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Previous Article | Next Article
The Journal of Neuroscience, April 15, 2001, 21(8):2687-2698
Rapid Signaling at Inhibitory Synapses in a Dentate Gyrus Interneuron Network
Marlene Bartos1, Imre Vida2, Michael Frotscher2, Jörg R. P. Geiger1, and Peter Jonas1 1 Physiologisches Institut and 2 Anatomisches Institut, Albert-Ludwigs-Universität Freiburg, D-79104 Freiburg, Germany
ABSTRACT
TOP
ABSTRACT
INTRODUCTION
Mutual synaptic interactions between GABAergic interneurons are thought to be of critical importance for the generation of network oscillations and for temporal encoding of information in the hippocampus. However, the functional properties of synaptic transmission between hippocampal interneurons are largely unknown. We have made paired recordings from basket cells (BCs) in the dentate gyrus of rat hippocampal slices, followed by correlated light and electron microscopical analysis. Unitary GABAA receptor-mediated IPSCs at BC-BC synapses recorded at the soma showed a fast rise and decay, with a mean decay time constant of 2.5 ± 0.2 msec (32°C). Synaptic transmission at BC-BC synapses showed paired-pulse depression (PPD) (32 ± 5% for 10 msec interpulse intervals) and multiple-pulse depression during repetitive stimulation. Detailed passive cable model simulations based on somatodendritic morphology and localization of synaptic contacts further indicated that the conductance change at the postsynaptic site was even faster, decaying with a mean time constant of 1.8 ± 0.6 msec. Sequential triple recordings revealed that the decay time course of IPSCs at BC-BC synapses was approximately twofold faster than that at BC-granule cell synapses, whereas the extent of PPD was comparable. To examine the consequences of the fast postsynaptic conductance change for the generation of oscillatory activity, we developed a computational model of an interneuron network. The model showed robust oscillations at frequencies >60 Hz if the excitatory drive was sufficiently large. Thus the fast conductance change at interneuron-interneuron synapses may promote the generation of high-frequency oscillations observed in the dentate gyrus in vivo.
Key words: GABAergic interneurons; basket cells; dentate gyrus; unitary IPSCs; paired-pulse depression; paired recording; interneuron networks; gamma oscillations; computational model
INTRODUCTION
The neuronal network of the hippocampus consists of glutamatergic principal neurons (granule cells and pyramidal neurons) and GABAergic interneurons (for review, see Freund and Buzsáki, 1996
). Inhibitory interneurons that innervate the perisomatic domain of principal neurons, referred to as basket cells (BCs), have a particularly powerful influence on their postsynaptic target cells, controlling the electrical activity of the principal neuron ensemble (Cobb et al., 1995
In the hippocampus of the behaving rat, oscillations in the theta (3-12 Hz) and gamma (40-100 Hz) frequency range occur during exploration (Bragin et al., 1995
The goal of this study was to test the implications of the network models directly by recording from pairs of synaptically connected basket cells in the dentate gyrus of rat hippocampal slices. This region shows gamma oscillations with the highest frequency and power in the entire hippocampus (Bragin et al., 1995
MATERIALS AND METHODS
Paired recordings from synaptically connected interneurons. Transverse hippocampal slices (300 µm thickness) were cut from brains of 18- to 25-d-old Wistar rats using a Vibratome (DTK-1000, Dosaka). Animals were killed by decapitation, in accordance with national and institutional guidelines. Patch pipettes were pulled from borosilicate glass tubing (2 mm outer diameter, 1 mm wall thickness). When filled with intracellular solution, the resistance was 1.4-2.2 M
for recordings from BCs and 2.0-2.5 M
55 mV and GC recordings with initial resting potentials more positive than
Two Axopatch 200B amplifiers (Axon Instruments) were used for recording. The presynaptic neuron was held in the current-clamp mode and stimulated at a frequency of 0.1-0.3 Hz, unless specified differently. Action potentials were initiated by brief current pulses (duration 2 msec, amplitude 1-1.4 nA). The postsynaptic cell was held in the voltage-clamp mode (holding potential
Solutions. The physiological extracellular solution contained (in mM): 125 NaCl, 25 NaHCO3, 25 glucose, 2.5 KCl, 1.25 NaH2PO4, 2 CaCl2, and 1 MgCl2 (bubbled with 95% O2/5% CO2 gas mixture). In some experiments, slices were stored in a solution containing (in mM): 87 NaCl, 25 NaHCO3, 2.5 KCl, 1.25 NaH2PO4, 0.5 CaCl2, 7 MgCl2, 25 glucose, and 75 sucrose. 6-Cyano-7-nitroquinoxaline-2,3-dione (CNQX) (5-10 µM) was added to the bath solution to block EPSCs. The intracellular solution contained K-gluconate and KCl (at concentrations of either 110 and 40 mM, or 70 and 70 mM, respectively), 0.1 mM EGTA, 2 mM MgCl2, 2 mM Na2ATP, and 10 mM HEPES; the pH was adjusted to 7.2 with KOH, and the osmolarity was 310-315 mOsm. Bicuculline methiodide was purchased from Sigma (St. Louis, MO); CNQX was purchased from Tocris (stock solutions in either distilled water or 0.1 M NaOH). Other chemicals were from Merck (Darmstadt, Germany), Sigma, Riedel-de Haën, or Gerbu.
Data analysis. The rise time of evoked IPSCs was determined as the time interval between the points corresponding to 20 and 80% of the peak amplitude, respectively. The peak current was determined as the maximum within a window of 2-4 msec duration after the presynaptic action potential. The synaptic latency was determined as the time interval between the maximum of the first derivative of the presynaptic action potential and the onset of the IPSC; the onset point was determined from the intersection of a line through the 20 and 80% points with the baseline. The decay phase of the IPSCs was fitted with a single exponential [A exp(
m)] or with the sum of two exponentials [A exp(
Morphological reconstruction and analysis. Morphological methods were similar to those reported previously (Martina et al., 2000
Axons and dendrites of the presynaptic and postsynaptic neuron were examined by light microscope using a 100× oil immersion objective. Putative synaptic contacts were identified as close appositions of a bouton and a dendrite in the same focal plane. In selected pairs, the morphology of presynaptic and postsynaptic neurons was reconstructed with the aid of a camera lucida. In two pairs, the contacts suggested by light microscopy (LM) were examined by electron microscopy (EM) of serial sections. In one pair, five contacts were suggested by LM, and three contacts were revealed by EM (two false positive contacts). In another pair, six contacts were suggested by LM, and seven contacts were revealed by EM (one additional contact found).
In a subset of pairs examined (14 IPSCs, 1 electrical coupling), both the presynaptic and the postsynaptic interneurons were identified morphologically as BCs. The main criteria were (1) the primary location of the axonal arborization in the granule cell layer (light microscopy) and (2) the preferential location of the synapses on somata and proximal dendrites of the target cells (electron microscopy; two BC-BC pairs) (Han et al., 1993
250 Hz during the first 100 msec of a depolarizing pulse; 18 pairs). These BC-BC pairs, referred to as "tentatively identified" in the text, were used together with the rigorously identified pairs in Figures 2, 6, and 7. Basic properties of synaptic transmission (latency, rise time, amplitude, and decay time constant) in rigorously and tentatively identified BC-BC pairs were not significantly different (p > 0.5 for all parameters).
Detailed passive cable simulations. Detailed passive cable modeling was performed using three biocytin-filled BC-BC pairs (Major et al., 1994
, with the space constant
(Rm d/4 Ri), where Rm is the specific membrane resistance, d is the diameter of the segment, and Ri is the cytoplasmic resistivity.
IPSCs were simulated using NEURON version 4.2.3 or 4.3.1 (Hines and Carnevale, 1997
To infer the time course of the inhibitory conductance change at the postsynaptic site, conductances were simulated at the morphologically identified contacts, and
Network simulations. The activity of networks of fast-spiking inhibitory interneurons was simulated using NEURON 4.3.1 running on a PC, following closely the procedures of Wang and Buzsáki (1996)
concentrations (to ~0.6 at 7.9 mM Cl
).
Average firing frequency (fµ) was determined from the mean interspike interval for the entire simulation period. Action potential patterns were represented in a binary format (with 0 when no action potential occurred and 1 if one or more than one action potential occurred in a given time interval
was calculated as the mean of the coherence in all pairs of interneurons defined by the following equation:
where i and j denote the two interneurons, X (l) and Y (l) are the binary action potential patterns, and K is the number of time bins.
(1)
RESULTS
Functional properties of unitary IPSCs at BC-BC synapses
To determine the functional properties of inhibitory synapses between hippocampal interneurons, we recorded from pairs of monosynaptically connected dentate gyrus BCs in rat brain slices at near-physiological temperatures (Fig. 1). A representative example of a recording from a BC-BC pair is shown in Figure 1A. Figure 1B shows histograms summarizing the basic properties of synaptic transmission from 14 BC-BC pairs in which the presynaptic and postsynaptic neurons were identified rigorously by light microscopy. The mean latency of unitary IPSCs, measured from the steepest point in the rise of the presynaptic action potential to the onset of the IPSC, was 0.8 ± 0.05 msec. The mean 20-80% rise time was 0.3 ± 0.02 msec, and the mean peak amplitude including failures was 110 ± 19 pA at
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Figure 1. Fast unitary IPSCs in synaptically connected BC-BC pairs. A, Presynaptic action potential (top), single unitary IPSCs (6 sweeps superimposed, center), and average IPSC (from 38 sweeps, bottom) at
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Table 1. Summary of functional properties of unitary IPSCs generated at the BC-BC synapse We next examined the dynamics of transmission at BC-BC synapses during repetitive presynaptic activity (Fig. 2). As the simplest paradigm, we studied paired-pulse modulation. When two action potentials were elicited in the presynaptic BC, separated by intervals of variable duration, the amplitude of the second IPSC in the postsynaptic BC was on average smaller than that of the first (Fig. 2A). The maximal paired-pulse depression (PPD), measured for 10 msec interpulse intervals, was 32 ± 4.6% (6 rigorously and 11 tentatively identified BC-BC pairs).
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Figure 2. Dynamics of transmission at inhibitory BC-BC synapses. A, PPD of IPSCs. IPSCs were evoked by two action potentials in the presynaptic BC, separated by a 20 msec interval. IPSCs shown are averages from 30 single traces (failures included). A1 and A2 were measured from the preceding baseline. B, Coefficient-of-variation analysis of PPD. The inverse of the square of the coefficient of variation (CV ) or 50 msec (
). Dotted line indicates identity line. Data are from 17 pairs. C, Time course of recovery from PPD. Amplitude ratio A2/A1 of unitary IPSC was plotted against the interpulse interval. The curve represents a fitted monoexponential function with a time constant of 0.63 sec. Data are from 17 pairs. D, Multiple-pulse depression of IPSCs. The bottom trace to the left of the double slash is an average of 10 single sweeps recorded with a stimulation frequency of 0.2 Hz; the traces to the right of the double slash are single sweeps (20 events at the onset, 20 events 1 sec after the onset of a 50 Hz train). E, Unitary IPSCs at an expanded time scale from the same pair as shown in D. Five consecutive IPSCs from different times (as indicated by brackets) are shown superimposed. F, Onset of depression during a 50 Hz train. Each data point represents the mean IPSC peak amplitude in three pairs, normalized to the mean peak amplitude at 0.2 Hz (479 pA on average) before the train. Each data point represents a single peak amplitude (first 10 points) or the mean of four amplitudes (all subsequent points). The curve represents the sum of two exponential components and a constant fitted to the data points, with
To determine whether PPD was generated by presynaptic factors [such as depletion of the vesicular pool (Stevens and Tsujimoto, 1995
In the intact hippocampal network, interneurons can generate high-frequency trains of action potentials during gamma oscillatory periods (Bragin et al., 1995
Morphological properties of BC-BC synaptic connections
Unitary IPSCs recorded at the soma decayed very rapidly. However, the time course of the real conductance change at the site of transmission is likely to be faster, because of imperfect voltage clamp and cable filtering. To infer the time course of the inhibitory conductance change at the site of generation, we first determined the location of the synaptic contacts. Presynaptic and postsynaptic neurons were filled with biocytin during recording and processed subsequently for light and electron microscopy. Figure 3 shows a camera lucida reconstruction of a representative synaptically coupled BC-BC pair. For both the presynaptic and the postsynaptic neurons, the axonal arborization was largely confined to the granule cell layer. This identifies the interneurons as BCs (Han et al., 1993
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Figure 3. Camera lucida reconstruction of a synaptically connected BC-BC pair. Soma and dendrites of the presynaptic BC are drawn in green. Axonal arborization of the presynaptic BC is drawn in red. Soma and dendrites of the postsynaptic BC are drawn in black. Axonal arborization of the postsynaptic BC is drawn in blue. Only the portions of the axons that could be unequivocally traced back to the soma are depicted. Synaptic contacts (confirmed by subsequent electron microscopy; see Fig. 4) are indicated by arrowheads. Additionally, the postsynaptic BC showed three autaptic contacts (confirmed by electron microscopy; data not shown). Note that the axonal arborization of both BCs was largely confined to the granule cell layer, identifying them as BCs. ml, Molecular layer; gcl, granule cell layer.
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Figure 4. Light and correlated electron microscopical analysis of synaptic contacts in a synaptically connected BC-BC pair. A, Low-power light micrograph of the same pair shown in Figure 3. ml, Molecular layer; gcl, granule cell layer; h, hilus. Scale bar, 50 µm. B, High-power light micrograph of the soma and apical dendrite of the postsynaptic BC. Two of the three synaptic contacts in this BC-BC pair are indicated by arrow and open arrow. Scale bar, 10 µm. C, Low-power electron micrograph of the proximal synaptic contact (open arrow). Scale bar, 2.5 µm. D, E, High-power electron micrographs of the two distal contacts (arrow and arrowhead). Contacts indicated by open arrow and arrow in C and D are also visible in the micrograph in B (same symbolic code; contact in E indicated by arrowhead is not shown in B). Scale bar, 0.25 µm.
The time course of the inhibitory conductance change at the postsynaptic sites
To determine the time course of the postsynaptic conductance change at the BC-BC synapse, the somatodendritic domain and the main axon of the postsynaptic BC were reconstructed and converted into a detailed passive cable conductor model. Figure 5A shows an electrotonic dendrogram of the postsynaptic BC shown in Figures 3 and 4. In this cell, the synaptic BC-BC contacts were located at electrotonic distances of 0.03, 0.14, and 0.20
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Figure 5. Estimation of the time course of the postsynaptic conductance change at the synaptic contacts. A, Electrotonic dendrogram of a postsynaptic BC (same cell as shown in Figs. 3, 4). Apical dendrites are represented in the center; basal dendrites are shown laterally in the dendrogram. The axon (shown truncated) is indicated by the asterisk; 150 schematic collaterals were attached to the main axon in a distributed manner (not shown). The locations of the synaptic contacts are shown by arrowheads (a, b, c). The physical and electrotonic distances of the three synaptic contacts from the soma were 17, 108, and 133 µm, and 0.03, 0.14, and 0.20
To infer the rise time, decay time constant, and amplitude of the postsynaptic conductance change, simultaneous synaptic events were simulated at all morphologically identified transmission sites, and their kinetic parameters and amplitude were varied to describe the experimentally observed average unitary IPSC in the same pair (Fig. 5Bc). In the pair shown, the inferred rise and decay time constants of the conductance change at the postsynaptic site were 0.20 and 1.02 msec, respectively. In three fully analyzed pairs, the mean values of the time constants were 0.17 ± 0.04 msec (rise, corresponding to mean 20-80% rise time of 0.14 msec) and 1.8 ± 0.6 msec (decay) (Table 1). Exploration of the parameter space indicates that these estimates are relatively insensitive to the assumptions of the cable model (Fig. 5C).
Electrical coupling between hippocampal interneurons
Electrical synapses between hippocampal interneurons were suggested previously on the basis of dye coupling (Michelson and Wong, 1994
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Figure 6. Electrical coupling in a subset of BC-BC pairs. A, Top panel, Electrical PSCs evoked by single presynaptic action potentials in a tentatively identified BC-BC pair. Presynaptic action potential is shown at top; single electrical PSCs are shown at bottom; six sweeps are superimposed. A, Bottom panel, Electrical PSCs evoked by a train of five presynaptic action potentials evoked with a frequency of 100 Hz (average from 15 sweeps). Note that the amplitude of the electrical PSCs is approximately constant and that the electrical PSCs are mirror images of the presynaptic action potentials. B, Postsynaptic voltage changes evoked by long depolarizing and hyperpolarizing current pulses (0.4,
Target-cell specificity in the decay time course of the unitary IPSC
The present results suggest that the measured IPSC at BC-BC synapses decays faster than that at the BC-GC synapse in the same microcircuit [amplitude-weighted decay time constant 2.5 msec (this paper) and 6.5 msec (Kraushaar and Jonas, 2000
0.006) (Fig. 7A,C). Furthermore, the peak amplitude of the IPSC was slightly, but not significantly, larger (p > 0.2) (Fig. 7D). Finally, the paired-pulse ratio (10 msec interval) was not significantly different (p > 0.2) (Fig. 7B,D). These results indicate significant differences in the time course of the inhibitory postsynaptic conductance change that are determined by the nature of the postsynaptic target cell.
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Figure 7. IPSC decay time constant is determined by the type of the postsynaptic target cell. A, B, Sequential triple recording from a presynaptic BC and a postsynaptic BC (left traces, first pair) and the same presynaptic BC and a postsynaptic GC (right traces, second pair obtained subsequently after pipette removal from the postsynaptic BC). Presynaptic action potential (top), single unitary IPSCs (6 sweeps superimposed, center), and average IPSC (from 22 sweeps, bottom) are depicted. Shown are single action potential in A and pair of two action potentials in B (10 msec interpulse interval). Note the difference in decay time constants but the comparable paired-pulse ratio. The fast inward current preceding the IPSC in the BC-BC traces represents putative electrical coupling. C, Summary bar graphs of 20-80% rise time, latency, and amplitude-weighted average decay time constant. D, Summary bar graphs of peak IPSC amplitude (left) and paired-pulse ratio (A2/A1, 10 msec interval, right). Bars indicate means (with SEMs). Data from seven sequential triple recordings; circles connected by lines represent data from the same triple recording. Note a significant difference in the decay time constant (**p
Rapid conductance changes support fast coherent network oscillations
Previous simulations indicated that gamma frequency oscillations emerge in networks of synaptically coupled inhibitory interneurons, emphasizing the importance of the time course of the postsynaptic conductance change [Wang and Buzsáki, (1996)
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Figure 8. Simulation of oscillatory activity in the gamma frequency range in a network of interneurons coupled by fast inhibitory synapses. Aa, Ab, Simulated voltage traces of 15 neurons and rastergram representation of the activity of a network of 100 neurons connected randomly by rapid synapses (synaptic delay 0.8 msec; ) and slow decay time constant of the inhibitory postsynaptic conductance change (
,
, and
, respectively). E, Plot of network coherence
We next analyzed the dependence of mean frequency and coherence on the mean driving current (Fig. 8B,C). Simulations with the fast postsynaptic conductance change revealed that coherent oscillations emerge above a threshold (~2 µA/cm2 assuming MSyn = 60 and I
We further analyzed the tolerance of the oscillatory activity against heterogeneity of the excitatory drive (Fig. 8D). In the absence of heterogeneity, population coherence is close to 1 once a threshold is exceeded (Iµ = 3 µA/cm2). If heterogeneity is included, coherence declines, with an e-fold decline at a relative heterogeneity I
Thus, in comparison to the WB network model, our model based on experimentally determined parameter values generates synchronized oscillations at higher frequencies and demonstrates a higher degree of tolerance against heterogeneity but requires larger driving currents.
DISCUSSION
To determine the functional properties of inhibitory synaptic transmission between interneurons and to examine the factors involved in the generation of fast network oscillations in the hippocampus, we combined paired recordings, morphological analysis, and simulations. We focused on the dentate gyrus for two reasons. First, in the behaving rat, gamma oscillations in the dentate gyrus show a markedly higher power and coherence than in hippocampal CA3 or CA1 regions (Bragin et al., 1995
Interneurons as fast signaling devices
Previous studies showed that interneurons differ from principal cells in several functional and molecular properties, which converge on a faster signaling time course in interneurons. BCs show a fast membrane time constant (~10 msec) (Geiger et al., 1997
Target cell-specific differences in IPSC time course
The major difference between BC-BC synapses and BC-GC synapses is the time course of the postsynaptic conductance change. The mean decay time constant of the IPSC at the BC-BC synapse is approximately two-fold faster than that at the BC-GC synapse (Otis and Mody, 1992
One possibility to explain the differences in the kinetics of IPSCs is the differential expression of GABAAR subunits in different types of postsynaptic target cells. Analysis of recombinant GABAARs revealed that
1
1
2 channels deactivate markedly faster than
Alternatively, the differences in IPSC kinetics may be caused by differential modulation, dependent on the type of the postsynaptic target cell. Immunocytochemical evidence suggests that interneurons, unlike principal cells, do not express calcineurin (Sík et al., 1998
Differences in IPSC kinetics will also have direct implications for network function in vivo. Because putative BCs generate action potentials at high frequency during exploratory activity (Bragin et al., 1995
Presynaptic homogeneity of BC output synapses
BC-BC and BC-GC synapses show similarities in several properties that are thought to be indicators of presynaptic function. First, the reliability of transmission, as assessed by the percentage of failures, is very similar at the two synapses, implying a high release probability and the presence of multiple release sites. Second, both synapses show paired-pulse and multiple-pulse depression, with similar extent and time course (Kraushaar and Jonas, 2000
A functional implication of presynaptic homogeneity is that the balance between excitation and inhibition is maintained during in vivo activity patterns, where GABAergic interneurons generate action potentials over a wide range of frequencies with mean values of 10-20 Hz (Penttonen et al., 1998
Comparison with other brain regions
The difference in the IPSC decay time constant between BCs and GCs in the hippocampus resembles a previously reported difference between Purkinje and granule cells in the cerebellum (Puia et al., 1994
Functional significance of fast IPSCs for the generation of network oscillations
Previous theoretical studies showed that networks of synaptically coupled inhibitory neurons can produce oscillations in the gamma frequency range (Wang and Buzsáki, 1996
Given these differences between experimental observations and the WB model, we have simulated the activity of an inhibitory interneuron network model with fast conductance change and high coupling strength (Fig. 8). A model based on these assumptions was able to generate coherent oscillations with high frequency (>60 Hz) but required a strong excitatory drive, resembling the scenario in the "strong coupling regime" (Neltner et al., 2000
Our interneuron model shows higher tolerance against heterogeneity than the WB model. An e-fold decrease in coherence corresponds to a heterogeneity of I
Fast inhibition: the synaptic basis for gamma oscillations in the dentate gyrus in vivo?
Could our model of inhibitory interneurons be a substrate of the generation of gamma frequency oscillations in the dentate gyrus in vivo? Three lines of evidence may support this view. First, the high oscillation frequency in the model is in good agreement with that observed in the dentate gyrus in vivo (80 Hz) (Bragin et al., 1995
FOOTNOTES Received Oct. 2, 2000; revised Jan. 26, 2001; accepted Jan. 31, 2001.
This work was supported by grants of the Deutsche Forschungsgemeinschaft (SFB 505/C6) and the Human Frontiers Science Program Organization (RG0017/1998-B). We thank Drs. M. V. Jones, J. Bischofberger, and U. Kraushaar for critically reading this manuscript. We also thank B. Taskin and A. Roth for advice in the use of reconstruction and modeling software, and S. Nestel, M. Winter, and A. Blomenkamp for technical assistance.
M.B. and I.V. contributed equally to this work.
Correspondence should be addressed to Dr. P. Jonas, Physiologisches Institut, Universität Freiburg, Hermann-Herder-Strasse 7, D-79104 Freiburg, Germany. E-mail: jonasp{at}uni-freiburg.de.
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