the oscillation dies. Figure
7B-D shows the phase planes at the times indicated in
A. When the H to L synapse is not graded, the synapse is
"off" below vH
L (Equation 3) and "on"
above vH
L, giving rise to a step-like shape
of the L nullcline (C, D). Because of the step-like shape of
the L nullcline, the left and right bifurcation values
VBLeft and VBRight (Fig.
6) are identical. Therefore there is no oscillation because
VT cannot be strictly between
VBLeft and VBRight. The
trajectory will approach the stable fixed point at the intersection of
VT and the two nullclines (Fig.
7D).

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Figure 7.
Oscillations are disrupted when the activation
curve of one of the reciprocal inhibitory synapses is too steep.
A, Voltage traces show the alternation of activity in L
and H. At the time indicated by the vertical arrow, the
H to L synapse is made all-or-none by changing its activation curve to
a step function. The dotted line denotes the threshold
VT for presynaptic inhibition.
B-D show the phase planes at the three times marked in
A. Solid and dashed curves
are the L and H nullclines. The vertical white line
indicates the threshold VT.
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If the activation curve of the H to L synapse is too shallow,
oscillations will also die. Figure
8A shows how the
voltage traces of H and L are affected when the slope of the gating
function of the H to L synapse is decreased. At the time indicated by
the first arrow, the slope of the gating function is reduced fivefold (see Fig. 8 legend for values). The oscillations after this change become fast and small in amplitude. A further twofold reduction of the
slope at the time indicated by the second arrow causes the oscillation
to die completely. Figure 8B-D shows the phase planes at the times indicated in A. In B and
C, the H and L nullclines are shown at the L plateau
termination. In the case shown in B, the two bifurcation
points are well separated and oscillations occur as described in Figure
5. In C, because the slope of the L nullcline is closer to
that of the H nullcline, the two bifurcation points are much closer to
each other. Consequently, oscillations still occur, but with small
amplitude. In D, the L nullcline is steeper than the H
nullcline, and the two nullclines always intersect in only one point.
As a result, no bifurcation points exist, and there is no oscillatory
solution.

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Figure 8.
Oscillations are disrupted when the activation
curve of one of the reciprocal inhibitory synapses is too shallow.
A, Voltage traces show the alternation of activity in L
and H. At the time indicated by the first vertical
arrow, the activation curve of the H to L synapse is made
fivefold shallower. At the time indicated by the second vertical
arrow, the activation curve of the H to L synapse is made less
steep by a factor of two. B-D show the phase planes at
the three times marked in A. Solid and
dashed curves are the L and H nullclines. The
vertical white line indicates the threshold
VT.
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The effect of the strength of the reciprocally
inhibitory synapses
The growth of the slow modulatory excitation s is
directly opposed by the H to L synapse; therefore, the stronger this
synapse, the longer the period. The decay of s interacts
with the L to H synapse by determining how long L will inhibit H. Therefore, if the L to H synapse is stronger, s must decay
longer before H can escape the inhibition. These effects can be
analyzed by examining how changing the strength of the synapses affects
the shape of the nullclines.
Increasing the strength of the H to L synapse pulls the left (top)
branch of the L nullcline left toward EH
L
(Fig. 9A). This increase
changes the shape of the L nullcline, and its effect is similar to
increasing the slope of the H to L activation curve discussed above.
This change in the shape of the L nullcline results in a larger period
because s has to grow to a larger value before the onset of
the L plateau occurs. This will affect mainly the H plateau duration;
to a smaller extent, the L plateau duration also increases. The
increase in the L plateau duration is limited, because on the bottom
right branch of the L nullcline s is initially large, but
exponentially decaying (see Equation 8), hence the phase point
traverses this piece of the L nullcline rapidly. If the H to L synapse
is made too strong and cannot be compensated for by the growth of
s, the bifurcation that allows the onset of the L plateau
will not occur, and the oscillation will be disrupted.

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Figure 9.
The effect of strength of the reciprocally
inhibitory synapses on the nullclines. A, Increasing the
strength of the H to L synapse pulls the top left branch
of the L nullcline (solid line) toward the reversal
potential (dotted line) of the H to L synapse.
B, Increasing the strength of the L to H synapse pulls
the bottom right branch of the H nullcline
(dashed line) toward the reversal potential
(dotted line) of the L to H synapse.
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Similarly, increasing the strength of the L to H synapse pulls the
bottom (right) branch of the H nullcline down toward
EL
H (Fig. 9B) and has an effect
similar to increasing the slope of the activation curve of the L to H
synapse. This change in the shape of the H nullcline hinders the
termination of the L plateau, because s has to decay to a
smaller value before the onset of the H plateau. However, this effect
is small, and increasing the maximal conductance of the L to H synapse
never disrupts the oscillation. In the extreme case where
this maximal conductance is very large compared with the leak
conductance of H, the bottom right branch of the H nullcline reaches
the reversal potential of the L to H synapse, but the L plateau still
terminates because the decay of s still shifts the L
nullcline to the left until it becomes tangent to the H nullcline (see
Fig. 5).
The effect of the strength and time constant of the excitatory
input s
Decreasing the maximal conductance gs of
the excitatory input to L has an effect that is similar to increasing
the maximal conductance of the H to L synapse. If
gs is too small, the L nullcline does not move
enough to the right for the bifurcation and the transition to L plateau
to occur. In this case the oscillations are disrupted. If
gs is decreased, but not to the extent that the
bifurcation is prevented, the period of oscillation will increase, mainly by increasing the H plateau duration. Note that changing the
time constants for the growth and decay of s will change the period of oscillation in a linear manner. This linear relation is a
simple consequence of the fact that Equation 8 is linear on either side
of VT.
The effect of fast periodic inhibition to H
Up to this point we have described the mechanism of oscillation in
an asymmetric pair of reciprocally inhibiting neurons, balanced by a
slow excitatory modulation. In the model of MCN1-activated gastric mill
rhythm that inspired this work (Nadim et al., 1998
), we found that this
gastric mill rhythm is strongly influenced by a periodic inhibitory
input to Int1, the neuron represented by H. We therefore ask how the
mechanism of oscillation and geometry of the phase plane, as described
above, is affected by the presence of a periodic input P to H.
The input of P to H is fast, inhibitory and periodic. When P is added
to the circuit, the network is described by Equations 8, 9, and 11.
Figure 10A shows the
H nullclines NH, when the P input is at
0, and ÑH, when the P input is at
its peak value. ÑH depends on the
conductances and reversal potentials of H and all of its synaptic
inputs (Equation 12). When VL is low, the L to H
synapse is off and the effect of the P input on
ÑH is relatively large. Therefore, the P
input lowers the left branch of the H nullcline more than the right
branch. This in turn implies that during an L plateau, when the phase
point is on the bottom right branch of the H nullcline, the input from
P can be effectively ignored.

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Figure 10.
The effect of fast periodic inhibition to H on
the nullclines. A, The H nullcline (dashed
line) is shown in the absence of the inhibition
(P) and in the presence of maximal inhibition.
This inhibition pulls the top left branch of the H
nullcline toward the reversal potential (dotted line) of
the P to H synapse. B, The periodic inhibition of H by P
swings the H nullcline back and forth between the two limits shown in
A. The L nullcline is not affected. At some intermediate
value of the P input, the two nullclines become tangent, producing a
saddle-node bifurcation point ( ). The vertical white
line indicates the threshold VT for
presynaptic inhibition of s by L.
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We start with an L/H/s network that is not oscillatory when
no P input is present. Figure 10B (top H nullcline)
shows such an example, where VT lies to the left
of the left bifurcation point (
). This case corresponds to a stable
steady state in the three-dimensional system, with H at a high membrane
potential and L at a low membrane potential. When the P input is added, the H nullcline swings periodically between the two limits shown in
Figure 10A. When the phase point is on the top left
branch of the H nullcline, during one such periodic swing, the
intersection between the two nullclines disappears through a
saddle-node bifurcation (Fig. 10B,
). Thus, the P
input allows a transition to an L plateau, even before reaching its
maximum (bottom H nullcline). This transition is sufficient to produce
an oscillatory solution in the system.
Figure 11A shows
VH, VL, and
s in the time domain. In B-E, we show the phase
planes at the times indicated in A. In each panel, the white
circle denotes the position of the phase point along the trajectory. In
B, the phase point is at the quasi-steady state (the
intersection of the two nullclines). The periodic input from P moves
the H nullcline down rapidly, back and forth between the two limits
shown as dashed curves. The trajectory follows this nullcline as shown
by the dotted curve. As s grows, the L nullcline moves to
the right. In C, the top left quasi-steady state is lost during a P input (through a saddle-node bifurcation), and the phase
point jumps to the bottom right quasi-steady state. At this time,
s starts to decay, and the L nullcline moves to the left (D). In E the bottom right quasi-steady
state is lost, and the phase point jumps back to the top left
quasi-steady state, completing the cycle. Note that the P input does
not contribute to the loss of the bottom right quasi-steady
state. In fact, the P input hinders the termination of the L
plateau, although to a very small extent.

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Figure 11.
Analysis of one cycle of the oscillation in the
presence of the periodic P input. A, Top,
middle, and bottom traces show the voltage
traces of H and L and the modulatory excitation s.
B-E show the
VL-VH phase
plane at the four representative times marked in A. In
each panel, the two dashed curves show the H nullcline
when the periodic input P is at zero and at its maximum. The
solid line is the L nullcline, and denotes the
position of the phase point at that time. In each panel, the
arrow indicates the movement of the phase point along
the trajectory (shown by the dotted line up to the next
representative time). The vertical white line indicates
the threshold VT for presynaptic inhibition
of s by L.
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We mentioned earlier that oscillations are disrupted if either of the
reciprocal synapses is all-or-none. However, in the presence of the P
input, oscillations are still possible when either one of the synapses
is all-or-none and the other is graded. We will discuss the case in
which the L to H synapse is all-or-none (and the H nullcline is
step-like) and the H to L synapse is graded (and the L nullcline is
sigmoidal). The discussion of the other case is similar. As discussed
in Figure 6, when one of the two synapses is all-or-none, the two
saddle-node bifurcations values VBLeft and
VBRight are identical. Recall that the decay of
s will result in the termination of the L plateau only if
VT is to the left of
VBRight. In general, the transition to an L
plateau onset occurs when the two nullclines separate, causing the top
left intersection point to disappear. However, when the L to H synapse is all-or-none, the growth of s is not sufficient to
separate the two nullclines, because VT is to
the left of VBLeft (because VBLeft = VBRight;
see the section entitled A necessary condition for oscillations).
In the presence of the P input, the left branch of the H nullcline is
periodically shifted downward (as shown in Fig. 10B).
This provides an alternative way for separating the two nullclines,
allowing an L plateau onset. Note that the growth of s
corresponds to accumulating excitatory input in L, whereas the P input
corresponds to removing inhibition from L. The L plateau onset in the
presence of the P input is caused by this periodic removal of inhibition.
The P input can also be added to an L/H/s network that is
already oscillatory, with minimal changes in the description of Figure
11. Moreover, whether or not the L/H/s network is
oscillatory, the input from P determines the timing of the transition
from H plateau to L plateau. The control of the timing of this
transition by P leads to the frequency control mechanism (F. Nadim, S. Epstein, Y. Manor, J. Ritt, E. Marder, and N. Kopell, unpublished observations).
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DISCUSSION |
Symmetric and asymmetric half-centers
Reciprocal inhibition is a common circuit element in the nervous
system. Brown (1914)
coined the term "half-center" oscillator to
capture the notion that reciprocal inhibition between functional antagonists in motor systems could account for the repeating patterns of alternating activity between flexors and extensors. Brown (1914)
understood that mechanisms for producing the transitions between activity in the two halves of the circuit were required. In Brown's work, and whenever reciprocal inhibition is found between different classes of neurons, the two sides of the half-center are, by
definition, not identical. In contrast, reciprocal inhibition also
subserves left-right alternation in many motor systems. For example,
in the leech heartbeat system, the kernel of the central
pattern-generating network is formed by two, apparently identical
neurons that form reciprocal inhibitory connections (Calabrese, 1995
;
Marder and Calabrese, 1996
).
There have been a number of theoretical studies on the factors that
control the behavior of half-center oscillators when the two neurons
that form them are identical (Perkel and Mulloney, 1974
; Wang and
Rinzel, 1992
; Skinner et al., 1993
, 1994
; Van Vreeswijk et al., 1994
;
Nadim et al., 1995
; Olsen et al., 1995
; White et al., 1998
). However,
almost no theoretical work has been done on the problem of how to
produce stable alternating bursts of activity from reciprocally
inhibitory neurons with different intrinsic membrane properties. This
is particularly striking because many, if not most, cases of reciprocal
inhibition occur between neurons that are not likely to have identical properties.
Several workers have noted the necessity of "balancing the
excitability" of the two sides of the half-center to produce rhythmic alternating bursts. For example, Miller and Selverston (1982b)
were
able to produce stable half-center-like oscillations from the
reciprocally inhibitory lateral pyloric and pyloric dilator neurons of
the stomatogastric ganglion by injecting current into one of them.
Sharp et al. (1996)
used the dynamic clamp to construct stable
half-center activity with gastric mill neurons of the stomatogastric ganglion and sometimes found it necessary to set the leakage current to
balance the two neurons (A. Sharp, F. K. Skinner, and E. Marder, unpublished observations). In a similar situation, Gramoll et al.
(1994)
demonstrated that a leak current controls a switch from the
peristaltic to the synchronous activation in the leech heartbeat system.
In this paper we describe mechanisms by which modulatory and synaptic
inputs compensate for the asymmetries in the membrane properties of two
neurons so that they can fire in alternating bursts in a half-center
mechanism (Fig. 12). One take-home
message of our work is that synaptic inputs can form or activate a
functional network by bringing the two neuronal elements into the
balance needed for stable alternation.

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Figure 12.
Schematic drawing showing circuit configurations
that can be driven to produce half-center oscillations from asymmetric
neurons. The basic circuit consists of two neurons that in the absence
of extrinsic input (A-C, left column) are quiescent
(L) and tonically active
(H). A, Circuit with a
single inhibitory synapse from L to H. An excitatory input to L that is
either periodic (white ) or presynaptically gated by
L (gray ) produces antiphase oscillations.
B, Circuit with a single inhibitory synapse from H to L. An inhibitory input to H that is either periodic (white
) or presynaptically gated by H (gray )
produces antiphase oscillations. C, Circuit with
reciprocally inhibitory synapse between L and H. An excitatory input to
L that is presynaptically gated by L and a periodic inhibitory input to
H work synergistically to produce antiphase oscillations.
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In Figure 12 we show several different circuit configurations that can
produce half-center alternations from asymmetric neurons: one tonically
firing neuron, H, and one quiescent neuron, L. In Figure
12A we show a circuit in which there is an inhibitory
synapse from L to H. In the absence of external input, this circuit
will not oscillate. However, a periodic excitatory input to L will entrain the two cells to fire in alternation at that period. Provided that the inhibitory synapse between the two cells is fast relative to
the period of the excitatory input, this circuit will faithfully follow
rapid changes in the input period. Alternatively, if the excitatory
input to L is not periodic but is presynaptically gated by L, the
circuit can still produce antiphase oscillations. In this case, the
period of oscillations will be determined by the time constants of
growth and decay of the excitation.
In Figure 12B, the H neuron makes an inhibitory
synapse onto the L neuron. This circuit will not oscillate in the
absence of external drive, but it can produce oscillations if H
receives external periodic or presynaptically gated inhibition.
In both cases described (shown in Figure 12A,B),
there is no reciprocity between the L and H cells. Hence, the circuit
is not very robust; in particular, an input (modulatory or other) to the postsynaptic cell (H in A or L in B) may
disrupt the antiphase oscillations. A natural extension of these two
elemental circuits is an asymmetric pair of reciprocally inhibitory
neurons such as the one described in this paper (Fig. 12C).
In this circuit external inhibition of H and external excitation of L
synergistically combine to produce robust alternations that can be
frequency-modulated over a large range.
Mathematical analysis
Although a detailed model of this network exists (Nadim et al.,
1998
), the small network we present shows with greater clarity the
origin of the oscillation and some of its properties, notably what
controls the frequency and how the oscillation depends on parameters
such as synaptic conductances.
We exploit the fact that the three-dimensional system (Equations 2, 8,
and 9) has two fast variables and one slow variable; the value of the
slow variable (the excitation) determines the values of the voltages to
which the two cells rapidly equilibrate. The separation of fast and
slow time scales is a fundamental tool for analysis of large classes of
equations. Our analysis uses methods described in Rinzel and Ermentrout
(1998)
, in which slowly changing parameters can produce sharp changes
in system behavior.
The analysis of oscillations in the network was performed in terms of a
family of slowly moving nullclines in the phase space of the two
voltages, with the amount of excitation to the low cell L as a
parameter. The construction of the periodic solution can also be made
using a family of I-V curves for each of the cells. As
stated in Results, the formulas for the I-V curves
are derived using the nullclines, so the explicit formulas are more complicated and therefore less transparent for understanding how changes of parameters change behavior. Other descriptions can also be
used. For example, we (F. Nadim, S. Epstein, Y. Manor, J. Ritt, E. Marder, and N. Kopell, unpublished observations) have analyzed the
effect of the fast forcing on this three-dimensional oscillator, and we
reduced the oscillator to a two-dimensional model whose variables are
the amount of excitation and the voltage of the low cell.
Graded transmission can produce network oscillations from
passive neurons
A novel finding described in this paper is that two entirely
passive neurons can generate oscillatory network activity when they are
connected by graded reciprocal inhibitory synapses and receive a
periodic input. The terms "escape" and "release" were introduced by Wang and Rinzel (1992)
to describe how the transitions in
a half-center formed from excitable cells occur. In a release, the
transition is determined by the properties of the active neuron, and in
an escape it is determined by the properties of the inactive neuron. In
the simplest case, release transitions occur when the active neuron
falls below a voltage threshold sustaining its burst, and an escape
occurs when the inactive neuron crosses a voltage threshold for burst
initiation. Both of these transitions occur because one of the neurons
crosses a voltage threshold independent of the properties of the other
neuron. However, in the case studied here, in which neither neuron has
intrinsic excitability, the concepts of escape and release are not
useful, because the transitions do not occur because either of the
neurons crosses a voltage threshold. Rather, it is the reciprocal
inhibition that constructs the network excitability, and therefore
neither cell has an individual voltage threshold that can provide a
transition independent of the network.
Here we have studied two kinds of periodic inputs: a fast synaptic
inhibition and a slow modulatory excitation that is converted to a
periodic input by its presynaptic inhibition by the network. The graded
activation of synaptic transmission creates a negative conductance
region in the I-V curve that allows the oscillation to
occur. The range and shape of the negative conductance region in the
I-V curve are determined by the steepness of both synaptic activation curves and the strength of both synapses.
In the absence of the fast periodic input, the period of the
half-center oscillation depends linearly on the rates of growth and
decay of the slow modulatory excitation. The strength and steepness of
the reciprocal inhibitory synapses also affect the period, but in a
nonlinear manner. As discussed in detail in Results, increasing the
steepness of activation or the strength of the inhibitory synapses
prolongs the period of the oscillation. The latter effect was also seen
by Sharp et al. (1996)
. The same relationships persist in the presence
of the fast periodic input, but the fast input gates the transition
time of one phase of the half-center oscillation.
When there is a periodic input (Fig. 12C), the network will
oscillate if one of the synapses is not graded, as was the case in
Nadim et al. (1998)
. Moreover, in the absence of a periodic input, both
synapses can be spike-mediated, provided that the durations of the
spike-mediated IPSPs are of the same order of magnitude as the mean
interspike interval during the burst, and either the synapse shows
depression or the presynaptic neuron has spike rate adaptation. Either
of these spike-mediated mechanisms is the functional equivalent of the
graded synapses studied here, when considered on a time scale that
averages over spikes.
Much of this analysis will hold for the case in which the asymmetric
neurons are not passive but have excitable membranes. We have shown
that a necessary condition for oscillations is that the threshold for
presynaptic inhibition of the modulatory input is within a finite
voltage interval. In some cases, intrinsic neuronal excitability may
make the network oscillations more robust by widening this voltage
interval. This will occur if the intrinsic excitability enlarges the
negative conductance region of the I-V curve produced by
the graded synapses. In other cases, the intrinsic voltage-dependent
membrane conductances of the neurons may attenuate the negative
conductance region of the I-V curve and therefore decrease
the stability of the network oscillations.
Activation of an asymmetric half-center is an example of
circuit reconfiguration
The asymmetric half-centers studied here do not function in the
absence of their modulatory or synaptic drive. Therefore, although the
circuit may be anatomically present, it will not be functional until
enabled by the appropriate modulatory inputs that act to balance the
well poised but inactive networks. In the case of MCN1 activation of
the gastric mill rhythm, a slow modulatory excitation is the mechanism
by which the half-center is balanced (Coleman et al., 1995
). However,
one can imagine a host of modulatory mechanisms (Harris-Warrick et al.,
1992
; Marder and Calabrese, 1996
) that could bring the two sides of a
half-center network close enough into balance to allow the circuit to
work. In summary, we provide here an analysis of several mechanisms relevant to the activation of rhythmic alternation in half-center oscillators formed by nonidentical elements. The challenge in biological terms is to understand the cellular mechanisms by which modulatory substances and synaptic inputs achieve the right balancing act.
 |
FOOTNOTES |
Received Aug. 28, 1998; revised Jan. 15, 1999; accepted Jan. 17, 1999.
This research was supported by National Institutes of Health
Grants NS17813 (E.M.) and MH47150 (N.K.), the Sloan Foundation, and the
W. M. Keck Foundation. We thank Dr. Michael Nusbaum for introducing us
to MCN1.
Correspondence should be addressed to Dr. Eve Marder, Volen Center, MS
013, Brandeis University, 415 South Street, Waltham, MA 02454.
Dr. Manor's present address: Department of Life Sciences, Ben-Gurion
University, POB 653, Beer-Sheva, Israel 84105.
Dr. Nadim's present address: Department of Mathematics, New Jersey
Institute of Technology and Department of Biological Sciences, Rutgers
University, 101 Warren Street, Newark, NJ 07102.
 |
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