SYMPOSIUM
Understanding the Agility of Running Birds: Sensorimotor and
Mechanical Factors in Avian Bipedal Locomotion
Monica A. Daley1
Structure and Motion Lab, Royal Veterinary College, Hawkshead Lane, Hertfordshire, AL9 7TA, UK
From the symposium “Sensory Feedback and Animal Locomotion: Perspectives from Biology and Biorobotics” presented
at the annual meeting of the Society for Integrative and Comparative Biology, January 3–7, 2018 at San Francisco,
California.
1E-mail: mdaley@rvc.ac.uk
Synopsis Birds are a diverse and agile lineage of vertebrates that all use bipedal locomotion for at least part of their life.
Thus birds provide a valuable opportunity to investigate how biomechanics and sensorimotor control are integrated for
agile bipedal locomotion. This review summarizes recent work using terrain perturbations to reveal neuromechanical
control strategies used by ground birds to achieve robust, stable, and agile running. Early experiments in running guinea
fowl aimed to reveal the immediate intrinsic mechanical response to an unexpected drop (“pothole”) in terrain. When
navigating the pothole, guinea fowl experience large changes in leg posture in the perturbed step, which correlates
strongly with leg loading and perturbation recovery. Analysis of simple theoretical models of running has further
confirmed the crucial role of swing-leg trajectory control for regulating foot contact timing and leg loading in uneven
terrain. Coupling between body and leg dynamics results in an inherent trade-off in swing leg retraction rate for fall
avoidance versus injury avoidance. Fast leg retraction minimizes injury risk, but slow leg retraction minimizes fall risk.
Subsequent experiments have investigated how birds optimize their control strategies depending on the type of pertur-
bation (pothole, step, obstacle), visibility of terrain, and with ample practice negotiating terrain features. Birds use several
control strategies consistently across terrain contexts: (1) independent control of leg angular cycling and leg length
actuation, which facilitates dynamic stability through simple control mechanisms, (2) feedforward regulation of leg
cycling rate, which tunes foot-contact timing to maintain consistent leg loading in uneven terrain (minimizing fall
and injury risks), (3) load-dependent muscle actuation, which rapidly adjusts stance push-off and stabilizes body me-
chanical energy, and (4) multi-step recovery strategies that allow body dynamics to transiently vary while tightly reg-
ulating leg loading to minimize risks of fall and injury. In future work, it will be interesting to investigate the learning
and adaptation processes that allow animals to adjust neuromechanical control mechanisms over short and long
timescales.
Birds as an animal model for agile
bipedal locomotion
Birds are diverse and agile vertebrates capable of
many combinations of aerial, terrestrial, and aquatic
locomotion. Living birds vary in size from hum-
mingbirds to ostriches, and exhibit diversity in the
length and mass proportions of the wings and legs,
reflecting adaptation for different locomotor ecolo-
gies (Gatesy and Middleton 1997; Zeffer et al. 2003;
Heers and Dial 2015). While wings and flight are a
defining locomotor innovation of birds, many living
bird species are impressive bipedal terrestrial athletes,
and all birds use bipedal movement for at least some
part of their lives (Abourachid and Ho¨fling 2012;
Heers and Dial 2015). Birds inherited bipedalism
and many hindlimb morphological features from
theropod dinosaurs, an ancient lineage that first
appeared around 230 million years ago (Gatesy and
Middleton 1997). This diversity and bipedal legacy
makes birds a valuable study system for investigating
how morphology, biomechanics, and sensorimotor
control are integrated for agile bipedal locomotion.
Advance Access publication June 12, 2018
 The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/
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Integrative and Comparative Biology
Integrative and Comparative Biology, volume 58, number 5, pp. 884–893
doi:10.1093/icb/icy058
Society for Integrative and Comparative Biology
What are the challenges in achieving
agile bipedal locomotion?
Legged locomotion is complex and dynamic, involv-
ing abrupt foot-contact transitions and uncertainty
due to variable terrain and sensorimotor errors.
Animals must precisely control limb dynamics to
move effectively over varied and uncertain terrain
while avoiding falls, collisions, and injury (Daley
2016). It remains poorly understood how the sen-
sory, neural, and mechanical components of control
are integrated to achieve robust, stable, and agile
locomotion. Here, robustness refers to how large a
disturbance an animal can tolerate while still meeting
the functional demands of the task, such as forward
movement at an acceptable speed (Daley 2016).
Disturbances can arise externally from the environ-
ment, internally from sensorimotor noise (such as
errors in motor commands), or from inaccurate sen-
sory information (such as lack of visibility or conflict
between sensory modalities). Stability quantifies how
rapidly the system attenuates perturbations from
steady-state locomotion, and agility refers to the
ability to rapidly adjust locomotor dynamics to
meet changing task demands (such as a rapid exten-
sion of the leg to leap over an obstacle) (Daley 2016;
Duperret et al. 2016). Locomotion must be robust,
stable, and agile for effective locomotion in natural
conditions.
Avoiding slip, fall, and injury requires precise reg-
ulation of foot-contact timing and leg-substrate in-
teraction forces (Alexander 2002; Clark and Higham
2011; Birn-Jeffery and Daley 2012; Daley 2016). Yet,
inherent uncertainty due to terrain variability, sen-
sorimotor noise, and sensing errors mean that the
system dynamics cannot be perfectly sensed or pre-
dicted. Considering these challenges, the agility and
robust stability of terrestrial animals is truly remark-
able. Bipedal animals face the additional challenge
that they have fewer legs to support the body com-
pared to quadrupeds and other many-legged ani-
mals. Quadrupeds can redistribute loads among the
legs in response to perturbations—a strategy not
available to a rapidly running biped. This likely
makes the challenges for dynamic balance control,
especially acute for bipedal animals.
One inherent challenge of animal systems is sen-
sorimotor delay that limits feedback response times
(More et al. 2010; 2013). Sensorimotor delays in-
clude delays from sensing, nerve transmission, syn-
apses,
muscle
electromechanical
coupling,
and
muscle
force
development
(More
et
al.
2013).
Delays necessitate the use of predictive feedforward
control, because motor commands must be issued in
advance
of
the
required
mechanical
demands.
Reactive feedback control is also crucial to modulate
and update motor commands to correct for devia-
tions between predicted and actual dynamics. Thus,
sensorimotor delay necessitates that animals effec-
tively integrate both predictive (feedforward) and re-
active
(feedback
mediated) sensorimotor
control
mechanisms
for
effective
locomotion
(Rossignol
et al. 2006; Ijspeert 2018).
Nerve transmission delays increase with the ana-
tomical distances of neural pathways. This physical
constraint creates a direct link between neuroanat-
omy and temporal scaling of control processes
(Fig. 1). Considering this, delay has probably been
Fig. 1. Schematic illustration of the hierarchical organization of
vertebrate neuromechanical control. Transmission delays lead to
a temporal scaling of sensorimotor processes that relate to the
anatomical distances between sensors, neural networks and
effectors. Consequently, central, peripheral and mechanical
mechanisms must be integrated over short and long timescales.
The fastest responses occur in the periphery, through intrinsic
mechanics, intermediate responses occur through short-latency
spinal reflexes, and slower responses involve processing and
planning in higher brain centers.
Agility of running birds
885
a selective factor in the evolution of a hierarchical
organization of the nervous system. The fastest
possible reactions occur locally, through intrinsic-
mechanical responses to altered limb-substrate inter-
actions (Brown and Loeb 2000; Daley and Biewener
2006; Daley et al. 2006; 2009). The shortest sensori-
motor loops and fastest neural responses occur
through monosynaptic spinal reflexes, and the lon-
gest delays are associated with processing and pre-
dictive planning in higher brain centers (Fig. 1)
(Rossignol et al. 2006; Grillner et al. 2008; McCrea
and Rybak 2008; McLean and Dougherty 2015;
Kiehn 2016). This suggests the natural emergence
of temporal scaling of sensorimotor control that
relates to neuroanatomical organization. While the
components of vertebrate sensorimotor systems are
increasingly well understood, it remains unclear how
these mechanisms are integrated over varying time-
scales to achieve robust, stable, and agile locomotion
in natural terrain contexts.
The phrase “passive-dynamics” has often been
used to refer to the intrinsic mechanical response
of the locomotor system. However, this phrase can
be somewhat misleading, because the intrinsic me-
chanical response is actively tuned by the selection of
a specific muscle activation pattern from the possible
solutions that could meet the mechanical require-
ments of the task (Brown and Loeb 2000). Each
muscle activation solution will confer a unique set
of characteristics in terms of muscle–tendon dynam-
ics, impedance response, stability, robustness and
sensitivity to perturbations, directional tuning, and
energy cost (Brown and Loeb 2000; Inouye and
Valero-Cuevas 2016; Valero-Cuevas 2016). Thus, in-
trinsic mechanical responses are under some active
control, because feedforward muscle activation pat-
terns can be tuned through learning and experience
to enable robust, stable, and agile performance.
However, the processes and timescales of such tun-
ing between intrinsic mechanics and muscle activa-
tion patterns remain unclear.
Terrain perturbation approaches help
reveal neuromechanical control
strategies
Terrain perturbations are ubiquitous in nature and
disrupt
the
predictability
and
timing
of
foot–
substrate interactions, requiring transient locomotor
responses to recover from disturbances. Understanding
transient locomotor dynamics is important for reveal-
ing natural locomotor behaviors, and for understand-
ing the specific mechanical demands and constraints
that have shaped animal locomotor control.
Birds are particularly useful for such studies of
transient locomotor dynamics, because it is possible
to simultaneously measure in vivo muscle force–
length dynamics, body dynamics, leg–substrate in-
teraction forces, and joint mechanics during loco-
motion (Daley and Biewener 2006; Daley et al.
2007, 2009). This facilitates integrated understand-
ing of neuromechanical function. Considering the
complex nature of neuromechanical control, it is
useful to start by investigating the response to
very simple terrain perturbation features, to mini-
mize the number of confounding factors in the
response.
Initial terrain perturbation experiments in running
guinea fowl aimed to reveal the immediate intrinsic
mechanical response to an unexpected perturbation,
in the time before a sensorimotor feedback response
is possible (Daley and Biewener 2006; Daley et al.
2007, 2009). This work was inspired by earlier
work in rapidly running cockroaches recovering
from an impulsive perturbation (Jindrich and Full
2002) and studies of humans recovering from sud-
den changes in terrain stiffness (Ferris et al. 1999;
Moritz and Farley 2004). In the guinea fowl experi-
ments, birds encountered a simple camouflaged pot-
hole step, 8 cm deep (40% of leg length), covered by
opaque tissue paper stretched across the gap (Daley
et al. 2006). When navigating the unexpected drop,
guinea fowl showed large changes in leg posture in
the perturbed stance, which correlated strongly with
leg loading and perturbation recovery. These findings
highlighted the role of leg angular trajectory control
for regulating foot contact timing and leg loading
(Daley and Biewener 2006), which has also been
found to be important in humans (Seyfarth et al.
2003; Daley and Biewener 2006). The dynamics fol-
lowing a drop in terrain can be explained by the
physics
of
a
spring-loaded-inverted
pendulum
(SLIP) model with very simple swing leg control,
in which the leg follows a sinusoidal, clock-like an-
gular trajectory, retracting backwards toward the
ground
just
before
the
swing-stance
transition
(Fig. 2; Seyfarth et al. 2003; Daley and Biewener
2006; Blum et al. 2014). In this model, contact angle
depends on the duration of the ballistic flight time
(Daley and Biewener 2006; Daley and Usherwood
2010; Blum et al. 2014). Although this is an ex-
tremely simplistic model of running, it is sufficient
to generate robustly stable gait dynamics (Seyfarth
et al. 2003; Blum et al. 2014).
Such model-based analyses of the coupling of
body dynamics and leg angular cycling during run-
ning over terrain perturbations have revealed an in-
herent
trade-off
in
leg
control
between
terrain
886
M. A. Daley
robustness and injury avoidance (Fig. 2; Daley and
Usherwood 2010; Blum et al. 2014). Drops in terrain
result in a delay of ground contact, longer fall time,
and greater downward vertical velocity at contact.
However, the specific dynamics of the response
depends on how fast the leg is retracted during the
falling phase, just before the swing-stance transition
(Daley and Usherwood 2010). Fast leg retraction
results in a large change in leg angle in response to
a given change in terrain height, and earlier ground
contact. This results in smaller fluctuations in verti-
cal velocity and leg loading in response to terrain
perturbations (Daley and Usherwood 2010; Blum
et
al.
2014).
However,
fast
leg
retraction
also
decreases the maximum terrain drop the animal
can safely negotiate, a measure of robustness, and
increases the risk that the leg will miss contact en-
tirely,
leading
to
a
fall
(Fig.
2B;
Daley
and
Usherwood 2010; Blum et al. 2014). In contrast,
slow leg retraction results in small changes in leg
angle for a given terrain drop, ensuring foot contact
even for large terrain perturbations, reducing risk of
fall; however, this leads to larger increases in vertical
velocity and leg loading in the stance following the
drop, increasing risk of overload injury (Fig. 2C).
Subsequent experiments have investigated how leg
control strategies vary depending on the type of per-
turbation (pothole, step, obstacle), and with ample
practice negotiating visible terrain features. In com-
paring locomotor control strategies between hidden
and visible potholes, guinea fowl slow down in an-
ticipation of visible potholes when they encounter
them for the first time, and actually stumble more
when
negotiating
the
visible
drop
(Daley
and
Biewener 2006). Although the high-speed intrinsic-
mechanical response to an unexpected drop is ro-
bustly stable, birds may not always choose this strat-
egy when they first encounter novel, visible terrain
features, perhaps to minimize risk of injury.
Blum and colleagues (2014) explored how animals
manage the trade-off between terrain robustness and
injury avoidance in leg angular control when given
ample practice negotiating a visible drop in terrain.
Under these conditions, guinea fowl converge upon a
strategy similar to the hidden pothole strategy—they
maintain high speeds and allow intrinsic leg mechan-
ics to mediate the perturbation response (Blum et al.
2014).
The
authors
compared
the
experimental
measures to SLIP-model predictions with swing leg
angular control optimized for disturbance rejection
(robustness) versus load regulation (injury avoid-
ance). The guinea fowl used a strategy that allowed
body dynamics to transiently vary, with swing leg
control optimized to maintain consistent leg loading
in uneven terrain, which avoids both fall and injury
conditions. Model analysis revealed that leg control
optimized for disturbance rejection, to maintain
Fig. 2. A trade-off in control of leg retraction rate for terrain
robustness versus injury avoidance, illustrated by two boundary
conditions. (A) Running dynamics modeled as a SLIP with the
swing leg retracted toward the ground just before stance. Leg
retraction rate influences the mechanical response in uneven
terrain: (B) Fast leg retraction results in steeper leg contact
angles and minimizes fluctuations in leg loading, but if leg loading
angle (bTD) reaches 90-degrees, the leg will miss stance, risking a
fall. Maximum terrain drop before a fall decreases with increasing
rate of leg retraction. (C) Slow leg retraction ensures leg contact,
minimizing fall risk, but incurs higher fluctuations in leg loading.
Evidence suggests that birds optimize their leg retraction rate to
minimize fluctuations in leg-loading (Blum et al. 2014), using in-
termediate leg retraction rates that ensure contact while avoiding
overload injury.
Agility of running birds
887
steady body dynamics, demanded dramatic increases
in leg loading, suggesting increased injury risk. This
study also revealed that birds showed very little stride-
to-stride variance in leg angular cycling rate in uneven
terrain. In contrast, leg length actuation rapidly
changed in response to altered leg posture and load-
ing, resulting in rapid adjustment of stance push-off
to stabilize body mechanical energy in the 1–2 steps
following the perturbation (Blum et al. 2014). These
studies have revealed optimization of leg angular cy-
cling rate as an effective control strategy for locomo-
tion in uneven terrain, allowing maintenance of
consistent
leg
loading and high running
speeds
(Seyfarth et al. 2003; Daley and Biewener 2006;
Daley and Usherwood 2010; Blum et al. 2011, 2014).
In another series of experiments, Birn-Jeffery and
colleagues investigated control strategies used by
ground birds when negotiating visible obstacles, to
investigate potential trade-offs in stance leg function
(Birn-Jeffery and Daley 2012; Birn-Jeffery et al.
2014). Similar to the studies on terrain drops, the
birds exhibited independent control of leg angular
cycling and leg length trajectory, with higher stride-
to-stride variance in leg length in uneven terrain
(Fig. 3) When running over a visible obstacle, birds
use a three-step negotiation strategy, with clear evi-
dence of feedforward, predictive adjustments in the
step preceding the obstacle (Fig. 3). Model-based
analyses suggest that the strategy used by birds is
most consistent with models optimized to regulate
leg loading in uneven terrain, not to maintain steady
body dynamics (Birn-Jeffery et al. 2014).
Regulation of leg cycling rate can be viewed as a
combined feedforward plus ‘preflexive’ control strat-
egy that minimizes the need for reactive adjustments
by exploiting the intrinsic mechanical coupling be-
tween
leg
contact
angle
and
leg
loading.
Experimental evidence from both humans and birds
running over a range of terrain perturbations are con-
sistent with leg angular trajectory as a key target of
neural control (Seyfarth et al. 2003; Blum et al. 2011;
Mu¨ller et al. 2016). Humans and birds allow body
dynamics to transiently vary, but exhibit tight cou-
pling between leg contact angle and leg loading across
many different terrain contexts (Grimmer et al. 2008;
Birn-Jeffery and Daley 2012; Birn-Jeffery et al. 2014;
Blum et al. 2014; Mu¨ller et al. 2016). Empirical evi-
dence from birds running over a range of terrain
perturbations, including visible overground obstacles,
treadmill obstacles, visible drops, visible and invisible
potholes, all suggest that leg angular trajectory is: (1)
relatively insensitive to perturbations and (2) adjusted
subtly over longer time-scales. This suggests a context-
dependent feedforward optimization of leg angular
trajectory at higher levels in the control hierarchy to
enable robust and stable locomotion with minimal
control intervention (Birn-Jeffery and Daley 2012;
Birn-Jeffery et al. 2014).
Whereas leg angular trajectory appears insensitive to
perturbations and adjusted over longer timescales, leg-
length actuation shows high stride-to-stride variance,
suggesting both predictive (feedforward) and reactive
(feedback) adjustment in uneven terrain (Fig. 3; Birn-
Jeffery and Daley 2012; Birn-Jeffery et al. 2014; Blum
et al. 2014). Leg length actuation is sensitive to altered
landing conditions, such that stance push-off is rapidly
adjusted to stabilize the total mechanical energy of the
body in uneven terrain. (Daley and Biewener 2006;
Birn-Jeffery and Daley 2012; Birn-Jeffery et al. 2014;
Fig. 3. Leg length and leg angular trajectories of pheasants ne-
gotiating visible obstacles, illustrating a typical three-step strategy.
At top, schematic illustration of the landing and take-off condi-
tions of the bird during the step preceding (Step 1), the step on
the obstacle (Step 0), and the obstacle dismount (Step þ1).
Below, leg trajectory (length and angle) during running on level
terrain (thin black lines, mean and 95% confidence intervals) and
over an obstacle height of 30% leg length (thicker gray lines).
Upward triangles indicate foot take-off at the end of stance. Leg
length exhibits high stride-to-stride variance in uneven terrain,
whereas leg angular trajectory follows a relatively consistent si-
nusoidal trajectory, with only subtle changes in rate in anticipa-
tion of terrain height changes. Data from Birn-Jeffery and Daley
(2012).
888
M. A. Daley
Blum et al. 2014). These findings suggest modular
control of leg angular trajectory and leg-length
actuation.
While modular control of leg angular trajectory and
leg-length actuation have emerged as consistent control
strategies for robustly stable running, it remains less
clear whether, and under what circumstances, leg stiff-
ness serves as a direct target of control. Research on
humans running over soft and hard surfaces suggests
that humans regulate leg stiffness to maintain steady
body trajectory (Ferris et al. 1999). However, the spe-
cific terrain conditions used, soft and hard surfaces, did
not allow a clear distinction between control priority
for steady body trajectory versus consistent leg forces,
because both were maintained. Humans running over
visible downward steps exhibit anticipatory shifts in leg
stiffness before a perturbation, but do not adjust leg
stiffness within perturbed steps (Mu¨ller et al. 2012). In
these
human
studies,
subjects
were
specifically
instructed to maintain constant running speed. In con-
trast, birds negotiating terrain drops exhibit high var-
iance in leg stiffness while allowing speed to transiently
vary (Daley et al. 2007; Blum et al. 2011; Mu¨ller et al.
2016). Whether or not leg stiffness is directly regulated
may depend on the context-dependent constraints on
the locomotor task.
Differences between birds and humans in stiffness
regulation could also relate to leg morphology. Birds
have a more crouched leg posture with four seg-
ments, in contrast to the vertically oriented three-
segment leg configuration of humans. The limb
morphology of birds may allow more flexible adjust-
ment of leg posture to accommodate terrain varia-
tion, minimizing the need for active regulation of leg
stiffness. This idea is supported by evidence from a
study that directly compared control strategies in
humans and birds from a model-based perspective
(Blum et al. 2011). Birds exhibited a wider range of
stable control solutions without adjusting leg stiff-
ness, whereas humans are required to adjust leg stiff-
ness to remain in the stable solution space (Blum
et al. 2011). Additionally, this study showed that
birds exhibited higher robustness to terrain height
variation than humans, consistent with the more
crouched posture enabling postural adjustments to
minimize disturbances.
In vivo muscle recordings reveal
neuromuscular mechanisms underlying
robust, stable, and agile locomotion
While external measures of body and limb mechan-
ics can help reveal task-level locomotor control strat-
egies, these measures do not reveal the underlying
neuromuscular mechanisms. In vivo recordings of
muscle force, length, and activation dynamics during
perturbed locomotion can help reveal the relative
contributions of intrinsic mechanical, feedback, and
feedforward control mechanisms. These studies also
help reveal how neuromechanics of locomotion are
integrated across levels of organization, from indi-
vidual muscle–tendon dynamics to joint, whole
limb, and body dynamics. The relationship between
muscle activation and mechanical output is known
to be nonlinear and dynamically variable, depending
on instantaneous fascicle length, velocity and recent
strain history (Askew and Marsh 1998; Josephson
1999; Edman 2012; Herzog 2014). In vivo measures
of muscle function during steady-state locomotor
behaviors have revealed muscle–tendon mechanisms
for economic bipedal locomotion (Biewener and
Baudinette 1995; Roberts et al. 1997; Daley and
Biewener 2003), but do not reveal the mechanisms
underlying robustness, stability, and agility in non-
steady behaviors.
In vivo recordings of distal hindlimb muscles of
the guinea fowl during negotiation of uneven terrain
has shown that these muscles exhibit rapid changes
in force and work in response to altered foot–
substrate interactions, contributing to the intrinsic
stability of locomotion. During negotiation of unex-
pected potholes, the peak force of the lateral gastroc-
nemius muscle (LG) during stance decreases by 81%
during perturbed steps compared to steady strides,
despite
maintaining
the
same
electromyography
(EMG) activation levels (Fig. 4; Daley et al. 2009).
The muscle shortens rapidly during the initial per-
turbation period, when the foot contacts and breaks
through the false floor (tissue paper) and extends
toward the true ground below (Fig. 4). In the sub-
sequent stance period, peak muscle force is reduced,
but peak ground reaction force is similar, and the
muscle is stretched, resulting in energy absorption
(Daley and Biewener 2006; Daley et al. 2009). This
has a stabilizing effect on the body mechanical en-
ergy, offsetting the increase in kinetic energy gained
through exchange of gravitational potential energy
during the fall (Daley and Biewener 2006; Daley
et al. 2009). A similar but converse response is ob-
served in upward steps and obstacles, in which in-
creased
stretch
and
longer
length
during
force
development during a step onto an obstacle results
in higher force production and work output, increas-
ing mechanical energy of the body (Daley and
Biewener 2011; Fig. 5). These studies revealed that
LG force–length dynamics rapidly adjust the degree
of stance push-off in response to altered foot–sub-
strate interactions. This load-dependent actuation
Agility of running birds
889
response of distal hindlimb muscles provides rapid
stabilization of body mechanical energy in uneven
terrain, and is consistent with observed whole-body
and leg dynamics. Subsequent modelling studies have
also
confirmed
that
load-dependent
actuation
increases robustness and stability of running dynam-
ics (Schmitt and Clark 2009).
Load- and posture-dependent shifts in muscle
force and work occur without shifts in total muscle
EMG activity during unexpected drop perturbations,
revealing that intrinsic mechanisms play an impor-
tant role in the response (Daley et al. 2009).
However, increased EMG activity does contribute to
the response during obstacle steps, likely mediated
through short-latency proprioceptive reflexes (Daley
and Biewener 2011). Interestingly, the qualitative pat-
terns of muscle force–length dynamics remain similar
in both unexpected and anticipated obstacle condi-
tions (Daley et al. 2009; Daley and Biewener 2011).
Nonetheless, while the overall force–length dynamics
of the muscles remain similar across contexts, there is
clear evidence of shifts in the relative contribution of
intrinsic and neurally-mediated mechanisms of con-
trol, depending on the sensory context.
In a more recent study, Gordon and colleagues
(2015) investigated context dependent shifts in sen-
sorimotor control by comparing muscle activation
patterns during obstacle negotiation at low and
high
speeds,
and
with
low
and
high-contrast
obstacles. In slower speed obstacle negotiation, an-
ticipatory increases in muscle activity are apparent in
Fig. 4. LG muscle length, force, and activation during the im-
mediate response to a hidden pothole perturbation. Figure
modified from Daley et al. (2009). At top, the guinea fowl is
pictured at the time of ground contact after breaking through the
false-floor of tissue paper. Below, thin lines indicate the mean and
95% confidence intervals for steady level running, and thick lines
illustrate a perturbed drop step. Force and length are rapidly
altered in response to the perturbation, although muscle activa-
tion (EMG) remains similar to the level terrain condition.
Fig. 5. Load- and posture-dependent actuation of the LG muscle
during negotiation of uneven terrain. When leg posture is altered
at the time of foot contact, altering the balance between muscle
and external forces, muscle length during force development
(Lt50) varies. Lt50 is the largest predictor of the force and total
work output of the muscle (Wnet) ( Daley et al. 2009, Daley and
Biewener 2011 ). This posture-dependent response is similar
between unexpected perturbations and repeating obstacles. This
suggests similar task-level control strategies across context, de-
spite potential for differing contributions of intrinsic mechanical,
feedforward, and feedback control mechanisms to the response.
890
M. A. Daley
the steps preceding obstacles. At higher running
speeds, the neuromuscular response is largely reac-
tive, occurring after foot contact with the obstacle
(Fig. 6; Gordon et al. 2015). Anticipatory increases
in muscle activity are larger when the obstacles are
more easily visible (higher contrast to surrounding
terrain), but mainly in slower speed obstacle negoti-
ation. In the higher speed condition, the response
remains mainly reactive, despite increased obstacle
visibility (Gordon et al. 2015). This likely relates to
the sensorimotor delays involved in visual contribu-
tions to path planning and navigation in higher
brain centers. The results are consistent with a shift
in sensorimotor control mechanisms with speed,
with greater reliance on vision and anticipatory
adjustments at slower speeds, and greater reliance
on intrinsic mechanics and reactive feedback mech-
anisms at high speeds. Thus, the regulation of mus-
cle
dynamics
reflects
a
redundant
system
with
coordinated contributions from intrinsic mechanical,
feedback, and feedforward mechanisms.
Conclusions
While
neuromechanical
control
of
locomotion
involves a complex interplay of mechanical and sen-
sorimotor mechanisms, studies of running birds have
revealed several strategies for robust, stable, and agile
bipedal locomotion that are consistent across terrain
contexts: (1) independent control of leg angular cy-
cling and leg length actuation, which facilitates dy-
namic stability through simple control mechanisms,
(2) feedforward regulation of leg cycling rate to
maintain consistent leg loading in uneven terrain,
(3) load-dependent muscle actuation to stabilize
body mechanical energy in response to disturbances,
and (4) multi-step recovery strategies that allow
body dynamics to transiently vary while tightly reg-
ulating leg loading to minimize risks of fall and in-
jury. Muscle proprioceptive feedback arising from
non-steady force–length dynamics likely plays im-
portant roles in effective tuning of perturbation
responses over time, as well as maintaining accurate
state estimates for internal models, path planning,
and navigation in higher brain centers. However, it
remains unclear how sensory feedback is integrated
with spinal neural circuits and higher brain centers
to adjust locomotor control over short and long
time-scales. In future work, it will be interesting to
investigate the learning and adaptation of neurome-
chanical control mechanisms through repeated expo-
sure to perturbations in controlled conditions.
Acknowledgments
Thanks to the past students, postdoctoral researchers
and collaborators who have contributed to the work
reviewed here, including Aleksandra Birn-Jeffery,
Yvonne Blum, Christian Hubicki, Hamid Vejdani,
Joanne
Gordon,
Jonathan
Hurst
and
Andrew
Biewener.
Funding
The work reviewed here was supported by grants
from the Biotechnology and Biological Sciences
Research Council of the UK (BB/H005838/1) and
the Human Frontier Science Program (RGY0062/
2010). Support for participation in this symposium
was provided by Photron (https://photron.com), the
Company of Biologists, the Society for Comparative
and Integrative Biology (Divisions of Comparative
Biomechanics,
Vertebrate
Morphology,
Animal
Behavior, and NNSB), the Air Force Office of
Fig. 6. Context dependent-shifts in the contribution of predictive
and reactive modulation of LG activity during obstacle negotia-
tion. Guinea fowl running over obstacles on a treadmill en-
countered a single footfall on an obstacle (black box)
approximately once in 5–7 steps. Step ID corresponds to the
sequence of steps with the obstacle encounter at step zero. LG
exhibits predictive increases in muscle activity at slower walking
speeds (0.7 m/s). Predictive shifts are larger when the obstacles
are more visible (higher contrast) relative to the level terrain. At
higher speeds (1.3 m/s) guinea fowl use a reactive strategy, with
increases in LG activity occurring after foot contact with the
obstacle. The influence of high versus low contrast terrain is
greater at slower speeds, when the bird has a longer time to
process visual information to modulate muscle activity.
Agility of running birds
891
Scientific
Research
(FA9550-16-1-0165),
and
the
National Science Foundation (IOS-1747859).
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Agility of running birds
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Understanding the Agility of Running Birds: Sensorimotor and Mechanical Factors in Avian Bipedal Locomotion.
Daley, Monica A