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1 Volen Center, Brandeis University, Waltham, Massachusetts 02454; 2 Federated Department of Biological Sciences, Rutgers University, Newark, New Jersey 07102; 3 Department of Mathematical Sciences and Federated Department of Biological Sciences, New Jersey Institute of Technology, Newark, New Jersey 07102
Submitted 14 April 2003; accepted in final form 27 June 2003
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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; Wong 1999; Wong et al. 1995), spinal cord (O'Donovan et al. 1998), hippocampus (Ben-Ari et al. 1989; Garaschuk et al. 1998), and cultures of young cortical neurons (Kamioka et al. 1996; Murphy et al. 1992). In the developing spinal cord, bouts of activity lasting 
1 min are interspersed with silent periods lasting 10–15 min. Individual activity bouts are composed of multiple cycles of action potential discharge that lengthen in duration over the course of the bout (Landmesser and O'Donovan 1984a,b). Calcium entry during bouts is necessary for the proper development of neuronal phenotype and for the regulation of neurite extension in spinal motor networks (Gu and Spitzer 1995; Holliday and Spitzer 1990).
Long-term changes in neuronal activity have been shown to occur after deafferentation in a variety of systems. Damage to the vestibuloreceptors or vestibular nerve in mammals results in an alteration of neural activity in the vestibular nucleus complex (VNC), which affects balance and postural control (Darlington et al. 2002; Him and Dutia 2001). The neurons in the VNC typically display a spontaneous output that is believed to be due to intrinsic membrane properties (Darlington et al. 2002). After deafferentation, this activity decreases but resumes over time, allowing a partial recovery of behavioral function (Darlington et al. 2002; Him and Dutia 2001). Damage to the sensory input to the spinal cord causes long-lasting changes in the activity of thalamic and cortical neurons and their synaptic organization, which may underlie abnormal sensory responses after loss of a limb or spinal damage (Jones 2000; Vaculin et al. 2000; Weng et al. 2000).
In this paper, we describe episodic bouts of activity, resembling bouts in developing motor systems, that accompany the recovery of the pyloric rhythm after removal of modulatory inputs to the pyloric network (Golowasch et al. 1999b; Mizrahi et al. 2001; Thoby-Brisson and Simmers 1998, 2000, 2002). The pyloric rhythm of the crustacean stomatogastric ganglion (STG) consists of a triphasic motor pattern with a frequency typically 1 Hz (Harris-Warrick et al. 1992). The STG receives descending modulatory inputs that under normal conditions are crucial for the expression of the pyloric rhythm, and removal of these inputs results in either a decrease in frequency or complete loss of the pyloric rhythm (Russell 1979; Russell and Hartline 1978). However, if preparations are maintained in the absence of neuromodulatory inputs for days, the pyloric rhythm recovers (Golowasch et al. 1999b; Mizrahi et al. 2001; Thoby-Brisson and Simmers 1998, 2000, 2002). We suggest that the activity bouts that we have observed are a consequence of retuning of cellular and synaptic properties so that the absence of the currents normally evoked by the neuromodulatory inputs is compensated by other changes in the network. Additionally, the time course of these activity bouts may provide insight into some important aspects of the underlying recovery mechanisms (Golowasch et al. 1999b; Thoby-Brisson and Simmers 2002).
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METHODS |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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All experiments were done using adult rock crabs, Cancer borealis, obtained from local seafood suppliers (Commercial Lobster, Boston, MA).
Physiological saline
The physiological saline contained (in mM) 440 NaCl, 11 KCl, 26 MgCl2, 13 CaCl2, 12 Trizma base, and 5 maleic acid; pH 7.4–7.5.
Organ culture
The stomatogastric nervous system (STNS; Fig. 1A) consisting of the single STG, two commissural ganglia (CoGs), and single esophageal ganglion (OG) was dissected and the STG was desheathed (Selverston and Moulins 1987). All dissection dishes were autoclaved and dissection tools were cleaned and soaked in 70% ethanol for 
10 min. All solutions were sterile filtered (0.2 µm, Nalge Nunc International, Rochester, NY). The physiological saline used for the dissection additionally contained 50 µg/ml streptomycin and 50 U/ml penicillin (Sigma, St. Louis, MO). After the dissection, and once a stable recording was obtained, the antibiotic concentration was lowered to 25 µg/ml streptomycin and 25 U/ml penicillin. Antibiotic concentrations were as follows: day 2, 25 µg/ml streptomycin and 25 U/ml penicillin; day 3, 33 µg/ml streptomycin and 33 U/ml penicillin; additional days, 100 µg/ml gentamicin (Invitrogen Life Technologies, Carlsbad, CA). Preparations were maintained in a humidified low-temperature incubator at 12–13°C, and the saline was exchanged approximately every 12 h.
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Isolation of the STG from descending inputs
The STG was isolated from descending inputs by transection of the stomatogastric nerve (stn). The stn was cut using iridectomy scissors approximately where indicated in Fig. 1A. In some cases, a petroleum jelly (Vaseline) well filled with isotonic sucrose (750 mM) containing 10–6 M TTX was placed on the stn to block action potential transmission through the stn prior to physically cutting the nerve. This procedure resulted in a more rapid loss of the pyloric rhythm than cutting alone.
Photoablation of neuromodulatory terminals
A Vaseline well was made around the stn as described in the preceding text and filled with isotonic sucrose and 10–6 M TTX for 20 min or until the rhythm began to stop. The sucrose/TTX was then replaced with 10–6 M TTX in water and the stn was cut. After several minutes dextran, tetramethylrhodamine 3000 MW (Molecular Probes, Eugene, OR), or Lucifer yellow (Sigma, St. Louis, MO), was added directly to the well, and the preparation was maintained overnight to allow the dye to fill the terminals (11–24 h). The following day the preparation was illuminated with a 100-W mercury bulb for 25–45 min. During the initial stages of the photoablation process, the preparations exhibited temporary resumption of the pyloric rhythm, presumably due to injury discharge-induced modulator release from the dying terminals of the descending axons. After photoablation the preparation was returned to the incubator and pyloric output was recorded overnight. To ensure that the terminals were ablated, the stn was stimulated the next day with 2.5-Hz trains of 3-ms voltage pulses at amplitudes substantially higher than normally needed to evoke modulator release (
100 V). None of the preparations responded to the stn stimulation, indicating that the modulatory terminals were inactivated by the photoablation. This stimulation protocol consistently evoked neuromodulator release (as assessed by an increase in the pyloric rhythm frequency) in both recovering preparations that had not been photoablated (n = 3/3) and stn-intact control preparations (n = 3/3; data not shown).
Electrophysiological recordings
Extracellular recordings were performed using monopolar stainless steel electrodes placed into Vaseline wells made around the lateral ventricular nerve (lvn), pyloric dilator nerve (pdn), and pyloric nerve (pyn; Fig. 1A). Recordings were made continuously throughout the culture period except during solution exchanges. All electrode and ground leads were soaked for 10 min in 70% ethanol. Signals were amplified using A-M systems 1700 differential amplifiers (Carlsborg, WA). Intracellular impalements were performed using 20–30 M
microelectrodes filled with 0.6 M K2SO4 and 20 mM KCl. An Axoclamp 2B amplifier (Axon Instruments, Union City, CA) was used in bridge mode to inject DC current into identified pyloric dilator (PD) neurons to alter the pyloric frequency. Signals were recorded to a computer hard drive using pClamp 8 software and a Digidata 1200A or a Digidata 1322A digitizer board (Axon Instruments, Union City, CA).
Data analysis and statistics
Bouts were readily identifiable by eye in extracellular recordings from the lvn and pdn as rapid increases in pyloric rhythm frequency (see Fig. 2B). The rhythm frequency, bout durations, and interbout intervals were measured from recordings from the pdn in Clampfit (pClamp 8 software, Axon Instruments, Union City, CA). Analysis of pyloric rhythm frequency and cellular phase relationships were performed using Spike 2 version 4 (Cambridge Electronic Design, Cambridge, UK). Phase relationships were defined relative to the onset of the PD burst and were calculated with the following formula: 
= (X – PDon)/cycle period, where X is the onset or end of the burst of each pyloric network neuron, PD, lateral pyloric (LP), or pyloric (PY) neurons, during the cycle period starting with that PD burst. At least 20 cycles, but typically more, were used to calculate phase in each case. Statistical analyses were performed using Sigma Stat software package (SPSS, Chicago, IL). Data are reported as means ± SD.
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RESULTS |
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)]. The PY neuron burst is terminated by discharge of the two PD neurons and the anterior burster neuron (AB; an interneuron with its axon in the stn). Figure 1C shows block diagrams illustrating the phase of firing of each of the neurons. Together with the AB neuron, the two PD cells form the pacemaker kernel for this circuit (Eisen and Marder 1982) and is, for this reason, used as reference for phase analysis. The timing of activity of the LP and PY neurons is set by their intrinsic membrane properties and the synaptic connections within the circuit (Harris-Warrick et al. 1992). Pyloric rhythm ceases when modulatory inputs are removed but then recovers
It has been long known that descending inputs from the two CoGs and the single OG are crucial for maintaining a strong and robust pyloric rhythm (Moulins and Cournil 1982; Russell 1976; Selverston and Moulins 1987). In all species studied, acute removal of the influence of these descending inputs always results in a decrease in pyloric rhythm frequency and often results in a complete cessation of the pyloric rhythm. Complete stomatogastric nervous systems consisting of the STG, OG, and CoG and their intact connecting nerves, however, remain rhythmic for several days after dissection when kept sterile (MacLean et al. 2003). In our hands, intact C. borealis preparations remain stably rhythmic for several days (2–6 days; n = 10, data not shown).
Figure 2 shows plots of pyloric frequency versus time on an extremely slow time base for two preparations in which the stn was transected. Both preparations were rhythmically active at 1 Hz at the start of the experiment. After removing the anterior modulatory inputs by transecting the stn, both preparations became silent for a period of time. The preparation in Fig. 2A remained completely silent until at hour 10 it produced a short bout of low-frequency activity. Between then and hour 18, the preparation produced more and more bouts of higher frequency, until by hour 18 a strong pyloric rhythm had recovered. The preparation in Fig. 2B, bottom, showed an overall higher level of activity during recovery and was not completely silent during interbout periods. Bouts were distinguishable as a rapid increase in pyloric frequency and were evident in extracellular recordings made from the lvn (Fig. 2B, inset). In this paper, we include data from 17 preparations recorded continuously for 7 days. In all of these preparations, the frequency of the pyloric rhythm stopped or decreased to <10% of control values in the first hours after removal of the modulatory inputs.
Recovery process shows episodic bouts of activity
Individual bouts were identified as a rapid increase in frequency followed by a slower decay back to the interbout frequency. Figure 3 shows the pyloric frequency profiles of individual bouts from three different experiments. In all activity bouts, the rate of frequency increase was more rapid than its decay, and the peak frequency range displayed during the bout varied from two- to almost fivefold. This phenomenon was observed in all preparations; however, the rates of rise and decay of individual bouts varied between and within preparations.
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Figure 4 shows raw data from a preparation after removal of the modulatory inputs and provides examples of activity patterns at four times during the experiment. Figure 4, top, shows a control pyloric rhythm with its characteristic PD, LP, PY alternating pattern. The second panel shows a much slower but triphasic pyloric rhythm seen during a bout that occurred 22 h after the stn was cut. The third panel shows an interbout interval after the bout in the previous trace. There was spontaneous activity in the PD, LP, and PY neurons, which was nevertheless still organized in the characteristic PD, LP, PY pyloric sequence. Activity between bouts was disorganized and variable, sometimes consisting of a slow triphasic rhythm (as shown in Fig. 4), and other times consisting of irregular firing of LP and/or PY neurons. Figure 4, bottom, shows a strong pyloric rhythm recorded after 4.4 days in the same preparation.
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In 16/17 preparations bouts of activity began 3.16 ± 2.50 h after cut or block of the stn, in the other preparation bouts did not begin until 24 h after cutting the stn. Bouts occurred in every preparation examined in this study, and ended after 55.9 ± 33.9 h, (range: 9–100 h) when the rhythm recovered a stable firing pattern. Our criterion for recovery was a strong and stable pyloric rhythm that lasted for 5 h. In 10 preparations, the recovered rhythm was stable throughout recordings lasting 5–60 h. In seven preparations the recovered rhythm was stable for 6–50 h and began to fail after that period. The overall number of bouts, number of bouts per hour, average bout duration, or total time spent in an activity bout was not correlated with the time to recovery or with the length of time the stable rhythm lasted after recovery (data not shown).
Frequency in control, bouts, and recovery
Figure 5 compares the mean pyloric frequency in control, bout, interbout, and recovery. The control pyloric rhythm frequency was 1.38 ± 0.4 Hz (n = 17). Pyloric frequency was higher during activity bouts (0.42 ± 0.14 Hz) than during interbouts when a triphasic rhythm was active (0.14 ± 0.05 Hz). The mean frequency during recovery, 0.53 ± 0.33 Hz, was significantly higher than that during interbouts but no different from that during bouts. The control frequency was significantly higher than that observed during bout, interbout, or recovery states (Kruskal-Wallis ANOVA on ranks, followed by Dunn's method; P < 0.05).
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Temporal pattern and time course of bouts
The pattern of activity bouts varied widely among preparations, n = 17. The bout duration was not directly correlated with the preceding interbout interval (Fig. 6A) or the subsequent interbout interval (not shown). The total number of bouts varied from 0.16 to 2.35 bouts/h across preparations (mean: 0.96 ± 0.80 bouts/h). Bout durations varied both within and between preparations and showed no correlation with the total number of events and no trend over time. Mean bout durations varied from 38 to 883 s across preparations and varied between 8- and 230-fold within preparations. Neither bout duration nor interbout interval showed a trend over time in culture (Fig. 6, B and C, data shown for 1 preparation). Some preparations exhibited a cluster of bouts at the beginning or ending of the culture period (the preparation shown in Fig. 2A showed bouts clustered near the end of the culture period), whereas other preparations exhibited a relatively even distribution over time, as for the preparation in Fig. 6, B and C.
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Photoablation of neuromodulatory terminals had no effect on bouts
Because transected axon terminals can be slow to degenerate in crustacean species (Bittner 1991; Parnas et al. 1991, 1998; Royer 1987), it is conceivable that pyloric activity bouts occur due to intermittent release of neuromodulators from axon terminal stumps in the STG neuropil. To determine if this was the case, we back-filled neuromodulatory axon terminals overnight with rhodamine-conjugated dextran beads or Lucifer yellow and illuminated the STG the next day to photoablate the terminals (Miller and Selverston 1979). We then recorded from the preparations overnight to determine if bouts occurred and the preparation recovered. Figure 7, A–D, shows extracellular recordings from the lvn at different times during one of these experiments. The graph in Fig. 7D shows pyloric frequency over time in organ culture. This preparation was illuminated for 25 min after 12 h in culture when the STG neuropil was clearly dye-filled. Illumination resulted in the damage-related release of neuromodulators from terminals in the STG neuropil and, consequently, an increased pyloric frequency and resumption of a typical triphasic output. After illumination, this preparation became briefly silent around hour 16 and subsequently displayed activity bouts for several hours, followed by recovery. Similar results were seen in six preparations. High-voltage stimulation of the stn stump with 2.5-Hz trains of 3-ms pulses had no effect on the recovered rhythm in any preparation, suggesting that the terminals were no longer active. This stimulation protocol evoked modulator release in both stn-intact and in recovering preparations that had not undergone photoablation (not shown).
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Dependence of phase on neuromodulatory input.
In addition to the burst frequency, the phase relationships of the pyloric network neurons were used to characterize the motor patterns of the network. As the phase relationships of network neurons depend on a variety of synaptic and intrinsic properties (Eisen and Marder 1984; Harris-Warrick et al. 1995b; Hartline and Gassie 1979), these can provide indications of the state of the processes that underlie network dynamics. However, bursting phase and duty cycles of pyloric network neurons also vary as a function of neuromodulatory condition (Eisen and Marder 1984; Harris-Warrick et al. 1995a; Hooper and Marder 1987), and previous work on the lobster, Panulirus interruptus, showed that some of the pyloric network phase relationships are frequency dependent (Hooper 1997a,b). To compare the control phase relationships to phase relationships during bouts and interbouts and after recovery, the changes in frequency in these states had to be taken into account. Therefore we first examined the effect of frequency on the onset and end phase of the LP and PY neuron firing and the end phase of PD in the control condition, by injecting current into one of the two PD neurons. Figure 8, A–C, shows raw data and phase plots of the pyloric rhythm in a preparation in which the frequency was altered over a range from 0.5 to 1.5 Hz by current injection into a PD neuron. This individual example shows that at the higher frequencies there was little change in phase, but when the preparation was slowed, the phase of firing of the LP and PY neurons was altered. The pooled data from seven preparations (Fig. 8D) show that at frequencies <0.8 Hz the PD neuron terminated its burst at an earlier phase, and the LP neuron (onset and end) and the PY neuron onset phases were also advanced. The PY termination (PYend) did not show this frequency dependence because the PY neurons tend to stay active until they are inhibited by the next PD burst. Thus PYend phase is always close to 1.
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Figure 9 provides comparisons of the phase relationships of the PD, LP, and PY neurons in control (stn intact), bout, interbout, and recovered states. Figure 9A shows the mean phase relationships for 11 preparations that showed clear and unambiguously analyzable pyloric rhythms in each state. The phase of PDend, LPon, LPend, and PYon were significantly decreased during bout and interbout states compared with control. During recovery all phase relationships increased compared with bout and interbout but were still decreased compared with control except LPon. This seems unlikely to be due entirely to increased rhythm frequency in recovery because the frequency recovered to only 43% of control (0.64 ± 0.29 vs. 1.48 ± 0.31 Hz). Figure 9, B–E, shows plots of phase versus instantaneous pyloric frequency for an individual preparation for control, bout, interbout, and recovered states (colored circles). The phase relationships for control (black) and recovered (blue) states are similar despite having different frequency ranges, whereas bout (orange) and recovered (blue) have different phase relationships but have overlapping frequency ranges. This suggests that the delay in phase seen in pyloric rhythm recovery is not only a consequence of changes in bursting frequency.
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To better separate the change in phase during recovery from the confound arising from the fact that phase is frequency dependent at low frequencies, we compared phase relationships for PDend, LPon, LPend, and PYon in seven preparations that displayed overlapping frequencies during bouts and recovery. For each preparation, data were selected from a 0.1-Hz bin that showed overlap between pyloric frequency in bouts and during recovery such that the frequencies were not statistically different. There was not sufficient overlap in frequency to include data from control or interbout intervals. Figure 10A shows histogram plots of phase values during bouts (
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) for each of the seven preparations, demonstrating that for LPend, LPon, and PYon, at the same frequency, phase was delayed during recovery relative to that during bouts. In each preparation, this reached statistical significance (P < 0.001), except in one case for LPend (3rd panel). For comparison, the preparation shown in Fig. 9, B–E, is represented by the second pair of columns from the right in each graph in Fig. 10A, 
. Mean values for each neuronal phase relationship were: PDend, 0.12 ± 0.01 versus 0.14 ± 0.02 Hz; LPon, 0.28 ± 0.02 versus 0.37 ± 0.03 Hz; LPend, 0.45 ± 0.05 versus 0.56 ± 0.05 Hz; PYon, 0.48 ± 0.04 versus 0.60 ± 0.04 Hz for bout versus recovered, respectively. Interestingly, the phase relationship for PDend did not differ greatly between bout and recovery in most preparations; this suggests that the differences seen in phase for the other cells are not simply due to changes in frequency. Figure 10B compares data from three additional preparations in which the PD neurons were hyperpolarized by current injection in control and/or after recovery so that the phase could be compared at the same frequency in control and after recovery. This comparison shows that the phase in the recovered preparations were delayed relative to the control preparations.
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Blockade of glutamatergic synapses in the STG does not prevent bouts or recovery
An alteration of the pyloric network that results in compensation for loss of neuromodulation and resumption of output could arise through changes in the intrinsic properties of individual neurons and/or changes in synaptic properties of the pyloric network. Glutamate and acetylcholine are the principal transmitters at synapses between STG neurons (Eisen and Marder 1982). Picrotoxin (PTX) blocks graded and spike-mediated glutamatergic synaptic transmission among STG neurons, therefore its application disconnects much of the network (Bidaut 1980; Marder and Eisen 1984). To test whether alterations in glutamatergic synapses were involved in the recovery process, we applied PTX during recovery from stn transection in culture. The PTX was applied shortly before transection of the stn and allowed to remain until the preparation recovered. In control, pyloric neuron groups burst alternately creating a triphasic pattern (Fig. 11A). With the stn intact, application of 10–5 M PTX disrupted but did not stop the pyloric rhythm (Fig. 11B). In the presence of PTX, bursts in the pyloric neurons overlapped temporally before and after recovery (Fig. 11, C–E). The triphasic pattern of alternate bursts returned when PTX was washed off (Fig. 11F). Six of nine preparations displayed activity bouts and recovered in PTX.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMETHODSRESULTSDISCUSSIONDISCLOSURESACKNOWLEDGMENTSREFERENCES |
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Adult crabs live many years, and the animals that we used in this study were several years old. In vivo recordings from behaving crabs showed ongoing pyloric rhythms in the 0.2- to 0.4-Hz frequency range in unfed animals, while rhythms of 1.0–1.5 Hz were routinely seen subsequent to feeding (R. Zarum and E. Marder, unpublished results). Thus in the behaving animal, the unfed baseline state has frequencies similar to those that we obtain subsequent to recovery after removal of descending modulatory inputs (Golowasch et al. 1999b).
Bout properties
Bouts of activity occurred in all preparations that showed recovery in this study, but the temporal pattern of the bouts and the overall number of bouts was highly variable between and within preparations. Although bouts had not been previously reported in decentralized STG preparations (Golowasch et al. 1999b; Mizrahi et al. 2001; Thoby-Brisson and Simmers 1998), in the earlier studies, recordings were not made continuously and the low frequency of activity bouts (on average, 1 3-min bout/h) would make them easily overlooked without continuous recordings.
The episodic bouts of activity characterized in this study in some ways resemble spontaneous activity bouts seen in developing neural networks in many systems (Ben-Ari 2001; Kamioka et al. 1996; Katz and Shatz 1996; Murphy et al. 1992; O'Donovan 1999). Similar spontaneous bursts are also observed in epileptiform bursting in adult hippocampal CA3 networks (Staley et al. 1998). Bouts of activity in these other systems are thought to be important for guiding the appropriate construction of the developing networks (Ben-Ari 2001; Katz and Shatz 1996; O'Donovan 1999). An attractive possibility is that bouts in the recovering pyloric network represent a similar underlying mechanism that guides the restructuring of the pyloric network to allow a physiologically meaningful output. Nonetheless, there are some important differences between bouts seen in developing motor systems and the bouts we see in the recovering pyloric network. There does not seem to be a refractory period or activity-dependent depression after bouts in the pyloric network because we observed no correlation between bout duration and the preceding or subsequent interbout interval. In contrast, a refractory period is thought to be a common factor contributing to episodic bouts in a variety of developing neural networks (O'Donovan 1999). Additionally, activity bouts did not appear to be related to recovery of phase or frequency of the pyloric rhythm. The overall number of activity bouts, number of bouts per hour, overall time spent in activity bouts, or average bout duration in a given preparation was not correlated with the time to recovery or the percentage recovery of phase or frequency in our study. This is in contrast to developmental changes, such as that occurring in the delayed rectifier potassium current kinetics seen in amphibian spinal neurons, that are dependent on spontaneous activity bouts in a particular frequency range (Gu and Spitzer 1995). Nevertheless, bouts of activity were consistently associated with rhythm recovery and ceased when a stable rhythm was generated. The discontinuous nature of the recovery process and the intermittent nature of activity bouts suggests that the underlying mechanism itself is discontinuous or is dependent on several competing processes that must reach equilibrium before the rhythm can resume stably. In the future, it will be important to determine if activity bouts are a necessary process that regulate pyloric rhythm recovery or if they are an epiphenomenon that occurs due to another underlying homeostatic process.
What processes might cause the bouts that we have observed? In developing retina and spinal cord, it is believed that spontaneous bouts of activity are caused by excitatory GABAergic, glutamatergic, or cholinergic synaptic contacts through network-dependent mechanisms, whereas the duration of the interbout is determined by the recovery from synaptic depression or depletion (Chub and O'Donovan 1998; Feller 1999; Feller et al. 1996). As all chemical synapses among the pyloric network neurons are inhibitory, it is possible that an endogenous burst in any pyloric network neuron could trigger a bout by a postinhibitory rebound-like mechanism. This seems unlikely, because we observed that blockade of glutamatergic synaptic transmission between STG neurons did not block either the appearance of the bouts or recovery. Additionally, we saw no evidence for a refractory period after bouts. However, this does not rule out that the cholinergic STG synapses might trigger bouts.
We showed that both the recovery process and bouts persist after descending modulatory inputs were photoablated. This indicates that activity in the presynaptic terminals of the descending modulatory neurons is not solely responsible for the production of bouts. We observed that neuronal phase relationships were different in recovered preparations compared with these during bouts or control at a given frequency. Because the phase relationships are determined by the intrinsic membrane properties of STG neurons and their synaptic connections, one or many of these properties may be altered during recovery. Evidence suggests that the recovery process involves changes in the intrinsic properties of the pyloric neurons (Golowasch et al. 1999b; Mizrahi et al. 2001; Thoby-Brisson and Simmers 2002) as they retune themselves in response to their altered environment and level of activity (Golowasch et al. 1999a; Soto-Trevino et al. 2001). Thoby-Brisson and Simmers (2002) reported that in the lobster, Jasus lalandii, the delayed rectifier and calcium-dependent potassium currents were downregulated and the hyperpolarization-activated cation current was upregulated in PD neurons after rhythm recovery. This alteration of membrane currents favors endogenous, regenerative bursting behavior, which PD neurons do not possess immediately after stn transection. A large increase in the propensity of the pacemaker kernel to display bursting behavior, as suggested by Thoby-Brisson and Simmers (2002), could account for rhythm recovery. However, an alternative possibility is that many small changes could occur in the intrinsic properties of many of the pyloric neurons, or their synaptic contacts, that together account for rhythm recovery. Future experiments will be needed to determine how much each of these potential mechanisms contribute to rhythm recovery in the pyloric network.
A similar mechanism is believed to occur in recovery of spontaneous activity of neurons of the vestibular nucleus complex after deafferentation (Darlington et al. 2002). If channel densities are functionally linked to neuronal activity, as suggested by modeling studies (LeMasson et al. 1993; Liu et al. 1998), it can be imagined that activity bouts arise as channel densities are altered. An incremental change in one or more membrane conductance may allow a temporary resumption of the pyloric rhythm, but further changes in membrane conductances could result in the network falling silent again. The rhythm could switch on and off in this manner until the processes that link activity and membrane conductances reach equilibrium. If this was true, then the pattern of bouts over time and the time to recovery would depend on the initial conditions of the network elements. This is likely to be different for each preparation, explaining the variability we see in the recovery process. Recent work (MacLean et al. 2003) showed that overexpression of A-type potassium channels subsequent to mRNA injection resulted in little change in PD neuron activity as the increase in A-type channel density was accompanied by a compensating increase in an inwardly rectifying cation channel. These data add to a growing body of evidence arguing for a number of homeostatic mechanisms, both activity dependent and independent, that may act together during recovery processes to reinstate baseline activity.
Crabs must benefit greatly from having a high degree of stability in a system that is essential to life such as the pyloric network. Indeed, a highly plastic or unstable feeding-pattern-generating network would be seriously detrimental to any animal. The processes that maintain a stable pyloric network may be common to many rhythmic networks, including essential systems such as those that control breathing, circulatory, or digestive processes. The mechanisms that stabilize the pyloric network seem to be highly versatile, as they can compensate for a change as dramatic as complete removal of all neuromodulatory input. Understanding these processes in the pyloric network will help elucidate mechanisms that maintain stability in neural networks in general during learning, physical growth, and development and in disease.
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DISCLOSURES |
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Present address for C. Reina: Department of Pharmacology, University of Pennsylvania, 3620 Hamilton Walk, Philadelphia, PA 19104.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: E. Marder, Volen Center, MS 013, Brandeis University, 415 South St., Waltham, MA 02454-9110 (E-mail: marder{at}brandeis.edu).
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REFERENCES |
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) were used to make extracellular recordings from 3 motor nerves, the lateral ventricular nerve (lvn), the pyloric dilator nerve (pdn), and the pyloric nerve (pyn). B: an extracellular recording made from the lvn showing the alternate firing of the pyloric dilator (PD), the lateral pyloric (LP), and the pyloric (PY) neurons. C: a phase plot generated from the recording shown in B. Phase (
). This preparation remained silent until bouts began to occur after 
