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Department of Psychology and Interdepartmental Neuroscience Program, University of California, Riverside, California
Submitted 6 September 2004; accepted in final form 7 March 2005
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ABSTRACT |
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INTRODUCTION |
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; Calford 2002) and in both developing (Katz and Shatz 1996) and adult (Kaas 1991; Weinberger 1995) animals. Cortical reorganization is associated with important physiological and pathological processes, including improvements in performance after sensory training (Diamond et al. 1999; Jenkins et al. 1990; Recanzone et al. 1992a,b; Wang et al. 1995), the genesis of "phantom" pain and sensation after amputation (Borsook et al. 1998; Flor et al. 1995; Ramachandran and Hirstein 1998), and recovery of function after stroke (Friel and Nudo 1998; Nudo 1997). Thus understanding the mechanisms that underlie cortical reorganization is an important question for integrative neuroscience.
In adults, cortical organization and reorganization has been particularly well-studied in the primary somatosensory cortex (S1) of primates (Kaas 1991; Kaas and Collins 2003) and rodents ("barrel" cortex; Fox 2002; Petersen 2003). A variety of experimental manipulations have been used to induce reorganization in S1, one of the most common of which is denervation of the sensory periphery by amputation or nerve section. Such denervation causes loss of sensory activity in the corresponding somatotopic representation in S1, which causes expansion of adjacent areas into the deafferented region of cortex. Thus the border between the two parts of the representation shifts into the deafferented region (Hickmott and Merzenich 2002; Kaas 2000; Merzenich et al. 1983). Such reorganization can occur very rapidly (minutes) and can progress for years (Calford and Tweedale 1991; Pons et al. 1991). It is important to note that reorganization occurs in the somatotopic maps in lower nuclei of the somatosensory pathway (thalamus, hindbrain, spinal cord), as well as cortex. Changes at these lower levels would be communicated to the cortex and account for some of the changes observed in cortex; however, at least some of the changes observed in the cortical map occur due to changes in the cortex itself (Jones and Pons 1998).
During reorganization, new pathways for information transfer in the cortex, either based on changes in existing connections or based on newly generated connections, must be created. How could these changes occur? Both anatomical and physiological changes have been observed in the cortex associated with cortical reorganization. Sprouting of new connections is associated with reorganization in primary visual cortex (Darian-Smith and Gilbert 1994; Trachtenberg and Stryker 2001) and S1 (Florence et al. 1998). The dendritic structure of neurons within the cortex can also change to reflect changes in cortical organization (Harris and Woolsey 1981; Hickmott and Steen 2005; Kossel et al. 1995; Steffan and Van der Loos 1980; Tieman and Hirsch 1982). In addition to these novel connections, there are clear changes in the efficacies of existing cortical synapses (Finnerty and Connors 2000; Finnerty et al. 1999), which may involve the well-studied processes of long-term potentiation (LTP) and long-term depression (LTD) (Allen et al. 2003; Buonomano and Merzenich 1998). Thus the cortical circuit is highly dynamic in response to changes in incoming activity. Another important, and less-studied, determinant of information flow through the cortical circuit involves the intrinsic excitability and input/output relations of cortical neurons. It is known that manipulations of experience, particularly learning (Disterhoft et al. 1986; Saar and Barkai 2003; Schreurs et al. 1998) and direct manipulations of activity (Aizenman and Linden 2000; Aizenman et al. 2003; Desai et al. 1999a; Franklin et al. 1992; Garcia et al. 1994; Li et al. 1996; Maravall et al. 2004a; Nelson et al. 2003; Sourdet et al. 2003; Turrigiano and Nelson 2004; Zhang and Linden 2003) can rapidly change the intrinsic properties of neurons in a variety of systems, including the cortex. For example, a recent study in developing rat S1 has shown that supragranular pyramidal cells increase their intrinsic excitability during early development (PND 12–17), that this change in properties is associated with the close of the critical period for deprivation-induced map plasticity, and that sensory deprivation affects some of the changes in intrinsic properties. Furthermore, the changes in spiking properties were related to changes in the strength of a slow Ca2+-dependent afterhyperpolarization (AHP) (Maravall et al. 2004a). Slow AHPs are also the target of experience and training-dependent plasticity in various other systems (Desai et al. 1999a; Disterhoft et al. 1986; Franklin et al. 1992; Nelson et al. 2003; Schreurs et al. 1998; Sourdet et al. 2003).
In this paper, I use denervation of the forepaw in the adult rat to induce reorganization in S1. This manipulation has been shown to cause a shift in the location of the border between the forepaw and lower jaw representations that occurs very quickly (<1 h of denervation) and continues to shift over time (Hickmott and Merzenich 2002). We have previously shown that these changes in the location of the border are associated with changes in the dendritic morphology and synaptic properties of supragranular neurons in the reorganized region (Hickmott and Merzenich 2002; Hickmott and Steen 2005), both of which change to reflect the presence of the new border. Here, I examined the intrinsic properties of supragranular pyramidal neurons in adult rat S1 after different durations of forepaw denervation. Two changes were observed at all durations of denervation (1 h to 28 days): 1) an increase in the amplitude of the fast and medium AHP and 2) an increase in the interspike interval (ISI). A transient increase in the AP threshold was also observed. Taken together, these data suggest that there is a general decrease in the excitability of supragranular pyramidal cells during denervation-induced reorganization of adult rat S1.
Some of these data have been previously presented in abstract form (Hickmott 2003).
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METHODS |
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Methods for extracellular recording from adult anesthetized rat primary somatosensory cortex (S1) were similar to those used previously (Hickmott and Merzenich 1998, 2002). These methods are briefly summarized here. For all surgical procedures, adult Sprague-Dawley rats (280–350 g) were anesthetized to an areflexic level with pentobarbital sodium (50 mg/kg, ip) and mounted in a stereotaxic frame. Supplemental doses of anesthetic were administered as needed. For all recovery surgeries, aseptic procedures were used. All surgical procedures were approved by the Institutional Animal Care and Use Committee at the University of California Riverside.
To determine the amount of shift in the forepaw/lower jaw border, the region of S1 around the border was mapped twice: once before the denervation and once after the desired duration of denervation. For animals subject to a chronic denervation (>1 h), the first map was derived using transdural electrode penetrations; otherwise, the dura was removed. Because the rat dura is relatively transparent, it was possible to see the larger surface blood vessels on the cortex. Carbon-fiber electrodes that had been cut well back on the glass supporting the fiber were used to penetrate the dura and cortex. The forepaw or lower jaw was stimulated with a fine probe to elicit multiunit cutaneous responses in S1. Responsiveness to forepaw and/or lower jaw stimulation was determined subjectively by listening to audio monitor output. Penetrations were introduced into the forepaw zone, 1–2 mm rostral to Bregma; subsequent penetrations were introduced more laterally until regions that responded to tactile stimulation of the lower jaw were encountered. Recordings were all at an approximate depth of 500–700 µm. The location of penetrations was recorded on the computer image of the cortex by using surface vasculature landmarks. Penetrations spaced <50 µm apart were made to locate the border more exactly. Typically, three of these rows of penetrations were made, arranged perpendicular to the forepaw/lower jaw border, which is normally oriented roughly parallel to the midline. Rows were separated by 400–500 µm. Three or four locations on the forepaw/lower jaw border were marked with a recording electrode that had been repeatedly dipped in a 1–2% DiI (Molecular Probes) solution (in ethanol), and the DiI crystals were allowed to deposit on the electrode (DiCarlo et al. 1996). The electrode was introduced into the cortex to recording depth, the responses of the penetration were confirmed, and the electrode was left in the cortex for 3–5 min. Subsequently, the craniotomy was covered with Gelfoam (Pharmacia and Upjohn) and the scalp sutured.
Reorganization of the forepaw/lower jaw region was induced in some animals by peripheral denervation of the forepaw. After the initial mapping of the forepaw/lower jaw border, the radial and median nerves of the forepaw contralateral to the mapped hemisphere were exposed, a 1–2 mm segment was cut from each nerve, and the remaining cut ends of the nerves were tightly ligated with 6–0 suture thread to prevent nerve regeneration. Animals were allowed to recover for the desired duration of denervation (1 h or 7, 14, or 28 days) before the second mapping of the forepaw/lower jaw border was performed. Note that after the second in vivo mapping, the forearm was reopened and the nerves were examined for signs of regeneration. Animals in which there was evidence of regeneration were not used for these experiments.
After the appropriate duration of denervation, the second map of the forepaw/lower jaw border in S1was derived in a similar manner to the first. The craniotomy was reopened, the dura was removed, and the exposed cortex was covered by silicone oil. Response mapping of the forepaw/lower jaw region was again performed using carbon-fiber electrodes. The novel forepaw/lower jaw border (i.e., the reorganized border) was marked by DiI. The shift in the border was defined as the distance between the two DiI marks. Because the DiI marks differed markedly in appearance, it was possible to determine which was at the original border and which was at the reorganized border (see Hickmott and Merzenich 2002). Note that for acute denervations, only a single DiI mark was necessary because the shift in the border could be quantified directly from the map in vivo. To assess possible effects of the surgery, two groups of sham animals were examined; in these animals, the mapping and marking was identical to experimental animals, but the nerves were not cut and ligated. Both 1-h and 14-day sham surgeries were performed. After marking, the animal was decapitated, the brain was rapidly removed, and 400-µm-thick coronal slices were cut on a vibratome from the marked region of cortex. Slices with dye marks locating the original and reorganized border were selected for use in vitro (Fig. 1C). These slices were maintained in standard mammalian bicarbonate buffer (in mM: 119 NaCl, 2.5 KCl, 1.25 NaH2PO4, 1.3 MgSO4, 2.5 CaCl2, 26.2 NaHCO3, and 11 glucose, saturated with 95%O2-5%CO2) for intracellular recording. Note that these and all subsequent chemicals were obtained from Sigma/Aldrich Chemical unless otherwise stated.
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Neurons for recording were obtained using blind whole cell recording (Blanton et al. 1989) from a region near the original or reorganized border (
100–300 µm) in cortical layer 2/3 (Fig. 1C). Patch electrodes were pulled on a Flaming/Brown puller to a tip diameter of 1.5–2.5 µm and filled with (in mM) 128 K-gluconate, 7 KCl, 1 EGTA, 10 HEPES, 2 Mg-ATP, and 0.2 Na-GTP; 0.3–0.5% biocytin was included in some experiments, pH 7.0–7.4. Such electrodes had tip resistances of 3–8 M
. Only neurons with initial resting potentials of less than –60 mV and stable input resistances of >50 M were used. Input resistance was determined using a –0.1 nA continuous current pulse. For recording, positive or negative current was injected to maintain the membrane potential at –70 mV (except when recording medium AHPs). Slices were maintained at 30.5 ± 1°C.
Recorded signals were amplified using an Axoclamp 2B amplifier (Axon Instruments), digitized at 10 kHz, and saved to the hard disk of a Macintosh G4 computer using the Igor Pro (Wavemetrics) data acquisition system. Stimuli were delivered in current-clamp mode. Square pulses of current (duration 200 ms) were delivered at 0.2 Hz. Input-output (I/O) relations were determined for subthreshold responses and for APs, typically starting at –1 nA and increasing in current amplitude by fixed steps, typically up to +2 to +4 nA. For single APs, the point of inflection where the depolarizing spike started was determined by differentiating the voltage trace twice and finding the inflection point. The AP amplitude was determined from baseline to peak, the threshold as the membrane potential measured at the inflection point, and the half-width as the width of the depolarizing spike at 50% of spike amplitude (see Fig. 2). For trains of APs, the number of spikes elicited by each suprathreshold current step was determined and plotted against the current amplitude (Fig. 3B). The resulting plot was fit with a single exponential function (Fig. 3B). The current to elicit a single spike (rheobase) was calculated by extrapolation of the exponential curve, and the maximum number of spikes was determined from the asymptote of the curve. To determine the input/output (I/O) relation of the cell, the data were replotted semi-logarithmically, and the slope of the linear fit to the data was calculated; this slope provided a measure of the I/O relation. Spike accommodation was quantified by measuring the minimum ISI for the first ISI and for the last ISI (Fig. 3A). For subthreshold responses, the steady-state amplitude was measured at 150 ms of the stimulus. The subthreshold I/O relation was determined by plotting the current versus the steady-state voltage. This I/O relation was divided into two plots: one corresponding to hyperpolarizing currents and one to depolarizing. The slope of the line through each of these plots (I/O slopehyp and I/O slopedep) was used for quantification (see Fig. 4). Also, for hyperpolarizing stimuli, there was a fast inward rectification (IR) of the voltage (Fig. 4A). This voltage was defined as the difference between the early transient hyperpolarization (measured at 20 ms after stimulus onset) and the steady-state voltage (see Fig. 4). For AHP, the fast AHP (fAHP) was defined as the difference between the peak of the rapid hyperpolarizing voltage after a single AP and the threshold of the AP (see Fig. 5A). The medium AHP (mAHP) was measured with the membrane voltage adjusted to –55 mV. The mAHP was evoked with a train of 8–10 APs and defined as the difference between the peak of the hyperpolarization after the offset of the current pulse and the baseline (see Fig. 5B).
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20 min of application. Washout, when possible, was by perfusion with normal buffer and was performed for 45 min. All data are presented as means ± SE. Data were analyzed using one-way ANOVA, followed by individual comparisons using Fisher's protected least-squares difference (PLSD). A P value of 0.05 was considered significant.
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RESULTS |
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Our previous studies have shown that the forepaw/lower jaw border shifts in the direction of the deafferented forepaw region after denervation of the forepaw (Hickmott and Merzenich 2002). This reorganization is depicted schematically in Fig. 1A and quantified in Fig. 1B. With an acute (<1 h) denervation, there was a rapid, small shift in the border (Fig. 1A, solid line) into a region of cortex that could not be driven from the periphery (Fig. 1A, stippled area). With longer durations of denervation, the shift in the border increased (Fig. 1B), and the region of cortex that was unresponsive to peripheral stimulation decreased until it was no longer detected (typically after 14 days of denervation). Note that there was no significant shift in the border with either acute (open bar) or 14-day (vertical hatch) sham denervation.
In vitro recording
A total of 90 neurons in 51 animals were analyzed: 13 in 7 for controls, 14 in 6 for acute denervation, 16 in 8 for 7 days of denervation, 15 in 8 for 14 days of denervation, 12 in 8 for 28 days of denervation, 5 in 3 for acute sham denervation, 6 in 3 for 14 day sham denervation, 9 in 6 for picrotoxin application, and 4 in 2 for apamin application. All cells analyzed were in cortical layer 2/3 and were classed as regular spiking (RS) cells based on the spike accommodation observed in response to larger current injections (Fig. 3). Cells exhibiting other spiking patterns (fast spiking) were encountered infrequently and were not analyzed in this study. In some cases, biocytin was included in the recording pipette, and the morphology of neurons was recovered. In all cases where the morphology of RS cells was determined, they were pyramidal cells (data not shown). Figure 1C depicts the locations at which cells were recorded in nondenervated control animals (Fig. 1C, left) and in denervated animals (Fig. 1C, right). In control animals, neurons were obtained close to the forepaw/lower jaw border on either the lateral (lower jaw; 7/13) or medial (forepaw; 6/13) side of the border. There was no significant difference in the values obtained from these two locations; therefore the data were pooled. In denervated animals, neurons were obtained in three locations: medial to the reorganized border, between the reorganized and original borders, and lateral to the original border. For each duration of denervation, there was no significant difference among the values obtained at each of these three sites, so the data were pooled for each duration of denervation. Data obtained from the two groups (acute and 14 days) of sham-treated animals did not differ significantly from those obtained from normal animals (data not shown). Thus the effects observed were specific to animals that underwent a denervation and were not influenced by the other surgical procedures.
Table 1 presents the mean resting potentials and input resistances for the five categories of neurons (control and the 4 durations of denervation). There was no significant difference among either of these parameters for any of the durations of denervation. The values for both resting potential and input resistance are, however, significantly smaller than those obtained in a previous study (unpaired t-test; Hickmott and Merzenich 2002). This difference is likely due to the use of K+-based filling solution in this study and Cs+-based filling solution in the previous study. Cs+ blocks a variety of K+ channels (Hille 2001) and thus would tend to depolarize the resting potential and increase the input resistance, as was observed.
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All neurons could be induced to fire APs with depolarizing current injection. Currents just above threshold produced a single action potential, consisting of a rapid depolarization (spike) followed by fast and slow AHPs (Fig. 2A). These APs are very similar to those observed in layer 2/3 pyramidal cells by other groups (Agmon and Connors 1992; Amitai and Connors 1995; McCormick et al. 1985). To quantify the spikes observed (AHPs are quantified in Fig. 5), three parameters were determined (Fig. 2, A and B): the threshold voltage to trigger the AP, the amplitude of the spike, and the width of the spike at 50% of the spike amplitude. The effects of denervation on these parameters are shown in Fig. 2C. There was a significant increase in the AP threshold after acute (black), 7-day (gray), and 14-day (diagonal hatch) denervations; however, at 28 days of denervation, AP threshold had returned to normal levels (horizontal hatch). No changes were observed in either AP amplitude or width after any duration of denervation.
Because it is possible that changes in tonic inhibition might underlie the changes in threshold, and tonic inhibition has been observed in cortical slices (Salin and Prince 1996; Ulrich 2003), we examined the effects of 20 µM picrotoxin on AP threshold in normal animals (n = 4 neurons) and in acutely denervated animals in which the threshold was increased (n = 4 neurons). No effect of picrotoxin on the threshold was observed in either case (data not shown).
I/O relations and accommodation of AP trains
All neurons fired a train of APs with sufficiently large suprathreshold depolarizations; these trains showed the accommodation diagnostic of RS cells and an increase in the number of spikes evoked (in 200 ms) with increasing depolarization (Fig. 3, A and B). An important determinant of the ability of neurons to transmit and amplify information is the I/O relation for that neuron, i.e., for a given amount of depolarization, what is the resulting number of APs. To quantify the I/O relation for a neuron, the number of APs was determined for depolarizing currents of increasing amplitude (200 ms duration), as shown in Fig. 3B. The resulting plots were well fit by a single exponential (Fig. 3B). The rheobase and maximal number of spikes were determined from these exponentials for each neuron. To determine the complete I/O relation for each cell, the data were linearized by plotting it semi-logarithmically and determining the slope of the linear fit to that plot. There was a no significant difference in any of these three parameters at any duration of denervation (Fig. 3C). Another characteristic of spike trains of RS cells is spike accommodation (or spike frequency adaptation). This phenomenon was quantified by measuring the first ISI and also the last ISI for the highest-frequency AP train (Fig. 3A). As shown in Fig. 3C, there was a significant increase in the minimal ISI for the last ISI, but not for the first ISI, for all durations of denervation. A possible role for tonic inhibition in this increase in ISI was assessed by bath-applying 20 µM picrotoxin to the slices. No significant effect of picrotoxin on ISI or on the other I/O parameters examined was observed in normal animals (n = 4 neurons, data not shown) or in acutely denervated animals (n = 4 neurons, data not shown).
Subthreshold response properties
Possible changes in other voltage-activated potentials were assessed using subthreshold current injections, both hyperpolarizing and depolarizing. Figure 4A shows an example of the subthreshold responses in a typical layer 2/3 pyramidal cell. Figure 4B shows the subthreshold I/O relation for the cell shown in Fig. 4A. The steady-state voltage (measured at 150 ms of depolarization) is plotted in Fig. 4B by the circles. For hyperpolarizing currents, the steady-state voltage is relatively linear. However, for depolarizing currents, there is clear outward rectification for the steady-state voltages, indicative of voltage-gated depolarizing currents. To quantify the subthreshold I/O relation, two lines were fitted to the plot: one fit to the voltages resulting from hyperpolarizing currents and one fit to those resulting from depolarizing currents (solid lines). The slopes of these lines (I/O slopehyp and I/O slopedep) were used to quantify the I/O relation for each neuron. There was no significant difference among either of these slopes after any duration of denervation (Fig. 4C, left). With larger hyperpolarizing currents, a transient inward rectification of voltage was typically observed, peaking at 20 ms after the onset of the current (Fig. 4A, IR amplitude). Thus there was also a hyperpolarization-activated voltage, at least for larger hyperpolarizations. In Fig. 4B, this transient voltage is plotted for the cell shown in Fig. 4A (squares, dotted line). To quantify this IR voltage, the difference between the transient peak voltage and the steady-state voltage was calculated for a hyperpolarization induced by a –1 nA current. This value is shown in the right graph of Fig. 4C. There was no significant difference in the IR voltage after any duration of denervation. Thus overall, there were no differences in the subthreshold properties of layer 2/3 pyramidal neurons after peripheral denervation.
Fast and slow AHPs
An important target for a variety of experience-dependent alterations in neuronal intrinsic properties are fast and slow AHPs (Zhang and Linden 2003). These AHPs are generated by the opening of K+ channels. fAHPs are generated by both voltage-gated K+ channels, such as IA, and by Ca2+-activated K+ channels. sAHP are generated by Ca2+-activated K+ channels and are divided into two types, referred to as mAHPs and slAHPs based on differences in time-course and pharmacology. AHPs are known to be important for regulating the spiking kinetics and spike frequency of neurons (Hille 2001; Sah 1996). fAHPs were observed after single APs (Fig. 2A) and were quantified as the difference between the peak of the negative voltage and the inflection point that defined the initiation of the spike (Fig. 5A). To observe sAHPs, current was injected into neurons to a membrane potential of –55 mV, and a train of 8–10 APs was evoked (Fig. 5B). The mAHP was quantified as the difference between the peak of the negative potential after this train and baseline (Fig. 5B). The slAHP was not quantified in these studies. Both fAHPs and mAHPs increased significantly after denervation (Fig. 5C). fAHPs increased at all denervations except acute (Fig. 5C, left), whereas mAHPs increased after all durations of denervation (Fig. 5C, right). To confirm the identity of the mAHP, 500 nM apamin, which specifically blocks the mAHP without affecting the fAHP or slAHP, was bath-applied to slices from acutely denervated animals. In all neurons tested (n = 4), apamin blocked the mAHP (Fig. 5D, right), with no effects on the fAHP (Fig. 5D, left). The mean amplitude of the mAHP before apamin was –6.03 ± 0.88 mV and was –2.41±.0.63 mV in the presence of apamin. Note that this block of the mAHP caused changes in the I/O relation and accommodation of the spike trains. The slope of the I/O relation was 11.07 ± 1.1 before and 11.3 ± 1.3 after; the maximum number of spikes before was 27.5 ± 2.7 and after was 28.6 ± 2.8; the minimum first ISI was 2.7 ± 0.3 before and 2.6 ± 0.5 after; and the minimum last ISI was 11.1 ± 1.4 before and 9.5 ± 1.8 after. In control animals, in which the mAHP was small (Fig. 5C, right), apamin reduced the mAHP amplitude from –2.1 ± 0.9 to –1.47 ± .55 mV (n = 4; data not shown). Apamin had no effect on the I/O relation or accommodation in these control neurons (data not shown).
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DISCUSSION |
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The reorganization observed is similar to those observed previously in this system (Hickmott and Merzenich 2002) and in other systems after denervation or amputation (e.g., McCandlish et al. 1996; Merzenich et al. 1983). A very rapid initial shift in the border was followed by a more protracted shift (Fig. 1B). While it is clear that reorganization of the somatotopic maps occurs at all levels of the ascending somatosensory pathway (Jones and Pons 1998), this subcortical reorganization does not explain all the reorganization that occurs in cortex (Buonomano and Merzenich 1998). Unsurprisingly, various types of changes have been documented to occur in the isolated cortex after reorganization, including sprouting of axons (Darian-Smith and Gilbert 1994; Florence et al. 1998; Trachtenberg and Stryker 2001), changes in synaptic efficacies (Finnerty et al. 1999; Li and Waters 1996), and restructuring of dendrites (Harris and Woolsey 1981; Hickmott and Steen 2005; Kossel et al. 1995; Maravall et al. 2004b; Steffan and Van der Loos 1980).
The neurons analyzed here were all classified as RS cells based on their response to depolarizing stimuli (Fig. 3A). Previous studies have shown that layer 2/3 pyramidal cells are the population that exhibits RS behavior in normal adult S1 (Agmon and Connors 1992; Amitai and Connors 1995; McCormick et al. 1985). In the cases where the morphology of neurons was determined, we also found that RS neurons had pyramidal morphology (data not shown) and thus are convinced that the neurons examined here were indeed layer 2/3 pyramidal cells. As such, these cells receive the bulk of their excitatory inputs from other layer 2/3 pyramids, as well as some from layer 4 and from thalamocortical projections. Their outputs are mainly to other parts of superficial cortex (Amitai and Connors 1995). Thus they play a vital role in shaping responses in the cortex, particularly in terms of intracortical communication. These layer 2/3 neurons are thus well positioned to participate in changes in cortical organization.
Given that peripheral denervation is accompanied by a large decrease in activity to S1, the effects of denervation on intrinsic properties were fairly small. No change in either resting potential or input resistance was observed (Table 1), in contrast to our previous results where a small reduction in input resistance was observed at all durations of denervation (Hickmott and Merzenich 2002). In addition, both the resting potential and input resistance were smaller in this study. These differences are likely due to the use of K+ based filling solution in this study, while Cs+ based solution was used previously. Cs+ blocks multiple types of K+ channels and would be expected to depolarize cells slightly and increase their input resistance.
Our previous results documented significant changes in the synaptic (Hickmott and Merzenich 2002) and dendritic (Hickmott and Steen 2005) properties of neurons during reorganization. Some, but not all, of these changes were specifically related to the shift in the location of the border induced by denervation (i.e., the changes were different at the original and reorganized border site). Such effects appear to be specifically related to the changes in relative activity patterns caused by the loss of peripheral input to the medial forepaw. Certain changes in dendritic structure (i.e., the observed increase in dendritic complexity close to the soma) were similar for the entire reorganized region. Perhaps these changes reflect more general signals, such as some form of permissive signal, in the reorganizing region. This reorganizing region includes all three populations of neurons that we examined (see Fig. 1C), and thus it is unsurprising that these three populations could respond to reorganization in a similar fashion. The changes in intrinsic properties documented here also did not differ when analyzed with respect to the original and reorganized borders; the changes were general across the reorganizing region.
The subthreshold properties, AP properties, and AHP properties observed here were similar to those observed previously (Agmon and Connors 1992; Amitai and Connors 1995; Maravall et al. 2004a; McCormick et al. 1985). Two main effects of denervation were observed for AP properties: a transient increase in threshold for acute, 7-day, and 14-day denervations (Fig. 2) and an increase in the ISI for multiple spikes (Fig. 3). There were further effects on AHPs: fAHPs were increased at denervations >7 days, whereas mAHPs were increased at all durations of denervation (Fig. 5). These changes would tend to decrease the excitability of neurons. This result was unexpected, because in many systems, decreasing activity leads to increases in the intrinsic excitability of neurons, a process often termed "homeostatic" plasticity (Turrigiano and Nelson 2004). Given that a major consequence of denervation, particularly with shorter durations of denervation, would be a loss of activity from the periphery, how can we explain the decrease in excitability observed at short durations of denervation? One possibility is that denervation may cause an increase in release of brain derived neurotrophic factor (BDNF) or a similar neurotrophin in the reorganizing forepaw/lower jaw border region to encourage the sprouting of new axons or dendrites (McAllister 2000). In cultures of cortical neurons, BDNF has been shown to block the increase in excitability observed in cultures of cortical neurons after 48 h of activity blockade, whereas decreasing levels of BDNF lead to increases in excitability. In these cultures, effects on both Na+ and on K+ currents were observed (Desai et al. 1999b), as was observed in our experiments (Figs. 2 and 5). Thus it is possible that increased levels of BDNF in the reorganizing region of S1 led to the decreases in excitability observed. In our studies, as in other studies, changes in the ISI were observed (Fig. 3) that almost certainly result from the increase in AHPs (e.g., Schwindt et al. 1988). Considering that the changes in excitability that we observed were not different depending on the location of neurons with respect to the original and reorganized borders (Fig. 1C), a general signal, such as BDNF release, is an attractive possibility.
Another possibility is that the assumption that changes in activity necessarily lead to the opposite change in neuronal excitability, particularly for neurons embedded in a complex excitatory/inhibitory network, may not be correct. For example, in mouse S1 repetitive depolarization of single neurons has been shown to result in long-lasting decreases or increases in the excitability of that neuron, not exclusively a decrease in excitability as would be expected from a strict homeostatic model (Loweth et al. 2003).
The changes observed here are similar to the ways in which intrinsic excitability is regulated by activity in other systems (see Zhang and Linden 2003 for review). In particular, sAHPs have been shown to be a very common target for experience and activity-dependent changes in excitability (Zhang and Linden 2003). These sAHPs are mediated by Ca2+-activated K+ currents (Hille 2001; Sah 1996). Particularly relevant to the data presented here is a recent study in developing rat S1, which showed that the change in firing pattern of layer 2/3 pyramidal cells at postnatal days 12–17 was related to changes in a slow Ca2+-mediated sAHP. Furthermore, the change in sAHP properties could also be delayed by manipulating activity (whisker trimming; Maravall et al. 2004a). Thus an important component of plasticity in the developing system continues to be important during adult plasticity. sAHPs have also been implicated in learning-induced modifications of excitability in rat frontal cortex (Saar et al. 1998) and in hippocampus (Disterhoft et al. 1988). Changes in AHPs (fast and slow) are thought to affect such diverse phenomena as the induction of various forms of synaptic plasticity (Sah and Bekkers 1996), changes in the I/O relation for spikes (Desai et al. 1999a), changes in excitatory postsynaptic potential (EPSP)-spike coupling (Daoudal et al. 2002), and changes in the temporal fidelity of APs (Sourdet et al. 2003).
In the studies referred to above (Maravall et al. 2004a; Saar et al. 1998), the precise identity of the sAHP that was affected was not determined. The sAHP is mediated by two major components (mAHP and slAHP) that are differentiated kinetically and pharmacologically and are mediated by different underlying Ca2+-activated K+ channels (Sah and Faber 2002). The sAHP that was increased by reorganization in our studies was the mAHP, because it was blocked by low concentrations of apamin (Fig. 5D); effects of denervation on the fAHP were also observed. It is interesting to note that apamin had a larger effect on the mAHP from denervated animals than on that from control animals (see RESULTS). Thus there was an increase in the apamin-sensitive component of the mAHP during denervation. Because the mAHP is mediated by SK channels (Sah and Faber 2002), this finding suggests that there is an increase in SK channel activity during cortical reorganization. An alternative hypothesis is that the change in mAHP was due to a change in calcium handling within these neurons, as was observed during S1 development (Maravall et al. 2004b), which would affect this calcium-activated current.
In cortex, blocking the mAHP with apamin is known to change the I/O relation of trains of APs, yielding more spikes for a given level of depolarization with a concomitant decrease in ISI (e.g., Schwindt et al. 1988). Similar effects of apamin were observed in the layer 2/3 pyramidal cells studied here, although the effects were small and not significant (see Fig. 5D and RESULTS). Thus the increase in the mAHP observed with denervation (Fig. 5C) probably is responsible for the increase in ISI observed (Fig. 3C). With this increase in mAHP and ISI, one might expect to observe a decrease in the number of spikes evoked with larger depolarizations, but no significant decrease was observed (Fig. 3C). Because the effects on I/O relation of completely blocking the mAHP with apamin were small (only 1–2 spikes over the 200-ms depolarization), it is unsurprising that the effects of the increased mAHP were also small and not significant. Perhaps using a longer duration depolarization (>200 ms) would allow this small effect on spike number to be observed.
The transient increase in AP threshold observed (Fig. 2) was not mediated by changes in the AHPs, because these AHPs do not contribute to the threshold of the first spike. Thus other mechanisms contribute to this change in excitability. In other systems, changes in activity or experience can also affect Na+ currents (e.g., Desai et al. 1999a; Maravall et al. 2004a), which could also affect threshold and I/O relation. Another possibility would be a change in tonic inhibition. Differences in the level of tonic inhibition can have an effect on threshold and on input/output relations of neurons, and tonic inhibition has been observed in cortical slices (Salin and Prince 1996; Ulrich 2003). Such a change was not responsible for the changes in threshold or ISI observed here, because blocking inhibition with picrotoxin (20 µM) had no significant effect on these parameters, either in normal animals or in acutely denervated animals (data not shown). These results are similar to those of Ulrich (2003), showing that picrotoxin did not significantly change the spiking properties of layer 5 neurons in rat S1. However, these data do not rule out such effects in the intact cortex, where tonic inhibition could be considerably higher.
Here we present data showing changes in the intrinsic properties of layer 2/3 pyramidal cells in adult rat S1 after peripheral denervation. As observed in other systems, a major site for change in intrinsic properties was found to be the AHP. These studies reinforce the idea that the cortical circuit uses multiple mechanisms to cause reorganization of cortical maps. Thus it is important to begin to understand the complementary roles of synaptic, anatomical, and intrinsic plasticity in these important events.
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ACKNOWLEDGMENTS |
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Address for reprint requests and other correspondence: P. W. Hickmott, Univ. of California, Dept. of Psychology, OLMH 1344, Riverside, CA 92521 (E-mail: peter.hickmott{at}ucr.edu)
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ABSTRACT
INTRODUCTION
Significantly different from values of sham animals, acute and 7 days. C: schematic diagram of locations of neurons analyzed. Filled circle, mark at forepaw/lower jaw border; dotted line, forepaw/lower jaw border; open circle, mark at site of original border; FP, forepaw; LJ, lower jaw; rec, recording electrode. Left: at the normal border, cells were analyzed from both forepaw and lower jaw sides of border (lower jaw shown). Right: in reorganized S1, cells were recorded medial to the reorganized border, between borders, and lateral to the original border, as shown.
