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REPORT

Background Activity Regulates Excitability of Rat Hippocampal CA1 Pyramidal Neurons by Adaptation of a K⁺ Conductance

Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, Amsterdam, The Netherlands

Submitted 1 March 2005; accepted in final form 18 November 2005

	ABSTRACT

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In the in vivo brain background synaptic activity has a strong modulatory influence on neuronal excitability. Here we report that in rat hippocampal slices, blockade of endogenous in vitro background activity results in an increased excitability of CA1 pyramidal neurons within tens of minutes. The increase in excitability constitutes a leftward shift in the input–output relationship of pyramidal neurons, indicating a reduced threshold for the induction of action potentials. The increase in excitability results from an adaptive decrease in a sustained K⁺ conductance, as recorded from somatic cell–attached patches. After 20 min of blockade of background activity, the mean sustained K⁺ current amplitude in somatic patches was reduced to 46 ± 9% of that in time-matched control patches. Blockade of background activity did not affect fast Na⁺ conductance. Together, these results suggests that the reduction in K⁺ conductance serves as an adaptive mechanism to increase the excitability of CA1 pyramidal neurons in response to changes in background activity such that the dynamic range of the input–output relationship is effectively maintained.

	INTRODUCTION

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Synaptic background activity in vivo is the main source of variance in membrane conductance and membrane voltage and therefore determines the probability of firing of the postsynaptic neuron (Destexhe and Paré 1999; Destexhe et al. 2003; Paré et al. 1998). Several in vivo and modeling studies have provided a theoretical framework on the functional role for background synaptic activity. It has been suggested that tonic background activity affects dendritic integration by keeping membrane resistance low and therefore reducing neuronal responsiveness (Bernander et al. 1991; Destexhe and Paré 1999; Holmes and Woody 1989; Paré et al. 1998). Another modeling study (Hô and Destexhe 2000) that focused on the effects of background activity on both membrane conductance and membrane voltage fluctuations predicted that the presence of high-amplitude membrane fluctuations enhances neuronal responsiveness. Experimental studies in which these different aspects of background activity were studied in detail showed that either the effect of background activity on membrane fluctuations alone (Fellous et al. 2003; Shu et al. 2003) or the effects on membrane conductance and membrane fluctuations together (Chance et al. 2002) affect the gain of neuronal input–output relationships.

These studies show how background activity can influence postsynaptic responsiveness and therefore determine the input–output gain of a neuron, although they do not consider the potential role of activity-dependent adaptive gain-setting mechanisms that dynamically control excitability when changes in background activity occur. Considerable changes in background activity will shift the dynamic range of the neuronal input–output relationship such that neuronal responsiveness might be restricted to a limited range of synaptic inputs. This gain-setting problem could be resolved by adapting neuronal gain to the new level of background activity by modulation of voltage-gated conductances. Several of such gain-setting mechanisms exist and it is becoming increasingly apparent that they operate at different timescales. Long-lasting changes in synaptic activity at a timescale of hours to several days induce changes in voltage-gated ionic conductances in a homeostatic manner (Aptowicz et al. 2004; Baines et al. 2001; Desai et al. 1999; Golowasch et al. 1999; Turrigiano et al. 1995). Recent studies, however (Baines 2003; Misonou et al. 2004; Nelson et al. 2003; van Welie et al. 2004), show that activity-induced adaptive mechanisms of neuronal excitability that engage on a timescale of minutes also exist. These experimental findings suggest that, both in vitro and in vivo, relatively rapid changes in background activity could induce adaptive gain-setting mechanisms by modulation of voltage-gated ion channels.

Background activity in vitro is much lower than that in vivo (Paré et al. 1998) but it is nevertheless present. We investigated whether the excitability of hippocampal CA1 pyramidal neurons in vitro is affected by blocking background activity. We show that blockade of background activity induces an adaptive reduction in a sustained K⁺ conductance with no significant activity-dependent changes in Na⁺ conductance, resulting in an increased neuronal excitability. We conclude that acute changes in the level of background activity in vitro can induce an adaptive modulation of a voltage-gated K⁺ conductance that serves to reset the dynamic range of the input–output relationship of CA1 pyramidal neurons.

	METHODS

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Parasagittal slices of the hippocampus (250–300 µm) were prepared from 14- to 21-day-old male Wistar rats (Harlan, Zeist, The Netherlands). Experiments were conducted according to the ethics committee guidelines of animal experimentation of the University of Amsterdam. After decapitation, the brain was rapidly removed and placed in ice-cold artificial cerebrospinal fluid (ACSF) containing (in mM): NaCl, 120; KCl, 3.5; CaCl₂, 2.5; MgSO₄, 1.3; NaH₂PO₄, 1.25; glucose, 25; NaHCO₃, 25, equilibrated with 95% O₂-5% CO₂ (pH = 7.4). Subsequently, slices were cut using a vibroslicer (VT1000S, Leica Microsystems, Nussloch, Germany) and were allowed to recover for 1 h at 31°C.

CA1 pyramidal neurons were visualized using an upright microscope (Zeiss Axioskop, Oberkochen, Germany) with Dodt contrast optics (Luigs and Neumann, Ratingen, Germany) and with a VX44 CCD camera (PCO, Kelheim, Germany). Patch-clamp recordings were made at room temperature. For perforated patch recordings, patch pipettes were pulled from borosilicate glass and had a resistance of 2–4 M when filled with (in mM): K-gluconate, 120; KCl, 20; HEPES, 10; MgSO₄, 1; and sucrose, 10 (pH = 7.4 with KOH). Gramicidin (100 µg/ml, dissolved in DMSO; final DMSO concentration in the pipette solution 0.01%) was added from a fresh stock solution. Input resistance and series resistance were monitored throughout perforated patch recordings to monitor whether the cell entered the whole cell configuration. For whole cell somatic recordings, pipettes were filled with (in mM): K-gluconate, 105; KCl, 30; HEPES, 10; EGTA, 5; CaCl₂, 0.5; and Mg-ATP, 2 (pH = 7.4 with KOH). Series resistance was 6–20 M during whole cell recordings and was compensated for 80%. No correction was made for liquid junction potentials. For cell-attached K⁺ current recordings, pipettes had a resistance of 1.5–3 M and were filled with (in mM): NaCl, 120; HEPES, 10; KCl, 3; MgCl₂, 1; and tetrodotoxin, 0.001 (pH = 7.4 with NaOH). For cell-attached Na⁺ current recordings, pipettes were filled with (in mM): NaCl, 120; HEPES, 10; CaCl₂, 2; KCl, 3; MgCl₂, 1; tetraethylammonium chloride (TEA-Cl), 30; and 4-aminopyridine (4-AP), 15 (pH = 7.4 with HCl). For cell-attached recordings, pipette capacitance was reduced by wrapping pipettes in parafilm. Current signals in whole cell voltage clamp were acquired at 1 kHz and filtered at 500 Hz and voltage signals in current clamp were acquired at 10 kHz and filtered at 3.3 kHz using an EPC9 amplifier and Pulse 8.31 software (HEKA Electronik, Lambrecht, Germany) run on an Apple Mac G3 computer. During cell-attached K⁺ current recordings, current signals were acquired at 10 kHz and filtered at 3.33 kHz. During cell-attached Na⁺ current recordings, current signals were acquired at 200 kHz and filtered at 66.7 kHz. Na⁺ currents were averaged over 10 consecutive sweeps. Fast synaptic background activity was blocked by bath application of 100 µM D-(–)-2-amino-5-phosphonopentanoic acid (AP5), 20–50 µM 6-cyano-7-nitroquinoxaline-2,3-dione disodium (CNQX) and 20–100 µM bicuculline-methochloride or bicuculline-methiodide. All chemicals were purchased from Tocris (Bristol, UK) or Sigma (Zwijndrecht, The Netherlands).

The input resistance of CA1 pyramidal neurons was calculated from voltage-responses to hyperpolarizing current injections given in current clamp (at t = 750–850 ms of the 1-s hyperpolarizing pulse). Synaptic events were detected and analyzed using a custom-made procedure in Igor (Wavemetrics, Lake Oswego, OR) as described previously (van Hooft 2002). K⁺ currents were leak-corrected off-line by using the calculated impedance from a 10-mV voltage step recorded with each trace. K⁺ conductance (g) as a function of voltage (V) was calculated from I(V) using

(1)

where V_rev is the reversal potential of K⁺ currents (–90 mV). The conductance (g) as a function of voltage (V) was fitted by a Boltzmann equation

(2)

where g_max is the maximal conductance, V_h is the potential of half-maximal activation, and V_c is the slope parameter. Na⁺ currents were leak-corrected by a P/4 procedure. Na⁺ currents were fitted to the Goldman–Hodgkin–Katz (GHK) current equation using a Boltzmann function to describe the voltage dependence of the sodium permeability

(3)

with = zF/RT and g_max = F[Na⁺]_outP₀, where F is the Faraday constant, R is the gas constant, T represents the absolute temperature, g_max is the maximal conductance, and P₀ is the maximal permeability.

Note that in the cell-attached configuration, the pipette potential and the resting membrane potential are in series to form the local transmembrane potential, i.e., a pipette potential of 0 mV refers to the resting membrane potential. In this recording configuration, applying a positive pipette potential results in membrane hyperpolarization and applying a negative pipette potential results in membrane depolarization. In the text and figures, we give membrane potentials relative to the resting membrane potential, but we use the standard sign convention that negative potentials indicate a hyperpolarization and positive potentials indicate a depolarization. All values are given as means ± SE. Differences were tested by a Student's t-test. P < 0.05 is assumed to indicate a significant difference.

	RESULTS

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To characterize the level of background activity in hippocampal slices, we recorded spontaneous synaptic events in the whole cell patch-clamp configuration before and after blockade of background activity. In control conditions, the mean frequency of spontaneous synaptic events recorded from CA1 pyramidal neurons for 10–15 min at a holding potential of –60 mV was 1.7 ± 0.3 Hz (n = 6). After blockade of -amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, N-methyl-D-aspartate (NMDA) receptors, and -aminobutyric acid type A (GABA_A) receptors, which mediate fast excitatory and inhibitory neurotransmission, by bath application of CNQX, AP5, and bicuculline, the mean frequency was reduced to 0.01 ± 0.01 Hz (n = 5, P < 0.05, Fig. 1A). Blockade of glutamatergic and GABAergic receptors was complete within <10 min and determination of the input resistance of CA1 pyramidal neurons immediately on complete block of synaptic events showed an increase in input resistance of 10 ± 8% (n = 6).

View larger version (39K): [in this window] [in a new window]   FIG. 1. Blockade of background synaptic activity increases excitability. A: spontaneous synaptic events were recorded in the whole cell patch-clamp configuration in control condition and after bath application of antagonists for AMPA (20–50 µM CNQX), NMDA (100 µM AP-5), and GABAA (20–100 µM bicuculline) receptors. Mean frequency of spontaneous synaptic events recorded for 10–15 min was 1.7 ± 0.3 Hz (n = 6) in control condition and 0.01 ± 0.01 Hz (n = 5) after bath application of antagonists (P < 0.05). B: firing responses of CA1 pyramidal neurons in response to a depolarizing current injection of 80 pA before (top trace) and after blockade of background activity (bottom trace). Bottom: mean input–output relationship in control situation (C), after application of antagonists (A), and after washout of antagonists (W). FF denotes the firing frequency in spikes/s, which is normalized to the maximal value observed in control condition. C: blocking background activity increased the input resistance of neurons, which partly reversed after washout of the antagonists. *P < 0.05. D: plotting firing frequency against calculated membrane potential shows that as a result of the change in input resistance, the input–output relationship covers the same range in membrane potential after blockade of synaptic activity; thus the change in input resistance serves to adaptively control the input–output relationship. E: changes in firing frequency in response to current injections in time. Start of blockade of background activity at t = 10. F: normalized resting membrane potential (Vrest) and input resistance (Rin) in time. Solid lines indicate the mean of the 3 control time points and the dotted lines represent 2 SE of this mean control. Bar indicates the period of block of synaptic activity. Data points in B–F represent means ± SE of 4 neurons.

The intrinsic membrane properties of neurons are largely determined by voltage-gated conductances. We thus set out to determine whether specific voltage-gated conductances were modulated after blockade of background activity. Cell-attached recordings from the soma of CA1 pyramidal neurons were made to investigate K⁺ conductances. K⁺ currents were evoked by depolarizing patches to membrane potentials between +10 and +150 mV after a conditioning hyperpolarizing prepulse of –75 mV (all voltages given are relative to resting membrane potential; see METHODS). Depolarization of patches typically evoked a sustained outward current component, which was often, but not in every patch, accompanied by a fast transient component (Fig. 2A). Simultaneous bath application and inclusion of 10 mM 4-aminopyridine (4-AP) and 30 mM TEA-Cl in the pipette solution blocked both the fast, transient component and the sustained component (data not shown). After 10 min of bath application of the AMPA-, NMDA-, and GABA_A-receptor antagonists, a significant decrease in sustained K⁺ current amplitudes was apparent compared with control recordings from separate patches in which ACSF was superfused. After 20 min of application of antagonists, sustained K⁺ current amplitudes were 46 ± 9% of those in time-matched control patches (n = 7, P < 0.05, Fig. 2B). At this time point we also determined the activation curve of the sustained K⁺ current and normalized it to its own control at t = 0. For control patches, the mean maximal K⁺ conductance (g_max, Eq. 2) after 20 min of ACSF perfusion was 91 ± 5% of its value at t = 0, whereas the K⁺ conductance after 20 min of blockade of background activity was 52 ± 11% of its value at t = 0 (n = 7 for both conditions, P < 0.05, Fig. 2C). The potential of half-maximal activation as well as the slope parameter were not significantly different after blockade of background activity compared with control (Fig. 2D). To test the involvement of large-conductance Ca²⁺-activated K⁺ channels in this sustained current component, we included Cd²⁺ (300 µM) in several patches, which showed equivalent decreases in K⁺-current amplitudes (53 ± 9% of those in time-matched control patches after 20 min of blockade, n = 4, P < 0.05), suggesting that Ca²⁺-activated K⁺ channels are not responsible for the observed effect.

View larger version (27K): [in this window] [in a new window]   FIG. 2. Reduced sustained K+ conductance after blockade of background activity. A: K+ currents in somatic patches in control condition (control) and after blockade of activity (antagonists) in the slice. Example traces are a mean of 5 consecutive sweeps. Amplitude of the sustained K+ current was determined at the end of current traces (squares). Blocking background activity reduced the amplitude of K+ currents. Voltage is indicated as relative to resting membrane voltage (see METHODS). B: normalized K+ current amplitudes before and during application of either standard artificial cerebrospinal fluid (ACSF) or antagonists (application period indicated by the solid bar). K+-current amplitude was normalized to its value at t = 0. After 20 min of blocking activity, K+ current amplitudes were 46 ± 9% of time-matched controls. Data points represent means ± SE of 7 cells. *P < 0.05. C: mean activation curves of K+ currents, normalized to its value at t = 0, recorded 20 min after blockade of background activity (open symbols) or ASCF perfusion (closed symbols). Solid lines represent the fit to the Boltzmann equation (Eq. 3). D: voltage-dependent properties of K+ currents derived from the Boltzmann fit (C) after blockade of background activity were not significantly different from those in control patches. Data points represent means ± SE of 7 cells.

The other main determinant of membrane excitability is the voltage-gated Na⁺ current. To test whether Na⁺ currents were also modulated by the level of background activity, we recorded Na⁺ currents from somatic patches in an experiment comparable to that described for K⁺ currents. Depolarizing the somatic membrane to potentials between +10 and +120 mV from a 1,000-ms hyperpolarizing prepulse of –30 mV (all voltages given are relative to resting membrane potential; see METHODS) resulted in fast transient inward currents (Fig. 3A). Figure 3B shows that the amplitude of the Na⁺ current tended to decrease in time. However, the decrease in time was similar in control condition and in the presence of synaptic receptor antagonists (Fig. 3B): Na⁺-current amplitude after 20 min of blockade was 84% of its time-matched control (control: 85 ± 8%, n = 6; antagonists: 72 ± 8%, n = 6). For control patches, the Na⁺ conductance determined at t = 30 was 52 ± 3% of its value at t = 0, whereas the Na⁺ conductance at this time point was 46 ± 6% of its value at t = 0 (Fig. 3C). The potential of half-maximal activation as well as the slope parameter were not significantly different after blockade of background activity compared with control (Fig. 3D). These results show that neither the conductance nor the voltage dependency of activation of Na⁺ currents is affected by blockade of background activity.

View larger version (25K): [in this window] [in a new window]   FIG. 3. Increase in excitability is not associated with a change in Na+ conductance. A: Na+ currents from somatic patches before and after blockade of background activity. Traces are averages of 10 consecutive sweeps. B: Na+ current amplitudes normalized to its value at t = 0 during either standard ACSF or antagonists application (the period of application is indicated by the solid bar). Na+ currents displayed some rundown in time that was equal in control condition and in the presence of antagonists, indicating that blockade of background activity has no effect on Na+ current amplitudes. C: mean I–V curve of Na+ current, normalized to its value at t = 0, recorded 20 min after blockade of background activity (open symbols) or ASCF perfusion (closed symbols). Solid lines represent the fit to the Goldman–Hodgkin–Katz (GHK) equation (Eq. 3). D: voltage-dependent properties of Na+ currents derived from the GHK fit (C) were not significantly different from those in control patches. Data points represent means ± SE of 4–6 cells.

	DISCUSSION

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The somatic patch recordings of K⁺ and Na⁺ currents suggest that the adaptive reduction in K⁺ currents is responsible for the increase in excitability as recorded in whole cell perforated patch mode. This reduction appeared to be the result of a change in maximal conductance, rather than a change in voltage-dependent properties of the sustained K⁺ current, although we cannot completely rule out the latter. Recently, it was shown that glutamate stimulation, which mimics an increase in synaptic activity, results in an enhanced sustained K⁺ current (K_v2.1) in cultured rat hippocampal neurons (Misonou et al. 2004). Glutamate application causes a rapid dephosphorylation of delayed rectifier K⁺ channels, a translocation of these channels to the membrane and a shift in the voltage-dependent activation of the delayed rectifying current. The change in voltage dependency of activation enhances the K⁺ current and this effect was already apparent after 10 min of glutamate stimulation. The observations of Misonou et al. describe a functional upregulation of the delayed rectifier as a result of glutamate application that is complementary to our condition of reduced background activity. However, we did not detect a significant change in voltage-dependent properties of the sustained K⁺ conductance, but a large decrease in maximal conductance, suggesting that the underlying molecular mechanisms may be different. Because of the similarity in timescale on which these two different mechanisms operate, however, they could be complementary mechanisms in the activity-dependent dynamic control of neuronal excitability.

Several studies have shown that voltage-gated conductances can be modulated in an adaptive or homeostatic manner by synaptic activity. Most of these mechanisms were found to occur after long-term modulation of activity of hours to days (Aptowicz et al. 2004; Baines et al. 2001; Desai et al. 1999; Golowasch et al. 1999; Turrigiano et al. 1995), although more recent studies have shown that adaptive modulation of voltage-gated conductances can also occur on a timescale of minutes (Baines 2003; Misonou et al. 2004; Nelson et al. 2003; van Welie et al. 2004). The fact that several mechanisms have now been observed at different timescales suggests the existence of a range of different underlying molecular mechanisms that may include modulation of ion channel density by either transcriptional or translational regulation as well as modulation of ion channel function by posttranslational mechanisms such as phosphorylation or dephosphorylation. It will be important to investigate how these modulatory mechanisms relate to the levels and duration of changes in activity. One study reported activity-dependent changes in Na⁺- and K⁺-channel conductances that occurred only after modulating activity for >24 h (Desai et al. 1999). In that study, activity was blocked in cultured neocortical neurons, which resulted in an increase in excitability that was correlated to an increase in Na⁺ conductance and a decrease in persistent K⁺ conductance. The downregulation in sustained K⁺ current we find is equivalent to the results from Desai et al. (1999), although we did not see an increase in Na⁺ conductance and the increase in excitability we report is already apparent after 10–20 min. Desai et al. (1999), however, did not investigate time points <2.5 h. Also, activity was blocked by blocking postsynaptic receptors in our experiments, whereas in the study of Desai et al. (1999) activity was blocked at the presynaptic side, which might have important implications for the mechanisms induced. These differences might indicate that sustained K⁺ conductances can be regulated at different timescales by a variety of underlying molecular mechanisms.

In summary, we have shown that CA1 pyramidal neurons in the in vitro slice preparation dynamically adapt their input–output relationship in response to blockade of background activity by scaling a voltage-gated K⁺ conductance. This mechanism may act in concert with the previously proposed gain-setting roles of background activity (Chance et al. 2002; Fellous et al. 2003; Shu et al. 2003). We conclude that regulation of neuronal excitability is a highly dynamical process and that voltage-gated channels are subject to activity-dependent adaptive modulation at shorter timescales than previously assumed.

	GRANTS

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This work was supported by a fellowship of the Royal Netherlands Academy of Arts and Sciences to J. A. van Hooft.

	ACKNOWLEDGMENTS

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Present address of I. van Welie: Systems Neurobiology Laboratories, The Salk Institute for Biological Studies, La Jolla, CA 92037.

	FOOTNOTES

 
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Address for reprint requests and other correspondence: W. J. Wadman, SILS–Center for Neuroscience, University of Amsterdam, P.O. Box 94084, 1090 GB Amsterdam, The Netherlands (E-mail: wadman{at}science.uva.nl)

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This Article Abstract Full Text (PDF) All Versions of this Article: 95/3/2007    most recent 00220.2005v1 Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (2) Citing Articles via Google Scholar Google Scholar Articles by van Welie, I. Articles by Wadman, W. J. Search for Related Content PubMed PubMed Citation Articles by van Welie, I. Articles by Wadman, W. J.