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The Journal of Neuroscience, May 1, 1999, 19(9):3298-3306
Electrotonic Coupling Interacts with Intrinsic Properties to
Generate Synchronized Activity in Cerebellar Networks of Inhibitory
Interneurons
Puah
Mann-Metzer and
Yosef
Yarom
Department of Neurobiology, Life Science Institute and Center for
Neural Computation, Hebrew University, Jerusalem 91904, Israel
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ABSTRACT |
Exploring the organization and function of local inhibitory
networks is an essential step on the way to understand the principles of brain operation. We show here that molecular layer inhibitory interneurons of the guinea pig cerebellar cortex are organized as local
networks, generating synchronous activity. Simultaneous recording from
two adjacent interneurons revealed a direct current flow between
synchronized pairs of neurons. Blocking inhibitory or excitatory
synaptic transmission did not alter the synchronization. The
electrotonic coupling coefficient (average 0.1) depended mainly on the
input resistance of the postsynaptic cell, indicating a homogenous
coupling resistance between different pairs. A presynaptic action
potential generated a short, attenuated spikelet in the postsynaptic
cell. The passive current flow was amplified by voltage-dependent intrinsic currents to create a reciprocal interplay between the presynaptic and postsynaptic cells. This interplay results in a time
window for synchronization that is wider than expected from the
duration of the spikelet. Intracellular staining with biocytin revealed
high incidence of dye coupling. Furthermore, the interneurons located
superficially in the molecular layer tend to form larger networks
compared with the inner interneurons. We propose that weakly coupled
inhibitory networks can generate loosely synchronous activity, which
results from the interaction of electrical coupling and intrinsic currents.
Key words:
cerebellum; electrotonic coupling; synchronization; inhibitory network; inhibitory interneurons; dye coupling
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INTRODUCTION |
A functionally intact inhibitory
system is a prerequisite for the adequate performance of the nervous
system and, indeed, elaborate and complex inhibitory networks can be
found throughout the CNS. Despite several recent attempts to
study inhibitory networks (Deschênes et al., 1985 ; Bouskila and
Dudek, 1993; Michelson and Wong, 1994; Whittington et al., 1995; Alonso
et al., 1996; Benardo, 1997; Dickson and Alonso, 1997; Häusser
and Clark, 1997; Pouzat and Hestrin, 1997; Kondo and Marty, 1998),
little is known about their basic functional organization.
A common finding in many of these studies is that networks of mutually
connected inhibitory interneurons exhibit, under various experimental
conditions, synchronized activity. Experimental findings, supported by
theoretical work, attribute this synchronicity to the mutual inhibitory
synapses (Van Vreeswijk and Abbott, 1994; Whittington et al., 1995;
Wang and Buzsáki, 1996). However, the involvement of electrical
synapses in creating synchronicity has also been suggested for some of
these systems (Bouskila and Dudek, 1993; Michelson and Wong, 1994;
Traub, 1995; Benardo, 1997). Because the synchronized activity is
frequently rhythmic (Deschênes et al., 1985; Michelson and Wong,
1994; Whittington et al., 1995; Benardo, 1997; Dickson and Alonso,
1997), it has been suggested that one role of inhibitory networks is to
impose a rhythm on the activity of the principle neurons, providing the
context to their operation (Buzsáki and Chrobak, 1995; Rinzel et
al., 1998).
Here we examine a network of inhibitory interneurons in the mammalian
cerebellar cortex whose structure has been described in great detail
(Palay and Chan-Palay, 1974). There are three main types of inhibitory
GABAergic interneurons: Golgi cells in the granular layer and the
interneurons in the molecular layer, the basket and stellate cells. The
mutually connected molecular layer interneurons receive excitatory
input from parallel and climbing fibers and innervate the principle
neurons of the cerebellar cortex, the Purkinje cells. Basket and
stellate cells have relatively short dendritic trees, which are
organized in an almost planar structure, and their axons always extend
perpendicular to the parallel fibers. Whereas the axons of basket cells
create a basket-like structure around the Purkinje cell somata,
stellate axons terminate on the dendritic trees of the Purkinje cells.
The axons of stellate cells are either confined to the proximal area of
their cell bodies (30-40 µm) or extend up to 450 µm from their
cell bodies (Palay and Chan-Palay, 1974; Sultan and Bower, 1998).
Structural considerations suggest two possible roles for the molecular
layer interneurons. First, because of their joint source of excitation,
the local axons of stellate cells can provide each Purkinje cell with
inhibition, which is proportional to the amount of its excitation
(Marr, 1969; De Schutter and Bower, 1994). Second, the length and
orientation of the longer axons of the molecular layer interneurons
enables them to induce lateral inhibition (Eccles et al., 1967). By
recording simultaneously from pairs of inhibitory neurons in the
molecular layer, we show here that these interneurons are organized in
local networks, interconnected by weak electrical synapses. These
networks synchronize their activity over a wide time window.
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MATERIALS AND METHODS |
Slice preparation. Sagittal slices
(300-µm-thick) were prepared from the vermis of a guinea pig
cerebellum. Guinea pigs (80-120 gm) were anesthetized intraperitonally
with pentobarbitone 60 mg/kg and perfused through the heart with 100 ml
of cold (0-1°C) oxygenated physiological solution (containing in
mM: 124 NaCl, 5 KCl, 1.3 MgSO4, 1.2 KH2PO4, 26 NaHCO3, 10 glucose, and 2.4 CaCl2, pH 7.4, aerated with 95%
O2 and 5% CO2). After decapitation, the cerebellum was quickly removed and sliced (Campden Instruments LTD 752M
vibroslice) in cold sucrose solution (containing in mM: 5 KCl, 1.3 MgSO4, 1.2 KH2PO4, 26 NaHCO3, 10 glucose, 2.4 CaCl2, and 124 sucrose). The slices
were incubated in the sucrose solution at room temperature for 20 min,
after which the sucrose solution was slowly replaced by normal
physiological solution over a period of 1 hr. This procedure was found
to be crucial for the viability of the stellate and basket cells.
Slices were kept at room temperature in an oxygenated physiological
solution until they were transferred into the recording chamber.
Recordings. The recording chamber, mounted on an upright
microscope stage (Zeiss Axioskop), maintained a constant temperature of
30°C by a temperature control unit and was continuously perfused with
aerated physiological solution. Drugs were added to the physiological solution to reach final concentrations of: TTX, 0.1 µM
(Molecular Probes, Eugene, OR); CNQX, 50 µM (Research
Biochemicals, Natick, MA); bicuculline, 50 µM (Sigma, St.
Louis, MO). Low Ca2+ solution contained 0.5 mM Ca2+ and 10 mM
Mg2+. Slices were perfused for 10 min with the
solution containing the drug before the examination of its effect. The
molecular layer interneurons in the slice were readily identified using
infrared differential interference contrast optics, and whole-cell
patch recordings were quickly attained. The patch pipettes were pulled on a Narishige pp-83 puller and had a DC resistance of 10-12 M . In
intracellular recordings the pipette solution contained (in mM): 140 K-gluconate, 4 NaCl, 0.5 CaCl2,
5 EGTA, 3 Mg-ATP, and 10 HEPES, pH 7.2. When QX-314 was used, it was
added to the pipette solution in concentration of 0.5 or 10 mM. Recordings were made with an Axoclamp 2B (Axon
instruments, Foster City, CA) in current-clamp mode. Two identical
amplifiers were used for simultaneous recordings from two cells.
Extracellular recordings were performed with the same amplifiers. The
patch pipette, which was placed near the cell membrane without
generating a seal, was filled with extracellular solution. Data were
stored on video cassette (Neurocorder DR-484) for off-line analysis.
Morphological procedure. Biocytin (0.5-1%, Sigma) was
injected intracellularly using short hyperpolarizing pulses of 4 msec, 50-100 pA at 20 Hz for 2 min. After 1 hr of incubation at 30°C, the
slice was fixed overnight at 4°C in 2% paraformaldehyde, 0.2% picric acid, and 0.1% glutaraldehyde in 0.1 M cacodilate
buffer. After rinsing several times with phosphate buffer, slices were treated with 0.5% sodium borohydride to prevent nonspecific staining, then rinsed and treated with MeOH (10%) and
H2O2 (3%) to block endogenous peroxidases. The
slices were then incubated for at least 3 hr in biotinylated
horseradish peroxidase conjugated to avidin (ABC kit; Vector
Laboratories, Burlingame, CA) with Triton X-100 (0.5%), then rinsed
and developed under visual control using the DAB reaction.
Analysis. To analyze the coupling between neurons, we assume
that coupling can be modeled as two point neurons with input resistance
R1 and R2, coupled by a resistance
Rc. Current pulse (I) injected into cell 1 will generate a voltage response in cell 1 (V1) as well as
in cell 2 (V2). The coupling coefficient (CC) defined as
V2/V1 is equal to:
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(1)
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The coupling coefficient was experimentally measured from the
average voltage responses to hyperpolarizing or depolarizing pulses of
various intensities within the range in which R2 is constant. Current was injected in turn into each cell of a pair allowing two coupling coefficients to be calculated for each pair.
A software program written in Labview was used to calculate the spike
cross-correlogram. Data were sampled at 10 kHz, and spikes were
detected by threshold peak detector. In cases of low signal-to-noise
ratio (as in extracellular measurements), sampling rate was increased
to 20 kHz, and a peak was considered valid only if at least four
consecutive points were above the predetermined threshold. This
excluded high-frequency noise from being counted as spikes. The spike
cross-correlogram was calculated for 50-100 traces of 1 sec duration,
with 1 msec time bins. Each histogram was normalized for firing rate
and number of traces by dividing the number of observed spikes by the
expected number of spikes, assuming a random firing of two neurons. The
expected number of spikes, E(t), was calculated
using Equation 2:
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(2)
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Where  1 and 2 are the firing rates
of cells 1 and 2, respectively,  t the bin size (1 msec),
N the number of traces, and T the trace duration
(1 sec). The normalized histogram thus expresses the deviation of the
results from randomly occurring spikes. The synchronization width was
defined as the width of the cross-correlogram at the 99% confidence
limit. The synchronization strength was defined as the integral of the
normalized histogram over the synchronization width.
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RESULTS |
The spontaneous activity of molecular layer interneurons in the
slice preparation has been well documented (Llano and Gerschenfeld, 1993; Häusser and Clark, 1997; Kondo and Marty, 1998). In our preparations, the spontaneous firing rate recorded extracellularly ranged between 4 and 34 Hz with an average of 13 ± 9 Hz
(n = 21). Autocorrelograms of the spontaneous activity
of these cells revealed regular rhythmic activity in 13 cells, whereas
the rest of the cells fired irregularly. Because the spontaneous
activity depends on the membrane potential, which may be affected by
intracellular recordings, a negative DC current was usually injected
into the cell to maintain a membrane potential of  45 to 55 mV. At
this membrane potential, the rate of spontaneous activity was in the same range as that measured extracellularly. These results fit those
from previous studies (Häusser and Clark, 1997).
Simultaneous recordings from pairs of adjacent molecular layer
interneurons revealed a significant tendency for synchronized firing in
40% of the recordings (n = 58), which can frequently be seen in visual inspection of both extracellular (Fig.
1A) or intracellular
(Fig. 1C) recordings. To quantify this observation, the
normalized cross correlation histogram of the spike trains was
calculated (see Materials and Methods) and plotted in Figure 1,
B and D, for the extracellular and intracellular
recordings, respectively. The clear peak around time 0 indicates the
strong tendency of these two pairs to fire in synchrony, with a
synchronization strength and width (see Materials and Methods) of 10.4 and 13 msec, respectively, for the extracellular recordings and 2.68 and 11 msec for the intracellular recordings. The synchronization strength in all the recordings ranged between 1.52 and 10.96, with an
average of 3.6 ± 2.5. The mean synchronization width was 12.8 ± 4 msec (n = 22). It should be noted that
the distribution around time 0 was not symmetrical in about half the
pairs, particularly with extracellular recordings.
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Figure 1.
Synchronous activity in inhibitory interneurons is
independent of chemical synaptic transmission. A,
C, Simultaneous extracellular (A)
and intracellular (C) recordings from two pairs
of inhibitory interneurons. Arrows mark spikes that
occur in both cells within a time window of 5 msec. B,
D, Normalized cross-correlograms of spike trains in the
pairs of cells shown in A and C,
respectively. Dashed line represents the normalized 99%
confidence limit. Note the asymmetry of the histograms around time 0. E, F, Normalized spike cross-correlograms
in the presence of bicuculline (50 µM; E)
and CNQX (50 µM; F).
Dashed and continuous plots represent the
control condition and the presence of the blocker, respectively.
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Synchronized firing may be caused by chemical synaptic transmission,
electrical synapses, or nonsynaptic interactions. To examine the
possibility that chemical synapses are involved in the synchronized
firing, we used bicuculline, CNQX, or low Ca2+
solution to block the inhibitory, excitatory, or all synaptic connections, respectively. Bicuculline (50 µM) had no
significant effect on the cross-correlogram (Fig.
1E). The synchronization strength and duration in
this pair of neurons were 10.96 and 12 msec, respectively, in
control conditions, and 10.63 and 11 msec in the presence of
bicuculline. Similar results were observed in four additional neuron
pairs. It should be mentioned that blocking the inhibitory synapses
occasionally increased the regularity of the spontaneous activity
(Häusser and Clark, 1997). Blocking the excitatory synapses
similarly failed to effect the synchronicity in two pairs of neurons in
which the effect of CNQX (50 µM) was examined (Fig.
1F). Finally, lowering the Ca2+
concentration in the external solution, thereby completely blocking all
chemical synaptic interactions, did not effect the synchronization as
well (results not shown). We therefore conclude that chemical synaptic
transmission is not involved in the synchronization of firing.
The possible involvement of electrical synapses in the synchronized
firing was examined using simultaneous intracellular recordings from
two adjacent neurons (Fig. 2). Current
pulses of various intensities were injected intracellularly into cell 1 (Fig. 2A, bottom traces), and the
voltage responses were observed in both cells (Fig.
2A, top and middle
traces). The responses in cell 2, however, were an order of
magnitude smaller than those in cell 1. These results, which clearly
demonstrate direct current flow between neurons, were obtained in 40%
of the recordings (n = 38). In 30 pairs of neurons, in
which cross-correlogram was calculated and direct current flow was
examined, nine pairs showed both synchronized firing and direct current
flow. The rest of the neuron pairs (21) showed neither direct current
flow nor synchronization. The coupling coefficient (see Materials and
Methods) for the pair of cells shown in Figure 2A was
0.124. The coupling coefficient over the whole sample under resting
conditions ranged between 0.018 and 0.28 with a mean of 0.12 ± 0.07 (n = 24).
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Figure 2.
Simultaneous recordings from two neurons reveal
direct current flow between two inhibitory interneurons.
A, Pulses of current of different amplitudes were
injected to cell 1 (bottom traces). Voltage responses
were measured in cell 1 (top traces) and in cell 2 (middle traces). Note the difference in scale.
B, Current was injected to cell 2 (bottom
traces), and voltage responses were recorded in both cells
(top and middle traces).
C, The postsynaptic response is voltage-dependent.
Current pulses of constant amplitude were injected into the presynaptic
cell (voltage responses in presynaptic cell, bottom
trace), and the voltage response in the postsynaptic cell was
measured at different membrane potentials, set by DC current injection.
Note the reduction in coupling at depolarizing membrane potentials.
D, The current-voltage curve of the postsynaptic cell
in C. Note the large and abrupt rectification at
potentials above 38 mV and the small anomalous rectification at
potential below 70 mV. E, The input resistance
(circles) and coupling coefficient
(stars) of the cell shown in C, as a
function of membrane potential. F, The coupling
coefficient between 21 pairs of inhibitory interneurons as a function
of the input resistance of the postsynaptic cell. The
line is the curve of best fit plotted according to
equation 1. Coupling resistance was calculated to be 4.25 G, and
R2 was 0.77. All the above
experiments were performed in the presence of 0.1 µM
TTX.
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The results of the complementary experiment, namely current injection
into cell 2, are shown in Figure 2B. In this case,
the coupling coefficient was 0.185, almost 50% larger than when
current was injected into cell 1 (Fig. 2A).
Nonsymmetrical current flow was found in 6 of 12 pairs of neurons. The
ratio of the two coupling coefficients for these six pairs of neurons
ranged between 1.85 and 8.04, with an average of 3.26 (ratios between
pairs of coupling coefficients of up to 1.25 were considered
symmetrical, and were not included in the average). It is reasonable to
assume that this asymmetrical current flow contributes to the
asymmetrical distribution of the cross-correlograms around time 0. However, we could not find any correlation between the asymmetric
current flow and the asymmetry of the cross-correlograms. Thus, it is likely that there are additional factors that contribute to the asymmetry of the cross-correlograms. For example, in some cases depolarizing the membrane potential of one cell can modulate the cross-correlogram, probably by holding the membrane potential closer to
the threshold, thus making this cell more responsive to any
depolarizing input. This might be the reason why asymmetric cross-correlograms were more often found with extracellular recordings where the resting potential could not be modulated by current injection, as in the case of intracellular recordings.
Asymmetric coupling between neurons results either from a rectifying
coupling conductance or from differences in the input resistance of the
cells, or both. The input resistance of the molecular layer
interneurons depends on their membrane potential. We therefore tested
the effect of the input resistance on the coupling strength by
manipulating the membrane potential. Figure 2D shows
a typical current-voltage relationship of a molecular layer
interneuron in the presence of TTX (0.1 µM). The
significant and abrupt rectification, which occurs at a membrane
potential of 35 mV, reflected as a 10-fold decrease in the input
resistance. As expected, the coupling between two cells also showed a
similar dependence on membrane potential. Figure 2C shows
that the voltage response of a postsynaptic cell (top
traces) to a constant voltage change in the presynaptic cell
(bottom trace) depends on the postsynaptic membrane
potential. Maximum responses were obtained at a membrane potential of
50 mV. A somewhat smaller response was recorded at hyperpolarizing
membrane potentials (90 mV), and the responses decreased greatly and
almost disappeared when the membrane was depolarized to 30 mV. A
comparison between the dependence of the input resistance
(circles) and the coupling coefficient (stars) on
the postsynaptic membrane potential is shown in Figure
2E. The similarity between the two shows that the
input resistance of the postsynaptic cell modulates the coupling coefficient.
The relationship between the input resistances of 21 postsynaptic cells
and their coupling coefficients is plotted in Figure 2F. As is to be expected, the higher the input
resistance, the larger the coupling coefficient. The predicted relation
between these two parameters is given in Equation 1 (see Materials and Methods). The curve (Fig. 2F, line) that
best fits our results yields a coupling resistance (Rc) of
4.25 G and has R2 of 0.77. The significant fit of
the results to the predicted curve has several implications. First,
differences in the coupling coefficient can be attributed to
differences in input resistance and, therefore, the asymmetrical
current flow between two cells is most likely caused by differences in
the input resistance of these cells. Second, the good fit of the
theoretical curve to the experimental results suggests similar coupling
resistances between the various pairs of neurons. This is a rather
surprising result because the coupling resistance reflects the number
of gap junctions, as well as their location relative to the cell body.
Having demonstrated direct current flow between neurons, we then
proceeded to examine its significance, particularly whether the current
generated by the brief action potential is sufficient to induce
synchronized firing. To answer this question, we analyzed the
postsynaptic potential during spontaneous firing of the presynaptic cell. Figure 3A shows the
average of only the subthreshold voltage response of cell 2 (top
trace) aligned by a spike in cell 1 (bottom trace). This response had two components: a prolonged
depolarizing potential and a short, attenuated spikelet (half width 2.4 msec; amplitude, 1.15 mV), which coincided with the action potential in
cell 1. As would be expected, the coupling coefficient for the brief
spike (average, 0.025 ± 0.007; n = 12) was
smaller than that calculated for long current pulses.
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Figure 3.
Intrinsic currents amplify the coupling.
A, Spike-triggered average of the subthreshold response
in cell 2 to a spike in cell 1. Traces were selected according to the
criteria that cell 2 did not respond with an action potential before
and at least 20 msec after the spike in cell 1. The horizontal
dashed line represents the average resting membrane potential
of cell 2 as measured 40 msec before the action potential in cell 1. Note the prolonged depolarization and the spikelet in cell 2 that
characterizes the postsynaptic response. B, The
subthreshold response measured as in A during
hyperpolarization of cell 2 to 79 mV by DC current injection. Under
these conditions the prolonged depolarizing response is attenuated, and
the membrane potential declines to resting level after the spikelet.
Note that resting potential in cell 1 was also affected, increasing the
amplitude of the action potential in cell 1 and the spikelet in cell 2. C, Three superimposed traces of the action potential in
cell 1 and the spikelets in cell 2 under normal and hyperpolarizing
conditions. D-F, Same as
A-C, cell 2 injected with 0.5 mM QX-314. Note the independence of the postsynaptic
response on the membrane potential and the absence of the postspikelet
depolarizing response (F), indicating its
dependence on QX-314-sensitive currents.
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The prolonged depolarizing component is particularly interesting;
presumably it reflects the slow depolarizing process leading to the
presynaptic action potential. However, it continues beyond the duration
of the spike. A possible explanation is that voltage-dependent currents
in the postsynaptic cell contribute to this slow depolarizing process.
This was examined by hyperpolarizing the postsynaptic cell to prevent
activation of voltage-dependent currents. Figure 3B indeed
shows that, under these conditions, the prolonged depolarization in the
postsynaptic cell was reduced.
The three superimposed traces in Figure 3C show the
postsynaptic responses at the two membrane potentials (Fig.
3A,B, top traces)
and their relation to the presynaptic action potential (Fig.
3B, bottom trace). Up to the point marked
by the arrow, the two postsynaptic responses follow the same
trajectory. Beyond this point, the postsynaptic response at the more
depolarized potential had a steeper slope, and it proceeded beyond the
duration of the spikelet. In contrast, at the more hyperpolarized
potential, the membrane voltage returns to baseline after the spikelet.
In both cases, the peak of the spikelets coincides with the falling phase of the presynaptic action potential.
The contribution of postsynaptic currents to the compound response was
further assessed by blocking postsynaptic sodium channels with
intracellular QX-314 (0.5 mM). Under this condition, the postsynaptic action potentials were blocked almost immediately after
breaking the neuron membrane and establishing the whole-cell recording.
Figure 3D-F displays the results of a QX-314
experiment in the same format as that shown in Figure
3A-C. The postsynaptic response in cell 2 (the
cell injected with QX-314) shows only a spikelet, whereas the prolonged
depolarizing component is absent. Furthermore, depolarizing the
postsynaptic cell to 44 mV failed to recover the prolonged
depolarization. We conclude that the voltage dependence of the
postsynaptic response is caused by postsynaptic, voltage-dependent,
QX-314-sensitive currents. Because, under normal conditions, the
membrane potential lies within the voltage range where these currents
are active, the most common subthreshold postsynaptic response will be
similar to that shown in Figure 3A. Interestingly, the
action potentials in the presynaptic cell were unaffected even after 1 hr of recordings, using 10 mM intracellular QX-314. This
suggests that the coupling path prevented the diffusion of the QX-314
to the coupled cell.
The cross-correlogram of the spike trains in these cells is shown in
Figure 4A. The
synchronization width was 12 msec, which is much broader than the
time-to-peak of the spikelet (1 msec), as measured in Figure
3A. To further assess the timing between the firing of the
neurons, we aligned 50 successive cell 2 traces by a spike in cell 1 (Fig. 4B). Of the 17 spikes that occurred within the
time window of significant correlation after the presynaptic spike,
only five spikes occurred within <1 msec. Thus, it appears that only
30% of the synchronized spikes were actually elicited by the
spikelets. Similar results were obtained when traces of cell 1 were
aligned by spikes in cell 2 (Fig. 4C).
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Figure 4.
The interaction between current flow and intrinsic
currents increases the time window of synchronization. All three panels
were measured from the same neuron pair. A, Normalized
spike cross-correlogram of spontaneous activity in the two cells.
B, Fifty consecutive spontaneous activity traces
of cell 1 (top traces) and cell 2 (bottom
traces) aligned by a spike in cell 1. Note the wide and
asymmetric distribution of the spikes in cell 2 around the time of the
spike in cell 1. C, Same as B, but
traces were aligned according to the spike in cell 2.
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The functional significance of this coupling depends on its prevalence
and spatial organization. We measured the extent of dye coupling by
adding biocytin (1%) to the pipette solution. Dye coupling was found
in 47% of dye injections to single cells, spreading to up to nine
neighboring cells, including stellate as well as basket cells. However,
the distribution of dye coupling was nonuniform. Dye coupling occurred
more frequently, and larger groups of cells were stained, when dye was
injected to superficial stellate cells as compared with deep stellate
and basket cells (Table 1). As shown in
Figure 5A-C, the
stained cells within a group tended to lie in the same sagittal plane.
Each of the two superficial groups shown in Figure 5, A and
C, contain five stained neurons. Note that their
intermingled dendrites occupy a limited area of ~100 × 100 µm. The two stained axons in Figure 5C spread over 250 µm in the sagittal plain. Figure 5B shows an example of
another type of group, one composed of a basket cell, identified by its
characteristic axonal ramifications, and a stellate cell
(arrow).
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Figure 5.
Dye coupling between molecular layer inhibitory
interneurons. Only a single neuron was injected with biocytin in each
example. A, A superficial group of dye-coupled neurons.
Typically the cell bodies are in close proximity, and the dendrites
intermingle. B, A deep group of dye-coupled neurons
composed of a basket cell and a single stellate cell
(arrow). Note the typical structure of the axon and the
elaborated dendritic tree of the basket cell. The outlines of the cell
bodies of nearby unstained Purkinje cells are drawn for clarification.
C, A superficial group of coupled stellate cells showing
the sagittal organization of their axons. Scale bars, 20 µm.
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Taking together all these observations, it is reasonable to conclude
that the inhibitory interneurons of the cerebellar cortex are organized
in specific networks that communicate via electrotonic coupling.
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DISCUSSION |
The main and novel finding of this in vitro
investigation is that 40% of the simultaneously recorded interneurons
in the molecular layer of the cerebellar cortex are electrically
coupled. This coupling is strong enough to generate synchronized
firing. Intracellular staining revealed groups of indirectly stained
neurons, therefore it is reasonable to assume that these interneurons
form local networks that give rise to synchronized activity.
Our physiological and morphological experiments were performed on
cerebellar brain slices, thus we must eliminate the possibility that
this electrical coupling is an experimental artifact of the in
vitro preparation. Although incidents of fusion of distal
dendrites caused by the preparation procedure have been reported
(Gutnick et al., 1985), there are several arguments against this
possibility. First, the coupling resistance derived from our results is
in the order of several gigaohms (Fig. 2), much larger than
expected from the axial resistance of the dendritic tree. Crude
calculation shows that a dendritic fusion located 100 µm from the
cell body on a 1 µm diameter dendrite will result in a coupling
resistance of only 100 M. Second, the almost two-dimensional
structure of these neurons minimizes the possibility of dendritic
damage during slice preparation. Furthermore, the probability of
encountering electrically coupled or dye-coupled cells was independent
of the cells depth within the slice. Third, adding QX-314
intracellularly to one cell failed to affect the action potentials in
the coupled cell. Action potentials in the injected cell were readily
blocked, even in a concentration as low as 0.5 mM. Because
the action potentials in the coupled cell were not affected even after
1 hr using a 10 mM concentration of the drug, we are bound
to conclude that QX-314 did not reach the coupled cell. Similar results
were described by Logan et al. (1996) when the QX-314, which was
intracellularly injected into sympathetic preganglionic neurons, failed
to effect the presynaptic action potentials. It is reasonable to assume that QX-314 is impermeable through gap junction, and therefore this
observation argues against dendritic fusion and supports the
possibility of an electrotonic junction. Finally, ultrastructural studies by Sotelo and Llinás (1972) have demonstrated gap
junction structures between perikarya and dendrites of the inhibitory
interneurons in the molecular layer. In view of these arguments, we
think it justified to conclude that the electrotonic coupling seen in
our preparation is not an experimental artifact.
At this point one should mention that Vincent and Marty (1996), in
their study of molecular layer interneurons, failed to find
synchronized activity or dye coupling in these neurons. The source for
this discrepancy could lie in their use of 9- to 15-d-old rats, as
opposed to our mature guinea pigs, in which the dendrites of
superficial stellate cells and the electrical connections may still be
in the process of development (Ito, 1984) (postnatal development of gap
junctions has been reported by Bourrat and Sotelo, 1983). A preference
to record from basket cells by Vincent and Marty (1996) is also a
plausible explanation. At this early developmental stage the big basket
cells are more likely to be selected for recordings. This would be in
agreement with our experiments where basket cells were rarely connected.
In characterizing the electrical coupling between the molecular layer
interneurons, we estimate the coupling resistance between neurons to be
of the order of gigaohms. This estimate, calculated from the
relationship between the coupling coefficient and the input resistance
of the postsynaptic cell, is based on several assumptions. First, the
coupled neurons are modeled as single compartments, meaning that the
axial resistance from cell bodies to the site of the gap junction is
lumped into the coupling resistance. However, as mentioned, the axial
resistance of the dendritic tree is of the order of 100 M. Even if
the length was increased to 200 µm, it would still be an order of
magnitude smaller than the estimated coupling resistance. Second, we
have assumed that the measured input resistance represents the true
value of the input resistance but, in fact, it is an underestimation of
the actual value. Only part of the injected current used to calculate
resistance flowed through the input resistance of the cell,
whereas the remainder flowed through the coupling resistance and the
input resistance of the coupled cell. Thus, calculating the input
resistance as the ratio between the voltage response and the injected
current underestimates the input resistance. Accordingly, an order of magnitude difference between the input resistance and the coupling resistance leads to a 10% underestimation of the input resistance. This underestimation reduces the estimation of the coupling resistance by about the same percentage. Third, in fitting the theoretical curve
to the experimental results we assumed that the coupling resistance is
similar for all recorded pairs, as indicated by our results. To further
check this point, we calculated the same curve for a case in which the
coupling coefficient between a pair of neurons was measured, whereas
the input resistance of the postsynaptic cell was set to different
values (Fig. 2C). This gave a coupling resistance of 6.8 G with a correlation factor of 0.94. Thus, it is reasonable to
conclude that (1) the coupling resistance between the molecular layer
interneurons is in the order of 5 G with relatively small variance,
(2) that the added coupling resistance caused by the location of the
coupling site along the dendritic tree is negligible, and (3) that the
asymmetric coupling is caused by differences in input resistance of the
postsynaptic cell.
The electrotonic coupling depends on the voltage of the postsynaptic
cell, and this voltage dependence is expressed in two ways: a
modulation of coupling strength caused by the voltage dependence of the
input resistance (Fig. 2C) and an increase in apparent
coupling by intrinsic currents that amplify the postsynaptic responses
(Fig. 3). This latter is particularly interesting because it
contributes significantly to what we regard as the physiological role
of the coupling. Specifically, a weakly coupled network of spontaneously active neurons can generate synchronized firing within a
time window that is larger than would be predicted from the time course
of the presynaptic action potential. This discrepancy results from
intrinsic currents that operate between the resting and the threshold
potentials, generating a slow depolarization that determines the
spontaneous activity of the neurons. The slow depolarization propagates
via the gap junctions to activate the same type of currents in the
postsynaptic cell. The slow process of depolarization proceeds in both
cells until threshold is reached and an action potential is elicited in
one of them. The current generated by the action potential also
propagates via the gap junctions and, if the combined depolarization of
the postsynaptic cell reaches threshold, the cell will fire within a
short time window of a few milliseconds. If the spikelet fails to
activate the postsynaptic cell, the slow depolarizing process continues until it eventually leads to a postsynaptic action potential. Thus,
although the postsynaptic action potential is synchronized with the
presynaptic action potential, the time window will be relatively wide.
This was exactly what was seen here; the width of the cross-correlogram
was wider than would be predicted from the rise time of the spikelet.
The time window of synchronization may also be increased if the
spikelet sums with spontaneous synaptic activity. However, as shown in
Figure 1, the width of the cross-correlogram does not change when
synaptic blockers are applied. It therefore appears that it is these
intrinsic currents that amplify the coupling coefficient and widen the
time window of synchronization.
At this stage, one can only speculate on the physiological relevance of
synchronized activity in the cerebellar inhibitory interneurons. Two
points appear to be functionally significant: the spatial distribution
of the axons of the interneurons and the size difference between the
superficial and the deep local networks. The superficial neurons appear
to innervate the distal dendrites of the Purkinje cells. Callaway et
al. (1995) have demonstrated that the superficial neurons are
very effective at blocking the Ca2+ responses evoked
by the climbing fibers. It has been suggested that their role is to
prevent an increase in intracellular Ca2+
concentration in well defined areas of the dendritic tree. The deeper
interneurons, particularly the basket cells, strongly inhibit firing of
specific Purkinje cells located laterally to the basket cells. It is
possible that effective inhibition of the distal Purkinje cell
dendrites requires the collaborative effort of a group of neurons,
particularly when an elaborate structure such as the Purkinje cells
dendrites has to be modulated and the Ca2+ spike
evoked by the powerful climbing fiber input has to be inhibited. The
rather weak coupling enables a synchronized activity in a relatively
wide time window. Interestingly, this time window is well within the
duration of the climbing fiber response. That is, this weak synchrony
may allow group of inhibitory interneurons to coordinate their activity
to achieve effective inhibition of the distal dendrites of the Purkinje cell.
This report adds to a growing body of evidence showing that
electrotonic coupling is more common in the CNS than previously realized (Bouskila and Dudek, 1993; O'Donnell and Grace, 1993; Draguhn
et al., 1998). Contrary to the classical view, we have demonstrated
here that electrical synapses and intrinsic currents interact to form a
highly modifiable communication pathway. A small modulation of membrane
potential or membrane resistivity, either by neuromodulators or by
spontaneous synaptic activity, can strongly modulate the strength of
electrotonic coupling as well as its interaction with intrinsic
currents. This enables a tight control on the strength and the time
window of the synchronized activity.
| |
FOOTNOTES |
Received Oct. 9, 1998; revised Dec. 30, 1998; accepted Feb. 10, 1999.
This work was supported by The Israel Science Foundation and the
European Commission.
Correspondence should be addressed to Y. Yarom, Department of
Neurobiology, Hebrew University, Givat Ram, 91904, Jerusalem, Israel.
| |
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(2000)
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[Abstract]
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D. Cohen and Y. Yarom
Cerebellar On-Beam and Lateral Inhibition: Two Functionally Distinct Circuits
J Neurophysiol,
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[Abstract]
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Q. Chang, A. Pereda, M. J. Pinter, and R. J. Balice-Gordon
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J. Neurosci.,
January 15, 2000;
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[Abstract]
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C. M. Pedroarena, I. E. Pose, J. Yamuy, M. H. Chase, and F. R. Morales
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Y. Loewenstein, Y. Yarom, and H. Sompolinsky
The generation of oscillations in networks of electrically coupled cells
PNAS,
July 3, 2001;
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[Abstract]
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L. Venance, A. Rozov, M. Blatow, N. Burnashev, D. Feldmeyer, and H. Monyer
Connexin expression in electrically coupled postnatal rat brain neurons
PNAS,
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ABSTRACT
INTRODUCTION
Compound via MeSH
