Interactive and individual effects of sensory potentiation and region-specific changes in excitability after spinal cord injury

Neuroscience 199 (2011) 563–576

INTERACTIVE AND INDIVIDUAL EFFECTS OF SENSORY POTENTIATION AND REGION-SPECIFIC CHANGES IN EXCITABILITY AFTER SPINAL CORD INJURY N. HOFFMAN AND D. PARKER*

either suggest a marked redundancy in descending systems or the involvement of other factors. These factors could include changes in spinal cord locomotor networks or sensory inputs: locomotion can be evoked in lesioned animals by activating networks below lesion sites (Gimenez y Ribotta et al., 2000; Edgerton et al., 2001; Lavrov et al., 2008; Rossignol et al., 2001), and recovery can be facilitated by sensory stimulation and locomotor training (De Leon et al., 1998, 1999; Muir and Steeves, 1997; Pearson, 2001; Edgerton et al., 2001; Edgerton et al., 2008; Wolpaw and Tennissen, 2001; Harkema, 2008; Dietz et al., 2002; Marsh et al., 2011). The relative influences of these various effects to recovery remain uncertain. Anatomical and retransection studies suggest that regeneration may not be necessary or sufficient for recovery (see Barrière et al., 2008; Tillakaratne et al., 2010), while the role of changes in locomotor networks and sensory inputs is unclear (see Dietz et al., 2002; Lee et al., 2005; Marsh et al., 2011). Edgerton et al. (2008) suggested that functional outcomes will reflect the interactions between components, but understanding these interactions is difficult (Darian-Smith, 2009; Marsh et al., 2011; Tetzlaff et al., 2009). The lamprey is a lower vertebrate model system for investigating functional recovery after spinal injury (Rovainen, 1979; Cohen et al., 1988; McClellan, 1994; Davis et al., 1993). Analyses in lamprey have also focused predominantly on regeneration (see Cohen et al., 1988; Lurie and Seltzer, 1991; McClellan, 1990 for reviews; see Shifman et al., 2009; McClellan et al., 2008; Oliphint et al., 2010 for recent analyses). However, regeneration alone is probably not sufficient for recovery (see Cohen et al., 1989, 1999; McClellan, 1990; Selzer, 1978). For example, activity can be recorded in intact, but not in in vitro, preparations at locations where there are no regenerated axons, an effect that suggested a role for intersegmental coordinating systems or mechanosensory inputs in recovery (Cohen et al., 1989, 1999; McClellan, 1990; Selzer, 1978). While intersegmental coordinating systems have been examined (Cohen et al., 1999), proprioceptive inputs have not previously been investigated. Here, we have examined changes in proprioceptive inputs after spinal cord lesions. We have also investigated the relative influence of proprioceptive inputs, changes in spinal cord excitability, and regeneration (using stimulation-evoked responses across lesion sites) on recovery. The results show that proprioceptive inputs and spinal cord excitability are both potentiated after lesioning, but that neither effect alone correlated with recovery. However,

Department of Physiology, Development and Neuroscience, University of Cambridge, Downing Site, Cambridge, CB2 3DY, UK

Abstract—While promoting regeneration across lesion sites is a main focus of research into spinal injury, changes also occur in the sublesion spinal cord and its sensory inputs. However, how these varied effects relate to recovery remains largely unknown. Here, we have examined changes in sensory inputs and region-specific changes in spinal cord excitability after spinal cord lesions in the lamprey, a model system for studying regeneration and functional recovery, and related the changes to the degree of locomotor recovery.Proprioceptive responses below lesion sites were potentiated and their rate of adaptation reduced 8 –10 weeks after lesioning (i.e. when animals usually showed significant locomotor recovery). These effects were associated with changes in cellular properties that were consistent with an increase in proprioceptor excitability. However, the changes in proprioceptive inputs did not correlate with the degree of locomotor recovery. There were region-specific changes in spinal cord excitability below lesion sites. In isolation, these excitability changes also did not correlate with the degree of locomotor recovery, but in this case, there were significant interactions between the magnitude of stimulation-evoked responses across the lesion site (used to assess the extent of regeneration) and sublesion changes in excitability. These interactions differed in animals that recovered well or poorly, suggesting that the nature of this interaction influenced recovery. These results add to the evidence for diverse changes in the spinal cord after injury, and suggest that regenerated inputs and their interactions with sublesion networks influence the degree of functional recovery. © 2011 IBRO. Published by Elsevier Ltd. All rights reserved. Key words: spinal cord, regeneration, sensory potentiation, excitability, lamprey.

Spinal cord injuries disrupt a distributed but integrated system of components that initiate, generate, and adapt motor outputs. Strategies for promoting functional recovery may thus need to consider a diverse range of effects. The traditional focus of research has been on promoting regeneration across lesion sites (Fawcett, 2002). While complete regeneration is unlikely, it is suggested that significant functional recovery could occur even if regeneration was limited (2–10%; Bregman, 1998; Ramer et al., 2000; Fawcett, 2002). Significant recovery in this case would *Corresponding author. Tel: 44 1223 333836; fax: 44 1223 330934. E-mail address: [email protected] (D. Parker). Abbreviations: EMG, electromyogram; EPSP, excitatory postsynaptic potential; IPSP, inhibitory postsynaptic potential.

0306-4522/11 $ - see front matter © 2011 IBRO. Published by Elsevier Ltd. All rights reserved. doi:10.1016/j.neuroscience.2011.09.021

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recovery was influenced by how regenerated inputs interacted with sublesion excitability changes, supporting a role for interactive effects.

spinal cord increases proportionally with body length (Ruiz et al., 2004):

EXPERIMENTAL PROCEDURES

y is the segment length and x, the total body length (Ruiz et al., 2004). Animals were measured from the tip of the oral hood to the end of the tail. To determine intersegmental phase lag (␸), the following equation was used (Boyd and McClellan, 2002):

Larval lampreys (Petromyzon marinus) between 100 and 130 mm were obtained from commercial suppliers (Lamprey Services, Ludington, Michigan, USA). Animals were anaesthetised by immersion in MS-222 (300 mg/ml, pH adjusted to 7.4). The spinal cord was transected by making an ⬃5 mm dorsal incision approximately 1 cm below the last gill and completely cutting the spinal cord with iridectomy scissors. In 20 animals, regeneration was blocked by placing a 0.1-mm plastic sheet between the cut ends of the spinal cord. The incision site was repaired with Vetbond Tissue adhesive (3M Animal Care Products). Following transection, animals were kept at 23 °C (Cohen et al., 1999).

Behavioural analyses Video and electromyogram (EMG) recordings were made from control animals and lesioned animals 8 –10 weeks after lesioning. EMG recordings were made by inserting bipolar Teflon-insulated electrodes (0.075 mm diameter) into the muscle under MS-222 anaesthesia. Electrodes were inserted approximately 0.5 cm rostral and caudal to the lesion site (the length of each animal and the location of the electrodes were measured before each experiment). After recovery from anaesthesia, muscle activity was recorded as the animals swam in a plastic aquarium (29⫻23.5⫻5.5 cm). Swimming activity was initiated by lightly pinching the tail or head of the animal using serrated forceps. A qualitative assessment of locomotor function was made from video recordings (Cooke and Parker, 2009). This was based on the study by Ayers (1989), who categorised locomotor recovery into different stages (see Fig. 2A, B): Stage 1. Animals can propel themselves forward by exaggerated movements of the head (“head wagging”), but are unable to avoid obstacles and often hit the aquarium walls. Stage 2. Animals can elicit one caudally propagating flexion wave that can turn the head away from the wall. This stage indicates the initial phase of recovery. Stage 3. The body caudal to the transection site can elicit multiple caudally propagating waves; the rostral body continues to head wag out of phase with caudal undulations. Stage 4. Rostral and caudal activity becomes coordinated so that propagating waves travel along the length of the body (suggestive of the recovery of intersegmental coordination). Stage 4 animals typically exhibit a bilateral asymmetry of curvature on one side of the body during swimming, which leads to an inability to maintain a normal dorsal-side-up orientation. Stage 5. The bilateral asymmetry in body curvature is largely eliminated, and animals can orientate themselves dorsal side up approximately 80% of the time while swimming. Stage 6. Animals swim dorsal side up 100% of the time, and swimming matched that in unlesioned animals. EMG activity was recorded using an A-M Systems 1700 Differential AC amplifier. All data acquisition and analysis were performed using a computer equipped with an analogue to digital interface (Digidata 1322A Molecular Devices) and pClamp9 software. To quantify the swimming behaviour in each animal, the frequency of muscle bursts, the coefficient of variation of bursting, the duration of swimming periods, and the intersegmental phase lag were measured. Lampreys undergo a change in body size during development. However, the spinal cord represents ⬃80% of the total body length in each of the life cycle stages (Ruiz et al., 2004). A linear function can fit the relationship of segment to body length, where each of the assumed 100 spinal segments along the

y⫽0.0066x⫹0.058

␾⫽关d ⁄ T兴 ⁄ N d is the interval between rostral and caudal bursts in the same cycle on the same side; T is the cycle time, which is inversely proportional to the bursting frequency; N is the number of intervening segments. Movement-related feedback was examined in the isolated spinal cord. Animals were anaesthetised with MS-222, and the spinal cord and notochord in the trunk region (i.e. between the last gill and the start of the dorsal fin) were isolated in oxygenated lamprey Ringer at 4 °C (Ringer contents: 138 mM NaCl; 2.1 mM KCl; 1.8 mM CaCl2; 2.6 mM MgCl2; 4.0 mM D-(⫹)-glucose; 2.0 mM HEPES; 0.5 mM L-glutamine, bubbled with O2 and adjusted to pH 7.4 with 1 M NaOH). The isolated spinal cord and notochord were pinned to a Sylgard-lined chamber and bathed in lamprey Ringer at 9 °C. The spinal cord was fixed so that only approximately 1.5 cm of the rostral end could move (Fig. 1A). The bending point was thus approximately 0.5 cm below the lesion site. A syringe tip (25-gauge) was attached to a vertical arm connected to a custom-made motor that moved the vertical arm sinusoidally 1 cm to the left and right of centre at frequencies of 0.1, 0.5, and 1 Hz for 300 s, 60 s, and 30 s, respectively (see Fig. 1A). The syringe tip was bent to create a hook that was inserted through the ventral side of the notochord approximately 2 mm from the rostral end (i.e. the end that was free to move). Imposed sinusoidal movements of the isolated spinal cord/notochord to mimic bending during swimming were programmed in MatLab. Extracellular recordings were made from the surface of the lateral tracts using glass suction electrodes to monitor movementrelated sensory feedback (see Grillner et al., 1982; McClellan and Sigvardt, 1988). Movement-related activity in this region reflects the activity of edge cells (Rovainen, 1979), intraspinal mechanoreceptors with cell bodies on the lateral edge of the spinal cord that are depolarised by stretch of the lateral margin (Grillner et al., 1983). The lateral tract also contains the axons of descending brainstem neurons (Rovainen, 1979). While we cannot unequivocally identify edge cells from extracellular recordings, as the imposed movements were behaviourally relevant (1 cm deflections at 0.1–1 Hz), it would seem unlikely that nonproprioceptive axons running in the lateral tracts would have been activated, as they should then also be activated nonspecifically by normal swimming movements. Extracellular recordings were taken at three and seven segments caudal to the bending point (we have thus only examined edge cells with descending axons; Tang and Selzer, 1979): there were no significant differences in the responses at these locations, and so only the three-segment data are presented here. In all recordings, the peak of the wavelength represented bending of the spinal cord to the ipsilateral side (i.e. the same side as the recording electrode), while the trough corresponded to bending to the contralateral side (Fig. 1B). Activity during bending was quantified by detecting spikes using pClamp9 software. Spontaneous activity from the lateral tract was also recorded. The source of this activity is unknown: it could arise from edge cells or from nonproprioceptive axons running in the lateral tract. This activity could differ markedly between experiments (spontaneous activity is shown on the graphs, but we have not examined it in any detail as we do not know its source): the baseline spontaneous activity (i.e. before bending) was subtracted to give only the bending-evoked response.

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Fig. 1. Diagrams of the experimental setup for imposed bending of the spinal cord and for assessing regional differences in spinal cord excitability. (A) The experimental setup for evoking swimming-like movements of the isolated spinal cord/notochord. The spinal cord was connected to a custom-made motor at its rostral end (to left), and fixed caudally to a Sylgard-lined chamber. The rostral end was thus free to move; the caudal end, fixed. Movement-related proprioceptive activity was recorded from the lateral tract below the fixation point. (B) Sample recording of extracellular activity recorded from the lateral tract in response to a sinusoidal movement command. (C) Diagram showing the stimulation and recording electrode arrangement for examining spinal cord excitability above (A1, A2), across (A3, A4), and below the lesion site (B1–B8, C1–C4). AStim, BStim and CStim show stimulation sites, and A1– 4, B1– 8, and C1– 4 show associated recording sites. The grey strip reflects the cell body region of the spinal cord. MN signifies the location of motor neurons in this region. E refers to the edge cell body in the lateral tract. Arrows show their ascending and descending axonal projections. The lateral and medial tracts are labelled. Descending axons project in these tracts.

Intracellular recordings were made from edge cells in the lateral tract in the absence of bending. An Axoclamp 2B amplifier (Axon Instruments Inc., Foster City, CA, USA) was used for amplification and in discontinuous current clamp mode for current injection (the sampling rate was 2–3 kHz; discontinuous current clamp was monitored to ensure complete voltage settling before measurements). The edge cells are the only cell bodies in the lateral tract. They could be distinguished from lateral column axons by their spontaneous synaptic inputs and slow afterhyperpolarisation (see Fig. 5C; Buchanan, 1993). Edge cell excitability was examined in control and lesioned animals by injecting depolarising current pulses (100-ms duration from 0.5 to 2.5 nA in 0.5 nA steps at 1-s intervals). Input resistance was examined from the response to a 100-ms–1-nA hyperpolarising current pulse. Both effects were examined from a current clamped potential of ⫺70 mV. This was necessary to avoid differences related to variability in resting potential between cells (note that the actual resting membrane potential of the cells was monitored and is reported). Spontaneous synaptic inputs to the edge cells were monitored by recording 30, 1-s intervals of baseline activity. The traces were rectified and integrated in pClamp to give a measure of the summed synaptic input (Cooke and Parker, 2009; Hoffman and Parker, 2010). No attempt was made to separate excitatory postsynaptic potentials (EPSPs) and inhibitory postsynaptic potentials (IPSPs): we simply assessed the extent of synaptic input that the edge cells received (in control animals, there was little spontaneous synaptic input and in lesioned animals, these were predominantly EPSPs; see below). Spinal cord excitability was assessed by stimulating extracellularly above and below the lesion site and recording the evoked activity extracellularly from ventral roots at various locations along the body using glass suction electrodes (Cooke and Parker, 2009; see Fig. 1C). Stimulation-evoked responses were quantified by a single

1-ms stimulation pulse at 1.5 times the threshold needed to evoke a single ventral root spike at the different stimulation locations: this aimed to offset differences in stimulation strength caused by variability in electrode placement in different cords (Cooke and Parker, 2009). We only used a single stimulation pulse, as in some cases stimulation trains can evoke prolonged activity (⬎30 s; Cooke and Parker, 2009). The stimulation was given 5 times at each location at an interval of 5 s. Spontaneous activity was also recorded from the surface of the spinal cord at the same level as the ventral root recordings (30, 1-s sweeps). Evoked and spontaneous responses were first rectified and then integrated over time (for evoked responses up to 150 ms after the stimulation; for spontaneous responses over the whole of each period) to provide a measure of the activity in each trace. The traces were then averaged (n⫽5) for quantification by measuring the peak of the integrated trace (see Ullström et al., 1999). We ensured that noise levels were constant (⬃20 ␮V in all experiments) using a Humbug noise eliminator (Quest Scientific). The effects of stimulation were localised to the region stimulated and not due to current spread, as the responses could be abolished by lifting the stimulating electrode just above the spinal cord (see Selzer, 1978). We also examined responses evoked by stimulating above and recording activity from the ipsilateral or contralateral surface of the spinal cord below the lesion site (A3 and A4 responses, respectively; Fig. 1C). This aimed to provide a measure of the regeneration across the lesion site. Extracellular stimulation cannot identify the components stimulated, whether they reflect ascending or descending inputs (Armstrong et al., 2003), large or small axons (or those closer to or further from the surface), or monosynaptic or polysynaptic effects. While the evoked responses will reflect the relative degree of regeneration across the lesion site (responses were again abolished when the electrode was moved just above the cord, ruling out current

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Fig. 2. The influence of regeneration on the degree of locomotor recovery. (A) Successive frames from a video recording of an animal scored as swimming at stage 5 (see Experimental procedure). The region marked by the bar is where the animal turned after it swam into the wall of the aquarium showing good motor coordination. (B) Successive frames from a video recording of an animal scored as swimming at stage 2. (C) Graph showing the individual swimming scores related to the presence or absence of regeneration, assessed by electrical stimulation of the spinal cord above the lesion site while recording from the surface of the spinal cord below the lesion. (D) Graph showing the relationship of the swimming score to the quantified activity evoked ipsilaterally (A3) or contralaterally (A4) below the lesion site to stimulation above at 1.5 times the threshold to evoke a single spike. Note that activity was not quantified (see Experimental procedure) in all of the animals shown on (C).

spread below the lesion site) because we cannot identify the source of the activity we refer to these effects as across-lesion or A3 (ipsilateral) and A4 (contralateral) responses. Cord activity was monitored here, as ventral root activity will be influenced by the properties of motor neurons, and in principle, there could be no activity even though regeneration had occurred. The stimulation and spinal cord recording electrodes covered the cell body region of the spinal cord and the lateral and medial tracts on that side (descending axons mainly run in the lateral and medial tracts, with those in the lateral tracts being important for initiating locomotion; McClellan, 1990). The stimulation strength was set at 1.5 times the threshold needed to evoke a single ventral root spike above the lesion site. When no activity was detected, the stimulation strength was increased to ensure that there was a complete absence of regeneration: in practically all cases this could be confirmed visually by the failure of the two sides of the cord to rejoin. The magnitude of the response was quantified by measuring the activity evoked from the surface of the spinal cord two segments below a lesion site ipsilateral or contralateral to stimulation above (i.e. A3 and A4 responses; see Fig. 1C). Values in unlesioned animals were obtained by stimulating and recording at the same sites and across the same distances as in lesioned animals. All graphs and statistical analyses were performed using GraphPad Prism.

RESULTS Analysis of functional recovery Swimming behaviour 8 –10 weeks after lesioning was scored qualitatively by video analysis using a six-point scale based on the study by Ayers 1989; see Experimental

procedure; Fig. 2A, B. Higher swimming scores (5/6) generally occurred in animals in which regeneration had occurred. This was assessed by the presence of activity evoked by stimulation across the lesion site in the isolated spinal cord (n⫽35 of 60; Fig. 2C; see Experimental procedure). In animals in which no activity was evoked across the lesion site (which included all of those in which a plastic barrier was inserted at the lesion site (n⫽20); see Experimental procedure), swimming scores tended to be low (n⫽25 of 60; Fig. 2C). However, there was some overlap: animals in which activity was evoked could have low swimming scores, and vice versa. In this small population of animals, effects other than regeneration presumably influenced the degree of functional recovery. When activity across the lesion site was quantified from the A3 and A4 responses (see Experimental procedure), there were significant correlations between the swimming score and the rectified and integrated activity recorded ipsilateral (A3, r2⫽0.58, n⫽36; Fig. 2D) and contralateral (A4, r2⫽0.42, n⫽36; Fig. 1C; P⬍0.05, Spearmans R). This suggested an influence of the magnitude of regeneration on the degree of functional recovery (see McClellan, 1990). However, note that the A3 and A4 values varied markedly, and there was some overlap in responses between swimming scores. Myogram recordings were made from lesioned animals (n⫽46) to examine the characteristics of swimming further.

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Fig. 3. Myogram activity examined in lesioned animals that showed good (stage 5/6) or poor (stage 1/2) recovery of locomotor function. For stage 5/6 animals the burst frequency (Ai), phase lag (Aii), coefficient of variation of bursting (Aiii), and duration of the swimming episode (Aiv) did not differ from that in control animals. The asterisk on all graphs indicates significant differences at P⬍0.05. Various locomotor dysfunctions occurred in animals showing poor locomotor recovery (stage 1/2). These included the absence of activity below the lesion site (Bi), the absence of activity above the lesion site (Bii), and rhythmic activity occurring on only one side of the body (Biii).

In stage 5/6 animals (n⫽28), there was no significant difference above or below the lesion site in the swimming frequency, intersegmental coordination across the lesion site, or burst regularity (assessed from the coefficient of variation of EMG bursts) compared with control animals (n⫽31; P⬎0.05; Fig. 3Ai–Aiii). However, there were significantly longer bouts of swimming in lesioned animals (P⬍0.001; Fig. 3Aiv). The significance of this effect to recovery is currently uncertain. These results support those of previous studies (McClellan, 1990; Davis et al., 1993; Cohen et al., 1999) that animals that recovered well showed comparable EMG activity with control animals. However, in poorly recovered animals (swimming scores of 1 or 2; n⫽18), there were significant differences in swimming parameters that led to various types of locomotor dysfunction (see also Cohen et al., 1999). These included the absence of activity below (n⫽5; Fig. 3Bi) or above the lesion site (n⫽3; Fig. 3Bii; see also McClellan, 1990); difference in frequencies (n⫽3, data not shown) or a drifting coupling between the activity above and below the lesion (n⫽4; data not shown); synchronous activity on the left and right sides of the body below the lesion site (n⫽1; data not shown); or the absence of rhythmic activity on one side of the body (n⫽2; Fig. 3Biii). The sample size of the individual dysfunctions was too small to meaningfully compare them statistically with the effects examined below. While not ideal, given that the various dysfunctions will presumably reflect different functional states of the spinal cord because of the low numbers for each, we have

grouped these animals into a single population of poorly recovered animals. Movement-related feedback is potentiated after lesioning In addition to regeneration, there is evidence for functional changes below lesion sites in lamprey (Cohen et al., 1999; Cooke and Parker, 2009). We continued our analysis of these effects by examining if there were changes in sensory inputs. This was done by imposing sinusoidal movements that mimicked the bending of the body during swimming and comparing the responses in control and lesioned animals (see Experimental procedure; Fig. 1A). During stretching and compression of the spinal cord (i.e. bending to the contralateral and ipsilateral sides relative to the recording site, respectively), lateral tract activity below the lesion site was significantly potentiated in lesioned animals (Fig. 4Ai–Aii, C). That this occurred for both stretching and compression responses suggested that both types of edge cell were potentiated (i.e. those with ipsilateral excitatory and contralaterally projecting inhibitory axons; Viana Di Prisco et al., 1990). For contralateral bending, there was significant potentiation of the initial response (i.e. response to first bending cycle) at 1 Hz and 0.5 Hz, but not at 0.1 Hz: for ipsilateral bending, there was only a significant increase at 1 Hz (Fig. 4C). There were also differences in the rate of adaptation (determined from the ratio of the 10th bending response to the 1st response;

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Fig. 4. Movement-related feedback is potentiated after spinal lesions. Examples of activity evoked in response to bending the isolated notochord/ spinal cord are shown in a control (Ai) and a lesioned animal (Aii). Examples of activity over repeated bending cycles are shown for a control (Bi) and a lesioned animal (Bii). Graphs showing the frequency of spiking (C) and degree of adaptation (D) at different bending frequencies in control and lesioned animals (open bars control animals, filled bars lesioned animals).

Fig. 4D). In control animals, adaptation to 40 – 60% occurred over the initial 10 bending responses at the different frequencies. The rate of adaptation was reduced after lesioning (Fig. 4Bi, Bii, D), with significant effects occurring with 1 and 0.5 Hz bending to both the ipsilateral and contralateral sides of the body. Similar effects on adaptation have been seen in mammalian systems (Thompson et al., 1992; Grey et al., 2008; Boulenguez et al., 2010). While lateral tract recordings have been used routinely to assay proprioceptive activity (e.g. Grillner et al., 1982; McClellan and Sigvardt, 1988), we also made intracellular recordings from the proprioceptive edge cells in the lateral tract to examine lesion-induced changes in these cells directly (recordings were made in the absence of bending). Edge cells in lesioned animals had significantly depolarised resting membrane potentials compared with control animals (63.5 mV⫾1.9n⫽10, compared with ⫺69.2 mV⫾ 1.3, n⫽10; P⬍0.05; Fig. 5A). There was no change in input resistance (Aii), but there was an increase in edge cell excitability in lesioned animals, shown by the increase in the number of spikes evoked by depolarising current pulses from a fixed membrane potential of ⫺70 mV (Fig. 5Bi). The edge cells have variable spiking responses (see Buchanan, 1993): control cells could adapt to stop spiking

before the end of the current pulse (n⫽4), spike only at the onset and offset of the current pulse (n⫽3), or spike continuously, albeit with some adaptation (n⫽3). Because of the different responses, spiking over the current pulses was examined over three regions: the initial 33 ms, the 2nd 33 ms and the final 34 ms (see Buchanan, 1993). In lesioned animals (n⫽10), edge cell responses across all three regions were significantly potentiated compared with control (P⬍0.05, n⫽10; Fig. 5Bii–iv), although 2nd and 3rd regions’ effects were only significant with current pulses of greater than 1.5 nA. In lesioned animals, there was also a significant reduction of the slow afterhyperpolarisation responsible for spike frequency adaptation (from 3.7⫾0.4 mV in control to 1.3⫾0.28 mV, P⬍0.05; Fig. 5C), an effect consistent with the increase in excitability. A similar effect occurs in rat motor neurons after locomotor training (Petruska et al., 2007). Finally, we examined spontaneous synaptic activity in the edge cells. The edge cells can receive inhibitory and excitatory inputs (Vinay et al., 1996). No attempt was made to separate the synaptic input here; we simply assessed the extent of the total synaptic input the cells received. There was little spontaneous synaptic activity in control animals (Fig. 5Dii), but activity was significantly increased after lesioning (Fig. 5Di, Dii; P⬍0.05).

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Fig. 5. Changes in the cellular properties of proprioceptive edge cells after lesioning. Bar graphs comparing the resting membrane potential (Ai) and input resistance (Aii) in control and lesioned animals (Bi). Traces showing the excitability of edge cells in a control (top) and lesioned animal (bottom) (Bii–Biv). Graphs showing the increased excitability in response to 100-ms depolarising current pulses. The excitability is split into the three regions representing the initial 33 ms (Bii), mid 33 ms (Biii), and final 34 ms over the 100-ms current pulse (Biv). (C) Graph showing the significant reduction in the slow afterhyperpolarisation after single edge cell spikes. The inset shows averaged single action potentials in an edge cell from a control (n⫽10, thin line) and a lesioned animal (n⫽10; thick line). (Di) Traces showing baseline synaptic activity in edge cells from a control and a lesioned animal. (Dii) Graph showing the significant increase in spontaneous synaptic inputs (assessed from the rectified and integrated activity) in lesioned animals.

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Fig. 6. Lack of relationship of potentiated sensory inputs to functional recovery. (A) Graph showing the lack of correlation of the frequency of movement-related activity at 0.1, 0.5, and 1 Hz to the swimming score. (B) Graph showing the movement-related frequency of spiking and adaptation in animals that recovered poorly (stage 1/2) or well (stage 5/6). There were no significant differences in the various sensory parameters studied in the two groups. (C) Graph showing the frequency of spiking and adaptation rate in the presence or absence of regeneration across the lesion site. (D) Graph showing the correlation between the A3 response and movement-related activity.

This usually reflected a marked increase in spontaneous EPSPs (n⫽9 of 10; see Fig. 5Di). Taken together, these effects are consistent with the increase in edge cell excitability suggested from the lateral tract recordings during bending. We related the change in sensory feedback to the degree of locomotor recovery. Because larger sample sizes were available, we used the extracellular activity evoked by bending for this analysis. There was no correlation between the degree of recovery and the ipsilateral or contralateral bending response (contralateral bending responses are shown in Fig. 6A) or rate of adaptation (data not shown), and no significant differences in the various sensory parameters in lesioned animals that recovered to stage 1/2 or stage 5/6 swimming behaviour (Fig. 6B). We also examined the interaction of the sensory input with across-lesion stimulation responses by separating animals on the basis of the presence or absence of activity across the lesion site (A3 and A4 responses). There were few differences in bending responses: the only significant effects were the significant reduction in ipsilateral bending responses at 1 Hz and 0.5 Hz and the significant increase

in 0.5 Hz adaptation when A3 or A4 responses were absent (Fig. 6C). However, there were no significant correlations between the quantified A3 and A4 responses and any of the sensory parameters studied (see Fig. 6D for A3 responses), suggesting against the regulation of these sensory properties by regenerated axons. Thus, while there was a clear potentiation of sensory inputs below lesion sites, we could not find any relationship between these changes and the degree of locomotor recovery (see Discussion). Spinal cord excitability changes after lesioning There are functional changes in identified excitatory interneurons and motor neurons below lesion sites that are consistent with an increase in spinal cord excitability (Cooke and Parker, 2009). As the relationship of this effect to recovery had not been examined, we investigated it here by examining changes in excitability at different locations along the spinal cord. Ventral root responses above the lesion site (A1 and A2; see Fig. 1C for stimulation and recording locations) did

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Fig. 7. Regional changes in spinal cord excitability after lesioning. (A) Graph showing the evoked activity at various sites above, across, and below the lesion site in control and lesioned animals. For clarity, only significant effects are shown on the graphs. The inset shows a B2 response in a control (left) and a lesioned animal (right). (B) Graphs showing the degree of spontaneous activity (assessed from the rectified and integrated baseline activity) in control and lesioned animals. There was no significant correlation between the swimming score and activity above (C) or below the lesion site (D).

not differ in control and lesioned animals (data not shown). Responses across the lesion site (A3 and A4 responses) were significantly reduced in lesioned animals, consistent with a lesion-induced reduction in descending and ascending inputs (P⬍0.05, n⫽25; Fig. 7A). Responses evoked by stimulating below the lesion site were significantly larger than control when examined up to five segments below the lesion (sites B1–B4; Fig. 7A): effects were generally not significantly different from controls at more caudal sites (from B5–B7, n⫽36; data not shown). However, significantly increased responses were also evoked when stimulation was performed 10 segments below the lesion site (i.e. C1–C4 responses; Fig. 7A). These results thus suggested the presence of region-specific changes in excitability (Grasso et al., 2004). In contrast to the general increase in evoked responses, spontaneous activity recorded from the surface of the spinal cord was significantly reduced at all sites in lesioned animals relative to control (Fig. 7B). This mimicked the situation in acutely isolated hemicords, where spontaneous activity is reduced, but evoked activity is increased (Hoffman and Parker, 2010), an effect that could suggest a functional or anatomical reorganisation of excitatory interactions in the spinal cord. While the evoked activity across the lesion site correlated with the degree of recovery (see Fig. 2A), there were no significant correlations between the swimming score and the level of excitability above (A1; r2⫽0.009, A2; r2⫽0.003; Fig. 7C) or at any point below the lesion site

(B1–C4 all r2 values of ⬍0.05; see Fig. 7D). Thus, as with the sensory potentiation, there was no simple link between the increased excitability and recovery. We examined the influence of excitability changes further by separating animals into those that recovered well (stage 5/6) or poorly (stage 1/2). In stage 1/2 animals, the A3 and A4 responses were significantly reduced compared with control or stage 5/6 animals (Fig. 8A), consistent with the link between regeneration and the degree of recovery, but apart from this, both groups showed the same general trend of increased evoked activity but reduced spontaneous activity below the lesion site (Fig. 8A, B). We also separated animals on the basis of the presence or absence of regeneration (assessed from the A3 or A4 responses). The significant increase in excitability at B1–B4 generally persisted when A3 and A4 activity was absent (i.e. when there was no regeneration), but significant effects only occurred at B2 and B4 when A3 or A4 activity was present (Fig. 8C). This argued against the increase in excitability simply being due to the additional activation of regenerated axons, as excitability was greater when regeneration was absent. There were also differences when stimulation was performed 10 segments below the lesion site: significant increases in excitability occurred at C2–C4 when A3 and A4 activity was present, but only at C4 when it was absent (Fig. 8C). However, the variability was higher in the no regeneration condition for C2 and C3, which may account for this difference. Spon-

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Fig. 8. The relationship of excitability changes to the degree of recovery and extent of regeneration across the lesion site. (A) Graph showing the evoked responses at different sites in control animals and in lesioned animals that showed good (stage 5/6) or poor recovery (stage 1/2): spontaneous activity in these animals is shown in (B). For clarity, only significant effects are again shown on the graphs. (C) Graph showing evoked responses at different sites in control animals and in lesioned animals when there was or was not regeneration (assessed from the A3 and A4 responses): spontaneous activity in these animals is shown in (D). For simplicity, only significant effects are shown on (A) and (C).

taneous activity remained significantly reduced relative to control in both sets of animals (Fig. 8D). As a final stage in the analysis, we examined the interactive effects of excitability changes with the quantified A3 and A4 responses. When animals were separated into those showing stage 5/6 behaviour, there were only positive correlations with the A3 response that were significant for A1, B2–B6, and C4 (B1–B8 responses are shown in Fig. 9A), but for stage 1/2 animals (n⫽4), there were predominantly negative correlations (as A3 inputs increased excitability responses below lesion sites were reduced, which cannot reflect the number of regenerated axons stimulated): these correlations were significant for B1 (r2⫽0.29) and B3 responses (r2⫽0.84; Fig. 9B). These relationships persisted for A4 responses. When stage 5/6 animals were examined, there were again only positive correlations, which were significant at A1, A2, B1–B6, and C3 (Fig. 9C). For stage 1/2 animals, there were negative correlations that were significant at B1, B3, and B7 (Fig. 9D) and nonsignificant positive relationships ipsilateral to A4 (Fig. 9D). There were thus significant differences in the interactions of regenerated axons with the sublesion spinal

cord excitability changes that were related to the degree of functional recovery.

DISCUSSION This study shows that sensory inputs are potentiated below lesion sites in lamprey, and that there are regionspecific changes in spinal cord excitability. These effects add to the evidence for sublesion functional changes (Cohen et al., 1999; Cooke and Parker, 2009). The extent of recovery correlated significantly with the extent of regeneration, but there is an indication that this may depend on how regenerated inputs interact with sublesion networks. The analysis of lesion-induced changes in sensory inputs was a principal aim of the study. A role for sensory inputs in locomotor recovery in lamprey was suggested based on differences in swimming in intact animals (sensory inputs intact) and fictive activity in the isolated spinal cord (sensory input removed; Davis et al., 1993; McClellan, 1990; Cohen et al., 1999). While the differences under these two conditions support a sensory influence (albeit requiring the assumption that fictive

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Fig. 9. The interaction between sublesion excitability changes and the magnitude of regenerated inputs. (A) Graph showing the correlation between the A3 response and the rectified and integrated evoked activity in stage 5/6 animals. (B) Graph showing the correlation between the A3 response and evoked activity in stage 1/2 animals. The response to A4 stimulation in stage 5/6 animals (C) and stage 1/2 animals (D) is also shown.

activity reflects activity in the intact animal; Ayers et al., 1983), lesion-induced changes in sensory inputs had not previously been examined. This contrasts the situation in mammalian systems, where sensory inputs have been studied extensively (e.g. Pearson, 2001; Petruska et al., 2007; Côté and Gossard, 2004; Côté et al., 2003; Reese et al., 2006), and locomotor training can facilitate locomotor recovery (De Leon et al., 1998, 1999; Muir and Steeves, 1997; Pearson, 2001; Edgerton et al., 2001; Edgerton et al., 2008; Wolpaw and Tennissen, 2001; Harkema, 2008; Dietz et al., 2002; Marsh et al., 2011). Here, sensory inputs were potentiated after lesioning: this was reflected in changes in the cellular properties of the proprioceptive edge cells, an increase in the magnitude and reduced adaptation of movement-evoked sensory responses. The potentiation of proprioceptive inputs could aid the patterning of activity below the lesion site by strengthening the sensory entrainment of the locomotor network (McClellan and Sigvardt, 1988; Viana Di Prisco et al., 1990). However, we were not able to determine the relevance of these effects to recovery. The lack of correlation between the sensory responses and the degree of locomotor recovery was surprising, as some positive or negative influence would be expected. In mammals, a reduction or potentiation of H reflexes (which is assumed to reflect changes in motor neuron excitability or sensory synaptic inputs, but could also reflect changes in proprioceptor activity as shown here) can be associated with deleterious (e.g. spasticity; Grey et al., 2008; Boulenguez et al., 2010) or beneficial effects on locomotor function (Murray and Gold-

berger, 1974). However, simple relationships between sensory changes and recovery are also often lacking. For example, there was a lack of correlation between stretch reflex-activated inputs (analogous to edge cell inputs in lamprey; Vinay et al., 1996) and stepping after human spinal cord injury (Dietz et al., 2002), and a lack of correlation between H reflex changes and behavioural scores assessed from hind limb function in rat (Lee et al., 2005). Lee et al. (2005) also showed a correlation between spared white matter after contusion injury and hind limb function, but no correlation between the degree of spared white matter and H reflex changes, mimicking the lack of correlation between across-lesion stimulation responses and sensory changes seen here (Fig. 6D). Thus, while changes in sensory systems typically occur after spinal cord lesions, there is some general uncertainty over how these changes influence motor outputs. When considered independently, the increase in spinal cord excitability also failed to correlate with the degree of locomotor recovery. As with the sensory potentiation, it was surprising that the changes in excitability did not have some positive or negative influence on recovery. It could be argued that this was because the changes in excitability and sensory inputs reflected nonspecific changes (e.g. skin or muscle damage during surgery), rather than injuryevoked neuronal changes. However, effects were examined 8 –10 weeks after surgery when tissue damage at the lesion site had fully healed, making nonspecific effects of this sort unlikely. The lack of correlation between the sensory potentiation and excitability changes below lesion

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sites means that our initial hypothesis, that changes below the lesion site alone directly influence recovery, has to be rejected. In contrast, responses evoked by stimulation across the lesion site correlated significantly with the degree of recovery, supporting a significant role for regeneration. However, while the sensory and excitability changes in isolation did not correlate with the degree of recovery, there were differences in how across-lesion responses interacted with rostral excitability changes in animals that recovered well or poorly. This interaction could contribute to the variable association between the magnitude of across-lesion responses and recovery, and may also account for the lack of sufficiency of regenerated inputs in recovery (e.g. see Cohen et al., 1989, 1999; McClellan, 1990; Selzer, 1978). The nature of the interaction is currently unknown: positive correlations between across-lesion stimulation responses and sublesion excitability changes could simply reflect the stimulation of larger numbers of regenerated axons, but this cannot account for the negative correlations associated with poor recovery. Regenerated inputs may instead regulate excitability changes in sublesion networks, or there may be a circular interaction where regenerated inputs and sublesion networks are modified in parallel to ensure an appropriate functional interaction. Further work is needed to examine these possibilities. An interaction between locomotor networks and sensory systems was also suggested by the lesion-induced increase in spontaneous synaptic inputs in the edge cells. Regional changes in excitability in response to stimulation immediately below the lesion site were suggested by increased excitability rostrally, but not caudally (⬎5–20 segments), below the lesion site. However, excitability was increased in lesioned animals at caudal locations (C1–C4) when stimulation was done 10 segments below the lesion. The increased excitability at rostral regions could reflect an influence of greater regeneration at this location (estimates of the distance of regenerated axons varied between studies, but axons could project to 10 segments below the lesion site at the times examined here; Davis and McClellan, 1994; Armstrong et al., 2003; Yin and Selzer, 1983), while changes at caudal regions could reflect changes in spinal cord excitability. However, as outlined above, the relative influence and interaction of regenerated axons and spinal cord excitability remain unclear, and it seems unlikely that the rostral changes in excitability simply reflect the number of regenerated axons. Taken together, these results support the idea that recovery from spinal injury reflects a distributed system of changes. This highlights the need to consider how various component effects interact rather than focusing on the individual effects. This could claim to be obvious, but this approach has not been reflected in traditional analyses (see Edgerton et al., 2008; Marsh et al., 2011). While they will be more difficult to understand than individual effects, insight into these interactions should reveal additional strategies for improving functional outcomes after injury. Even when regeneration occurs, functional recovery is often poor (see Woolf, 2003; Ruff et al., 2008), which

suggests that regeneration will only make sense in the context of appropriate interactions below lesion sites. Establishing the nature of these interactions and their underlying cellular basis is likely to provide more significant improvements in functional outcomes than a focus on regeneration alone. While this is difficult in mammalian systems, the lamprey should facilitate these analyses.

CONCLUSION In summary, this study has highlighted three aspects: stimulation-evoked responses across a lesion site correlated with the degree of recovery, which suggests a significant influence of regenerated axons in recovery, a far from controversial conclusion; sensory inputs are potentiated below lesion sites, but we have not yet been able to identify a direct relationship between this potentiation and recovery; and finally, there are region-specific changes in excitability below lesion sites that can interact with regenerated inputs to influence recovery. An obvious limit to the analysis is that it is correlational: we now need to manipulate effects to negatively or positively direct recovery to attempt to identify causal links. This is currently difficult, as it requires information on how the changes are mediated. This could reflect neuromodulator activity or homeostatic plasticity in neurons at various levels of the motor system (Boulenguez and Vinay, 2009), or in glial cells, which could also be functional components of the locomotor networks (Baudoux and Parker, 2008). A second limit is that we have treated poorly and successfully recovered animals as homogeneous groups. This may be reasonable for animals that recovered well, as there were few differences in myogram activity in these animals (although similar outputs could still reflect different underlying motor systems), but the heterogeneity in motor dysfunction in poorly recovered animals means that larger sample sizes of each of the specific dysfunctions are needed so that they can be related individually to the functional effects that we have studied. Analyses of dysfunctional animals may ultimately prove to be more informative in identifying causal influences on recovery than those that have recovered well (see also Cohen et al., 1999). Finally, we have only looked at activity evoked across the lesion site to relatively crude stimulation. There are likely to be regional (various descending or ascending pathways, monosynaptic or polysynaptic pathways) or other divisions (e.g. transmitter content; Cohen et al., 2005) that may reveal further causal roles. Acknowledgments—N.H. was supported by fellowships from the National Research and Engineering Council of Canada and the Cambridge Commonwealth Trusts. We thank Drs. Erik Svensson and Tom Gilbey for comments on the manuscript.

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(Accepted 9 September 2011) (Available online 16 September 2011)