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Department of Biokinesiology and Physical Therapy University of Southern California, Los Angeles, California
Submitted 1 August 2005; accepted in final form 7 September 2005
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ABSTRACT |
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INTRODUCTION |
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; Ianniruberto and Tajani 1981), and neonatal infants take alternating steps when supported upright on a treadmill (Thelen et al. 1987; Yang et al. 1998). Leg kinematic patterns for infant stepping are similar to patterns in cats during treadmill locomotion; this inspired the view that neonatal stepping may be produced by a central pattern generator (CPG) (Forssberg 1985; Forssberg and Dietz 1997). Such findings also suggest a developmental continuum from fetal kicking to locomotion in humans (Bradley 2003; Forssberg and Dietz 1997; Thelen 1985). Thus extending our understanding of the relationship between fetal movements and development of locomotion can serve to improve clinical examinations of fetal behavior. The chick, also a biped, expresses a continuum of spontaneous limb movements extending from embryonic day (E) 3.5 to hatching and walking (Hamburger 1963). Because the chick embryo is readily accessible, study of its movements can assist in understanding the continuum of motor control development in infants.
We know spinal circuits produce the earliest leg movements in chick embryos (Hamburger et al. 1965, 1966; O'Donovan and Landmesser 1987). We also know spinal circuits produce leg movements having electromyographic (EMG) and kinematic features by E9 that could be produced by a CPG (Bekoff 1976; Bradley and Bekoff 1990; Landmesser and O'Donovan 1984; O'Donovan and Landmesser 1987). However, studies in isolated spinal cord have required us to rethink whether motility is produced by a CPG (Bradley 1999, 2001; O'Donovan and Chub 1997). In chick spinal cord, the excitatory drive for spontaneous activity changes from cholinergic at E4 to glutamatergic at E10–E12 (Hanson and Landmesser 2003; Milner and Landmesser 1999). If these excitatory systems are pharmacologically blocked, GABAergic pathways provide compensatory drive and restore spontaneous activity (Chub and O'Donovan 1998; Hanson and Landmesser 2003; Milner and Landmesser 1999). The spontaneous activity is associated with waves of excitation that broadly spread from ventral to dorsal horn (O'Donovan et al. 1994). Such findings lead to the proposal that embryonic motility is produced by population dynamics arising from recurrent excitation and synaptic depression within an immature network rather than a CPG (O'Donovan and Chub 1997; Tabak et al. 2000). Nonetheless recent findings in mutant fetal mice lacking choline acetyltransferase for acetylcholine synthesis indicate that flexor/extensor and left/right motor output patterns are altered, suggesting that acetylcholine both drives motility and configures the locomotor CPG (Myers et al. 2005).
Assuming motility is dependent on population dynamics does not necessarily exclude the possibility that it is part of a behavioral continuum for locomotion. Walking ability of hatchlings hours after cervical transection or deafferentation is evidence that locomotion in the chick is controlled by a CPG (Bekoff et al. 1987, 1989; Jacobson and Hollyday 1982b), so presumably the CPG is assembled during embryogenesis. Embracing these assumptions, we hypothesized that there is a behavioral continuum in control of limb movements between early and late embryogenesis and that discontinuities might reveal the emergence of the locomotor CPG in the chick embryo. To that end, we recorded motility at four time points, provide the first detailed study of kinematics and EMG at E15 and E18, and report age-related continuities and discontinuities between E9 and E18. Findings lead us to propose that fundamental attributes of motility extend across embryonic development and may be driven by population dynamics enlisting an immature locomotor CPG. Raw kinematic data for a portion of E9 and E12 embryos included in this study were drawn from an earlier study (Bradley 1999) and are here analyzed using methods that could be applied uniformly across all ages. These analyses have not previously appeared elsewhere.
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METHODS |
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; reprinted 1992) were used to verify embryonic age. All procedures were approved by the University Institutional Animal Care and Use Committee. Kinematic and EMG recordings
Embryos were prepared for behavioral recordings in ovo by placing a window in the shell and deflecting egg membranes to obtain a sagittal view of the entire body. The estimated surface locations for eight joints (shoulder, elbow, wrist, lower thoracic spine, hip, knee, ankle, foot) in the ipsilateral wing and leg were marked for digitizing by either applying spots of white nail enamel or inserting modified minutin pins. A point was placed on the outer shell for X-Y registration of digitized points across consecutive pictures, and a 5- to 6-mm stick for distance calibration was placed adjacent to the embryo. Muscles of the ipsilateral leg and wing were implanted with bipolar fine wire electrodes (25 µm platinum or 50 µm silver) for electromyographic recording (EMG). Four of the following muscles were implanted: sartorius (SA), hip flexor; femorotibialis (FT), knee extensor; tibialis anterior (TA), ankle dorsiflexor; lateral gastrocnemius (LG), ankle extensor; latissimus dorsi (LD), shoulder retractor; triceps brachii (TR), elbow extensor.
Video acquisition at 30 fps was continuous along with output from a SMPTE time code generator (SR50, Horita) that uniquely identified each video picture. A synchronizing pulse was manually triggered at 5-min intervals, and the output directed to both video and computer for off-line synchronization of kinematic data with EMG. EMG signals were amplified (1,000x), high pass filtered at 100 Hz, and computer sampled at 2–4 kHz (Datapac, Run Technologies).
Kinematic and EMG analyses
Motility sequences typically increase with age, so we selected three to five video sequences of continuous activity amenable to computer digitizing to sample 4–5 min of movement per embryo. Each joint marker and reference was automatically digitized at 60 Hz to generate x and y (2D) coordinates (Motus, Peak Performance Technologies). Coordinates were low-pass filtered using a Butterworth (double pass, 6 Hz at E9–E15, 12 Hz at E18 based on best fit to raw data) for linear trend analyses, or fast Fourier transform (FFT, smoothing factor of 4) for peak frequency analyses. Filtered coordinates were entered into an algorithm that first calculated changes in distance between adjacent joint markers to estimate a z coordinate for movement out of plane. The three coordinates were used to calculate joint angles (Orosz et al. 1994). Joint angles were calculated for the ipsilateral wing (shoulder, elbow) and leg (hip, knee, ankle) employing methods previously described (Bradley 1999; Bradley and Sebelski 2000; Chambers et al. 1995).
Joint angles were imported into analyses software to construct time-displacement plots, merge EMG data, and complete analyses (Datapac R2K, Run Technologies). Wing and leg joints displayed similar spatiotemporal changes within a motility sequence, so linear trend analyses were performed to obtain measures of intralimb (shoulder/elbow; hip/knee; knee/ankle) and interlimb coordination (shoulder/hip). ANOVA and post hoc Student's t-test were applied to Pearson correlation coefficients (R) produced by trend analyses to test for age-related changes in coordination patterns. Significance testing for the ANOVA was set at P < 0.05, and post hoc Student's t-test employed the Bonferroni correction of P < 0.05/3 comparisons (E9 vs. E12, E12 vs. E15, and E15 vs. E18). We examined temporal attributes of repetitive joint motion by applying FFT analyses to identify peak frequencies. The time series for each joint was parceled into sequential frames of 4.25 s, and 256 points were sampled per frame (zoom ratio 1:1) to identify the amplitudes and power for frequencies between 0.2 and 30 Hz. The three greatest peak frequencies within a frame were pooled across frames by joint per embryo to complete power trend analyses. ANOVA and post hoc Student's t-test were applied to power coefficients (R2) produced by the trend analyses to test for age-related changes in the spectral content of the time series. Numerical summaries of group data report means ± SD.
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RESULTS |
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) during an interval when the embryo remained fully buoyant in the center of the egg and movements appeared unconstrained by the environment. The decreasing joint ranges E12 to E18 coincided with substantial body growth and increasing space limitations, such that any portion of the body might intermittently contact the shell wall. The foot frequently contacted the shell, but not all limb extensions resulted in contact or appeared mechanically unconstrained. However the embryo was also less buoyant beyond E12 and contacts or constraints acting on the contralateral half of the body could not be reliably tracked.
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Joints within a limb tended to move together and the extent of intralimb coordination was reliable as indicated by significant linear co-variations between joints within embryo at all ages. However, the linear trends exhibited complex age-related changes between E9 and E18. Age-related changes in wing coordination are characteristic of the complexity. Trend analyses for the wing time series in Fig. 1, A and D, are shown in Fig. 3 to serve this point. In these two sequences, wing linear trends at E9 in A1 and E18 in B1 appear similar with Pearson coefficients exceeding 0.7. ANOVA and post hoc comparisons for Pearson coefficients confirmed that shoulder and elbow excursions co-varied to a similar extent from E9 to E15 but decreased from E15 to E18 (Fig. 4A). The down turn at E18 was attributable to eight sequences yielding negative coefficients, indicating that the shoulder and elbow tended to rotate in opposite directions. These sequences were distributed among four embryos (Fig. 4B), and in all four cases, elbow excursion range rarely exceeded 10°. Video clips for two of these embryos also revealed that the head was tucked under the wing, abducting the shoulder and elevating the elbow. These findings suggested to us that the negative co-variations may have arisen from postural configurations and/or constraint of the wing but that overall intralimb coordination of the wing was similar between E9 and E18.
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At E9–E12, knee and ankle traces exhibited similar spatiotemporal patterns (Fig. 1, A and B) that frequently yielded moderate to strong positive coefficients (Fig. 3A3). The knee and ankle rarely rotated in opposite directions at E9 or E12 (Fig. 4C). At E15, there were many instances when the ankle rotated out of phase with the knee (vertical arrow, Fig. 1C), but subject averages for 50% of E15 embryos fell within the E9–E12 range (Fig. 4C). By E18, the out-of-phase knee/ankle pattern was characteristic in 8 of 12 embryos, many sequences yielding moderately or strongly negative linear parameters (Fig. 3B3). Post hoc comparisons for ankle and knee excursions indicated that the increase in negative co-variations between E12 and E15 was significant (, Fig. 4C). Here too, video for some motility sequences appeared to indicate mechanical constraint might account for out-of-phase limb kinematics. In some sequences, plantar flexion (ankle extension) during foot contact with the shell appeared to generate reactive forces that displaced the knee in a rostral direction, synchronously flexing the knee and hip. However, shell contact was not always apparent and in many cases the foot clearly did not contact the shell wall.
We asked whether age-related changes in leg EMG patterns might account for the kinematic transformation from an in-phase to out-of-phase knee/ankle pattern at E15–E18. Over numerous attempts to obtain synchronized EMG at E9–E12, we found that fine wire electrodes only occasionally captured the distinct repetitive muscle bursting seen in suction electrode recordings at E9–E10 (Bekoff 1976; Bradley and Bekoff 1990). TA frequently exhibited tonic low-amplitude activity, whereas extensor muscles appeared to be inactive except during abrupt extensions. When repetitive TA bursting was apparent, the activity coincided with ankle flexion (
, Fig. 5A); and if LG or other extensors were active, bursting coincided with joint extension (*, Fig. 5A). At E15–E18, repetitive muscle activity was readily detected, and during repetitive limb motions, alternating ankle flexor (TA) and extensor (LG) activity was common (Fig. 5, B and D–F). If multiple muscles were active, hip flexor (SA) bursting was coincident with TA bursts, forming a flexor synergy (
, Fig. 5B), and FT bursts were typically paired with LG, forming an extensor synergy (*, Fig. 5B). FT activity was notably the most variable, and there were many instances when FT onset shifted, increasing the extent of coactivity with TA, forming a "mixed synergy" (Fig. 5, E and F). We at first speculated that the mixed FT+TA synergy might account for the out-of-phase knee/ankle kinematics but observed that the out-of-phase kinematic pattern also occurred when FT activity was synchronous with LG (
, Fig. 5B). More extensive study of these EMG and movement patterns will be required to determine if small latency shifts in FT can induce inertial lags between leg and foot segments.
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). We constructed 713 plots (15 ± 2 plots/embryo) from which we identified 4 patterns: elliptical (Fig. 6, A–C), diagonal (D and E), polygonal, and complex (not shown). In most cases the angle-angle pattern varied substantially across consecutive excursions, generating a combination of patterns such as one elliptical and two diagonal plots (Fig. 6F). The number of elliptical and diagonal plots increased from E9 to E12 and most were rightward leaning (ER, DR, Table 1), conveying the close in-phase scaling of amplitude and time between knee and ankle motions. The total number of elliptical and diagonal plots did not vary E12–E18, but the number of leftward leaning plots (EL, DL) progressive increased, conveying a close out-of-phase scaling of amplitude and time for knee and ankle motions. Disregarding lean direction, plots within a category appeared similar in pattern across age even as duration of elliptical and diagonal plots decreased from 
1.7 s (E9) to 0.8 s (E18).
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Motility sequences on E18 were distinguished by extended bouts of limb oscillations that resembled tremor (Fig. 5, B and C). Oscillations of the leg were generally 2–3 Hz and only a few degrees in amplitude. The amplitude and timing attributes of kinematics were particularly stable over multiple tremor-like excursions and were the only samples of motility generating several overlapping elliptical plots (Fig. 6G). Note that knee and ankle excursions were out of phase with one another, generating leftward leaning plots. During these sequences FT activity was paired with LG and/or slightly phase advanced (Fig. 5, B and D).
The 2- to 3-Hz oscillations were at times abruptly interrupted by explosive 3- to 10-Hz movements resembled shivering (right horizontal bar, Fig. 5C). We refer to the latter events as repetitive ballistic limb movements (RBLM). RBLM also frequently erupted during otherwise inactive stretches of recording, often several times in sequence with only a few seconds of pause in between. It was during RBLM we most frequently noted a distinct shift in timing of FT bursts to form the mixed FT+TA synergy, alternating with LG (Fig. 5, E and F). All E18 embryos exhibited tremor-like and/or RBLM movements accompanied by one or more of the EMG features we describe. These kinematic and EMG features were not readily apparent at E15. However, less-organized oscillations in kinematic traces were found in eight embryos, and in four of these embryos, oscillations were occasionally accompanied by irregular bursts in the TA, LG, FT, or IF EMG.
The emergence of tremor-like oscillations and RBLM at E18 raised the possibility of age-specific changes in the frequency content of motor output commands and potential cues to changes in motility circuitry. Therefore we performed FFTs on each time series (joint). The three frequencies having largest amplitude and power peaks per frame of the FFT were complied across all sequences per embryo; examples of two knee data sets are plotted in Fig. 7. After determining there were no differences in mean peak frequency between joints, we selected knee peak frequencies to test for age-related variations in light of its stable co-variation with hip across age but variable relationship with ankle (Fig. 4A). Contrary to our predictions, FFTs revealed that the mean peak frequency and range of 0–10 Hz were similar across ages. The only distinct trends were a decline in power at lower frequencies and power coefficients for trend analyses of peak frequencies with increasing age. Exemplary power plots for knee excursions in an E9 (Fig. 7A) and E18 embryo (Fig. 7B) are shown. To test for age-related differences, we parceled the peaks into four bandwidths: frequencies <1, 1–1.99, 2–2.99, and 3–10 Hz. Age-related declines in power between E9 and E18 were significant for frequencies <2 Hz. Post hoc tests were mostly nonsignificant, indicating the trends were progressive rather than stepwise. Absolute power for frequencies 2–10 Hz did not vary with age, but they represented a significantly greater percent of total power with increasing age.
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Time series for shoulder and hip excursions also shared spatiotemporal features in many samples at all ages (Figs. 1 and 3, A4 and B4). Again, the relationship between shoulder and hip varied significantly with age (Fig. 4A). At E9, embryos exhibited a moderately strong pattern of in-phase shoulder and hip excursions; but at E12 and E15, only three to four embryos exhibited an in-phase pattern. At E18, a moderately strong out-of-phase pattern predominated. The out-of-phase shoulder and hip excursions at E18 were common during tremor-like movements (Fig. 8), and intermittent during less regular excursions (*, Fig. 1D). EMG activity for wing muscles at E12 and E18 appeared consistent with kinematic traces, i.e., latissimus dorsi (LD) was active during shoulder retraction, and the triceps brachii (TR) was active during elbow extension. During repetitive bursts in two experiments at E12, TR bursts were coincident with FT and LG bursts during leg extensions (*, Fig. 5A). In three experiments at E18, LD bursts were observed during RBLM (Fig. 5E). Distinct LD bursting accompanied tremor of the wing that could last for many seconds (Fig. 8). No one pattern of LD and leg muscle activity was apparent during faster movements and leg EMG tended to decay or cease over the course of wing excursions.
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DISCUSSION |
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; Muir et al. 1996). Spinal transection and deafferentation in hatchlings indicates walking is controlled by a CPG (Bekoff et al. 1987, 1989; Jacobson and Hollyday 1982b). Whether motility is also controlled by a CPG is not yet clear. By E9, chick embryos generate motility sequences characterized by coordinated flexion and extension of leg joints and alternating flexor and extensor muscle synergies (Bradley and Bekoff 1990; Chambers et al. 1995). Between E9 and E12, both the wing and limb exhibit an increase in intralimb coordination (Bradley 1999). However, leg movements exhibiting a disassociation of knee and ankle excursions at E13 raise the possibility that intralimb coordination breaks down during subsequent development (Sharp et al. 1999). Our findings extend these observations to E18 and reveal five critical points for advancing our understanding of embryonic leg movements. One, coordinated kinematic and/or EMG patterns observed at E9 were expressed at all four time points E9-E18. Two, variable knee and ankle excursions at E15–E18 sorted into in-phase and out-of-phase patterns. Third, leg EMG patterns at E18 did not directly account for out-of-phase coupling between the knee and ankle. Fourth, 2- to 10-Hz limb excursions emerged at E15–E18, and during the faster movements, mixed muscle synergies were produced resembling EMG patterns during the paw shake in cat. Fifth, wing and leg movements were intermittently coordinated E9–E18, but an in-phase pattern at E9 and out-of-phase pattern at E18 were the most distinct, confirming and extending an earlier observational study of motility in ovo (Provine 1980). Continuum in motor development
Coordinated kinematic and EMG patterns observed at E9 were also expressed E12–E18, supporting the view that the leg pattern for early motility forms the basis for mature motor patterns such as hatching and walking (Bekoff 1992). Sharp et al. (1999) observed that the extent of in-phase coupling of hip and knee did not vary E9–E13, and our results extend this pattern to E15–E18 (Fig. 4A). In-phase hip and knee coupling is consistent with the model of unit burst generators (half-centers) that synchronize flexion and extension across joints (Orlovsky et al. 1999). Consistency of hip/knee coupling during spontaneous motility suggests hip and knee unit burst generators are established and functionally interconnected by E9. In addition, alternating ankle flexor and extensor EMG activity was observed at all four time points, suggesting the ankle burst generator is functioning E9–E18. Further, in-phase coordination of wing excursions also suggests that limb movements are controlled by coupled unit burst generators E9–E18.
Our kinematic findings are consistent with the variable coupling between knee and ankle at E13 reported by Sharp et al. (1999); and they extend the observation to E18. The in-phase coupling of ankle and knee excursions at E9–E12 and more variable coupling after E12 might seem to suggest knee and ankle unit burst generators are initially synchronized but that coupling breaks down between E12 and E18. However, a breakdown in coordination between burst generators seems unlikely given the continued expression of alternating muscle synergies at E18, even as knee and ankle moved out of phase (Fig. 5, B–D). Further, the discrepancy between EMG and kinematic patterns at E18 may indicate that embryonic unit burst generators are not readily decoupled by movement related feedback. Thus we propose an alternative view, one that attributes developmental changes in limb coupling during embryogenesis to biomechanical dynamics. There are seemingly substantial changes in the musculoskeleton, force-generating capabilities of leg muscles, and environmental constraints as the embryo increases in size and begins to fold over itself in tight quarters. Any of these variables alone or in combination may exert mechanical forces sufficient to mask coordination of knee and ankle unit burst generators. For example, the variability in knee/ankle coordination at E15–E18 was partially attributed to a reversal from in-phase to out-of-phase coupling rather than to a loss of coupling. The out-of-phase excursions during 2- to 10-Hz oscillations and some startles could have resulted from inertial interactions between limb segments such as during paw shaking in cats (Hoy et al. 1985). Further, in the adult cat muscle afferent input is required to reconfigure leg muscle patterns during rapid limb movements (Koshland and Smith 1989a,b), but muscle afferents appear to be significantly immature over the ages of our study (Maier 1992, 1993).
Transformations in the source of drive to unit burst generators may also account for the increasing variability in limb kinematics over age. Glycinergic and GABAergic actions switch from excitatory to inhibitory during the later half of embryogenesis (Chub and O'Donovan 1998). Descending pathways (Glover 1993; Glover and Petursdottir 1991; Okado and Oppenheim 1985) and proprioceptive afferents (Maier 1992, 1993) are undergoing refinements that may provide a more variable source of drive to unit burst generators. Immature excitation may be intermittent and poorly modulated resulting in the occasional rhythmic excursions that resemble a series of startles as seen E15 (horizontal bar, Fig. 1C). Emergence of 2- to 3-Hz oscillatory limb movements and 3- to 10-Hz RBLM at E15–E18 may herald the emergence of more sustained brain stem drive of wing and leg unit burst generators.
Is motility produced by a locomotor pattern generator?
Chicks are precocious walkers capable of running to stay up with a mobile brood shortly after hatching (Muir et al. 1996). Further, chicks can walk 
2 days earlier if time to hatching is accelerated by rearing in continuous light (Bohren and Siegel 1975; Fairchild and Christensen 2000) or exposure to artificial clicking (Vince et al. 1976). These findings seem to suggest the CPG can produce adaptive locomotion as early as E19. Although investigators have intermittently explored the possibility of a functional continuity between embryonic motility and locomotion, evidence favors the view that motility does not serve a functional role in locomotor development (Haverkamp and Oppenheim 1986). In chicks for example, motility appeared to fully recover after 1–2 days of neuromuscular blockade, and the immobilization had no impact on hatching and posthatching development if the embryo was free of foot deformities (Oppenheim et al. 1978). Prolonged immobilization of Xenopus and Ambystoma embryos between the stages of premotility and established swimming only transiently altered swimming behavior (Haverkamp 1986; Haverkamp and Oppenheim 1986). Results of these studies were interpreted to indicate that the nervous system develops in forward reference to functional activity at later stages of development independent of experience (Haverkamp and Oppenheim 1986). However, resilience to transient paralysis may also indicate that CPG networks are already sufficiently established to remain robust in the face of perturbations. If this is correct, a clearer understanding of early CPG circuitry assembly in chicks may offer some indication as to why they are precocious walkers and why altricial animals appear more vulnerable to transient paralysis (Moessinger 1983).
Alternately active antagonist muscles about a joint and alternating flexor and extensor synergists are evidence that half-centers or unit burst generators forming CPG for limb movements may be established by E6–E9 in chicks (Bekoff 1976; Bradley and Bekoff 1990). Spontaneous activity in isolated spinal cord may be important for establishing the CPG circuitry. The E4–E12 lumbar spinal cord produces episodic motor activity composed of cyclic bursting similar to EMG and kinematics during repetitive leg movement (Bekoff 1976; Bradley 1999; Landmesser and O'Donovan 1984). Cycle durations and alternating antagonist leg muscles also appear similar between preparations (Bradley 1999; Bradley and Bekoff 1990; O'Donovan and Landmesser 1987). However, spinal preparations produce more stereotypic activity and more consecutive cycles bracketed by longer pauses (Bradley 2001; Landmesser and O'Donovan 1984). The spinal activity is driven E4 by acetylcholine, then by glutamate and GABA between E4 and E9 (Chub and O'Donovan 1998; Milner and Landmesser 1999; Sernagor et al. 1995). In mice, the absence of acetylcholine appears to reduce activity and alter development of motor output for intralimb and interlimb coordination (Myers et al. 2005). Differences between spontaneous spinal cord activity and motility may indicate they are not one and the same, but the general repetitive structure suggests to us that the spontaneous spinal activity is important to intact motility.
The characteristics of and continuities in kinematic and EMG activity we observed at E9–E18 seem to suggest limb movements for motility are produced by coupled unit burst generators equivalent to a functional CPG for control of locomotion at hatching. Excluding negative knee/ankle correlations at E15 and E18, our regression results are consistent with the close positive co-variations between hip and knee, and knee and ankle during forward treadmill locomotion in cat (Buford and Smith 1990; Buford et al. 1990). It is of note that the negative knee/ankle correlations we observed at E18 were accompanied by alternating flexor and extensor synergies. Alternating flexor and extensor synergies are also expressed during backward locomotion in cat, even as the hip moves out of phase to the knee (Buford and Smith 1990). Further, in-phase elliptical and diagonal angle-angle plots, similar to those we observed during motility E9–E18, are also observed during treadmill locomotion in cats (Buford et al. 1990) and swimming in rats (Walton et al. 2005). Finally our E18 EMG data suggest there is a physiological bridge binding E9 data with the CPG for locomotion. The frequency range for alternating flexor and extensor EMG synergies at E18 fell within ranges observed during walking, swimming and airstepping 1–3 days post hatching (Johnston and Bekoff 1996).
Significance of findings
During normal embryonic development, the patterns of limb movement appear to be coordinated soon after they first emerge, suggesting that many of the key organizational elements (e.g., unit burst generators or half-centers) within the spinal cord for CPG control of locomotion are functional at the developmental onset of limb movement. Similar observations have been made regarding development of motor skills in kittens (Bradley and Smith 1988a,b). Achievement of repetitive limb movements between E4 and E9 may be emblematic of the embryo having completed a critical phase of development beyond which the developmental progression of these motor patterns may be less fragile in the face of unexpected prenatal events and therefore predictive of the capacity to attain locomotor skill. Conversely, limb movements lacking these patterns may be evidence that establishment of the requisite circuitry was altered very early in embryogenesis and likely to impact later locomotor outcome. However, our results also caution that seemingly altered motor patterns do not necessarily indicate neural control has been compromised. The embryo or fetus is just as likely as the adult to experience the biomechanical consequences of moving the limb's segmented masses. Embryonic motor behavior may be dramatically shaped by variables such as physical constraint that change dramatically over development even as the limb and body to which it is attached are changing.
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GRANTS |
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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Address for reprint requests and other correspondence: N. S. Bradley, Dept. of Biokinesiology and Physical Therapy, University of Southern California, 1540 E. Alcazar St., CHP155, Los Angeles, CA 90089 (E-mail: nbradley{at}usc.edu)
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