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FP7-PEOPLE-2012-IEF Motor_Dev

STARTPAGE

PEOPLEMARIE CURIE ACTIONS

Marie Curie Intra-European Fellowships (IEF)Call: FP7-PEOPLE-2012-IEF

Final Report

“Motor_Dev”

Final Report - of 49


TABLE OF CONTENTS

A Summary of Activities (Months 1-24)...............................................................................................3 Scientific summary.................................................................................................................................3

Manuscripts published, submitted or in preparation.............................................................................4 Presentation of results in national and international conferences.........................................................4

Supervision activity and collaborations..................................................................................................4 Courses...................................................................................................................................................5

B Global Results Part I........................................................................................................................6

C Figures and Figure Legends Part I...................................................................................................12

C Global Results Part II.....................................................................................................................29

D Figures and Figure legends Part II...................................................................................................31

E Perspective....................................................................................................................................36 Significance of the obtained results......................................................................................................36

F Experimental Protocols..................................................................................................................38

G Reference List................................................................................................................................48



A SUMMARY OF ACTIVITIES (MONTHS 1-24)

Scientific summary

Integration of motor and somatosensory functions is a primary requirement for body

movement control and exploration (Llinas, 2001). Motor and somatosensory systems develop and

bind together to support sensorimotor integration (Arber, 2012). Early stages of sensorimotor

system development are characterized by the occurrence of spontaneous movements. Whether and

how these movements support coordination in developing sensorimotor circuits remains unknown,

however.

Part I. Using translaminar recordings from the spinal cord of neonatal rats in vivo, we found

highly correlated activity in sensory and motor zones, provided by movement-related bursts in

motor zones that were followed by bursts in sensory zones, suggesting a potential involvement of

sensory feedback and efferent copy. Deafferentation did not affect activity in motor zones and

movements, but profoundly suppressed activity bursts in sensory lamina and resulted in almost

complete sensorimotor uncoupling, implying a primary role of sensory feedback in sensorimotor

integration. This was further supported by largely dissociated activity in sensory and motor zones

observed in the isolated spinal cord preparation in vitro. Thus, sensory feedback resulting from

spontaneous movements is instrumental for coordination of activity in developing sensorimotor

spinal cord circuits.

Part II. Through simultaneous recordings of primary motor cortex (M1) activity and motor

behavior in neonatal rats, we found so far that, over the first postnatal week, spontaneous hindlimb

movements trigger spindle-bursts in the corresponding area of the contralateral M1. At these ages,

epileptiform discharges, induced by local delivery of bicuculline, in M1 also were driven by

spontaneous movements. From the second postnatal week, spontaneous movements and M1

spindle-bursts waned in parallel with the development of continuous background activity, and local

bicuculline-induced M1 epileptiform discharges started driving contralateral hemiclonic jerks. Thus,

during the first postnatal week, M1 operates essentially in a somatosensory mode, with sensory

feedback resulting from spontaneous movements triggering topographic spindle-bursts that are

potentially involved in the activity-dependent formation of sensorimotor circuits. Epileptiform

discharges in M1 cortex during the neonatal period remain largely infraclinical.



B GLOBAL RESULTS PART I

To understand the neural basis of early sensorimotor integration in the spinal cord, we

developed a method enabling recording simultaneously translaminar, spinal cord network events

and movements, in vivo. Subjects were neonatal rats, 5 to 7 days old (i.e. P5 to P7, P0 = day of birth).

Extracellular, local field potential (LFP) and multiunit activity (MUA) were recorded through a linear

silicone-based electrode array (16 recording sites with a center-to-center separation of 100 μm).

Motor behavior (left hindlimb movements) was recorded using a piezoelectric transducer. Our

experimental setup is schematically illustrated in Figure 1A. The electrode array was inserted at the

lumbar enlargement (hindlimb representation), at the L3-L5 left hemi-segment level. Anatomical

localization of each recording site was based on the electrode array insertion coordinates and on the

corresponding or age-matched histological assessment (as demonstrated in Figure 1B). Throughout

the text, depth refers to the subdural spinal depth along the electrode array axis.

Spatiotemporal properties of tactile stimulus-evoked spinal activity and intraspinal

microstimulation-evoked movements

Systematic tactile stimulation of different points along the hindlimb allowed establishing

topographic relationships, identifying the location of spinal sensory neurons and examining the

spatiotemporal properties of spinal tactile stimulus-evoked activity in the ipsilateral L3-5 spinal

hemisegments. Tactile stimulation consisted of a brief (5-10 ms) touch, provided at a rate of 5 s -1.

The two recording sites (or equivalent intraspinal depths) showing the shortest response latencies

were considered as “sensory zone”. Figure 2A shows a case example of response (sensory zone,

average within-burst MUA frequency) by stimulation point, reminiscent of the large receptive fields

previously described for this age group (Fitzgerald, 1985;Fitzgerald and Jennings, 1999). Stimulations

of the back, tail, contralateral hindlimb, and forelimbs did not produce alterations in spinal activity in

L3-5 hemisegments. The stimulation point for which we obtained the shortest latency and highest

multiunit frequency response was considered “topographic”, and this response was analyzed

further.

Recordings of tactile stimulus-evoked activity were done in slightly anesthetized (0.5 %

isoflurane) and non-anaesthetized animals. In both conditions, topographic, tactile stimulation

reliably evoked a primary, sharp LFP deflection and sink within dorsal horn laminae, with field

potentials reversing at relatively deeper dorsal horn laminae (Figure 2B and Figure S2). These field

events were associated with an increase in spiking activity (Figure 2C and D), from 11.9 ± 4.6 s-1



(baseline) to 193.2 ± 141.4 s-1 (average within-burst), (mean ± SD, n = 10 non-anesthetized animals, p

≈ 0.002, Wilcoxon signed-rank test). Evoked bursts onset and offset were estimated at 12 ± 2 ms and

77 ± 43 ms post-stimulus, respectively (mean ± SD, n = 10 non-anesthetized animals, Figure 2C). For

the vast majority of cases (n = 12 of 14 animals), a secondary activity burst also was observed. These

secondary bursts were restricted to the upper most regions activated by sensory stimulation

(generally at the subdural depths of 100-200 m, consistent with the location of laminae I-II), and

occurred with a delay ranging from approximately 70 to 100 ms in relation to stimulus onset. While

primary bursts likely result from incoming A-fiber inputs, the secondary bursts might reflect

responses to C-fibers activation, as shown previously (Fitzgerald, 1985).

While we obtained qualitatively and quantitatively similar sensory responses when using or

not isoflurane (Figure 2D and Figure S2), one main difference was found: in the no-anesthesia

condition, sensory bursts correlated with following activity in motor zones (as demonstrated in

Figure 2C and D). This activity profile is reminiscent of the activation of reflex pathways. In addition ,

the mean baseline MUA in sensory zones was approximately 2 fold higher in the absence of

isoflurane: 4.9 ± 2.4 s-1 (with isoflurane) and 11.9 ± 4.6 s-1 (without isoflurane), (mean ± SD, pulled

data, p ≈ 6.5 x 10-4, Wilcoxon rank-sum test). The mean MUA in motor zones also was higher in the

absence of isoflurane: 9.6 ± 6.3 s-1 (with isoflurane) and 18.2 ± 11.4 s-1 (without isoflurane), (mean ±

SD, pulled data, p ≈ 0.045, Wilcoxon rank-sum test). It should be noted that topographic, tactile

stimulus-evoked burst onsets in sensory zones tended to decrease from P5 to P7 (pulled data, p =

0.0531, Kruskal-Wallis), about 2 ms per day (Figure S2), which is largely in agreement with previous

reports on the development of sensory processing in the spinal cord (Fitzgerald and Jennings,

1999;Fitzgerald, 2005) and, in particular, with fiber myelination (Friede and Samorajski, 1968)

(Webster, 1971).

Then, to probe the anatomical location of premotor/motor networks, we provided brief

electrical pulses (50 μs) at different spinal cord depths, with electrical stimulation sites matching

recording sites. For that purpose, a bipolar electrode was lowered to the maximum depth used for

recordings (expected location of motoneurons): the minimum current required to elicit detectable

movement was determined and used at all depths (100-200 m steps). Electrical stimulation was

performed in deeply anesthetized (1.5 % isoflurane) animals. Muscle activity was reliably evoked for

electrical stimulations in intermediate to ventral horn laminae (Figure 2E). Movement onset and

offset (as measured by piezoelectric transducers) were located at 11 ± 2 ms and 146 ± 15 ms post-

stimulus, accordingly (mean ± SD, n = 9 animals, Figure 2E). The 2 depths of electrical stimulation

associated with the highest amplitude movements were considered as “motor zone”.



Closer examination of the depth distribution of topographic tactile stimulus-evoked MUA

across animals revealed increases in spiking between a minimum depth of 100 μm and a maximum

depth of 600 μm (n = 9 animals, Figure 3A), with the highest within-burst spiking rates being located

at 100-300 μm, estimated to correspond roughly to laminae I-IV (n = 23-37 responses per depth

range, 15 animals, p = 0.0046, Wilcoxon rank-sum test, Figure 3B). Consistently, short-latency MUA

responses also were found predominantly at the depths of 100-300 μm (p = 0.0030, Wilcoxon rank-

sum test, Figure 3C). Indeed, while in adult rats Aβ-fiber inputs (innocuous tactile stimulation) are

restricted to laminae III-IV, in neonatal rats A-fiber inputs reach superficial and deeper dorsal horn

laminae (Fitzgerald, 2005;Petersson et al., 2003). Muscle activity, on the other hand, was evoked for

stimulations at a minimum depth of 600 μm (deep dorsal horn) and reached the highest magnitude

when stimulations were performed at a depth of 1000-1200 μm (ventral-most regions, n = 14-16

responses per depth range, 9 animals, p = 0.046, Wilcoxon rank-sum test, Figure 3B), without any

depth-dependence in movement onset (Figure 3C).

Peri-twitching spinal network dynamics: intermediate/ventral activity → twitching → dorsal

activity

Next we recorded spontaneous spinal cord activity and behavior in non-anaesthetized

animals, under buprenorphine analgesia. Spontaneous spinal cord activity was characterized by

intermittent LFP deflections and correlated MUA bursts (Figure 4A), which, within sensory and motor

zones, occurred at the approximated frequencies of 4.3 ± 1.0 min -1 and 3.6 ± 0.9 min-1, respectively

(mean ± SD, n = 4249 sensory zone bursts and n = 3362 motor zone bursts recorded in 15 animals).

The occurrence of activity bursts did not differ significantly between the two zones (Wilcoxon rank-

sum test). Mean multiunit spiking activity also did not differ significantly between motor (55 ± 20 s -1)

and sensory (41 ± 18 s-1) zones (mean ± SD, n=15 animals, Wilcoxon rank-sum test). Temporal

analysis of ipsilateral hindlimb movements (4.5 ± 2.1 min -1 mean ± SD, n = 4363 events recorded in

15 animals) and spinal cord activity revealed that ≈ 75 % of the recorded MUA bursts in motor zones

were followed (within 100 ms) by overt hindlimb movement. Importantly, the majority (≈ 60 %) of

MUA bursts in sensory zones were preceded (within 100 ms) by movement. Thus, activity in the

spinal cord dorsal horn may be, to large degree, externally driven. It should be noted that the

numbers above provided, although activity and movement onsets cross-correlation peaks, are

underestimates of the amount of both motor and sensory bursts that in fact correlated with overt

movement. First, in complex movement sequences, preceding or following events might not be

established as such. Second, recorded movements do not necessarily correspond to the single

segment level of recordings.



Of all the detected behavioral events, 54 ± 17 % (mean ± SD) fell in the twitches category,

which was defined essentially as events lasting less than 600 ms (252 ± 122 ms, mean ± SD) and

occurring in a background of atonia, i.e. absence of preceding or following continued motor activity

(for methodological details, see Figure S3). These results are in line the predominance of active sleep

and of the twitching behavior in neonatal rats, over the first postnatal week (Blumberg et al., 2013).

Twitches were consistently preceded by LFP events with sinks and prominent elevation of spiking

activity in intermediate-ventral spinal cord laminae; by contrast, within sensory zones, LFP

deflections, current sinks and increased firing rates were generally triggered by twitches (Figure 4B,

single twitch; Figure 4C and 4D, single animal; Figure 4E, 15 animals). The general of pattern of peri-

twitching network activity observed includes two additional main features. First, in all animals, we

found two main current sinks initiated prior to twitching, within the ventral and in the intermediate

spinal cord. Second, increases in spiking frequency within sensory and motor zones overlapped, to

some extent, after twitch onset. Cross-correlating motor and sensory spikes occurring within a ± 1 s

time period in relation to twitch onset revealed peak correlations at a lag of approximately 48 ± 29

ms (sensory zone spike times referenced to motor spike times, mean ± SD, n=15 animals, Figure 4F).

Cross-correlating spike times in motor and intermediate zones further confirmed a predominantly

synchronous activation of these two zones (Figure 4F).

Deafferentation eliminates twitches-related activity in sensory zones

Next, we examined, causally, whether activation of sensory neurons by a feedback mechanism

is at the origin of the twitching-related dorsal horn activation. For that purpose, in a subset of

animals, we recorded spinal cord activity before and after deafferentation (n = 3). Specifically, we

transected dorsal rootlets innervating the electrode array-implanted region, as illustrated in Figure

5A (see also Figure S4). Local deafferentation was confirmed by lack of topographic, tactile stimulus-

evoked LFP deflections and correlated MUA bursts (Figure 5B).

Activation of dorsal horn neurons after twitching, as observed in the control condition, was

strikingly diminished or completely abrogated by the deafferentation (Figure 5C, single animal, and

Figure 6A, group data). Consistently, the previously described correlation between peri-twitching

spike times in motor and sensory zones was no longer present after deafferentation (Figure 6B).

Transection of dorsal rootlets also caused, in all animals, a striking reduction (of approximately 73 ±

27 %, mean ± SD) in the occurrence of bursts within sensory zones (Figure 6C). Yet, the spiking

capacity of neuronal populations within the dorsal was preserved (the mean firing rate in sensory

zones after deafferentation was 88 ± 27 % of the control conditionSD, Figure 6C). The partial overlap

between activity in sensory and motor zones raises the possibility that sensory feedback contributes



to motor activity and behavior. Following afferent transection, activity within motor zones, typically

preceding hindlimb movements (including twitches), was to a large extent preserved (Figures 5C-D,

single animal, and Figure 6C-D, group data), as we did not detect alterations in bursting frequency

(Figure 6C), nor in the peri-twitching bursting behavior, including multiunit frequency peak value and

time, as well as return to baseline (Figure 6D). Moreover, the twitching frequency, as well individual

twitches maximal amplitude, power (i.e. signal waveform power normalized to duration) or duration

also did not change following afferent transection (Figure 6E).

Note that, following recordings, movements were consistently evoked by electrical stimulation

at the expected depths (Figure S4), as demonstrated before (Figures 2 and 3).

While twitches represent the most prominent form of motor activity in rat pups, neonatal

behavior is also characterized by more complex movement patterns mainly occurring in awake

periods. Analysis of complex motor sequences (such as crawling), classified based on duration,

revealed that similarly to twitches, complex movements drive firing of spinal dorsal neurons, and no

fundamental difference was found neither in the patterns evoked by different types of motor activity

at the single segment level nor in correlation of activity in the motor and sensory zones (Figure S5).

Moreover, as for twitching, global metrics of more complex motor behavior were not affected by the

deafferentiation procedure (Figure S5).

Dissociation of sensory-motor networks function in the isolated spinal cord

Our in vivo data suggest that the predominant function of developing spinal cord networks

consists in generating spontaneous bursts in intermediate to ventral (motor) zones, which drive

movements and cause, through sensory feedback, activation of dorsal (sensory) zones. This is

supported by the loss of activation of sensory zones in association with movements after transection

of dorsal rootlets.

Spontaneous activity also has been described in the neonatal isolated spinal cord preparation

or spinal cord slices, in which correlated sensorimotor activity may be supported by intrinsic

connections and emphatic interactions (Bos et al., 2011;Demir et al., 2002;Fellippa-Marques et al.,

2000;Kremer and Lev-Tov, 1998). Therefore, we further investigated interactions between sensory

and motor zones in the isolated spinal cord in vitro, through silicone probe recordings, as performed

in vivo (Figure S6-7). Spontaneous activity in isolated spinal cords was characterized by regular bursts

within the dorsal horn, occurring at 15 ± 4.9 min -1 (mean ± SD, n = 5 animals, ≈ 6860 bursts), (Figure

7A). These were associated with a dorsal sink and MUA bursts, lasting approximately 119 ± 27.7 ms

(mean ± SD, n = 5 animals, ≈ 6860 bursts; Figure 7A-C). A main feature of activity in motor zones was

its organization in "megabursts" - 3.0 ± 0.27 s long periods of oscillatory activity at 6 ± 0.1 s Hz,



occurring at 1.7 ± 0.3 min-1 (mean ± SD, n = 5 animals, ≈ 760 bursts; Figure 7D). These bursts were

similar to those evoked by rhythmic dorsal roots stimulation (Figure S6). Isolated, short-lasting bursts

(lasting about 62 ± 14 ms) reminiscent of twitch-related events in vivo also occurred in motor zones,

at a frequency of approximately 2 min-1 (n = 5 animals, ≈ 760 bursts; Figure 7E).

Sensory or motor bursts-triggered PSTHs of MUA, and cross-correlation analysis of bursts in

both areas revealed weakly (or failed to reveal any) correlated firing between the two zones (Figure

8A-D). Indeed, only about 3 % of bursts within sensory zones were followed (within maximum lag of

100 ms) by bursts within motor zones (average, n = 5 animals, for which in total ≈ 6860 events were

detected). Moreover, in average, only 5 % of mega- and 16 % of short-lasting motor bursts were

preceded by sensory bursts. Further cross-correlation analysis of units in sensory and motor zones

referenced to entire recording sessions showed only a weak correlation, with sensory neurons firing

2 to 46 ms ahead of motor units (peak value of 5.4 spikes s -1). This is in striking contrast to the

activity recorded in vivo, where motor units leaded sensory activity both during twitching and

complex movement episodes, with a lag of 58 ± 22 ms (peak value of 24 ± 17 spikes ms -1, mean ± SD,

n=15 animals). It also differs from the overall activity pattern through entire recording sessions after

transecting dorsal rootlets in vivo, where the correlation between the two zones was dramatically

decreased or completely lost (Figure 8E).

Pharmacological analysis of the spontaneous activity in the isolated spinal cord confirmed

that: (i) combined application of ionotropic glutamate receptor antagonists CNQX and APV

completely suppressed network-driven events both in sensory and motor zones (Figure S8); (ii)

blockade of GABA(A) receptors with gabazine eliminated regular bursts in sensory zones and

significantly increased LFP power and MUA during motor megabursts, with loss of the prominent

within-burst 6Hz oscillation; during these epileptiform discharges in motor zones evoked by

disinhibition (Bracci et al., 1996), activation of neurons in sensory zones was not observed (Figure

S9).

Thus, in contrast to the in vivo situation, activity in the isolated spinal cord was characterized

by much weaker interactions between sensory and motor zones, and by a temporal lead of sensory

neurons in the isolated sensory-motor network, inverse to the in vivo situation, where motor zones

headed population activity. Taken together, data obtained in the isolated spinal cord provide strong

support to the hypothesis that sensorimotor integration in spinal cord under physiological conditions

is primarily driven by sensory feedback resulting from motor unit-driven movements.



C FIGURES AND FIGURE LEGENDS PART I

Figure 1_ Electrophysiological procedures in neonatal rats (P5-P7). A) Schematic illustration of the experimental setup. Laminectomy was performed typically at the Th13 to L1 level, after which the lumbar vertebral column was immobilized, accounting for spinal stabilization. A linear silicone-based electrode array (with 16 recording sites) was inserted in a left hemi-segment and allowed recording LFP and MUA. Left hindlimb movements were monitored through a piezoelectric transducer in direct contact with the corresponding paw. Tactile stimulation (brief touch) was achieved through a metal bar (0.6 mm diameter) driven by a piezoelectric bending actuator, at a frequency of 5 s -1. Following recordings of tactile stimulus-evoked and spontaneous activity, we performed intraspinal microstimulation (ISMS), with stimulation sites matching recording sites. B) Overlaid dark-field and epi-fluorescence (DiI, red) images and scheme of the different recording sites in relation to spinal cord laminae (dashed lines), in particular to motor neurons (laminae IX; ChAT-Alexa633), (see also Figure S1).



Figure S1_ Histology. A-C) Representative confocal micrographs (Z-projections) of ChAT (Alexa633, represented in gray), NeuN (Alexa488, green) and DiI (red) signals within a transverse spinal cord slice (same as in Figure 1, L3). Scale bar: 200 μm. D) Anatomical organization of the lumbar spinal cord (segment L3) in adult rats (adapted from Anderson et al., 2009). Collectively, these data were used to extrapolate the laminar location of recording sites.



Figure 2_ Functional mapping of sensory and motor zones in spinal cord. A) Tactile stimulus-evoked MUA frequencies represented as color-coded dots overlaid on corresponding stimulation points in aged-matched hindlimb photographs (response map; single, anesthetized animal). Note that firing frequencies correspond to the two recording sites showing the shortest response onsets, which were consistent across all stimulation points (depths of 100 and 200 μm). The response characterized by the highest MUA frequency (marked by an asterisk) was considered topographic and is described in more detail in Figure 2B-C. B) Tactile stimulus-triggered mean LFP traces and CSD map (n = 100 stimuli, single, non-anesthetized animal). C) Corresponding normalized PSTH of MUA. Note the duration of response across non-anesthetized animals (mean ± SD, n = 10). D) Normalized PSTHs of MUA in sensory zone (depths of 100 and 200 μm), intermediate zone (depths of 800 and 900 μm) and motor zone (depths of 1100 and 1200 μm) in the presence versus absence of isoflurane (as indicated in the figure; single animal). E) Mean movement traces obtained for each depth of ISMS (n ≈ 50 pulses per depth) overlaid on a respective normalized (color-coded) amplitude map (single animal). Movement onsets and offsets were as graphed (mean ± SD, n = 9 animals), (see also Figure S2).



Figure S2_ Isoflurane suppresses tactile stimulus-triggered ventral horn activation. A) Tactile stimulus-triggered mean LFP traces and CSD map (n ≈ 100 stimuli, single, anesthetized animal). Changes in extracellular potential are qualitatively equivalent to those observed when the animals were not administered 0.5 % isoflurane (Figure 2B, same animal and stimulation point). B) Corresponding normalized PSTH of MUA. C) Sensory zone: Tactile stimulus-evoked MUA bursts onset and duration under 0.5 % or no isoflurane per animal (n = 9-10 for each of the conditions tested); in 4 animals, responses were recorded in both conditions (represented by blue and orange data points). No difference was found when comparing within-burst MUA frequency (paired data, n = 4), bursts onset and duration (pulled data, n = 10 with and n = 9 without isoflurane). These results are consistent with a previous study showing that isoflurane at low concentrations (<1.5%) does not produce a significant effect over cortical sensory responses in neonatal rats (first postnatal week), (Sitdikova et al., 2014). D) Sensory zone: Tactile stimulus response onsets per age group in pulled isoflurane and non-isoflurane data (mean ± SD, n = 4-6 animals per age group; p = 0.0531, Kruskal-Wallis one-way ANOVA).



Figure 3_ Trans-laminar profiles of sensory and ISMS responses across animals. A) Occurrence, per depth, of tactile stimulus-evoked MUA responses (blue) and ISMS-evoked movements (black) per animal (n = 9). B) Mean tactile stimulus-evoked MUA frequency (blue-filled bars, n = 15 animals) and ISMS evoked-movement amplitude (black-filled bars, n = 9 animals) per depth. C) Corresponding mean sensory response and evoked movement onsets per depth. * p < 0.05 (Wilcoxon rank-sum test).



Figure 4_ Peri-twitching spinal cord network dynamics: intermediate/ventral activity twitching dorsal activity. A) Original LFP traces and MUA (red), as well as movement trace (Hindlimb mov) demonstrating typical field events and synchronized MUA bursts associated with a representative twitch and complex movement (single animal). B) The twitch highlighted in Figure 5A is shown here in more detail (twitch onset is indicated by a back vertical line). C) Mean LFP traces and CSD map triggered by twitch onset (n = 330 twitches, single animal). D) Corresponding normalized PETH of MUA, showing trans-spinal network dynamics, and twitch waveform (mean ± SEM, n = 330 twitches; single animal). E) Top: Normalized PETHs of MUA of sensory, intermediate and motor zones MUA, demonstrating consistency of spiking dynamics across animals (each grey trace corresponds to a single animal; the mean is represented by a black trace, n = 15 animals). Bottom: MUA peak frequency and return to baseline times in relation to twitch onset (ms) for each zone analyzed (mean ± SD, n = 2217 twitches, 15 animals). F) Top: Cross-correlogram of peri-twitching spike times in motor and sensory zones (mean ± SEM, n = 15 animals); correlation peak lags were as graphed, (see also Figure S2). Bottom: Cross-correlogram of peri-twitching spike times in motor and intermediate zones (mean ± SEM, n = 15 animals), (see also Figure S3).



Figure S3_ Semi-automatic movement detection. A) Illustrative original movement trace, with detected events highlighted in black. B) The event marked by an asterisk in Figure S3 A (twitch) is here shown in more detail to demonstrate precise onset and offset detections. A threshold (red horizontal dashed lines) was set based on a minimum SD of the data (calculated from 10 s sliding windows). Local minimum and maximum values were then used to separate distinct events: values less than 300 ms apart were considered part of the same event. An event onset was then given by the first zero value of the signal first-derivative (blue horizontal line) preceding the original signal intersection with the threshold. Offsets were determined in a similar manner. C) All detected events lasting more than 600 ms were considered complex movements, and all events lasting less than 600 ms were considered putative twitches. Putative twitches were further classified into twitches or short movements, manually, based on existence of preceding or following activity. C) Resulting histogram of complex movement durations (red-lined bars; n = 2146 long movements and 2132 short movements) and twitch durations (black-filled bars, n ≈ 2248). Short movements were typically end parts of complex movement sequences and, thus, were not analyzed further.



Figure 5_ Deafferentation abolishes twitches-triggered activity in dorsal horn. A) Schematic representation of the deafferentation procedure performed in a subset of animals (n = 3 of 15). B) Tactile stimulus-triggered mean LFP traces and normalized PSTHs of MUA before and after local afferent transection (n ≈ 100 stimuli, single animal). C) Twitch onset-triggered mean LFP traces and CSD maps before and after deafferentation (n before = 66 and nafter = 108 twitches, single animal). D) Corresponding normalized PETHs of MUA and twitch waveforms (mean ± SEM). E) Twitch onset-triggered time histograms of sensory, intermediate and motor zones MUA per animal (each trace corresponds to a single animal; gray traces - before transection; black traces - after transection), see also Figure S5.



Figure S4_ Deafferentation procedure. A) Macroscopic pictures representing the local afferent transection performed, in this case, in a P7 animal. Left: View the dorsal spinal cord; intact dura matter. Middle: Dural incision, followed by natural protrusion of dorsal rootlets. Right: Transected rootlets. B) Rat 2: Mean movement trace obtained for each depth of ISMS (n ≈ 50 stimuli per depth) overlaid on a respective color-coded (normalized) amplitude map; ISMS was performed upon conclusion of post-deafferentation recordings.



Figure 6_ Effect of deafferentation on translaminar activity. A) Twitch onset-triggered time histograms of sensory (sen), intermediate (int) and motor (mot) zones MUA (mean ± SD). Right: Before deafferentation (n = 3 animals, 273 twitches). Left: After deafferentation (321 twitches) B) Cross-correlograms of peri-twitching motor (mot) and sensory (sen) spikes times before and after deafferentation (mean ± SD). C) Effect of deafferentation of bursting and mean firing frequencies in sensory (sen) and motor (mot) zones, graphed as percentage of control (mean ± SD). D) Effect of deafferentation on peri-twitching ventral spiking activity (% of control, mean ± SD). Graphs showing, for motor (mot) zones, the twitches-related within-bursts MUA peak frequency (spikes ms-1) and respective time in relation to twitch onset (“latency”), as well as bursts offset (peak frequency to baseline return - “duration”). E) Twitches frequency (min-1), and twitches maximal amplitude, power (normalized to duration) and duration after versus before transection of afferent fibers (% of control). Given that we not discriminate wake-sleep cycles, twitches frequency (min- 1) is an underestimate. (see also Figures S6). * p < 0.05.



Figure S5_ Sensory feedback during complex movement sequences. A) Mean LFP traces and CSD maps triggered by the onsets of complex movement sequences recorded before and after deafferentation (n before = 33 and nafter = 24 complex movements, single animal). B) Corresponding normalized PETHs of MUA and complex movement waveforms (each gray trace corresponds to a single movement – absolute values - trace, and the back trace corresponds to the mean). Bottom left: Complex movement onset-triggered time histograms of sensory, intermediate and motor zones MUA in the control condition (n = 3 animals, 69 complex movements, mean ± SD). Bottom right: Complex movement onset-triggered time histograms of sensory, intermediate and motor zones MUA after deafferentation (n = 3 animals, 136 complex movements, mean ± SD). A-B) Only stereotypical movements lasting 900 - 1500 ms were included in this analysis. C) Cross-correlogram of peri-movement motor and sensory spikes times (n = 3 animals, mean ± SD). Left: Control condition. Right: After transection of dorsal rootlets. D) Frequency (min-1), maximal amplitude, power (normalized to duration) and duration of complex movements after versus before transection of afferent fibers (presented as % of control).



Figure 7_ Spontaneous sensory and motor events in the spinal cord in vitro. A) Original LFP traces representing stereotypical sensory zone bursts and heterogeneous motor zone events (S - short lasting motor event; L - long lasting motor even). B) Autocorrelograms of spike times in selected sensory and motor zones recording sites (as highlighted in Figure 10 A). C) Histogram of inter-sensory event intervals (with a peak at 3 s). D) Top: Original LFP traces and MUA (red); the long-lasting motor event indicated in Figure 10 A is shown here in more detail. Bottom left: Filtered LFP trace and coherent MUA at a recording depth of 900 m. Bottom right: Mean power spectrum of bursts referent to a selected motor zone recording site (mean ± SD, n = 5 animals, ≈ 760 bursts). E) Original LFP traces and MUA (red); examples of isolated, short-lasting motor events, (see also Figures S7 and S8).



Figure S7_ Nature of activity patterns induced by dorsal root stimulation in the in vitro spinal cord preparation.A) Overlaid dark-field and epifluorescence (DiI, red) images representing the typical positioning of the electrode array in the in vitro spinal cord preparation (in this case, L3 segment), equivalent to that of the in vivo experiments. B) Dorsal root (L3) stimulus-triggered mean LFP and CSD map (n ≈ 50 stimuli). Note the short-latency LFP deflections and current sinks evoked in dorsal horn (sensory zone). C) Top: Associated normalized PSTH of MUA. Bottom: Average MUA response times, with graphed onsets and offsets (mean ± SD, n = 5 animals). The sensory potential was associated with a MUA burst, at a latency of 3.6 ± 0.65 ms and lasting 42 ± 14 ms post-stimulus (mean ± SD, n = 5 animals), essentially limited to the dorsal horn (depth range of 100 - 400 µm). D) Original LFP traces denoting spinal responses to rhythmic dorsal root stimulation. Motor zones were weakly activated by single stimulus. However, rhythmic stimulation of dorsal roots (at least 5 stimuli at 1-2 Hz) evoked long-lasting rhythmic oscillatory bursts in motor zones, with coherence between motor units and oscillation. E) Normalized PSTHs of MUA (Z-scores) demonstrating the effect of stimulus intensity (as indicated in the figure) in firing rates in sensory and motor zones (Z-scores, n = 3 animals). F) Ventral root (L3) stimulus-triggered mean LFP traces (n ≈ 50 stimuli), revealing clear anterograde population spikes in ventral horn (motor zone). Generally, electrical stimulation of the respective ventral root evoked anterograde population spikes in the ventral horn (depth range: 900 - 1100 mkm, n = 5 animals), showing peak amplitude at 2.8 ± 0.45 ms after stimulus (mean ± SD, n = 5 animals).



Figure S8. Nature of activity patterns induced by dorsal root stimulation in the in vitro spinal cord preparation: specificity. For each preparation, dorsal roots anterior and posterior, as well as contralateral to the root innervating the hemi-segment in which the electrode array was inserted also were electrically stimulated. Figure S8 A-C refers to Figure S7. A) Anterior dorsal root (L2) stimulation-triggered mean LFP and PSTH of MUA (n ≈ 50 stimuli, same animal as in Figure S7). B) Contralateral dorsal root (L3) stimulation-triggered mean LFP and PSTH of MUA (n ≈ 50 stimuli, same animal as in Figure S7). Note that equivalent stimulations of anterior, posterior or contralateral roots evoked no or a weaker spinal response. C) Dorsal root (L3) stimulation triggered mean LFP traces (n ≈ 50 stimuli) before (black traces) and after combined bath application of the ionotropic glutamate receptor antagonists APV and CNQX (purple traces). Response suppression in the presence of AP-V and CNQX confirmed its dependence on synaptic transmission.



Figure 8_ Spontaneous in vitro spinal cord events: dissociation of dorsal and ventral activities. A) Sensory bursts-triggered: mean LFP and CSD map (single animal), as well as normalized PETH of MUA across all spinal depths (single animal); normalized PETHs of MUA of sensory, intermediate and motor zones (Z-scores, one trace corresponds to a single animal, n = 5), as well as the percentage of detected surrounding motor events (mean ± SD, n = 5 animals). B and C) Equivalent graphics instead triggered by long- and short-lasting motor events, respectively. D) Left: Representative histograms of inter-sensory event intervals during bursting and non-bursting periods in motor zone (black-filled and orange-lined bars, respectively; single animal). Right: Mean inter-event interval values during bursting and non-bursting periods in motor zone per animal (n = 4). E) Cross-correlograms of all motor and sensory units recorded per animal in vitro (mean ± SEM, n = 5), in vivo under control conditions (mean ± SEM, n = 15) and in vivo after deafferentation ((mean ± SEM, n = 3). * p < 0.05 (see also Figures S8 and S9).



Figure S9. Spontaneous sensory and motor events in the spinal cord in vitro: suppression of network driven events by APV and CNQX. A) Original LFP traces before and following combined application of AP-V and CNQX. B) Time course of drug effect on bursting and spiking activity (min -1) within sensory and motor zones (blue and black traces, respectively).



Figure S10. Spontaneous sensory and motor events in the spinal cord in vitro: suppression of sensory events and emergence of epileptiform motor events in the presence of gabazine. A) Top: Original LFP traces before and following bath application of gabazine (single animal). Bottom: Exemplary motor events prior to and after gabazine application. B) Ventral root stimulation triggered mean LFP traces (n ≈ 50 stimuli), identifying motor neuron pool depths. C) Mean power spectrum of detected bursts referent to a selected motor zone recording site before and after gabazine application (mean ± SD, single animal), showing a loss of event structural stereotypy in the presence of the GABAA antagonist. D) Time course of drug effect on bursting and spiking activity (min -1) within sensory and motor zones (blue and black traces, respectively). D) Motor event duration for each of the analyzed conditions (mean ± SD, single animal). E) Gabazine: motor burst-triggered mean LFP and CSD map, as well as normalized PETH of MUA across all spinal depths (single animal).



C GLOBAL RESULTS PART II

Data referent to part II are still under analysis, and thus only a preliminary description of the

results will be provided.

Spontaneous movements trigger M1 spindle-bursts in neonatal rats

To study the relationship between neuronal activity in M1 and spontaneous movements of

neonatal rats, we performed simultaneous recordings of LFP and MUA from the hindlimb

representation in M1, using silicone-based electrode arrays (Part II, Figure 1), and the corresponding

hindlimb movements in P5-P6 rats. Coordinates for recordings were based on a priori functional

mapping using cortical microstimulations (data not shown). At P5-6, electrical activity in M1 was

characterized by discontinuous temporal pattern reminiscent of “tracé discontinu” described in

premature human neonates (Lamblin et al., 1999), with bursts of activity alternating with periods of

silence. Each burst of activity was typically organized in short-lived oscillation reminiscent of

“spindle-bursts” previously described for the primary somatosensory cortex (S1, (Khazipov et al.,

2004). M1 spindle-bursts were associated with a sharp elevation in MUA locked to the troughs of

oscillation (Part II, Figure 2) and their phase reversal was observed typically at a depth of 1000 µm

(Part II, Figure 2).

M1 spindle-bursts were highly correlated with spontaneous movements of the

corresponding extremity (Part II, Figure 2). Cross-correlation analysis revealed a clear correlation

between limb movements and M1 spindle-bursts (Part II, Figure 5), with movements preceding the

vast majority of M1 spindle-bursts. Thus, M1 behaves very similarly to the somatosensory cortex at

this developmental stage (Khazipov et al., 2004;Mohns and Blumberg, 2010;Yang et al., 2009), with

most of the activity organized in spindle-bursts which are typically preceded by spontaneous

movements. This phenomenon also has been recently described by An et al., 2014.

Developmental profile of population activity in M1

We further addressed the developmental changes in M1 activity and its relation to

spontaneous movements by recording from rats between P3 to P21.

During the first week, the characteristic pattern of activity in M1 was spindle-bursts,

triggered by spontaneous movements. Developmental changes during this period included: (i) an

increase in the ongoing activity that was also manifested in a decrease of discontinuity, and (ii) a



decrease in the correlation between spindle-bursts and movements manifested in an increase of

spontaneous – i.e. not preceded by movements – negative LFP troughs of M1.

At around P8, both motor and M1 activity rapidly changed. First, the occurrence of

spontaneous movements decreased (Figure 4). Second, electrical activity in M1 became more

continuous (Figure 4A). The less frequent twitches were still associated with an increase of M1

activity. However, due to an increase in the ongoing M1 activity and to a decrease in the frequency

of spontaneous movements, the correlation between M1 events and spontaneous movements

decreased, and the number spontaneous, i.e. not preceded by movements, cortical events increased

dramatically.

Spontaneous movements trigger bicuculline-induced M1 epileptiform events in neonatal

rats

We further addressed the relationship between spontaneous movements and epileptiform

activity in M1. Epileptiform activity was induced in M1 by local, topical application or intracortical

injection of the GABA(A) receptor antagonist bicuculline (1 mM, ≈1 µL). In keeping with previous

observations obtained in vitro (Wells et al., 2000) and in vivo (Minlebaev et al., 2007;Minlebaev et

al., 2009), blockade of GABA(A) receptors caused recurrent epileptiform events (Part II, Figure 3).

The electrographic phenotype of the epileptiform events was age-dependent. At P3-4, epileptiform

events largely maintained a spindle-bursts oscillatory structure yet became longer-lasting. From P5-

6, large amplitude population spikes often followed by lower amplitude oscillatory events started to

emerge (Part II, Figure 2). Cross-correlation analysis between movement of the left hindlimb and

epileptiform events in the corresponding area of M1 revealed that: (i) at P4-P5, epileptiform events

were either spontaneous or triggered by hindlimb movements, (ii) after P10, virtually all (98±2%, n=5

rats) M1-right forelimb population spikes were followed by a myoclonic twitch of the right forelimb,

(iii) during transitory period at P6-10, some bicuculline-evoked population spikes preceded

movements, while others followed. While the frequency of myoclonic twitches remained unchanged

in P3-7 rats, starting from P8 local M1 bicuculline application increased jerks frequency (Figure 5).

These results indicate that during the first postnatal week, local epileptiform events are triggered by

spontaneous physiological jerks and remain largely infraclinical, whereas from the second postnatal

week, epileptiform events in M1 cortex start to drive epileptic jerks.



D FIGURES AND FIGURE LEGENDS PART II

Figure 1_ Recordings of neuronal population activity in M1 (P3-P21). A) A linear silicone-based electrode array (16 recording sites; center-to-center separation of 100 μm) was inserted vertically in M1, in order to record LFP and MUA. Overlaid epi-fluorescence images (Hoechst, inverted gray-scale image; DiI, red) and scheme of the different recording sites in relation to all cortical layers in a P6 animal. Note the dense Hoechst signal corresponding to layer IV in primary somatosensory cortex (S1), and lack of this dense layer in M1, where the silicone-based array was inserted.



Figure 2_ Spontaneous movement trigger activity in M1 over the first postnatal week. A) LFP traces and CSD maps denoting cortical events in relation to spontaneous movements in a P6 animal. Left: Control condition. Right: Following topical application of bicuculline. Note that under both conditions, cortical events were reliable preceded by movement (see also Figure 5), although some events occurred spontaneously (i.e., not associated with movements). B) Corresponding LFP power before and after bicuculline application. Note the dramatic increase in power. C) Typical inter-cortical event interval (900 μm depth) in the presence of bicuculline. D) Histograms of movement durations in the control condition and following application of bicuculline, showing similar distributions (Wilcoxon rank-sum test = 0.638). Movement frequency also did not differ prior to or after bicuculline delivery (13.8 and 14.5 events per min, respectively, mean, single animal); A-D) Single animal (P6).



Figure 3_ Global effect of local bicuculline delivery. A) LFP and corresponding hindlimb traces denoting, in a P14 animal, the penetration of topically applied bicuculline, in M1, and the striking increase in movements amplitude ad frequency associated with a striking increase in LFP power in deeper (≈ 1000 μm) cortical layers.



Figure 4_ Epilepform discharges in M1 reliably trigger movements during second postnatal week. A ) LFP traces and CSD maps denoting cortical events in relation to spontaneous movements in a P14 animal. Top Left: Control condition. Top right: Following topical application of bicuculline. Bottom: Filtered LFP trace and coherent MUA at a recording depth corresponding to Layer V (1000 μm), and respective movement trace. B) Corresponding LFP power before and after bicuculline application. Note the dramatic increase in power. C) Typical inter-cortical event interval (1000 μm depth) in the presence of bicuculline. D) Histograms of movement durations in the control condition and following application of bicuculline, showing similar distributions (Wilcoxon rank-sum test = 0.599). However, movement frequency increased after bicuculline delivery (3.15 events per min before and 20 events per min after delivery of convulsive agent, mean, single animal); note the consistency between inter-cortical event interval and movement frequency after delivery of bicuculline. A-D) Single animal (P14).



Figure 5_ Developmental shift in the temporal relationship between cortical events and spontaneous movements. A) Cross-correlograms of spontaneous movement onset and cortical event onset (normalized to movements) in a P6 and In P14 animal reveling peaks of correlation after and before movements, respectively.



E PERSPECTIVE

Significance of the obtained results

Our results reveal two fundamental aspects of early sensorimotor development, at distinct

input output levels. First, our results provide direct evidence to the hypothesis that sensory feedback

from spontaneous movements is instrumental for the temporal binding of motor and sensory

neurons in the developing spinal cord. Second, prior to formation of its main output, the

corticospinal tract, M1 operates essentially in a somatosensory mode. In this mode almost all

activity, either natural or epileptic results from sensory feedback from spontaneous movements.

This sensory-evoked activity does not effectively drive movements, rendering early epilepsy

infraclinical.

We also observed that in contrast to adult animals, in which somatosensory responses are of

relatively short duration, sensory stimulation evoked long-lasting bursts in spinal cord sensory zones

(as demonstrated in Part I, Figure 2). Long-lasting sensory responses are conveyed upstream and

likely contribute to bursting in thalamus-cortical networks. Our results also strongly suggest that the

sensory output from the spinal cord triggers, but does not drive thalamo-cortical oscillations. First,

the duration of thalamo-cortical oscillations evoked by sensory stimulation is, at this ages,

significantly longer, up to 1 s (Khazipov et al., 2004;Yang et al., 2013). In addition, sensory-evoked

bursts in the spinal cord were not organized in any prominent oscillatory pattern in the frequency

range characteristic of early gamma oscillations (EGOs) (Minlebaev et al., 2011;Yang et al.,

2009;Yang et al., 2013) or spindle-bursts, (Khazipov et al., 2004;Minlebaev et al., 2009;Yang et al.,

2009). This is also supported by the findings that spindle-bursts in S1 hindlimb area persist, although

at lower frequency, after spinalization at mid-thoracic level (Khazipov et al., 2004).

Our results further indicate that developing sensory systems share common principles but also

point to an important peculiarity in the early function of the somatosensory system. In the visual

system of neonatal altricial animals, such as rodents and ferrets, transient patterns of activity in LGN

and visual cortex are driven by spontaneous retinal waves (Ackman et al., 2012;Colonnese and

Khazipov, 2010;Hanganu et al., 2006;Mooney et al., 1996;Weliky and Katz, 1999). Spontaneous

activity bursts also are generated in the cochlea and drive activity in auditory thalamus and cortex

(Tritsch et al., 2007). Considerable evidence indicates the participation of these activity patterns in

the development of sensory maps (Blankenship and Feller, 2010;Katz and Shatz, 1996) Importantly,

during these early developmental stages, neither the retina nor the cochlea are sensitive to sensory

stimuli, and artificial introduction of this sensitivity disturbs the formation of sensory networks



(Zhang et al., 2012). In contrast, the somatosensory periphery does not generate spontaneous

activity, and activation of somatosensory networks involves sensory feedback from spontaneous

movements, thus requiring an open somatosensory gate. We propose that this unique modus

operandi of the developing somatosensory systems enables early sensorimotor integration and

binding of motor and sensory neurons.

This study sets a framework for further understanding the role of spontaneous neuronal

activity in the emergence of complex sensorimotor operations in subsequent studies.



F EXPERIMENTAL PROTOCOLS

ETHICAL CONSIDERATIONS

All experiments were performed in accordance with protocols approved by the Ethical

Committee for Animal Research of Marseille (Comité d’éthique en expérimentation animale de

Marseille, reference 00708.01).

SUBJECTS

Subjects were male and female Wistar rats, 3 to 7 days old (i.e. P3 to P7, with the day of birth

being considered as P0), from multiple litters. Animals were obtained from the breeding colony at

the INMED (INSERM UMR 901, Marseille, France). All animals were housed in enriched laboratory

cages, in climate-controlled rooms (22°C, 60% humidity), under a 12 hours light/12 hours dark cycle,

and with ad libitum access to water and food. Prior to the onset of experiments, we verified that the

pups had been recently fed (with ingested milk being visible through the abdominal skin).

SPINAL CORD

Electrophysiological recordings, in vivo

We developed a method for simultaneously recording electrical activity across all spinal cord

laminae and motor behavior in neonatal rats, based in part on previous preparations for chronic

imaging of the dorsal spinal cord and spinal single-wire or patch-clamp electrophysiological

recordings in adult rodents (Berg et al., 2009; Cuellar et al., 2004; Cunningham et al., 2005; Davalos

et al., 2008; Farrar et al., 2012; Fenrich et al., 2012; Graham et al., 2004; Misgeld et al., 2007).

Animals were anesthetized using isoflurane (Aerrane, Baxter, France) in O 2, provided through an

open mask (induction: 4%; maintenance: 0.5-1.5%). Once anesthetized, rat pups were given a

subcutaneous injection of the analgesic buprenorphine (Buprecare, Anxience, France) in saline (at a

dose of 0.03 mg/ Kg of body weight). In initial experiments (n = 4 of 16), a relatively small dose of

urethane (0.2 g/Kg of body weight) was injected subcutaneously, which was later considered

unnecessary. In order to minimize spinal cord displacements associated with eventual (large) head

movements, animals were mildly head-restrained (Khazipov et al., 2004). A metal bar was fixed

(parallel) to a relatively small portion of the scalp (top of the head), using cyanoacrylate and dental

adhesive, and anchored onto a customized stereotaxic frame. Our system allows for small

adjustments over the x-y-z axes. Subsequently, a dorsal midline skin incision covering the expected

location of the TXI-LIII vertebrae was made. Local anesthesia and vasoconstriction were provided by



subcutaneous injection of lidocaine-adrenaline (Xylocaïne Adrenaline, AstraZeneca, France) prior to

incision. Using blunt dissection, the dorsal aspect of the six vertebrae was gently exposed.

Laminectomy was performed on the two central exposed vertebrae (Th13-L1), using micro-scissors.

Exposed spinal segments were protected by a thin layer of silicone oil. A ring-shaped metal adaptor

was fixed onto the remaining exposed vertebrae, using cyanoacrylate (thin layer) and dental

adhesive, enabling the creation of a chamber. The adaptor was then cemented onto two metal bars

anchored on the stereotactic frame, allowing stabilization of the spinal cord; adjustments were

made over the z-axis so that the ventral side of the animal could comfortably touch the heating pad,

avoiding respiration-related spinal displacements. The tail was mildly restrained also in order to

prevent relatively large spinal cord displacements. Throughout the experiments, body temperature

was kept at 37°C using a heating pad (TC-344B, Warner Instruments, Hamden, CT, USA). Rat pups

were surrounded by a cotton nest, mimicking the presence of the mother and littermates (contact).

An extra dose of buprenorphine was administered 6 hours after (when applicable).

Implantation of the electrode array. We recorded extracellular, local field potential (LFP) and

multiunit activity (MUA) using a linear silicone-based electrode array (16 recording sites with a

center-to-center separation of 100 μm, A1x16-5mm-100-703-A16, Neuronexus, Ann Arbor, MI, USA).

Labeling of the electrode array with the fluorescent dye 1,1 -Dioctadecyl-3,3,3 ,3 -′ ′ ′tetramethylindocarbocyanine perchlorate (DiI, Sigma-Aldrich, Europe) prior to insertion facilitated

the later anatomical localization of each recording site. The tip of the electrode array was positioned

at 0.3-0.5 mm lateral to the central vein (typically over L3-L5, left hemi-segment). Following dural

puncture, the array was lowered with a medial to lateral angle of approximately 17°, to a maximum

of 1100-1400 μm of depth (depending on the age of the animal). The chamber was filled with 4%

low-melt agar (Sigma-Aldrich) in saline. Two chlorided silver wires placed at the surface of the spinal

cord and a vertebra served as reference and ground electrodes.

Data acquisition. Following a recovery period of 30 min to 1 h, electrophysiological recordings

were initiated and performed essentially as described before (Khazipov et al., 2004). Signals were

amplified and filtered through a custom-built amplifier (1000 x, 0.1-3000 Hz) and digitized at 10 kHz

(Digidata, Axon Instruments, CA, USA). We recorded both tactile stimulus-evoked and spontaneous

activity. Stimulations of the limbs, back and tail consisted of a brief touch using a 0.6 mm-diameter

metal bar connected to a piezoelectric bending actuator (PAB-4010, Nihon Ceratec, Japan). The

duration and magnitude of the bar/piezoelectric bending actuator displacement was controlled by a

square pulse (5-10 ms), delivered at 5 s -1, using a stimulator (Master 8, AMPI, Jerusalem, Israel) and

stimulus isolator (ISO-Flex, AMPI, at 7.0 V). Animals were generally under the effect of isoflurane

(0.5-1%); in some cases, anesthesia was discontinued and the identified “topographic” response was



re-recorded 30-60 min after. Spontaneous activity also was recorded 30-60 min after discontinuing

anesthesia.

Following recordings, animals were given an overdose of urethane (3 g/Kg, Sigma-Aldrich) and

perfused intracardially with saline for 1 min and, subsequently, with 4% formaldehyde for 2 min (at a

rate of 5 mL/min).

Motor behavior

Motor behavior, namely left hindlimb movement, was recorded through a piezoelectric

transducer (KPEG165, Kingstate, Taiwan) placed in direct contact with the non-glabrous surface of

the left hindpaw (see Part I, Figure 1). The signal was digitized at 10 kHz, as described before

(Digidata interface). The sensitivity of the piezoelectric transducer was enough to detect the smallest

visible movements, including respiration-related limb displacements.

Intra-spinal microstimulation (ISMS). Following recordings, identification of premotor/motor

networks was achieved by trans-spinal electrical stimulation. A bipolar 50 µm nichrome-wire

electrode (A-M Systems, Carlsborg, WA, USA) was inserted in the spinal cord. The electrode was

lowered to the maximum depth used for recordings (expected location of motor neuron pools); the

current required to evoke detectable movements was determined (threshold) and used for all

subsequent stimulations. Stimulation sites matched recording sites. Electrical pulses (50 µs,

delivered at a frequency of 5 s-1) at near-threshold current were generated by an AMPI stimulator

and stimulus isolator, as above described.

Transection of dorsal rootlets

In a subset of animals, durotomy was performed in order to expose the dorsal rootlets

innervating the locus of recording and adjacent regions. Rootlets were gently set aside with the aid

of an ultrafine forceps and transected using micro-scissors. Electrophysiological recordings of tactile

stimulus-evoked and spontaneous activity were performed as described above. The completeness of

local afferent transection was verified by lack of tactile stimulus-induced spinal responses.

Electrophysiological recordings, in vitro

Spinal cords were isolated essentially as described previously by others (Bos et al., 2010).

Neonatal rats were anesthetized using isoflurane (4% in O2), decapitated and rapidly eviscerated.

The preparation was immersed quickly in ice-cold, carbogenated (95% O2 - 5% CO2) artificial

cerebrospinal fluid (aCSF) and pinned down. We then performed a dorsal laminectomy, from sacral

to cervical segments. The dura matter was carefully excised, and the lumbar spinal cord and intact



adjacent regions, together a substantial portion of its dorsal and ventral roots, was quickly

transferred to and maintained in a holding chamber (containing carbogenated aCSF), at RT, for at

least one hour. The spinal cord was then placed, dorsal side up, in the recording chamber

(Cunningham et al., 2008), at the interface between a continuous stream of carbogenated aSCF (3-4

mL/min) and humidified carbogen (95% O2 - 5% CO2), at RT. Composition of the aCSF, in mM: 130

NaCL, 4 KCl, 2 CaCl2, 1.3 MgSO4, 0.58 NaHPO4, 25 NaHCO3 and 10 glucose. A DiI-labeled linear silicone

probe (16 recording sites; center-to-center separation of 100 μm) was inserted typically at the L3-L5

segment, in a manner similar to that used in in vivo recordings.

Data acquisition. Following a recovery period of approximately 15 min, electrophysiological

recordings were initiated; signals were amplified and filtered using a xCellAmp64 amplifier (DIPSI,

Cancale, France) and digitized at 10 kHz. We recorded both spontaneous activity and responses

obtained by systematic, electrical stimulation of dorsal and ventral roots using a bipolar 50 µm

nichrome-wire electrode. Electrical pulses were generated by a Grass stimulator and stimulus

isolator; stimulation parameters were as specified in the Results section (generally, pulses were 50

µs and delivered at a frequency of 5 s-1). In a subset of experiments, recordings were performed

under control conditions and in the presence of (2R)-amino-5-phosphonopentanoate (APV, 50 µm)

and 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX, 20 µm), or 4-[6-imino-3-(4-

methoxyphenyl)pyridazin-1-yl] butanoic acid hydrobromide (gabazine, 5 µm).

Upon completion of the experiment, one preparation was gently turned ventral side up, and

the silicone probe inserted in order to match the previous dorsal-side up configuration; the activity

patterns obtained in the dorsal side up preparation were verified in the inversed set-up.

Histology

Isolated spinal cords were kept in 4% formaldehyde for at least 1 week, at 4°C. First, to

confirm the spinal cord segment in which the electrode array was inserted, we studied the position

of the dorsal DiI signal in relation to lumbar ventral roots, which are characterized by different sizes.

In parallel, the (dorsal) lumbar enlargement was imaged: epifluorescence (DiI) and dark-field

micrographs were acquired under standardized conditions using an Olympus SZX16 microscope and

the CellSens software (Olympus, Tokio, Japan). In acquired images, the area corresponding to the

lumbar enlargement (dorsal surface) was divided in six equal segments, considered as L1-L6 (≈1mm).

Then, a spinal cord block encompassing the lumbar enlargement was enwrapped in 4% agarose

(Sigma-Aldrich) and sliced, transversally, using a vibratome (HM 650V, Thermo Scientific Microm,

Waltham, MA, USA). Slices (200 μm-thick) were imaged as above described. Subsequently, we

performed choline acetyltransferase (ChAT) and neuronal nuclei (NeuN) immunohistochemistry.



Slices (free-floating) were rinsed three times with PBS and kept in a 5% blocking solution - 5% normal

serum (Jackson ImmunoResearch, Suffolk, UK) and 0.25 % Triton X-100 (Sigma-Aldrich) in PBS - for 1

h, at room temperature. Thereafter, slices were incubated with a goat anti-ChAT antibody (1:100,

Chemicon, Merk Millipore, Darmstadt, Germany) and a mouse anti-NeuN antibody (1:200,

Chemicon) in 2% blocking solution overnight, at 4 °C. After rinsing, slices were incubated with an

anti-goat Alexa633-conjugate antibody and an anti-mouse Alexa488-conjugate antibody (both from

Molecular Probes, Invitrogen) in 2 % blocking solution for 2 h, at room temperature. Fluorescent

dyes (DiI, Alexa488 and Alexa633) were imaged using a Leica TCS SP5 X confocal miscroscope (Leica,

Nanterre, France). Note that the DiI presence and/or fluorescence intensity was(were) strikingly

diminished by the immunohistochemistry protocol.

To our knowledge, there is no available systematic study on the anatomical organization of

the neonatal rat spinal cord. Hence, laminae borders were extrapolated from analysis of dark-field

images (slice morphology), ChAT and NeuN immunoreactivity patterns, and knowledge of the adult

rat spinal cord (Anderson et al., 2009). Note that images were linearly altered for better visualization

of slice morphology. The anatomical location of each recording site of the electrode array was

estimated using the insertion coordinates and the corresponding or age-matched histological

assessment (as demonstrated in Part I, Figure 1B and Figure S1). Throughout the manuscript, depth

refers to the subdural depth considering the electrode array (and not the dorsal-ventral) axis, for

simplification.

PRIMARY MOTOR CORTEX

Electrophysiological recordings, in vivo

Animals (P3-P21, n = 32) were anesthetized using isoflurane and given the analgesic

buprenorphine. A lidocaine solution was additionally used to provide local anesthesia. The parietal

and frontal bones were exposed, and the periosteum gently removed. Two metal or plastic adaptors

were fixed onto the skull, using a thin layer of cyanoacrylate and dental adhesive. Then, the adaptors

were attached to a customized stereotactic frame, enabling head stabilization. A small craniotomy

was performed over M1 (hindlimb representation), as determined a priori through intra-cortical

microstimulation experiments (not shown). A linear silicone-based electrode array (16 recording

sites with a center-to-center separation of 100 μm, Neuronexus) was inserted vertically in M1. As

previously described, labeling of the electrode array with DiI prior to insertion facilitated the later

anatomical localization of the array track. Also here, body temperature was kept at 37°C using a

heating pad, buprenorphine was re-administered every 6 hours (when applicable), and animals



were, at all times, surrounded by a cotton nest, mimicking the presence of the mother and

littermates.

Data acquisition. Recordings were initiated after a minimum waiting period of 30 min

following implantation of the electrode array and performed essentially as described above -

wideband neurophysiological signals were amplified through a xCellAmp64 amplifier and digitized at

10 kHz (DIPSI). Tactile stimuli were provided through a 0.6 mm-diameter metal bar driven by a

piezoelectric bending actuator, which was controlled by a square pulse (5 ms, delivered generally at

5 s-1, depending on the age of the animal). Spontaneous activity was recorded 30 to 60 min after

discontinuing anesthesia, first under control conditions and secondly upon local intracortical delivery

of the GABAA receptor antagonist bicuculline. Bicuculline (≈ 0.5 μL, 1 mM, Tocris) was either applied

topically or injected using a glass pipette pulled from a glass capillary that was lowered to a depth

consistent with the location of layer V and close to the recording electrode array.

Following recordings, animals were deeply anesthetized and perfused intracardially with

saline and, thereafter, with 4% formaldehyde, as detailed above.

Histology

Brains were kept in 4% formaldehyde for at least 1 week, at 4 °C. Free-floating 100 μm-thick

slices were incubated with the nuclear florescent marker Hoechst, at 4 °C, overnight. Slices were

imaged under standardized conditions using an Olympus SZX16 microscope and the CellSens

software.

DATA ANALYSIS

Data were analyzed offline using the Axon Instruments software, as well as conventional and

custom-made MATLAB routines.

Raw data were preprocessed using a custom-developed set of programs in the MATLAB

analysis environment. Events exceeding 10 SD from the baseline mean were considered artifacts and

excluded from analysis. With respect to in vitro recordings, stimulation artifacts were eliminated by

truncating the original signal trace at -1 to 1 ms considering the first stimulus peak. For spike

detection, the original wide-band signal was band-pass filtered (300-4000 Hz) and negative events

exceeding 3-3.5 SD from the baseline mean were considered spikes. The wide-band signal was re-

sampled to 1000 Hz and used for analysis of LFP and movement traces. Positive polarity is depicted

up in all figures. Tactile stimulus times or behavioral event onsets (in vivo), as well as electrical

stimulation of dorsal and ventral roots or spontaneous sensory and motor bursts onsets ( in vitro)

were used as triggers to compute mean LFP and current-source density (CSD, second spatial



derivative of LFP) maps, as well as individual trigger spectrograms of field. CSD analysis was used to

eliminate volume conduction and localize synaptic currents; CSD was computed for each recording

site and smoothed with a triangular kernel of length 3. Spectral analysis was carried out using the

Chronux toolbox. Spectral power was given by direct multi-taper estimators (generally, 5 Hz

bandwidth, 3 tapers, 200 ms spectral window); to remove the slow frequency envelope, the LFP was

filtered (5-100 Hz).

Activity evoked by tactile stimulation, in vivo, spinal cord. For each animal and stimulation

point, peri-stimulus time histograms (PSTHs) of MUA were computed using a time window of -1 to 1

s in relation to stimulus onset and 1 ms bins. We performed approximately 100 trials per stimulation

point. Detection of channels showing stimulus-evoked activity was achieved by the Otsu’s method

(REF). In all cases, the identified channels were located within the dorsal horn, as estimated

histologically. It should be noted, however, that when recordings were done in the absence of

isoflurane, an elevation of MUA at the level of the ventral horn also could be found (see Part I, Figure

2 and Figure S2). For each identified channel, the precise average response onset and offset were

determined using a trapezoidal sum-based method (adapted from Mitrukhina, Suchkov et al., 2014).

Then, we selected the two channels showing the earliest onsets; these were always contiguous and

the corresponding depths referred to as “sensory zone”. The corresponding within-response MUA

frequencies were averaged, and normalized to the maximum value obtained across stimulation

points (for each animal). Normalized MUA frequency values were represented as color-coded dots

overlaid on respective stimulation sites in aged-matched hindlimb photographs, allowing the

creation of a “response map”. The stimulation site associated with the shortest onset and maximal

MUA frequency (“topographic”) was considered for further single animal and group data analyzes.

For presentation, for each channel, firing rates were smoothed with a mean filter, and a between

channels interpolation of 5th order was used.

Activity evoked by tactile stimulation, in vivo, M1.A similar analysis was carried out with

respect to stimulation-induced somatosensory cortical activity, except that depths corresponding to

Layer IV were considered.

Activity evoked by electrical stimulation of dorsal roots, in vitro. An equivalent analysis was

carried out with respect to the activity evoked by electrical stimulation of different dorsal roots ( in

vitro).

Intraspinal microstimulation (ISMS), in vivo. For each depth of electrical stimulation, the

stimulus onset was used as trigger for averaging the corresponding movement signal (recorded



through a piezoelectric transducer). For that purpose, we used a time window of -1 to 1 s; we

performed approximately 100 trials per stimulation depth. Movement onset and offset were

determined as described above (Mitrukhina, Suchkov et al., 2014). Results are presented as the

mean signal per depth overlaid on a color-coded amplitude map, which was normalized to the

maximum value obtained across depths of stimulation. The 2 depths associated with the highest

evoked-movement amplitudes were considered as “motor zone” and used for subsequent analysis.

With respect to the “intermediate zone”, we considered 2 channels located 300 and 200 µm

dorsal to the dorsal-most channel corresponding to the motor zone; thus, intermediate zones

corresponded to the average depths of 680-780 mkm.

Activity evoked by electrical stimulation of ventral roots, in vitro. Here, the stimulus onset

was used as a trigger for averaging LFP and computing a CDS map. Response-associated channels,

generally 2, were identified by analysis of PSTHs of MUA and confirmed by visual inspection of single

responses (population spikes). In one case, the response was evident for 3 (and not 2) channels;

here, we selected the 2 channels showing the highest amplitude LFP deflections.

Spontaneous activity, in vivo, spinal cord. To quantify the relationship between behavior and

spinal cord activity, we first defined behavioral events. We determined the minimum standard

deviation of the original movement signal found in sliding windows of 1 to 106 ms (log scale), with 50

% overlap. For all records, a striking increase in the minimum SD was obtained for windows bigger

than 104 ms, and thus, a multiplier (generally 4-6) of the minimum SD obtained when using 10 ms

windows used was as (±) threshold to discriminate noise from real events, on demeaned traces.

Then, local minimum and maximum signal values were calculated, and peaks less than 300 ms apart

were considered part of a single event, taking into account signal resolution and previous studies

(Blumberg et al, 2013; Khazipov et al, 2004). The first derivative of the demeaned trace was then

calculated, and the precise twitch onset given by the first zero of the differential preceding the

event’s first intersection with the threshold. Offset detection followed an equivalent rule.

Thereafter, events lasting at least 600 ms were considered as complex movements, and events

shorter than 600 ms were considered as putative twitches and manually classified using a

customized data viewer, showing single cases in a time window of 4 s. Data. Specifically, events were

classified as twitches (which likely includes indiscernible bouts of twitches at different joints) if

occurring on a background of atonia (i.e. there were no detected events in the preceding and

following ≈ 1 s). All remaining events were classified as short movements (typically ending complex

movement sequences, 27 % of all detected events) or noise (13 % of all detected events), and were



not considered for further analysis. A schematically illustration of the described detection method in

included Part I Figure S3.

For each animal, a peri-event time histogram (PETH) of MUA, with all detected twitch onsets

as reference point, was computed essentially as described before. For further analysis of

spontaneous trans-spinal cord MUA, we used data from previously identified sensory and motor

zones, as well as from intermediate zones. For each twitch, the mean baseline (entire session) was

used to detect MUA frequency peaks in motor, intermediate and sensory zones; results are

presented as average MUA frequency peak times, and baseline return times. Similar analysis was

carried out for complex movements. However, only stereotypical movements lasting 900 - 1500 ms

(see Part I, Figure S4 C) were taken as triggers for calculating the mean LFP, CSD maps and PETHs of

MUA. First, these events lasted at least 300 ms more than events considered as twitches. Second,

the large repertoire of complex movement durations would otherwise preclude interpretation of

averaged data sets. Cross-correlation analyses of spiking in motor and sensory zones were

performed considering a time window of -1 to 1s in relation to motor spike times. For these analyses

we considered motor spikes within 300 ms prior to and to 1 s after twitch or 300 ms prior to 1.5 s

after complex movement onsets; 2) acquired during an entire recording session. For comparisons

across animals, the correlation waveform was moved to zero considering baseline (first 100 points).

To further understand temporal correlations between behavior and spinal cord network

activity, we detected activity bursts within sensory and motor zones, based on a previously

described method (Kaneoke and Vitek, 1996). For that purpose, individual channels instantaneous

firing rates were calculated using sliding windows of 50 ms (10 % overlap). Bursts were generally

considered as events exceeding 5 SD of the instantaneous firing rate, and events (MUA frequency

peaks) less than 500 ms apart were considered as one. Then, event onsets and offsets were

estimated taking into account the nearest intersections with the baseline mean (respectively).

Spontaneous activity, in vivo, brain. With respect to analysis of cortical MUA, an equivalent

approach was undertaken, except that yet again cortical depths corresponding to Layer IV were

considered.

Spontaneous activity, in vitro. To detect bursts of activity within sensory and motor zones, as

identified a priori, we used an approach similar to that described for the in vivo data, with a few

modifications. Bursts were generally considered as events exceeding 3 SD of the instantaneous firing

rate. Bursts within sensory zones were rather stereotypical. In motor zones, however, we observed

two main event types: short- and long-lasting (or mega-) bursts organized in ≈6 HZ LFP and MUA

coherent oscillations. Here, a first threshold (3 SD) was used to more sensibly establish mega-bursts,

while a second threshold (4 SD) was used to eliminate between-bursts potentially spurious increases



in firing rates (i.e. isolated ultra short-lasting events - 56 % of detected events were excluded). Here,

local minimum LFP values were used to align events. Sensory and motor events were then used as

triggers to compute mean LFP, CSD maps and PETHs of MUA. Onsets and offsets of sensory and

short-lasting motor events were estimated using the trapezoidal sum-based method on triggered,

spike histograms. Mega-bursts onsets and offsets were simply estimated by the first and last local

minimum LFP value.

Cross-correlation analysis of spike times, and bursts times (onset phase) in the two different

zones was carried out essentially as described previously.

Statistics

We did not use statistical methods to calculate the required sample size, a prior, but the

number of animals used in this study is consistent with that used in previous reports (e.g., Khazipov

et al., 2004). Data could not be acquired by an experimenter blinded to the study design.

Nonetheless, data were analyzed offline, in serial runs, and was independently verified by different

analysts. Unless otherwise indicated, the statistical tests used do not assume a normal distribution of

the data. Unless otherwise specified, to compare two groups, we used the Wilkoxon rank-sum test

(unpaired data) or the Wilkoxon signed-rank test (paired-data), as indicated in the Results section

and figure captions. In some cases (twitches-related within-bursts MUA peak frequency and

respective time in relation to twitch onset, as well as bursts offset, i.e., peak frequency to baseline

return, twitch/complex movements, maximal amplitudes, power and durations, before and after

deafferentation), the Kolmogorov–Smirnov test was used instead. In additional particular cases,

namely comparisons relative to firing, bursting or movement rates before and after deafferentation,

to test for significance, we used a shuffling/bootstrap method. For each animal, we randomly

selected 30 recorded minutes. The spikes/bursts train in a selected sensory or motor channel was

circularized, and the beginning of a trial was randomly chosen. Then, surrogate trials were

recomputed 100 times to generate a global band of confidence (the 5% highest and lowest values of

the 100 trials × 3 animals). Results were considered significant when p < 0.05. The Matlab codes

used are available upon request.



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ENDPAGE

PEOPLEMARIE CURIE ACTIONS

Marie Curie Intra-European Fellowships (IEF)Call: FP7-PEOPLE-2012-IEF

Final Report

“Motor_Dev”


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