Download Genetically identified spinal interneurons integrating tactile afferents

J Neurophysiol 114: 3050 –3063, 2015.
First published October 7, 2015; doi:10.1152/jn.00522.2015.
Review
CALL FOR PAPERS
Neurophysiology of Tactile Perception: A Tribute to Steven
Hsiao
Genetically identified spinal interneurons integrating tactile afferents for
motor control
Tuan V. Bui,1,2 X Nicolas Stifani,3 Izabela Panek,3 and Carl Farah1
1
Department of Biology, University of Ottawa, Ottawa, Ontario, Canada; 2Center for Neural Dynamics, University of Ottawa,
Ottawa, Ontario, Canada; and 3Department of Medical Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada
Downloaded from http://jn.physiology.org/ by 10.220.33.3 on June 11, 2017
Submitted 29 May 2015; accepted in final form 28 September 2015
Bui TV, Stifani N, Panek I, Farah C. Genetically identified spinal interneurons
integrating tactile afferents for motor control. J Neurophysiol 114: 3050 –3063,
2015. First published October 7, 2015; doi:10.1152/jn.00522.2015.—Our movements are shaped by our perception of the world as communicated by our senses.
Perception of sensory information has been largely attributed to cortical activity.
However, a prior level of sensory processing occurs in the spinal cord. Indeed,
sensory inputs directly project to many spinal circuits, some of which communicate
with motor circuits within the spinal cord. Therefore, the processing of sensory
information for the purpose of ensuring proper movements is distributed between
spinal and supraspinal circuits. The mechanisms underlying the integration of
sensory information for motor control at the level of the spinal cord have yet to be
fully described. Recent research has led to the characterization of spinal neuron
populations that share common molecular identities. Identification of molecular
markers that define specific populations of spinal neurons is a prerequisite to the
application of genetic techniques devised to both delineate the function of these
spinal neurons and their connectivity. This strategy has been used in the study of
spinal neurons that receive tactile inputs from sensory neurons innervating the skin.
As a result, the circuits that include these spinal neurons have been revealed to play
important roles in specific aspects of motor function. We describe these genetically
identified spinal neurons that integrate tactile information and the contribution of
these studies to our understanding of how tactile information shapes motor output.
Furthermore, we describe future opportunities that these circuits present for
shedding light on the neural mechanisms of tactile processing.
tactile information; spinal cord; sensorimotor integration; genetically identified
spinal neurons
activity is a product of signals
arising from three main sources: supraspinal centers, spinal
networks, and peripheral sensory afferents. In most general
terms, supraspinal centers generate motor commands and select appropriate sequences of motor activity; spinal networks
translate descending motor commands into muscle activity.
Sensory information conveys important information about the
external world (exteroceptive) and about the internal self (interoceptive) to central networks. Whereas basic motor activity
can be generated by spinal networks, with or without motor
commands from supraspinal networks, the achievement of high
complexity, range, accuracy, and fluency of movement within
THE NEURAL CONTROL OF MOTOR
Address for reprint requests and other correspondence: T. V. Bui, Dept. of
Biology, Univ. of Ottawa, Gendron Hall 285, 30 Marie Curie, Ottawa, ON,
Canada K1N 6N5 (e-mail: [email protected]).
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changing and challenging environments is impossible without
sensory information (Acevedo and Diaz-Rios 2013; Akay et al.
2014). Sensory information is vital to ensuring appropriate
motor execution by evaluating and adjusting motor commands
during ongoing motor activity.
Sensory information can be arranged into functional groups
or modalities, such as sight, hearing, balance, taste, smell,
temperature, nociception, proprioception, and touch. Proprioception contributes to the control of movement by communicating muscle properties and body position. Tactile information is also integral to the control of movement, as it guides
movements by providing information about physical features
of the external world. This occurs via a process where tactile
stimuli are detected and transduced by specialized mechanoreceptors in the skin [for review, see Abraira and Ginty (2013)]
and transmitted via afferent fibers from the periphery to the
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SPINAL SENSORIMOTOR INTEGRATION OF TACTILE INFORMATION
Properties of Spinal Circuits Processing Tactile Information
Location. The most likely location of spinal INs processing
tactile information for motor control can be estimated based on
the topographical distribution of the central terminals of
LTMRs within the spinal cord. The spinal cord is composed of
INs located in Rexed laminae I–VIII and X and motoneurons
located in laminae IX (Rexed 1952, 1954). Whereas nociceptive sensory neurons predominantly contact spinal INs in the
most superficial laminae (I and II) of the dorsal horn, tracing
studies of myelinated cutaneous afferents have described the
most dense labeling of terminals to be found in laminae III–V
of the spinal cord in rodents (Levinsson et al. 2002; Molander
and Grant 1986; Panneton et al. 2005), cats (Brown et al.
1981), and primates (Florence et al. 1991). Consistent with this
distribution of tactile afferents within the spinal cord, electrophysiological recordings of touch-evoked sensory inputs to
spinal neurons in laminae III–V have been reported in primates
(Wagman and Price 1969), rats (Woolf and King 1989), hamsters (Schneider 2005), and cats (Koerber et al. 1990; Sahai et
al. 2006), amongst others. Some of these laminae III–V spinal
neurons receiving sensory inputs from LTMRs have been
identified as premotor INs [i.e., neurons projecting directly to
motoneurons (Egger and Wall 1971; Hongo et al. 1989a, b)],
whereas some have been observed in more ventral laminae VI
and/or VII (Edgley and Jankowska 1987; Moschovakis et al.
1992; Stepien et al. 2010). This anatomical specificity reflects
functional differences that are embedded in the spinal network
connectivity.
Shaping specific forms of motor activity. Whereas the precise connectivity between tactile afferents and spinal neurons
has not been fully characterized, tactile information has been
shown to be particularly important for several motor functions,
such as the control of grip strength (Jenner and Stephens 1982;
Johansson and Flanagan 2009). During hand grasp, activation
of tactile afferents increases hand muscle contraction (Collins
et al. 1999; Johansson et al. 1987). Local anesthesia of the
fingers or hands precludes human subjects from performing
gripping tasks accurately (Augurelle et al. 2003; Johansson and
Westling 1984). Furthermore, this deficit could not be compensated by consciously attempting to increase grip strength.
Tactile afferents are also involved with locomotor function at
the level of the spinal cord. Activation of LTMRs can evoke
sets of stereotyped limb reflexes [e.g., tripping perturbations;
see Drew and Rossignol (1987); Forssberg et al. (1977);
Quevedo et al. (2005a)], as well as modulate the timing
(Duysens and Pearson 1976) and levels of muscle activation
during locomotion (Duysens and Loeb 1980; Loeb et al. 1987).
These reflexes have been suggested to be involved in finetuning the timing of locomotor activity (MacKay-Lyons 2002),
as well as stabilizing gait in the wake of unexpected perturbations (Bunday and Bronstein 2009; Choi et al. 2013; Zehr et al.
1998). These results underline the importance of the recruitment of spinal circuits by tactile afferents to perform precise
motor functions.
Gating of sensory integration at the level of the spinal cord
by motor circuits. As alluded earlier, the relationship between
tactile inputs and spinal motor circuits is not strictly unidirectional, where sensory inflow adjusts motor activity through
spinal circuitry. Rather, it is bidirectional; there is ample
evidence that sensory transmission to the spinal cord from
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central nervous system (CNS). These signals enter the spinal
cord and are directed to the sensory areas of the brain via brain
stem nuclei and the thalamus. At the cortical level, tactile
information is processed, organized, and interpreted, which in
turn, is used to guide behaviors by adjusting descending motor
commands. In parallel to the perception of tactile signals
generated at the cortical level, tactile signals are also integrated
at the level of the spinal cord. That is, in addition to sending
projections that travel rostrally up the dorsal column, cutaneous afferents project collaterals that branch out within the
spinal cord and terminate onto spinal interneurons (INs)
(Brown et al. 1981). Thus the spinal cord serves as a site of
active integration of tactile information, putatively for the
purpose of shaping tactile perception and/or sensorimotor integration.
With regards to the perception of touch stimuli, little is
known about how it is influenced by integration of tactile
information at the level of the spinal cord. However, it has been
established that movement itself can both stimulate sensory
receptors and suppress cutaneous sensation (Prochazka 1989).
Indeed, the perceived intensity of cutaneous stimulation is
reduced during movement (Duysens et al. 1995; Milne et al.
1988). This may be a result of suppressed sensory transmission
at the level of the spinal cord, as suggested by experiments in
monkeys where cutaneous sensory-evoked potentials recorded
in the spinal cord were reduced during active hand movement
(Seki and Fetz 2012). Hence, spinal networks likely contribute
to the final tactile perception.
The involvement of tactile information in shaping motor
control through spinal circuitry is much more established than
its role in tactile perception [briefly reviewed in Panek et al.
(2014)]. In humans, motor reflexes can be evoked by electrical
stimulation of cutaneous afferents applied through surface or
ring electrodes. The early components of these reflexes were
revealed to be mediated by spinal circuits rather than through
long ascending and descending pathways connecting the brain
and the spinal cord (Jenner and Stephens 1982). These circuits
denote a strong coupling of low-threshold mechanoreceptors
(LTMRs) to both hand and leg motoneurons (Fallon et al.
2005; McNulty et al. 1999). As described below, these observations are part of a growing body of work demonstrating
integration of tactile information by spinal circuits involved in
motor control. However, the precise outcome of this integration in actually sculpting motor activity has not been well
understood. Recent studies have started to shed light on spinal
circuits processing tactile signal and their role in motor function (Bourane et al. 2015; Bui et al. 2013; Fink et al. 2014). In
this review, we provide an overview of the spinal circuits that
have been shown to be involved in sensorimotor integration of
tactile information. Furthermore, we discuss the properties of
these spinal circuits, including their location, connectivity, and
interactions, with spinal motor circuits. We focus on spinal INs
that have been identified recently using molecular and genetic
studies and that have been ascribed to sensorimotor integration.
The study of these INs has added to our understanding of how
tactile information can shape motor activity through spinal
circuitry. Finally, we outline potential avenues for research
using genetically identified spinal neurons to address outstanding questions.
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Review
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SPINAL SENSORIMOTOR INTEGRATION OF TACTILE INFORMATION
dI3 INs
dI3 INs represent one of six identified, early born, dorsally
derived populations of INs (dI1– dI6) of the spinal cord (Fig.
1B). These neurons were described initially following the
analysis of transcription factors active in the spinal dorsal horn
during development, in particular, through the assessment of
the effects of gene knockouts on expression patterns of transcription factors (Gross et al. 2002; Muller et al. 2005; Nakada
et al. 2004; Wine-Lee et al. 2004). As a result, the dI3 IN
population is well characterized by the expression of Brn3a/b,
Tlx3, Gsh1/2, and Ascl1, amongst other transcription factors in
progenitor and/or postmitotic cells derived from this population (Mizuguchi et al. 2006; Zou et al. 2012). More importantly, they are characterized further by the expression of Isl1,
a LIM homeodomain transcription factor that is also expressed
in motoneurons but uniquely found in dI3 INs amongst neurons
of the dorsal spinal cord (Liem et al. 1997; Pfaff et al. 1996).
This exclusive expression of Isl1 amongst dorsal neurons has
enabled the application of genetic, electrophysiological, and
immunohistochemical methods to characterize dI3 INs and to
determine their role in motor control (Bui et al. 2013; Goetz et
al. 2015; Pivetta et al. 2014; Stepien et al. 2010).
Conditional expression of yellow fluorescent protein by Isl1
has been used to determine that dI3 INs are primarily located
in laminae V–VII at similar densities in cervical and lumbar
spinal segments (Bui et al. 2013). Cell labeling and in situ
hybridization for vesicular glutamate transporter 2 (vGluT2)
mRNA showed that dI3 INs are predominantly glutamatergic
with ipsilateral projections (Bui et al. 2013). Retrograde tracing
of synaptic inputs to motoneurons using modified rabies virus
demonstrated that dI3 INs directly contact motoneurons in the
spinal cord (Goetz et al. 2015; Stepien et al. 2010). They are
therefore part of a large group of “last-order” spinal INs that
control motor activity through direct excitation of motoneurons
(Brownstone and Bui 2010).
Of these last-order spinal INs, dI3 INs belong to the subset
that receives sensory inputs. Indeed, vGluT1 labeling revealed
that dI3 INs receive primary afferent input (Alvarez et al.
2004). A large portion of these vGluT1-immunoreactive afferents were characterized by an absence of expression of parvalbumin, suggesting that much of the sensory input to dI3 INs
is not proprioceptive in nature but may rather originate from
cutaneous afferents (Bui et al. 2013). Transgenic mice (named
dI3OFF)—in which dI3 IN neurotransmission was genetically
silenced through conditional ablation of vGluT2, a protein used
by these INs for glutamatergic synaptic transmission—were
used to define further the nature of the cutaneous afferents that
project to dI3 INs (Bui et al. 2013). In control mice, in vivo or
in vitro stimulation of the sural nerve, which predominantly
carries cutaneous information (Peyronnard and Charron 1982),
resulted in strong motor reflexes. The early components of this
reflex exhibited latencies characteristic of a disynaptic pathway. Concurrently, recordings of dorsal root potentials demonstrated that the reflex was generated by stimulation of
low-threshold myelinated fibers corresponding to low-threshold myelinated A␤-LTMRs. This reflex response was completely absent in dI3OFF mice, suggesting that dI3 INs are
involved in a disynaptic microcircuit linking cutaneous afferents (conveying touch) with motoneurons (Figs. 1B and 2) (Bui
et al. 2013).
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LTMRs is, in turn, modulated by motor activity. For instance,
motor reflexes evoked by tactile input are phasically modulated
during locomotion in cats (Degtyarenko et al. 1998; Forssberg
et al. 1977; Quevedo et al. 2005a, b) and in humans (Baken et
al. 2005; Van Wezel et al. 1997; van Wezel et al. 2000; Zehr
et al. 1997, 1998). Cutaneous reflexes also seem to be modulated by the type of activity during which they are evoked, as
observed in humans, for example, during different gaits
(Duysens et al. 1993; Hoogkamer et al. 2012), fine vs. coarse
hand movements (Evans et al. 1989), and different limb or
hand postures (Garnett and Stephens 1981; Gibbs et al. 1995).
The modulation of cutaneous reflexes by motor activity may
be due to gating of sensory transmission, which seems to
occur at many levels of the CNS, including at the level of
the spinal cord (Seki and Fetz 2012). However, there is also
evidence suggesting that modulation of spinal INs integrating tactile information for motor control may contribute to
gating of cutaneous reflexes (Burke et al. 2001; Quevedo et
al. 2005a).
It is not clear whether the bidirectional interactions between
tactile inputs and motor networks are mediated strictly by
spinal circuits or whether they rely on supraspinal control.
Indeed, motor control involves hierarchical circuits spanning
both spinal and supraspinal networks that enable motor adaptation and motor learning (Kawato et al. 1987). Likewise,
sensorimotor integration is distributed across the CNS hierarchy. The distance of a sensorimotor circuit to the musculoskeletal system (spinal circuits being closer, supraspinal circuits
being farther) introduces a relative delay to when sensory
information influences motor activity (Shadmehr et al. 2010).
Therefore, the understanding of at which levels of the CNS
sensorimotor interactions occur is important to uncover the
roles of these widely distributed sensorimotor circuits. In spite
of the truly heroic efforts in earlier decades to demonstrate the
presence of spinal circuits integrating tactile afferents, ascribing detailed motor roles to particular groups of spinal INs has
been a difficult goal to achieve. The advent of recent genetic
approaches to studying spinal neurons has enabled combinations of electrophysiological, cell labeling, and behavioral
testing techniques that have provided strong evidence that
spinal circuits integrating tactile information play crucial roles
in ensuring proper motor control (Bourane et al. 2015; Bui et
al. 2013). These genetic approaches are based on the insight
that during development, populations of neurons emerge
from common progenitor pools that arise from the interaction of inductive signals released by structures, such as the
roof plate, floor plate, and notochord (Jessell 2000; Stifani
2014). These signals promote the activation of many transcription factors involved in a diverse set of developmental
processes, such as cell cycle progression and exit, cell
migration, axon guidance, and establishment of neurotransmitter phenotype, to name a few. Each progenitor pool will
express a unique combinatorial set of transcription factors
(Fig. 1F). The partitioning of spinal neurons into genetically
identified populations has been particularly successful
(Alaynick et al. 2011; Francius and Clotman 2014; Lu et al.
2015; Stifani 2014). Herein, we describe those populations
of genetically identified spinal neurons that have been determined to integrate tactile afferents for the purpose of
shaping motor activity and the fundamental insights that the
study of these neurons has provided.
Review
SPINAL SENSORIMOTOR INTEGRATION OF TACTILE INFORMATION
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Higher centres
Supraspinal
Centers
A
I II
III
IV
V
VI
SN
X
VII
IX
Spinal
INs
VIII
LMC
MMC
LTMRs
Muscles
C
LRN
CST
LVST
ROR
α
dI3
V0c
vGluT2
vGluT2
D-hair
Meissner
Merkel
Lanceolate
LTMRs
except
Merkel
D
E
?
dI4
vSCT
dI1
?
GAD2
GlyT2
NPY
Enkephalin
dSCT
dI1
IN
?
cont
ipsi
LTMRs
LTMRs
?
F
Progenitor
domain
pd1
?
Pax6 Irx3
Progenitor
zone
Post-mitotic
zone
Gdf7 Atoh1 Pax3 Msx1 Bmpr1a Olig3
?
Brn3a
BarH1
Lhx9
Cell
type
Lhx2 TAG-1
dI1
Cbln2 SMARCA
dI1
RORα c-Maf PKCγ Lmx1b ROR
α
pd3
Brn3a/b
Pax6 Irx3 Pax7 Ngn2 Pax3 Msx1 Ascl1 Gsh2 Olig3Isl1 Isl1
Tlx3 Tlx3
Drg11Drg11
Bm3a
pd4
Pax6 Irx3 Pax7 Ngn2 Pax3 Msx1 Ascl1 Gsh1/2 Ptf1a
Lbx1 Pax2 Lhx1/5 Ptf1a
To determine the functional role of the tactile sensorimotor
circuit mediated by dI3 INs, motor function of the dI3OFF mice
was tested in a number of behavioral tests. dI3OFF mice demonstrated greater difficulty with the ladder test and displayed an
increase in missteps compared with control littermates (Bui et al.
dI3
dI4
2013). Even so, the most striking deficit was an inability to
mediate grip strength in the face of increasing loads—their own
weight— during the wire hang test (Bui et al. 2013). Both of these
handicaps resulted from the silencing of dI3 INs. Whereas the
above experiments did not identify exact types of LTMRs con-
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B
Fig. 1. Genetically identified spinal interneurons (INs) implicated in microcircuits integrating tactile information for sensorimotor control. A: diagram representing the typical spinal
circuitry integrating tactile sensory information, where a lowthreshold mechanoreceptor (LTMR) sensory neuron (SN) enters the spinal cord and bifurcates to project to spinal INs and
neurons in supraspinal centers. Subpopulations of spinal INs
(Spinal INs) receiving tactile inputs project to spinal targets,
including motoneurons of the lateral motor column (LMC) and
medial motor column (MMC) and/or to supraspinal centers.
Roman numerals refer to the Rexed laminae. B–E: diagrams
representing dI3 INs (B), retinoic acid receptor-related orphan
receptor ␣ (ROR␣) INs (C), dI4 INs (D), and dI1 INs (E). SNs
(blue) connect to spinal IN populations. The established implication of some LTMR subtypes is indicated. IN connections to
and from supraspinal centers are indicated. Ascending and
descending projections are not represented at their exact location for simplicity purposes. B: dI3 INs project to motoneurons
as well as to the lateral reticular nucleus (LRN). Note the
weaker connection to MMC motoneurons. vGluT2, vesicular
glutamate transporter 2. C: ROR␣ INs project to both V0
cholinergic (V0c) INs (maroon) and motoneurons. ROR␣ INs
also receive inputs from the cortex via corticospinal tracts
(CST) and the vestibular nucleus via the lateral vestibulospinal
tract (LVST). D: dI4 INs are involved in a presynaptic axoaxonic inhibition of sensory projection onto spinal INs (pink).
dI4 INs that mediate axo-axonic inhibition of proprioceptive
afferents are not depicted. dI4 IN supraspinal connections have
yet to be identified. GAD2, glutamate decarboxylase 2; GlyT2,
glycine transporter 2; NPY, neuropeptide Y. E: two defined
subpopulations of dI1 INs are represented by having either
ipsilateral (ipsi; light purple) projections to the cerebellum via
the ventral spinocerebellar tract (vSCT) or contralateral (cont;
deep purple) projections to the dorsal SCT (dSCT). Subpopulation-specific genetic markers are listed above the IN symbols;
a number of shared genetic identifiers are listed below the IN
symbol. F: transcriptional code involved in the development of
genetically identified spinal INs that integrate tactile information. See Table 1 for more description of the transcription
factors listed. Note that the progenitor domain or domains from
which ROR␣ INs originate are not known [panel F adapted
from Lu et al. (2015) under CC-BY].
Review
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SPINAL SENSORIMOTOR INTEGRATION OF TACTILE INFORMATION
A
B
C
Control
L6
L5 ventral root
Sural nerve
L5 Dorsal Root
L5 dorsal root
Tibial nerve stimulation (1 to 10 mA)
L5 Ventral Root
Sural nerve stimulation (1 to 10 mA)
cut. DRP
L1
dI3
10 ms
OFF
Tibial nerve
proprio. DRP
D
10 ms
E
F
Sural Nerve
Gastrocnemius
Tibialis
Anterior
Gastrocnemius
Amplifier Stimulator
DRG
dI3
SN
dI3
OFF
5 ms
MN
LTMRs
Fig. 2. Demonstration of a genetically identified spinal circuit integrating tactile input for motor control. A: scheme of isolated in vitro spinal cord preparation
with sural nerve left in continuity used to test for the presence of reflexes evoked by stimulation of tactile inputs. Stimulating electrodes (red) were placed on
the sural nerve, which is predominantly cutaneous, and the mixed sensory tibial nerve distal to the sural nerve branchpoint. Recording suction electrodes (green)
were placed on the ipsilateral lumbar L5 dorsal (sensory) and L5 ventral (motor) roots. B: to demonstrate the predominantly cutaneous nature of the sural nerve,
electroneurogram (ENG) recordings of L5 dorsal root potentials (DRPs), in response to sural nerve or tibial nerve stimulations, were made. In this example, note
the longer latency of the sural nerve DRP compared with the tibial nerve DRP, which is due to the proprioceptive component of the tibial nerve. Furthermore,
the threshold to evoke a DRP was higher for sural nerve [cutaneous (cut.) DRP; 3 ␮A] than tibial nerve [proprioceptive (proprio.) DRP; 2 ␮A] stimulation.
C: to test for motor reflexes in response to stimulation of cutaneous afferents, ENG recordings of L5 ventral root responses to multiple stimulation pulses applied
to the sural nerve were made. A putative disynaptic reflex response, highlighted in the dashed box, can be observed in control mice but not in animals that had
dI3 INs genetically silenced (dI3OFF). D: diagram of experimental design used to test for the presence of motor reflexes evoked by tactile inputs conveyed by
the sural nerve and mediated by dI3 INs. Chronically implanted electrodes into gastrocnemius and tibialis anterior muscles of adult control and dI3OFF mice
enabled electromyographic (EMG) recordings in awake, behaving mice. E: similar to in vitro tests, EMG recordings of gastrocnemius to multiple stimulation
pulses applied to the sural nerve show a putative disynaptic reflex response (dashed box) that is absent in dI3OFF mice. F: diagram representing dI3 INs (dI3)
as part of a disynaptic pathway among SNs that are LTMRs, dI3 INs, and motoneurons (MN) [adapted from Bui et al. (2013) with permission from Elsevier].
DRG, dorsal root ganglion.
tacting dI3 INs, it is possible to exclude a major contribution from
Merkel cells, as experiments in which Merkel cells were eliminated from mice did not result in any deficits in grasping, as tested
by the wire hang test (Maricich et al. 2012).
The genetic silencing studies and the previous immunohistochemical and electrophysiological experiments lead us to
believe that dI3 INs integrate cutaneous information necessary
for motor behaviors. The most evident involvement of this
circuitry is in grasping; however, their full involvement in
other motor behaviors has not been fully determined.
Related Orphan Receptor INs
To identify putative populations of spinal neurons that process tactile information for motor control, Del Barrio and
colleagues (2013) performed a preliminary transcription factor
screening to probe the molecular identities of INs in laminae
III–V, which are predominantly innervated by LTMRs that
transduce cutaneous mechanosensory information. From this
screen, INs expressing the protein retinoic acid receptor-related
orphan receptor ␣ (ROR␣) were targeted and studied further
using transgenic methods (Bourane et al. 2015). The ROR␣ IN
population is characterized by its expression of ROR␣, MafA,
c-Maf, and Lmx1b, amongst other transcription factors, where
the latter can mark excitatory INs in the dorsal spinal horn
(Ding et al. 2004). To confirm the excitatory nature of these
cells, in situ hybridization for vGluT2 mRNA revealed that
ROR␣ INs are predominantly glutamatergic.
The mapping of ROR␣ INs demonstrated that they are
mostly located between inner lamina II (IIi) and lamina III.
ROR␣ INs are primarily innervated by LTMRs and receive
little to no nociceptive input. The combination of recent advances in recombinant rabies virus techniques to label genetically identified neurons (Weible et al. 2010) and identification
of molecular markers for LTMRs (Li et al. 2011; Luo et al.
2009) allowed for characterization of the sources of sensory
input to ROR␣ INs. Interestingly, these INs were demonstrated
to be innervated by Meissner corpuscles in glabrous skin and
Merkel cells, D-hair terminals, and transverse lanceolate endings in hairy skin (Bourane et al. 2015). Furthermore, putative
evidence suggests the implication of Ruffini endings as sensory
input; however, the full extent of the innervation of ROR␣ INs
by LTMRs innervating this class of sensory receptors requires
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Control
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SPINAL SENSORIMOTOR INTEGRATION OF TACTILE INFORMATION
dI4 INs
So far, we have described two populations of genetically
identified spinal neurons that integrate tactile afferents. These
two populations are predominantly composed of excitatory
neurons. However, integration of tactile afferents by spinal
cord circuitry may also involve inhibition. For instance, stimulation of low-threshold cutaneous inputs can gate the transmission of tactile information within the spinal cord by shunting the excitability of other cutaneous afferents through axoaxonic contacts in a phenomenon known as presynaptic
inhibition (Rudomin 2009).
The origin of GABAergic projections to spinal terminals of
sensory neurons mediating presynaptic inhibition was discovered to originate commonly from dI4 INs, a class of dorsally
derived spinal INs marked by the expression of the transcription factor Ptf1a (Fig. 1D). In fact, most, if not all, GABAergic
boutons contacting sensory terminals within the spinal cord
were found to derive from dI4 INs (Betley et al. 2009).
GABAergic boutons apposed to sensory afferent terminals
were demarked from GABAergic boutons apposed to dendrites
or somas by the expression of the protein glutamate decarboxylase 2 (Gad2) (Betley et al. 2009). Remarkably, even though
Gad2-immunoreactive GABAergic boutons contacting cutaneous afferent terminals and those contacting proprioceptive
afferent terminals originate from dI4 INs, only the former
shows GlyT2, enkephalin, and neuropeptide Y expression
(Betley et al. 2009). Therefore, subpopulations of dI4 INs
clearly exist, which can be distinguished by expression of
selective proteins at synaptic terminals and more importantly,
by the type of sensory afferents they target.
The role of presynaptic inhibition in motor control has
recently been investigated using genetic techniques. Genetic
silencing of Gad2-immunoreactive GABAergic boutons mediating presynaptic inhibition has been shown to disrupt smoothreaching movements (Fink et al. 2014). However, this effect
was attributed to loss of presynaptic inhibition of proprioceptive afferents rather than of cutaneous afferents. Therefore, the
role of presynaptic inhibition of tactile afferents or the role of
presynaptic inhibition driven by tactile afferents remains an
open question.
dI1 INs
Defined by expression of Atoh1 (formerly Math1), dI1 INs
are also a population of dorsally derived neurons that migrate
ventrally to be positioned in the deep dorsal horn of the spinal
cord (Bermingham et al. 2001). These neurons form three
distinct spinocerebellar tracts (SCTs), by which sensory feedback is relayed to the cerebellum. In more rostral spinal cord
segments (cervico-thoracic), dI1 INs form the rostral SCT
(rSCT), whereas in more caudal spinal cord segments (thoracolumbo-sacral), dI1 INs are found in two clusters that form the
dorsal SCT (dSCT) and the ventral SCT (vSCT) (Miesegaes et
al. 2009) (Fig. 1E). The SCTs convey sensory information
from muscle afferents and to a lesser degree, from LTMRs to
the cerebellum (Edgley and Jankowska 1988; Randic et al.
1981), a region important for correcting movements and for
motor learning (Brownstone et al. 2015; Kawato et al. 1987).
Therefore, these neurons are involved with sensorimotor integration at supraspinal levels. There is less information about
their interaction with motor circuitry at the spinal cord level;
however, neurons of the dSCT are contacted by corticospinal
inputs, suggesting that the sensory feedback that they relay is
shaped by descending motor commands (Hantman and Jessell
2010).
Key Insights and Open Questions
Much work has been dedicated in the past to revealing the
presence of spinal neurons that integrate tactile input and in the
process, sculpt ongoing motor activity. The recent studies of
genetically defined spinal INs that we have described (summarized in Fig. 1) build on the work of the past decades and serve
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further investigation. These anatomical experiments were substantiated further by whole cell recording of these neurons,
which demonstrated the presence of monosynaptic excitatory
potentials mostly in response to electric recruitment of lowthreshold myelinated A␤ and high-threshold myelinated A␦
fibers (Bourane et al. 2015).
To determine whether ROR␣ INs play a role in motor
control, projections to spinal neurons involved in motor activity were sought (Bourane et al. 2015). Indeed, spinal ROR␣
INs were found to project directly on motoneurons in the
lumbar spinal cord. Furthermore, contacts were found on V0
cholinergic (V0c) neurons, which are known to modulate the
excitability of motoneurons, suggesting perhaps that ROR␣
INs possess the ability to modulate motor output through the
intermediary of V0c neurons (Zagoraiou et al. 2009). Additionally, ROR␣ INs were found to be innervated by corticospinal tract neurons in motor cortex and by lateral vestibulospinal tract (LVST) neurons. LVST neurons are known to originate in the pons and project downwards to the spinal cord
carrying information about posture and balance (Markham
1987). Collectively, these results demonstrate that ROR␣ INs
are spinal neurons that are implicated in integrating tactile
inputs to shape motor activity (Fig. 1C).
To study the specific role of ROR␣ INs in motor control,
ablation of ROR␣ INs in the caudal spinal cord was achieved
by inducing selective expression of the diphtheria toxin receptor in ROR␣ INs and subsequent treatment with diphtheria
toxin (Bourane et al. 2015). The resulting mice were subjected
to a battery of sensory tests. Most interestingly, these mice
displayed an impairment in sensing dynamic and static light
touch on the plantar surface of the foot. Nonetheless, the
ROR␣ IN-ablated mice showed no difference in pain sensation, suggesting that ROR␣ INs mainly contribute to lighttouch perception without compromising responsiveness to
other sensory modalities. ROR␣ IN-ablated mice did not show
any significant locomotor differences to control littermates
when tested on a treadmill or on a horizontal ladder. However,
when fine motor control during locomotion was accessed by
the raised beam test (Crawley 2008), a significant increase in
hindlimb missteps was reported. These results suggest that
ROR␣ INs mediate cutaneous sensory information for use in
motor commands involved in corrective foot movements.
The ablation and tracing studies showed that ROR␣ INs integrate cutaneous sensory information from LTMRs with descending cortical inputs into motor commands for corrective feet movements; however, the mechanisms by which these neurons integrate this descending cortical input have yet to be studied.
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Table 1. Molecular markers expressed by spinal interneurons involved in sensorimotor integration of tactile information
Common Name
Ascl1
BarH1
Brn3a
Brn3b
Cbln2
c-Maf
Drg11
Enkephalin
Gad2
GlyT2
Tag-1
Tlx3
vGluT2
UniProt ID
References
Achaete-scute family bHLH transcription factor 1
BarH-like homeobox 1
POU class 4 homeobox 1
POU class 4 homeobox 2
Cerebellin 2 precursor
v-maf Avian musculoaponeurotic fibrosarcoma oncogene
homolog
Dorsal root ganglia homeobox
Prodynorphin
Glutamate decarboxylase 2 (pancreatic islets and brain,
65 kDa)
Solute carrier family 6 (neurotransmitter transporter),
member 5
GS homeobox 1
GS homeobox 2
ISL LIM homeobox 1
LIM homeobox 1
LIM homeobox 2
LIM homeobox 5
LIM homeobox 9
LIM homeobox transcription factor 1, beta
Atonal homolog 1 (Drosophila)
Neuropeptide Y
Paired box 2
Pancreas transcription factor 1 subunit alpha
RAR-related orphan receptor A
SWI/SNF-related, matrix-associated, actin-dependent
regulator of chromatin, subfamily a, member 2
Contactin 2 (axonal)
T Cell leukemia homeobox 3
Solute carrier family 17 (vesicular glutamate
transporter), member 6
P50553
Q9BZE3
Q01851
Q12837
Q8IUK8
O75444
dI3 IN, dI4 IN: Mizuguchi et al. (2006)
dI1 IN: Bermingham et al. (2001)
dI1 IN, dI3 IN: Zou et al. (2012)
dI3 IN: Zou et al. (2012)
dI1 IN: Miesegaes et al. (2009)
ROR␣ IN: Bourane et al. (2015)
A6NNA5
P01213
Q05329
dI3 IN: Rebelo et al. (2010)
dI4 IN: Betley et al. (2009)
dI4 IN: Betley et al. (2009)
Q9Y345
dI4 IN: Betley et al. (2009)
Q9H4S2
Q9BZM3
P61371
P48742
P50458
Q9H2C1
Q9NQ69
O60663
Q92858
P01303
Q02962
Q7RTS3
P35398
P51531
dI4 IN: Mizuguchi et al. (2006)
dI3 IN, dI4 IN: Mizuguchi et al. (2006)
dI3 IN: Liem et al. (1997); Pfaff et al. (1996)
dI4 IN: Pillai et al. (2007)
dI1 IN: Bermingham et al. (2001)
dI4 IN: Pillai et al. (2007)
dI1 IN: Bermingham et al. (2001)
ROR␣ IN: Bourane et al. (2015)
dI1 IN: Bermingham et al. (2001)
dI4 IN: Betley et al. (2009)
dI4 IN: Glasgow et al. (2005)
dI4 IN: Glasgow et al. (2005)
ROR␣ IN: Del Barrio et al. (2013)
dI1 IN: Miesegaes et al. (2009)
Q02246
O43711
Q9P2U8
dI1 IN: Miesegaes et al. (2009)
dI3 IN: Cheng et al. (2005); Mizuguchi et al. (2006)
dI3 IN: Bui et al. (2013); ROR␣ IN: Bourane et al.
(2015)
bHLH, basic helix-loop-helix; IN, interneuron; ROR␣, retinoic acid receptor (RAR)-related orphan receptor ␣; SWI/SNF, switch/sucrose nonfermentable.
Sources: http://www.genenames.org/ and http://www.uniprot.org/.
to highlight a number of key features of integration of tactile
inputs within the spinal cord. First, there are populations of
spinal neurons defined by the expression of specific combinations of transcription factors and molecular markers that receive inputs from cutaneous afferents conveying tactile information (Table 1). Second, based on the types of LTMRs
involved and specificity of the connectivity with spinal and
supraspinal motor networks, these genetically defined populations of spinal INs form specialized networks. Manipulation of
genetically defined spinal INs revealed that they indeed play
roles in distinct aspects of motor control. Finally, although
sensorimotor integration also occurs at the brain level, integration by spinal INs is vital in ensuring proper motor control.
Below, we offer a short and nonexhaustive list of further
avenues of investigation into sensorimotor integration of tactile
information, taking advantage of genetically defined spinal
INs.
Identification of Other Spinal Populations/Subpopulations
that Integrate Tactile Information
A long-standing question in neuroscience is how to classify
populations of neurons (DeFelipe et al. 2013). Classes of
neurons can be defined based on single or combinations of
intrinsic properties, such as protein expression, morphology,
anatomical location, neurotransmitter phenotypes, synaptic inputs, and/or outputs. Alternatively, neurons can be classified
along functional lines, such as firing behavior and involvement
with certain neuronal or physiological forms of activity. Needless to say, the classification of neurons is an ongoing, fluid
exercise that is necessary for the proper study of neural
systems. For the immediate purpose of discussing classes of
spinal neurons involved with the integration of tactile information for motor control, it is necessary to highlight that each
of the canonical populations of genetically identified spinal INs
(dI1– dI6; dIL,A-B; V0 –V3) and motoneurons is likely to consist of many subpopulations of neurons that are differentiated
along molecular and/or functional lines. For instance, the V2
population of ipsilaterally projecting ventral neurons, which
are characterized by Lhx3 expression, has been parsed out to
consist of V2a, V2b, and V2c, based on Chx10, Gata2, and
Sox1 expression (Al-Mosawie et al. 2007; Lundfald et al.
2007; Panayi et al. 2010; Zhou et al. 2000). These neurons are
also distinguished by different neurotransmitter phenotypes
and likely, functional roles as well (Crone et al. 2008; Zhong
et al. 2010). Not surprisingly, there is some degree of functional heterogeneity within each subpopulation (Dougherty et
al. 2013). Clearly, the identification of the functional roles of
spinal neurons from common progenitor pools is only the
starting step to understanding fully the roles of spinal circuits
in processing tactile information. The identification of subpopulations within these cardinal cell populations, based on
molecular, anatomical, and functional properties, will refine
the classification further. With the consideration that spinal INs
receiving both proprioceptive and cutaneous afferents have
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Gsh1
Gsh2
Isl1
Lhx1
Lhx2
Lhx5
Lhx9
Lmx1b
Math1
NPY
Pax2
Ptf1a
RORa
Smarca2
Approved Name
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SPINAL SENSORIMOTOR INTEGRATION OF TACTILE INFORMATION
Connecting Spinal Circuits for Sensorimotor Integration of
Tactile Information
It is clear that dI3 INs and ROR␣ INs both use tactile
information but play distinct roles in motor control. For instance, when dI3 INs were silenced, mice showed deficits on
the ladder test as well as in controlling grip strength (Bui et al.
2013), whereas ablation of caudal populations of ROR␣ INs
did not impact performance on the ladder test but resulted in
impairments on the raised beam test (Bourane et al. 2015).
However, this does not preclude the possibility that to serve
their respective motor functions, these two populations of
neurons interact. Along the same lines, dI4 INs may be linked
to dI3 INs and ROR␣ INs through presynaptic inhibition of
cutaneous afferents to the two groups of excitatory neurons.
In addition to studying the interactions between genetically
identified spinal INs involved in sensorimotor integration of
tactile inputs, their interactions with other spinal neurons
involved in complementary aspects of motor function must be
determined. For example, whereas dI3 INs have been implicated with controlling grip strength, they do not seem to be
critical for other aspects of hand control, such as skilled reach
(unpublished observation). On the other hand, the V2a population of spinal neurons has been shown to be intimately
involved with skilled reaching (Azim et al. 2014b). A subset of
dI4 INs is also involved in ensuring smooth hand trajectory
(Fink et al. 2014). Evidently, dI3 INs, dI4 INs, and V2a INs
seem to operate concurrently to achieve proper hand control
(Azim et al. 2014a). Therefore, as the individual contributions
of genetically identified spinal INs to motor control and to
sensorimotor integration of tactile inputs are revealed, the
mutual connectivity between spinal neurons has to be mapped
to understand fully how tactile information truly tailors motor
output across the spectrum of possible motor activities.
Connecting Spinal Circuits with Supraspinal Circuits for
Sensorimotor Integration of Tactile Information
Whereas spinal circuits involved in sensorimotor integration
are able to operate in isolation without supraspinal input (e.g.,
tendon reflex), cortical and subcortical regions of the brain, as
well as the cerebellum, are involved with motor processes,
such as motor planning, motor learning, and motor adaptation.
In addition, several regions of the brain stem are involved in
the control of motor activity, such as locomotion (Grillner and
Shik 1973) and hand function (Soteropoulos et al. 2012),
through direct recruitment of spinal circuitry. Therefore, spinal
circuits are likely to operate in conjunction with descending
inputs from supraspinal areas. Indeed, cortical stimulation has
been shown to modulate hindlimb cutaneous reflexes (Bretzner
and Drew 2005). Similarly, cutaneous reflexes may modulate
corticospinal efficacy through ascending reflex pathways
(Christensen et al. 1999). ROR␣ INs have been shown to
receive supraspinal inputs from motor cortex and the cerebellum, the latter through the intermediary of projections originating from the lateral vestibular nuclei (Bourane et al. 2015).
In addition, they project to ascending postsynaptic dorsal
column neurons that may link these neurons with the cerebellum (Bourane et al. 2015). We also expect dI3 INs to receive
supraspinal inputs based on clinical observations. For instance,
dI3 INs mediate a palmar grasp reflex at early postnatal stages
(Bui et al. 2013) that resembles a postnatal grasp reflex in
humans. This reflex disappears in time (Mestre and Lang
2010), in parallel with the maturation of descending pathways
to the spinal cord (Clarac et al. 2004). In addition, abnormal
grasp reflexes in human patients have often been associated
with frontal cerebral lesions (Mestre and Lang 2010), perhaps
due to loss of supraspinal regulation of dI3 INs or of an
analogous population in humans. Supraspinal regions may also
be targeted by dI3 INs, as revealed by their innervation of the
lateral reticular nucleus, a precerebellar nuclei (Pivetta et al.
2014). Therefore, the sources of supraspinal inputs to these
neurons will be an active area of investigation. In addition, the
role of these supraspinal projections in shaping sensorimotor
integration of tactile information at the level of the spinal cord
will be important. A prominent role for supraspinal projections
may be the gating of sensory information during motor activity
(see above). Therefore, how supraspinal inputs influence the
gating of tactile information at the spinal level and during
which forms of motor activity may be answered through the
study of supraspinal projections to genetically identified spinal
neurons.
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long been identified in deep dorsal horn and intermediate
laminae of the spinal cord (Edgley and Jankowska 1987;
Moschovakis et al. 1992), it would not be altogether surprising
if subpopulations of ventrally derived spinal neurons were
found to integrate tactile information for motor control. A
prime candidate for ventrally derived spinal neurons integrating tactile information is a subpopulation of the V3 IN
population, which consists of commissural INs, involved in
maintaining locomotor stability (Zhang et al. 2008), found
to migrate during development and to be ultimately positioned in the deep dorsal horn (Blacklaws et al. 2015;
Borowska et al. 2013).
The work on spinal ROR␣ INs is a prime example of the
need for studying subpopulations as well. It is not clear
whether these neurons form a subpopulation of neurons that
arise from a common progenitor domain or whether they
consist of neurons from several progenitor domains. The latter
would reveal that functional roles may be distributed amongst
spinal neurons originating from a broad distribution of progenitor pools. A precedent for the distribution of functional roles
amongst neurons arising from different progenitor pools was
demonstrated when the spinal neurons responsible for reciprocal inhibition mediated by Ia afferents were found to arise from
both V1 and V2b populations (Siembab et al. 2010; Zhang et
al. 2014). The screening for genes commonly expressed in
spinal lamina III–V, where sensory neurons innervating
mechanoreceptors are most abundantly found, has revealed a
number of candidate proteins that may mark other classes of
functionally related spinal neurons that integrate tactile information and shape motor activity (Del Barrio et al. 2013). It
would not be altogether surprising to discover that neurons
belonging to the dI1, dI3, and dI4 IN populations consist of
several subpopulations, as is already suggested for dI1 INs,
based on anatomical location and ascending tract formation
(Miesegaes et al. 2009). The dissection of these canonical
populations of sensorimotor INs is a crucial step to understanding further the integration of tactile information for motor
control.
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Neural Coding
One of the many achievements of Steven Hsiao (Hsiao and
Yau 2008) in the field of tactile perception was the discovery
of neural codes for the perception of object features, such as
texture, size, and shape. Whereas much focus has been paid to
the role of the somatosensory cortex in this process, recent
studies in humans provide evidence that sensory neurons innervating glabrous skin of the hand can perform higher-order
feature detection, such as edge detection (Pruszynski and
Johansson 2014). In light of this, we propose that spinal
neurons receiving inputs from cutaneous receptors may further
process features detected by sensory neurons for the purpose of
motor control.
Indeed, spinal neurons have characteristics that hint at their
capability to detect object features. For instance, the response
of dorsal spinal neurons to tactile stimuli applied to the skin has
been shown to depend on the nature of the stimuli and the
receptive field. Responses can be graded (Fitzgerald 1985;
King et al. 1990; Schneider 2005), excitatory, inhibitory, or a
mixture of both (Hillman and Wall 1969; Kato et al. 2011;
Kolmodin and Skoglund 1960; Woolf and King 1989), subthreshold or suprathreshold (Woolf and King 1989), and short
or sustained (De Koninck and Henry 1994; Schneider 2005).
The wide ranges of response patterns of spinal neurons are a
reflection of the range of activation patterns of LTMRs (Abraira and Ginty 2013; Johansson and Flanagan 2009), as well as
heterogeneity in intrinsic properties of spinal neurons (Ku and
Schneider 2011).
Recordings of genetically identified spinal neurons can further establish whether detection of features of objects can occur
at the spinal level. We know that dI3 INs have a number of
ionic currents that alter the latency and the duration of their
response to sensory inputs (Bui et al. 2013). As well, both dI3
INs and ROR␣ INs receive inputs from multiple sources of
sensory information. In fact, they also exhibit a number of
different firing responses to electrical stimulation of sensory
afferents (Bourane et al. 2015; Bui et al. 2013). To determine
fully whether these neurons are capable of detecting object
features, studies detailing the receptive fields of individual INs
and their response to different forms of tactile stimuli, as well
as the integration of stimuli applied to multiple sites on the
skin, various tactile receptors, or other sensory modalities,
need to be undertaken.
Another important aspect of feature detection and sensory
processing, in general, is the representation of sensory information at different neural layers as information flows centrally
through the nervous system. Studies of other sensory systems,
such as the visual, olfactory, and electrosensory systems,
suggest the involvement of common mechanisms of sensory
information processing that may apply to sensorimotor integration of tactile information within the spinal cord as well
(Babadi and Sompolinsky 2014). First, sensory processing is
characterized by an expansion of sensory representations,
whereby as sensory information travels centrally, it is processed by an increasing number of neurons. A second commonly observed mechanism of sensory processing is sparse
representation, whereby as sensory information travels centrally, it only projects to a subset of downstream neurons (Bui
and Brownstone 2015), despite the larger number of downstream neurons devoted to the processing of sensory information (see expansion). These two mechanisms are illustrated in
the fly olfactory system, where ⬃150 projection neurons,
relaying signals from olfactory receptor neurons, project to
2,500 Kenyon cells in the fly mushroom body (Turner et al.
2008). However, as a consequence of limited convergence of
inputs from projection neurons to Kenyon cells, each individual Kenyon cell responds only to a small sample of possible
odors captured by olfactory receptor neurons. In the context of
the flow of tactile information from the skin to spinal circuits,
an expansion of tactile signals conducted by sensory neurons in
exclusive parallel fibers would imply a projection of these
signals to a wide array of spinal neurons. These sensory fibers
account for specific sensory modalities but additionally, for
their intensity and spatiotemporal distribution. The requirement for sparseness would dictate that the tactile signals
relayed to the spinal cord would converge toward a network of
spinal INs composed of nonoverlapping and/or partially overlapping populations. The study of genetically identified spinal
neurons involved in sensorimotor integration could reveal
whether there is expansion and sparseness in the representation
of tactile information at the spinal level. Finally, to shape
motor control through an integration of tactile information,
these spinal INs must project a set of instructive motor commands. We suggest that these motor commands diverge to
activate spinal circuits or motor modules dedicated to specific
aspects of motor control (Giszter and Hart 2013). The activity
of a single or multiple motor modules generates a coordinated
motor response to the tactile stimuli (Fig. 3).
Concluding Remarks
Most of the studies of genetically identified spinal INs
were performed in mice, testing the cutaneous afferents
either on hairy or glabrous skins. Therefore, caution should
be exercised in attempting to generalize these finding to
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Alternatively, spinal circuits may also influence the processing of tactile information by supraspinal regions dedicated to
somatosensation, as demonstrated by findings that dI1 INs, dI3
INs, and ROR␣ INs are part of ascending pathways from the
spinal cord to the brain. Postsynaptic dorsal column neurons
contacted by ROR␣ INs send ascending projections that may
ultimately be relayed to somatosensory cortex. Indeed, mice
lacking ROR␣ INs showed delays in detecting an irritant taped
to their paws (Bourane et al. 2015). In addition to shaping
somatosensation, spinal circuits may shape the motor strategies
used to probe the external world. Indeed, perception and action
are often processes that overlap (Hsiao et al. 2011). Classically,
the relationship between sensory and motor systems has been
viewed as sensory circuits informing motor systems. However,
motor systems can shape sensory processing. For example, by
changing whisking strategies, an animal can change the rate of
tactile sensory inflow (Saig et al. 2012). By virtue of their
access to motor circuits, both dI3 INs and ROR␣ INs may
influence tactile perception by shaping motor processes involved with sensing the external world. Therefore, the mutual
interactions between spinal and supraspinal circuits must be
investigated to understand further the processes by which
tactile information shapes motor activity, and spinal circuits
shape somatosensation and the motor strategies used to acquire
sensory information.
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3059
Computational
convergence
Parallel processing
Instructive
divergence
Sensors
Spinal interneuron
network
Coordinated
action
Motor
modules
Fig. 3. Conceptual model of sensorimotor neural processing in the spinal cord. Proposed scheme in which sensory inputs from multiple modalities are
conveyed in parallel to partially overlapping spinal IN populations. The converging sensory information is processed, and sets of instructive motor
commands are generated. These commands diverge to motor modules that generate individual motor actions, which together, form the desired coordinated
motor response. We propose that this anatomical and functional structure provides a biological framework to neuronal computations underlying spinal
sensorimotor integration.
approach is the characterization of a number of spinal neuron
populations that integrate tactile information and the identification of their role in shaping motor control as reviewed above.
Each identified population of spinal INs presents further opportunities to probe mechanisms by which sensorimotor integration of tactile input occurs. Whereas this approach is conditioned by our ability to 1) identify and 2) manipulate defined
neuronal populations, recent technical advances are meeting
these challenges. Cellular RNA expression profiling, for example, has been used successfully to identify new neuronal
populations (Del Barrio et al. 2013), whereas optogenetic and
chemogenetic techniques, such as channelrhodopsins (Zhang
and Oertner 2007) or designer receptors exclusively activated
by designer drugs (DREADDs) (Coward et al. 1998; Lechner
et al. 2002), offer exquisite approaches for the manipulation of
genetically identified neurons. The greater popularization of
advanced molecular techniques, such as intersectional genetics,
virus-based mapping, and optogenetics, to name just a few, can
lead to significant advances in manipulating and addressing the
respective roles of spinal neuronal populations involved in
processing tactile information. The integration of tactile information is complex and requires multiple circuits distributed
within the spinal cord and supraspinal regions. Recent technological advances, such as two-photon in vivo and in operandi
recordings, combined with post hoc dimensionality reduction,
will be invaluable tools in tackling the complexity of network
activity in the spinal cord.
The greatest challenge in relating the findings from studies of genetically identified spinal neurons in animal models
to our understanding of human function is in determining
whether analogous, genetically defined spinal circuits are
present in the human spinal cord. However, genetic techniques have already been applied in nonhuman primate
models to dissect the spinal circuitry associated with hand
function (Kinoshita et al. 2012). The importance of bridging
the gap between our understanding of how tactile information shapes motor control through spinal circuitry in human
and nonhuman animal models goes beyond understanding
how sensorimotor control is implemented by the nervous
system. In addition to applying genetic techniques for mechanistic studies, genetic identification of spinal neurons offers the potential for targeted control of spinal circuits for
biomedical applications. As pointed out by Steven Hsiao
(Hsiao et al. 2011) in a review detailing the use of sensory
feedback for upper-limb prostheses, electrical and optical
stimulation of the fibers associated with specific sensory
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other species. However, many of the transcription factors
and molecular markers studied are phylogenetically conserved and expressed in spinal neurons (e.g., Isl1 in chicks
and in zebrafish) (Avraham et al. 2010; Uemura et al. 2005),
leading us to believe that there are some universal mechanisms of tactile integration at the spinal level that are shared
among various species, perhaps also including humans.
However, before insights into tactile sensorimotor integration at the spinal level gleaned from studies of animal
models can be confidently related to our understanding of
human function, it is instructive to consider the directions
taken in human studies and how the studies using animal
models can complement or supplement the former.
Human studies are currently limited in terms of their access
to spinal circuitry. However, compared with animal models, a
greater range of sensorimotor tasks can be studied, and there is
much greater access to peripheral sensory neurons that have
frequently been recorded in human studies. The linkage between various tactile afferents and muscle activity in hands and
feet (Fallon et al. 2005; McNulty et al. 1999) has been
demonstrated. Furthermore, recordings of different cutaneous
afferents during specific motor tasks have revealed complex
patterns of activity. In particular, studies of hand grasp suggest
that there is an intricate spatiotemporal pattern of activation of
different types of tactile afferents distributed across the hand
(Dimitriou and Edin 2008; Johansson and Flanagan 2009;
Macefield et al. 1996). The ability to study these spatiotemporal patterns of sensory transmission during specific motor tasks
in human and nonhuman primates is a powerful technique that
remains relatively inaccessible in nonprimate animal models.
These techniques enable the investigation of tactile integration
at the spinal level during motor activity, motor learning, and
motor adaptation. They provide a detailed understanding of the
sensory signals used to inform certain movements, and they
hint at certain central mechanisms (supraspinal and spinal) by
which these signals are processed. However, current technical
limitations prevent a better understanding of the neural mechanisms operating within the human CNS, by which complex
patterns of tactile information shape motor control. To understand these phenomena further requires a dissection of the
different neural circuitry within the periphery, the spinal cord,
and supraspinal regions.
Therein lies the strengths of the animal model. The genetic
identification of spinal neurons has spurred the application of
genetic techniques to expand our understanding of how spinal
circuitry controls movement. Of the many outcomes of this
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pathways will be required for optimal prostheses design.
The potential involvement of tactile information in recovery
of motor function following spinal cord injury is beginning
to come to light (Bouyer and Rossignol 2003; Frigon et al.
2012; Hurteau et al. 2015; Slawinska et al. 2012). Moreover,
as mentioned previously, the process of motor control encompasses a number of sensory modalities that are being
studied, for the most part, in isolation. Better understanding
of the circuitry implicated in the integration of tactile
sensation is paramount to understanding the role of multimodal integration during movement (Kim et al. 2015).
Genetic identification of spinal circuits, along with sensory
neurons (Abraira and Ginty 2013) and supraspinal circuitry,
will therefore be critical in all of these endeavors.
The authors thank Frédéric Bretzner and Andrew Pruszynski for their
invaluable comments on a prior draft of this manuscript. The authors also thank
William Alaynick for permission to adapt a number of his published figures
and Rob Brownstone for helpful comments through this process.
GRANTS
Support for T. V. Bui was provided by a grant from the Natural Sciences
and Engineering Research Council (RGPIN-2015-06403).
DISCLOSURES
No conflicts of interest, financial or otherwise, are declared by the author(s).
AUTHOR CONTRIBUTIONS
Author contributions: T.V.B. analyzed data; T.V.B. and N.S. interpreted
results of experiments; T.V.B., N.S., I.P., and C.F. prepared figures; T.V.B.,
N.S., and C.F. drafted manuscript; T.V.B., N.S., I.P., and C.F. edited and
revised manuscript; T.V.B., N.S., I.P., and C.F. approved final version of
manuscript.
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