Volume 16, Number 22,
Issue of November 15, 1996
pp. 7297-7307
Copyright ©1996 Society for Neuroscience
Organization of Octopus Arm Movements: A Model System for
Studying the Control of Flexible Arms
Yoram Gutfreund1,
Tamar Flash2,
Yosef Yarom1,
Graziano Fiorito3,
Idan Segev1, and
Binyamin Hochner1
1 Department of Neurobiology and Center for Neuronal
Computation, Institute of Life Sciences, Hebrew University, Jerusalem
91904, Israel, 2 Department of Applied Mathematics, The
Weizmann Institute of Science, Rehovot 76100, Israel, and
3 Laboratorio di Neurobiologia, Stazione Zoologica ``A.
Dohrn'' di Napoli, Napoli 80121, Italy
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
FOOTNOTES
REFERENCES
ABSTRACT
Octopus arm movements provide an extreme example of controlled
movements of a flexible arm with virtually unlimited degrees of
freedom. This study aims to identify general principles in the
organization of these movements. Video records of the movements of
Octopus vulgaris performing the task of reaching toward
a target were studied. The octopus extends its arm toward the target by
a wave-like propagation of a bend that travels from the base of the arm
toward the tip. Similar bend propagation is seen in other octopus arm
movements, such as locomotion and searching. The kinematics (position
and velocity) of the midpoint of the bend in three-dimensional space
were extracted using the direct linear transformation algorithm. This
showed that the bend tends to move within a single linear plane in a
simple, slightly curved path connecting the center of the animal's
body with the target location. Approximately 70% of the reaching
movements demonstrated a stereotyped tangential velocity profile. An
invariant profile was observed when movements were normalized for
velocity and distance. Two arms, extended together in the same
behavioral context, demonstrated identical velocity profiles. The
stereotyped features of the movements were also observed in spontaneous
arm extensions (not toward an external target). The simple and
stereotypic appearance of the bend trajectory suggests that the
position of the bend in space and time is the controlled variable. We
propose that this strategy reduces the immense redundancy of the
octopus arm movements and hence simplifies motor control.
Key words:
movement control;
muscular-hydrostat;
kinematics;
octopus;
cephalopods;
motor program;
flexible arm;
arm extension;
reaching movements
INTRODUCTION
The control and coordination of arm movements in
three-dimensional (3D) space is a complicated task, a challenge to both
biological and artificial systems. Increasing the number of degrees of
freedom of the arm makes this task more complicated (Hollerbach,
1990a
), and yet most biological movements involve a large number of
degrees of freedom (in a rigid arm this number is directly related to
the number and type of joints). An extreme case with especially high
degrees of freedom is given by systems in which muscles are unattached
to any internal or external skeleton whatsoever. Consequently, these
structures are much more flexible than jointed limbs and have virtually
unlimited degrees of freedom. Examples of such structures are
cephalopod tentacles, some of the vertebrate tongues, and the elephant
trunk. These structures are composed solely of muscles used to generate
movement and provide the necessary skeletal support (Kier, 1982
; Smith
and Kier, 1989
; Chiel et al., 1992
). Kier and Smith (1985)
have termed
these structures muscular-hydrostats because they are composed of
incompressible muscle tissue. They suggested that the production of
movement and force in muscular-hydrostats is dictated by the constraint
that the volume remains constant.
The octopus arm is of special interest as a muscular-hydrostat, because
it combines extreme flexibility (an octopus arm can bend at any point
and in any direction, and it can elongate, shorten, and twist) with a
capability for executing various sophisticated motor tasks, such as
building a shelter, manipulating small objects (Wells and Wells, 1957
),
and opening a jar (Fiorito et al., 1990
). These combined capabilities
of flexibility and precision are of interest to both physiologists and
robotics engineers. As a first step toward understanding the principles
of the motor control of the octopus arm, we have studied the kinematics
of arm extension, which as we demonstrated is a stereotyped, simple,
and reproducible movement.
One strategy for gaining insights into the principles of planning and
control of a motor system is to look for kinematic invariance in
movement trajectories (Atkeson and Hollerbach, 1985
). This strategy,
successfully applied to the study of multijoint human arm movements
(Morasso, 1981
; Flash and Hogan, 1985
) and speech movements (Smith et
al., 1995
), has been used here to study octopus arm trajectories. The
aim of our study is to identify common kinematic features, or
stereotyped patterns, which characterize arm movements. We report here
on such features in arm extension, which we show is executed by a
forward propagation of a bend along the arm. This bend propagation is a
basic movement pattern that is used in different behaviors, such as
locomotion, searching, and reaching. The bend travels along a simple
planar path connecting the body of the animal with the location of an
external target. The velocity of this bend usually follows a
stereotyped profile, which is appropriately scaled for different speeds
and distances. The simple and stereotyped nature of the reaching
movement can reduce the complexity of the control of the flexible arms
of the octopus.
MATERIALS AND METHODS
Experimental animals. Specimens of Octopus
vulgaris were either caught on the Mediterranean shore by local
fishermen or supplied by the Stazione Zoologica in Naples, Italy. The
animals were maintained in 50 × 50 × 40 cm glass tanks
containing artificial seawater. The water was circulated continuously
in a closed system and filtered through coral dust and active charcoal.
Water temperature was held at 16°C in a 12 hr light/dark cycle. For
this study we used three animals weighing 300, 470, and 700 gm. Before
video recording, the animals were placed in a bigger glass tank
(80 × 80 × 60 cm) with a water temperature of 18°C. Video
recording began only after the animals were well acclimatized to the
new tank (after a few days).
Behavioral task and video recording. The trial started when
a target, a green plastic disk of 2 cm diameter (see Fig.
1A, circle), was lowered into the water.
The target was moved slightly to draw the attention of the octopus to
it. The octopus either extended one or more arms or swam toward the
target. Every few trials, the animal was rewarded with a piece of crab
meat tied to the target.
Fig. 1.
An example of two stereotyped motor patterns: bend
propagation (A) and bend initiation (B).
Four video frames taken during the course of the movement are presented
for each example (1-4). Time in milliseconds is
given in the top right corner of each frame. The target,
a green plastic disk (marked by a circle in
A1 and B1), is in the bottom left
corner. The arrowhead in
A1 shows the sucking rings. Notice the bend in the arm
(arrow in A), which propagates
toward the tip. In an already extended arm (B1), a bend
is initiated at a certain point along the arm
(arrow in B2), and the part distal
to this point is pulled backward (B3-4).
[View Larger Version of this Image (126K GIF file)]
Two video cameras were used to record the arm movements. The cameras
viewed the subject from the same aquarium face with an angle of
~90° between them. Shutter speed of both cameras was set to 1/250.
The PAL superVHS video system was used, allowing a temporal resolution
of 20 msec between adjacent images. The video images from both cameras
were combined into one image through a video mixer.
Those trials in which the octopus extended its arm toward the target
were termed ``successful trials,'' regardless of whether the arm hit
or missed the target. Successive video images of successful trials were
digitized and displayed on a Silicon Graphics work station. Points of
interest were marked manually with the mouse cursor on each image. The
coordinates of the points from both cameras were saved.
Transformation between camera coordinates and external
XYZ coordinates. The positions of designated points in
3D space were obtained by applying the direct linear transformation
(DLT) method, a method commonly used for obtaining 3D coordinates from
two cameras. Briefly, each camera is characterized by 11 parameters.
The relation between these parameters and the external XYZ
coordinates is defined by the DLT equations as follows:
where x1and y1are the image coordinates of a designated point in the image of camera
1. X, Y, and Zare the unknown 3D
coordinates of that point, and
P1-P11are 11 camera
parameters that are related to the camera position, orientation, and
optical properties (Wood and Marshall, 1986
; Woltring and Huiskes,
1990
). In the beginning of each experiment, we recorded images of a
40 × 20 × 20 cm calibration cube made of aluminum rods.
Fourteen light-emitting diodes were placed on the corners and midpoints
of the cube and served as control landmarks. This structure was then
removed, and the octopus movements were recorded approximately within
the volume defined by the calibration cube and using the same camera
setup. The image coordinates of at least six of the control landmarks
were later used to calculate the 11 (P1-P11) camera
parameters. Cognizance of these parameters for both cameras enables one
to solve the DLT equations and obtain the 3D coordinates of any point
recorded by both cameras. The above transformation was repeated for
sequential video images (with a 20 msec interval), resulting in a
description of the position of the designated points in both space and
time. Note that the coordinates used to represent the movements are
defined by a laboratory fixed-coordinate system, which is attached to
the calibration cube and not to the animal or the aquarium.
Although the DLT transformation assumes ideal cameras, video cameras
are expected to have some image distortions. It has been shown
empirically that as long as the object location is limited to within
the calibration volume, sufficient accuracy is achieved (Wood and
Marshall, 1986
). The accuracy of our set-up has been assessed
empirically in both space and time. Spatial errors were estimated in
each experiment. This was accomplished either by comparing the
calculated positions of six known landmarks to their actual positions,
or in other cases, by reconstructing the length of six rods, 20 cm
long, placed within the same workspace. Data were collected only from
trials in which the maximal spatial error or the difference between the
measured and the actual length was <1 cm. Velocity errors were
estimated by measuring the velocities of points moving at known speeds
(see ``Tangential velocity'').
Determination of the plane of motion. A multiple linear
regression method was used to determine the plane of motion. We
calculated the coefficients a0,
a1, and a2 that give the
best fit, in a least-square approximation, of the motion trajectory to
a linear plane equation:
where the Y values are the coordinates of the data
points along one of the axes for the dependent variable, and
X1 and X2 values are the
corresponding coordinates of the independent variables. For each
movement we repeated the multiple regression analysis three times, each
time using a different axis as a dependent variable
(Y). The plane of motion was determined by the
coefficients a0, a1, and
a2, which gave the least-square error. The
coefficient of determination R2 was used to
describe the fit of the data to a plane. An F-test was used to examine
the statistical significance of R2.
Finally, to present the data in a clear manner, the data coordinates
were transformed to another coordinate system in which the origin is
located at the first data point and one of the axes is perpendicular to
the plane of motion.
Tangential velocity. The tangential velocity of a point,
that is, its velocity in the direction of movement, was calculated from
the position data. We first smoothed the data by fitting a fifth order
polynomial to the projection of the points on the X,
Y, and Z axes as a function of time [one
polynomial for X(t), one for
Y(t), and one for Z(t)].
The six coefficients of these three polynomials were obtained by
calculating the least-square equation, using the singular value
decomposition algorithm (Press et al., 1992
). Then, the tangential
velocity Vtan was calculated from the
derivatives of the smoothed X(t),
Y(t), and Z(t) coordinates
according to:
The accuracy of the tangential velocity calculations was
estimated by measuring the velocity of a point moving at a known speed
(an oscilloscope beam). It was found that within the speed range of
5-50 cm/sec (the range of velocities measured in the experiment), the
error increased slightly with velocity. The root mean square (RMS) of
the error measured at a speed of 50 cm/sec was ± 4%, with a
maximal error of 9%.
RESULTS
Arm extension in the octopus is a fundamental component in various
behaviors, such as locomotion, searching, and reaching toward a target.
In all cases, the arm is extended in what seems to be a stereotyped and
robust pattern. An example of an arm extended toward a target is shown
in Figure 1A (the target is marked by
a circle). The four images, taken during the course of the
movement, show that the arm is extended by using a wave-like
propagation of a bend in the arm (arrow), which travels from
the base of the arm toward its tip. The bend is always curved dorsally
so that the sucking rings, located on the ventral side of the arm
(arrowhead in Fig. 1A, frame
1), point in the direction of movement. In cases where the arm is
already extended, as in Figure 1B, the movement is
initiated by first creating a bend, which is formed by twisting the arm
(arrow in Fig. 1B, frame 2),
and then pulling the distal part backward. After this maneuver, the
bend travels toward the tip of the arm in the desired direction, as
demonstrated in Figure 1A.
We outline the extension of the arm by registering the movement
of two designated points: (1) one of the eyes (marked in Fig.
1A) and (2) the midpoint of the bend, which we termed
``bend-point'' (marked in Fig. 1A). Figure
2A depicts the path of these two
points during a reaching task, at 20 msec intervals. The octopus
reached toward the target (marked by X) by moving the
bend from the vicinity of its body outward. At the same time the
octopus moved toward the target. This body movement is represented on
the graph by the changes in eye location, which because the head of the
octopus is rigid give a good estimation of the movement of the body
center. To characterize the kinematic features of arm extension
independent of body movements, we have analyzed the movement of the
bend-point relative to the body. The relative movement was obtained by
vectorially subtracting the measured movement of the eye from the
bend-point movement. An example of the subtraction is depicted in
Figure 2B. This procedure was repeated in all trials.
Fig. 2.
Movement of the bend-point (the midpoint of the
bend in the arm) in 3D space. The DLT algorithm (see Materials and
Methods) for analyzing stereo video recordings was used to obtain a
description of the movements in space and time. A, 3D
graph showing eye (rectangle) and bend-point
(circles) position during a reaching task. Target
location is marked by an X. Each point on the graph
represents the position in a single video field (20 msec interval
between images). The arrow marks the direction of
movement. B, The movement of the bend-point relative to
the eye. The direction of movement is marked by the
arrow.
[View Larger Version of this Image (28K GIF file)]
Bend-point path
Analysis of the bend-point path in 84 reaching movements shows
that the bend-point tends to move within a single plane in a simple,
slightly curved path. The plane of motion and the degree of planarity
were determined by multiple linear regression (see Materials and
Methods). Table 1 summarizes the average distance
traveled by the bend-point in the plane of motion, the average SE of
the fit (residual error), and the average R2. In
all trials (except one in octopus C), R2 was
significantly positive (p < 0.01; F-test). The
average SE is small compared with the average movement in the plane of
motion. This, as well as the high average R2
values, indicates that to a good approximation the bend-point moves
within a single plane. In general, this plane corresponds to the
sagittal plane of the arm, which is defined by the ventral location of
the sucking rings.
Table 1.
Summary for three octopuses showing the average SE of the
fit of the bend-point path to the plane of motion, the average distance
traveled by the bend-point in the plane of motion, and the average
R2
|
Octopus A |
Octopus B |
Octopus
C |
|
| SE |
0.60
± 0.25 cm |
0.42 ± 0.16 cm |
0.49
± 0.19 cm |
| Distance |
33.44 ± 12.3 cm |
25.80
± 8.9 cm |
29.74 ± 8.1 cm |
| R2 |
0.88
± 0.10 |
0.89 ± 0.14 |
0.75 ± 0.24 |
| Number of
trials |
33 |
29 |
22 |
|
|
Values are averaged over all trials with ±SD.
|
|
The planarity of the movement enables us to reduce the space of
interest to two dimensions without losing significant information.
Figure 3A shows the data from Figure 2 in a
transformed coordinate system where the XZ plane is parallel
to the best fitted plane. As expected from a planar movement, the data
points in the two-dimensional view of the transformed YZ
plane are organized along a straight line (Fig. 3B).
Fig. 3.
Bend-point path is planar. A, 3D
graph showing the data from Figure 2B in a
transformed coordinate system where the XZ plane is
parallel to the plane of best fit. B, 2D view of the
YZ plane, demonstrating the planar organization of the
movement. In the example shown, the SE of the fit is 0.61 cm.
[View Larger Version of this Image (27K GIF file)]
The characteristic features of the bend-point path within the best
fitted plane are shown in Figure 4A-C
for the three animals tested. Four different reaching movements are
shown for each animal. The dots mark the data, and the lines mark the
fitted fifth-order polynomials. The direction of movement is indicated
by the arrows. In all animals the path is either slightly curved or,
less frequently, nearly a straight line. These results indicate that
the bend-point moves in a relatively simple path in respect to the
animal's body.
Fig. 4.
Examples of the bend-point path measured in
different trials and from different octopuses. The path of four
different reaching movements is depicted for each animal
(A-C) on the plane of movement (the
best-fit linear plane). The dots show the measured
positions, and the lines are the fitted fifth-order polynomials (see
Materials and Methods). The direction of movement is indicated by the
arrows. The initial point of the movements was displaced
on the graph to improve clarity of display.
[View Larger Version of this Image (17K GIF file)]
Bend-point velocity
The tangential velocity of the bend-point as a function of time
(velocity profile) during a reaching task was calculated from 84 trials
(see Materials and Methods). It should be noted that a bend is a
dynamic structure that can evolve or disappear during the movement of
the arm, and so the velocity may start and end at values other than
zero, as can be seen in Figure 5A. This
contrasts with measurements of the velocity of fixed points in moving
structures, like the tip of the arm (Hollerbach and Flash, 1982
).
Fig. 5.
Tangential velocity profiles are invariant.
A, Bend-point tangential velocity, calculated from the
smoothed kinematic data during three trials, is plotted against time.
The profiles share a similar pattern, which can be divided into three
phases (marked by the arrows). This division corresponds
to different stages of the movement (see Results). B,
The velocity profiles shown in A, normalized for
velocity and distance and aligned at the peak, demonstrate a
substantial overlap during phase II.
[View Larger Version of this Image (17K GIF file)]
Figure 5A shows three velocity profiles measured from the
same octopus. Although the range of velocities of these movements
varies, they all demonstrate a characteristic velocity profile. This
profile can be divided into three phases (Fig. 5A,
arrows in curve c). Phase I is the initial part
of the movement. This phase ends at the minimum (marked by the
left arrow) and is characterized by a monotonic decrease in
velocity (profiles a and c) or by an initial
increase in velocity followed by a local peak (profile b).
Phase II, which starts at the local minimum and ends at the peak
velocity (right arrow), is characterized by a monotonic
increase in velocity. Phase III is the final phase of the movement
where the velocity decreases until the bend-point disappears.
Phase I corresponds to the transition between the initiation and
propagation of the bend (Fig. 1B). This stage of the
movement is variable; it depends on the initial position of the arm and
on the direction of arm extension. Phase II corresponds to the
propagation of the bend-point along the arm. This stage, which is the
most prominent and robust, is shown in Figure 1A. The
main part of the arm extension occurs during this stage. Typically, the
velocity reaches a maximum in the vicinity of the target. After this
maximum, the bend moves toward the tip with what seems to be a passive
wave propagation. This stage corresponds to the decrease in velocity in
phase III. In many cases, the bend disappears before reaching the tip
of the arm. This basic velocity pattern was observed in 65 of the 84 tangential velocity profiles. The remaining 19 cases, which were
distributed among the three animals, did not match this basic pattern
and demonstrated various velocity profiles.
Invariance of tangential velocity is commonly tested by normalizing the
movement speed with respect to amplitude and duration (Atkeson and
Hollerbach, 1985
). A major problem in using this method in the study of
the movement of the bend in the octopus arm is the uncertainty in
determining the beginning and end of the movement. This uncertainty
arises from (1) the nature of this movement, which as mentioned above
can begin and end with various velocities, and (2) the fact that we are
studying movements of naturally behaving animals. The latter, in
contrast to studies of a controlled movement in humans or in well
trained animals, imposes various initial and terminal conditions. To
overcome this problem, we took advantage of the fact that the
tangential velocity profiles of the octopus arm extensions almost
always followed a profile with a well defined minimum and maximum
(marked by the arrows in Fig. 5A). We therefore
normalized the velocity [V(t)] and the time
(t) according to the maximum velocity
(Vmax) and the distance (D) traveled
by the bend-point between these minima and maxima as follows:
Dwas calculated using:
where Xand Zare the coordinates of the
smoothed data in the best fitted plane, and the index
tdesignates the image num- ber (time ).
In Figure 5B, the three profiles from Figure 5A
have been normalized and superimposed by aligning the peaks. These
normalized curves demonstrate a clear overlap in phase II, suggesting
that some common constraint dictates the pattern of velocity increase
during this phase. To examine the generality of this observation, all
velocity profiles with the characteristic pattern as shown in Figure
5A were superimposed in Figure
6A-C. In addition, an average
velocity profile and its variance were calculated for each animal (Fig.
6D). The superimposition of the normalized velocities
(Fig. 6A-C) shows that the result of Figure
5B, in which phase II is invariant and phases I and III are
variable, holds for the majority of arm extensions. The similarity of
the velocity profiles during phase II is demonstrated further by the
variance shown in Figure 6D: the variance during
phase II is very low, relative to the variance during phases I and III.
Velocity profiles are similar, not only in individual animals but also
among different animals, as shown by the remarkable overlap of the
average normalized velocity profiles from different animals (Fig.
6D).
Fig. 6.
Comparison between normalized tangential velocity
profiles from different animals. Sixty-five normalized velocity
profiles aligned at the peak are displayed in three graphs
(A-C) corresponding to three animals. An
average velocity profile and its variance were extracted for each
animal and superimposed in D. A remarkable similarity of
the average normalized velocity profiles from the different animals is
observed (D, top graph).
[View Larger Version of this Image (44K GIF file)]
Two-arm coordination
The issue of coordination between different arms is especially
interesting in the case of the octopus, because of its need to control
eight flexible arms. An insight into the mechanism of arm coordination
can be obtained from those trials in which the octopus extends two or
more arms. Figure 7, A and B,
shows two examples where the octopus extends two arms toward the target
(located in the bottom left corner of the picture) by
propagating a bend in each of the arms (marked by arrows).
The arms can either move together, as shown in Figure 7A, or
move one after the other, as shown in 7B. We have analyzed
the velocity of the bend-point propagation for the cases of synchronous
and consecutive movements. Figure 7C shows the bend-point
positions of two arms moving simultaneously; the tangential velocities
are depicted in 7D. Note that the curves in Figure
7D are not normalized. It is clear that the velocity of both
arms follows a similar pattern. Such velocity coupling was also
observed in arms moving consecutively with a short delay between them.
An example is shown in Figure 7, E and F.
In this trial, the octopus first extended one arm toward the target,
and 1.3 sec later a second arm was extended (bend-point positions are
shown in E). Clearly, in this case the two arms also moved
with almost identical velocity profiles but with a constant phase lag
of ~1.3 sec between them (F).
Fig. 7.
Two arms moving toward a target simultaneously, or
one after the other with a short delay, tend to move at the same speed.
A, B, Video frames showing an octopus extending two arms
toward the target, which is in the left side of the
frame. A, Two arms moving simultaneously.
B, Two arms moving one after the other. C,
D, Bend-point trajectories of two arms moving simultaneously
were measured. The positions of the bend-points and eye are shown in
C. The tangential velocity profiles (D)
follow a similar pattern. E, F, Bend-point trajectories
from two arms moving one after the other with a short delay. The path
of the two arms is shown in E, and the tangential
velocities plotted against time are shown in F.
[View Larger Version of this Image (45K GIF file)]
To quantify the similarities between the velocity profiles of two
moving bend-points, we first aligned the profiles at the beginning of
the movement and then calculated the RMS of the velocity differences
according to:
where V1 and V2 are
the velocities of the two bend-points, t is the image number
(20 msec interval), and n is the number of images where the
velocity was measured and compared. This procedure was repeated for
three groups of movements: (1) synchronous movements, where the two
arms moved toward the same target at the same time; (2) consecutive
movements, where the arms moved to the same target (same trial) but
with a short delay between them (0.4-1.3 sec); and (3) control group
movements. For this group we arbitrarily chose movements from two
different trials performed by the same octopus. The average RMS of
these three groups is shown in Table 2.
Table 2.
The average root mean square (RMS) of the differences
between pairs of velocity profiles measured from synchronous movements,
consecutive movements, and different trials (control
group)
|
Average RMS ± SD
(cm/sec) |
Number of pairs |
|
| Synchronous
group |
6.26
± 1.7 |
10 |
| Consecutive group |
6.84 ± 2.5 |
7 |
| Control
group |
13.46 ± 5.1 |
10 |
|
|
The average RMS is given here as a quantitative estimation for
the similarity between pairs of tangential velocity profiles.
|
|
The similarity between the velocity profiles in the synchronous group,
as well as for the consecutive group, is significantly larger than for
the control group (p < 0.01; Mann-Whitney rank
test). We conclude that when two arms are moving toward the same
target, they tend to move with the same velocity profile. This result
suggests a common source for the generation of movements that are
produced within the same behavioral event.
Bend propagation in spontaneous movements
As mentioned above, the generation and propagation of a bend
occurs during various behaviors. This raises the question of whether
the same stereotyped characteristics of bend-point path and velocity as
seen in the reaching task are also to be found during other behaviors.
To answer this question, we compared the trajectories generated in
spontaneous movements (those not directed toward a target) with those
measured during reaching movements.
Bend propagation in spontaneous movements occurs either when the arm is
moving freely in the water (unconstrained movements) or when the arm is
extended along a solid surface such as the aquarium side (constrained
movements). In the latter case, the bend travels on the surface while
the sucking rings proximal to the bend grip this surface. We examined
bend-point trajectories from both of these modes of movement
(unconstrained and constrained).
The spontaneous movements were analyzed using the same analytical
procedure as for the reaching movements. First, the planarity of the
movement was tested by calculating the best fit linear plane containing
the movement. This part of the analysis was applied only to
unconstrained movements, because the constrained movements are limited
a priori to a surface. We found that the paths of the bend-points in
the unconstrained movements were confined to a single plane (average
R2 of 0.81 ± 0.19; n = 11, all statistically significant). This was similar to the results
obtained in the reaching movements (Table 1).
In 10 of the 11 unconstrained movements measured, the tangential
velocity profiles had a characteristic pattern similar to that shown in
reaching behavior (compare Fig. 8A
with Figs. 5 and 6). In Figure 8C, the four tangential
velocity profiles from Figure 8A (solid
lines) have been normalized and superimposed together with three
normalized velocity profiles measured during a reaching task
(dashed lines). The significant overlap of all the curves
demonstrates that the invariant nature of the velocity profiles shown
in reaching movements is found in spontaneous unconstrained movements
as well.
Fig. 8.
Tangential velocity profiles measured from
spontaneous arm extensions. A, Four tangential velocity
profiles measured during spontaneous unconstrained movements (i.e.,
movements freely in the water and not directed toward a target).
B, Four tangential velocity profiles measured during
constrained spontaneous movements (touching the surface of the aquarium
walls or floor). C, The normalized velocity profiles of
the unconstrained movements shown in A (solid
lines) are superimposed on three normalized velocity profiles
obtained from movements during a reaching toward a target
(dashed lines).
[View Larger Version of this Image (18K GIF file)]
In contrast, six of eight constrained movements did not resemble this
basic pattern. Four examples are shown in Figure 8B.
Their velocity profiles showed either constant velocity (two
lower traces) or slight changes in speed. The constrained
movements had generally lower velocities.
DISCUSSION
This study is the first detailed and quantitative kinematic
analysis of octopus arm movements. It shows that despite the fact that
an octopus arm has virtually infinite degrees of freedom, arm movements
are executed in a stereotyped manner. Our study has focused on
extension movements that are generated by a bend propagating along the
arm. This bend propagation is a basic movement pattern that is used in
different behaviors, such as locomotion, searching, and reaching.
In flexible structures, a propagating bend can be generated by either a
passive whip-like action or an active mechanism involving muscle
contraction along the arm. We have shown previously that bend
propagation in the octopus arm is associated with a propagating wave of
muscle activity (Hochner et al., 1995
), indicating an active mechanism.
According to the constant volume constraint for muscular-hydrostats,
contraction of the longitudinal muscles on one side of the arm and
simultaneous activation of the transverse muscles, to resist increase
in arm diameter, should result in the formation of a bend (Kier and
Smith, 1985
). Hence, a propagating bend would be generated by a wave of
coordinated local contractions. It is also possible that after the
initiation of a bend, its propagation is a result of a stiffening wave
that propels the bend toward the tip of the arm. This issue is
currently under investigation.
The present kinematic study demonstrates that in the octopus arm, the
bend tends to propagate along a stereotyped trajectory. In particular,
the bend propagates along a relatively simple curved path, which is
contained in a linear plane. Although the path itself is not
necessarily invariant, the normalized velocity profile has the same
kinematic form regardless of movement direction, speed, or amplitude.
This observation resembles results obtained from human and primate arm
movement studies (Morasso, 1981
; Abend et al., 1982
; Hollerbach and
Flash, 1982
; Atkeson and Hollerbach, 1985
).
Is there a general movement-generation principle that is common to both
cases? Octopus arms are essentially different from human-like arms in
both anatomy and control mechanisms. The aim of the control system in
human-like arms is to bring the tip of the arm to the target, whereas
in octopus any part of the arm can be used to grab the target. There
is, therefore, no special significance to the tip point or any other
fixed point along the arm; however, the bend is instrumental in leading
the arm in the desired direction. In this sense, like the human hand,
controlling the bend-point trajectory is a reasonable strategy. We have
shown that the bend-point follows a simple planar path from the body
center toward the target. The simplicity and stereotyped appearance of
this path suggests that bend-point position is an important variable
for the planning and control of octopus arm movements. Another
possibility, however, is that the simple and stereotyped appearance is
a by-product of some unknown constraint in the system. In this case the
bend-point per se would not be controlled directly by the nervous
system.
Researchers of motor control of articulated arms have pointed out the
trade-off between planning movement in external coordinates and the
computational difficulties of executing the planned movement
(Hollerbach, 1990b
; Flanders et al., 1992
; Haggard et al., 1995
).
Planning in terms of the external coordinates of the tip of the arm
allows the external constraints to be dealt with more easily. Executing
a movement planned in this way, however, raises computational
difficulties because of the complex transformations between end-point
coordinates, joint coordinates, and muscle activity (Bizzi, 1993
;
Gielen, 1993
). The complexity of such transformations, which are termed
the ``inverse problems,'' arises mainly from the excess degrees of
freedom of the limb compared with the degrees of freedom of the end
effector or the task (Bizzi et al., 1991
).
What is the analogy for the inverse problem in octopus arm movements?
If bend-point location in time and space is an important controlled
variable, the inverse problem in the octopus is the transformation from
bend-point coordinates to muscle activity. This transformation,
however, need not be that complicated. Assuming that only one bend is
traveling along the arm, and indeed this is the case in the reaching
task, the number of degrees of freedom of the arm can be reduced
dramatically: one for the movement of the bend along the axis of the
arm and two for the yaw and pitch movements of the arm around its base
(roll movements are not observed during reaching). Such a system
reduces computational complexity tremendously. Moreover, because bend
propagation is generated by a propagating wave of muscle contraction
(Hochner et al., 1995
), the position of the bend along the arm and
muscle activity share the same coordinates, allowing relatively simple
transformations between the planned bend-point movement and the
required muscle activation. Therefore, assuming that inverse
computation takes place in this system, it is plausible that this basic
motion pattern has evolved not only as a result of biomechanical
constraints or motor objectives (such as energy minimization or
maximizing motion smoothness) but also as a result of the need to
minimize computational complexity.
We have found that different reaching movements vary in speed and
distance but maintain a basic velocity pattern repeated in both
target-oriented and spontaneous movements. Furthermore, the same
pattern is observed in different octopuses. The particular shape of the
velocity profile (tangential velocity of the bend as a function of
time) may reflect an optimal neuronal control strategy or might be
attributable to some mechanical factors. We found further that the
mid-part of the movements (i.e., phase II in Fig. 5) can be attributed
to the same basic profile scaled for speed and distance. One
explanation for the scaling properties is that bend propagation is
generated by a built-in motor program that can be adjusted by simple
scaling of the same pattern to produce different speeds. The output of
such a system is a basic invariant trajectory that reflects the
dynamics of the underlying neural activation pattern (Gracco, 1988
;
Smith et al., 1995
). Because bend propagation is a common movement
frequently repeated in the course of different motor behaviors, it is
plausible that a stored neuronal pattern coordinates muscle contraction
to generate a propagating bend along the arm. We propose that this
pattern can be simply modified to produce different velocities. Support
for this idea is provided by the results of the tangential velocity
profiles of two arms moving together. Two arms moving synchronously, or
at a short time lag, generate similar velocity profiles with the same
peak velocity. This result suggests that the movement is generated by a
similar motor command at the neuronal level and that this command is
stored, at least for short times, in the control system. Furthermore,
the fact that the same bend-point trajectories are measured in
unconstrained spontaneous movements as well as in movements toward a
target suggests that a common movement source or pattern generator
produces bend propagation in these two different behavioral
contexts.
A number of issues, however, still remain unclear. What is the
explanation for the variance observed in the scaled velocities and in
the path of the bend-point? Why is the basic pattern not demonstrated
in all reaching movements? The nervous system of the octopus is divided
into a central brain and axial nerve cords along the arms. The majority
of the nerve cells are located in those axial nerve cords (Young,
1971
). The muscles of the arm are innervated by ~3.8 × 105 fibers, which originate from neurons within the arm.
They are controlled by the brain via only 4000 efferent nerve fibers.
Sensory information is gathered by some 2.3 × 106
receptors but only ~17,500 sensory nerve fibers reach the brain from
each arm (Young, 1965
). These numbers indicate the extensive role of
the local neural circuitry in controlling the behavior of the arm, and
indeed, various local reflexes involving chemical and touch sensation
have been reported in the octopus arm (Wells and Wells, 1957
; Rowell,
1966
; Wells, 1978
; Altman, 1971
). Thus, it is most reasonable to assume
that the movement of the arm is the outcome of both preplanned
feedforward central commands and interactions with the environment
through the local sensorimotor circuits. It is possible that deviations
from the basic movement pattern observed in the present experiments
reflect adjustment of the neuronal command according to incoming
sensory input. Indeed, stereotyped tangential velocity profiles were
abundant in the unconstrained movements, whereas in the constrained
movements, where sensory input from the arm is probably dominant in
shaping the movement, such an invariant form of the velocity profiles
was not observed.
FOOTNOTES
Received May 30, 1996; revised Aug. 13, 1996; accepted Aug. 26, 1996.
This work was supported by the Office of Naval Research
(N00014-94-1-0480) and by the Israel Academy of Sciences and Humanities
(190/95-1). We thank Dr. A. Sigalov and the Visualization Center of the
Hebrew University for their assistance in analyzing video images. We
also thank Hanoch Meiri and Shira Oren for technical assistance.
Correspondence should be addressed to Yoram Gutfreund, Department of
Neurobiology, Institute of Life Sciences, Hebrew University, Jerusalem
91904, Israel.
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