Download Escape behavior and neuronal responses to looming stimuli in the

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The Journal of Experimental Biology 210, 865-880
Published by The Company of Biologists 2007
doi:10.1242/jeb.02707
Escape behavior and neuronal responses to looming stimuli in the crab
Chasmagnathus granulatus (Decapoda: Grapsidae)
Damián Oliva, Violeta Medan and Daniel Tomsic*
Laboratorio de Neurobiología de la Memoria, Depto. Fisiología, Biología Molecular y Celular, Facultad de Ciencias
Exactas y Naturales, Universidad de Buenos Aires, IFIBYNE-CONICET, Buenos Aires 1428, Argentina
*Author for correspondence (e-mail: [email protected])
Accepted 4 January 2007
Summary
Behavioral responses to looming stimuli have been
that trigger the behavioral response; (v) the neurons
studied in many vertebrate and invertebrate species, but
respond to the object approach by increasing their rate of
neurons sensitive to looming have been investigated in very
firing in a way that closely matches the dynamics of the
few animals. In this paper we introduce a new
image expansion. Finally, we compare the neuronal with
experimental model using the crab Chasmagnathus
the behavioral response showing that: (vi) differences in
granulatus, which allows investigation of the processes of
the neuronal responses to looming, receding or laterally
looming detection and escape decision at both the
moving stimuli closely reflect the behavioral differences to
behavioral and neuronal levels. By analyzing the escape
such stimuli; (vii) during looming, the crab starts to run
response of the crab in a walking simulator device we show
soon after the looming-sensitive neurons begin to increase
that: (i) a robust and reliable escape response can be
their firing rate. The increase in the running speed during
elicited by computer-generated looming stimuli in all
stimulus approach faithfully follows the increment in the
tested animals; (ii) parameters such as distance, speed,
firing rate, until the moment of maximum stimulus
timing and directionality of the escape run, are easy to
expansion. Thereafter, the neurons abruptly stop firing
record and quantify precisely in the walking device; (iii)
and the animal immediately decelerates its run. The
although the magnitude of escape varies between animals
results are discussed in connection with studies of
and stimulus presentations, the timing of the response is
responses to looming stimuli in the locust.
remarkably consistent and does not habituate at 3·min
stimulus intervals. We then study the response of neurons
Supplementary material available online at
http://jeb.biologists.org/cgi/content/full/210/5/865/DC1
from the brain of the crab by means of intracellular
recordings in the intact animal and show that: (iv) two
subclasses of previously identified movement detector
Key words: visual behavior, escape response, looming detection,
neurons from the lobula (third optic neuropil) exhibit
looming sensitive neurons, intracellular recording, Crustacea,
Chasmagnathus granulatus.
robust and reliable responses to the same looming stimuli
Introduction
Looming images can provide animals with information
about the speed and direction of approach of objects, when both
these objects and the animals themselves move. The ability to
detect and react to looming objects is present in most visual
animals from insects to mammals, even though their visual
systems are very different. This raises the question of whether
analysis of retinal image expansions is performed by similar or
different computational principles across species.
To trigger a collision-avoidance response upon an expanding
image, animals might perform several different neural
calculations. One possibility is a ‘time-to-contact’ model,
where the individual determines the time left to collision with
an object (e.g. Hatsopoulus et al., 1995; Lee, 1976; Wang and
Frost, 1992). Alternatively, an animal may generate a response
when the image across its retina subtends a certain size (e.g.
Glantz, 1974; Nalbach, 1990b) or when the borders of the
expanding image exceed a certain retinal speed (e.g. Hemmi,
2005b). Finally, animals might integrate image motion over
space and time, with responses occurring when the integral
exceeds a threshold, referred to as the ‘spatio-temporal
integration’ model (Borst and Bahde, 1988).
Behavioral reactions elicited by looming stimuli have been
studied in species as diverse as flies (e.g. Jablonski and
Strausfeld, 2000; Tammero and Dickinson, 2002), crabs (e.g.
Hemmi, 2005a; Hemmi, 2005b), frogs (Yamamoto et al.,
2003), chickens (Evans et al., 1993), gannets (Lee and Reddish,
1981), wood-chucks (Kramer and Bonenfant, 1997), monkeys
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D. Oliva, V. Medan and D. Tomsic
(e.g. Maier et al., 2004) and humans (e.g. Regan and Hamstra,
1993). Conversely, electrophysiological investigations of
neurons underlying looming detection have been performed in
relatively few species [e.g. flies (Borst, 1991), hawkmoth
(Wicklein and Strausfeld, 2000), goldfish (Gallagher and
Northmore, 2006), locust (Gabbiani et al., 2002; Gray, 2005;
Rind and Simmons, 1992), pigeon (Wang and Frost, 1992; Wu
et al., 2005)], but it is only in locusts where attempts have been
made to relate the neuronal activity with an actual behavioral
response (e.g. Gray et al., 2001; Santer et al., 2005; Santer et
al., 2006).
The visual system of locusts contains several types of
movement-sensitive interneurons (Rind, 1987). Two of these,
known as the Lobula Giant Movement Detector 1 and 2
(LGMD1 and LGMD2), strongly respond to looming stimuli
(Simmons and Rind, 1997). Continuous effort from different
laboratories has concentrated almost exclusively on studying
the response to looming stimuli of the LGMD1 (usually just
called LGMD). Nonetheless, the exact mechanism by which
this neuron encodes information and uses spike trains to trigger
behavioral reactions remains contentious (e.g. Rind and Santer,
2004). There are thus good reasons for the development of
additional experimental models in which both behavioral and
neuronal studies can be performed.
In semiterrestrial crabs, the conspicuous escape reaction
elicited by looming stimuli has largely captured the attention
of field researchers (e.g. Hemmi and Zeil, 2005; Jennions et al.,
2003; Land and Layne, 1995a; Land and Layne, 1995b;
Nalbach, 1990a). Recently, however, it has become evident that
semiterrestrial crabs offer excellent opportunities for
investigating the processing of biologically meaningful visual
stimuli at the neurophysiological level, because stable
intracellular recordings can be made in the intact, awake animal
(Berón de Astrada et al., 2001; Johnson et al., 2002; Nalbach,
1990b; Tomsic et al., 2003). Thus it is possible to characterize
several classes of neurons from the optic neuropils of the crab
Chasmagnathus by their response to visual and tactile stimuli.
Amongst these classes, there is a generic group of large
tangential neurons from the lobula that share a clear preference
for motion stimuli. Intracellular dye injections revealed that
these neurons arborize extensively in the lobula and in the
lateral protocerebrum, and their axons project centripetally,
leaving the optic ganglia through the protocerebral tract. In the
lobula, the dendritic trees are organized as tangential branches
that run parallel to each other, indicating that the cells sample
information from a large part of the visual field (Berón de
Astrada and Tomsic, 2002; Sztarker et al., 2005).
The wide field movement detector neurons (MDNs) of the
crab were previously investigated in connection with the escape
response of the animal to a stimulus moving horizontally
overhead (Berón de Astrada and Tomsic, 2002; Sztarker and
Tomsic, 2004). The profile of elicited spikes of MDNs to this
stimulus was found to correspond well with that of the
behavioral reaction. Neurons reacted to this stimulus with a
delay of 30–50·ms, and their elicited activity anticipated the
behavioral response by about 120·ms. In addition, the short-
and long-term reduction of the escape response caused by
stimulus repetitions can be entirely accounted for by the
reduction of the response of MDNs to that stimulation (Tomsic
et al., 2003). Altogether, these results indicate that MDNs are
good candidates to be involved in the decision to initiate the
escape response to visual danger stimuli. By examining both
the animal’s performance in a walking simulating device and
the neuronal responses through in vivo intracellular recording,
we identify in this paper two subclasses of MDNs that appear
to play a fundamental role in the escape response of the crab
to looming stimuli.
Materials and methods
Animals
Animals were adult male Chasmagnathus granulatus Dana
1851 crabs 2.7–3.0·cm across the carapace, weighing
approximately 17·g, collected in the rías (narrow coastal inlets)
of San Clemente del Tuyú, Argentina, and transported to the
laboratory, where they were lodged in plastic tanks
(35·cm⫻48·cm⫻27·cm) filled to 2·cm depth with diluted
seawater to a density of 20 crabs per tank. Water used in tanks
and other containers during the experiments was prepared using
hw-Marinex (Winex, Hamburg, Germany), salinity 10–14‰,
pH 7.4–7.6, and maintained within a temperature range of
22–24°C. The holding and experimental rooms were
maintained on a 12·h:12·h light:dark cycle (lights on 07.00·h to
19:00·h) and the experiments were run between 08.00·h and
19:00·h. Experiments were performed within the first 2 weeks
after the animal’s arrival. Crabs were fed rabbit pellets
(Nutrients, Buenos Aires, Argentina) every 3 days and after
feeding the water was changed. Following experiments,
animals used in behavioral experiments were returned to the
field and released in an area separated by 30·km from the
capture area.
Visual stimuli
Computer-generated visual stimuli were projected either
simultaneously or alternatively in four flat screen monitors
(Phillips 107T, Suzhou, China; horizontal and vertical screen
dimensions 32·cm⫻24·cm respectively, refreshing rate 60·Hz),
located at 20·cm in front, above and at both sides of the animal
(Fig.·1A). The monitors were located inside a Faraday cage
completely covered to prevent outside visual stimuli from
reaching the animal, and anti-glare screens reduced reflections
among the monitors. Three of the monitors stood on a
vibration-damped table and the fourth was hanging from the
ceiling. Both behavioral and electrophysiological experiments
began after a black curtain was lowered in the front part of the
cage and after the animal had remained visually undisturbed
for 10·min. All visual stimuli were generated from a single PC
using commercial software (Presentation 5.3, Neurobehavioral
Systems Inc., Albany, CA, USA). The stimulus image
generated from the PC was first split and then sent to four
selector switches. From each selector the video signal could be
rapidly turned on and off. The selectors as well as other control
THE JOURNAL OF EXPERIMENTAL BIOLOGY
Looming detection in crabs
A
Front screen
Right
screen
Left
screen
Selector
switch
Reads
mouse 1
Reads
mouse 2
Trigger
Image
generator
B
Screen
Eye
20 cm
Virtual object
Fig.·1. Experimental set-up and generation of visual stimuli. (A) The
set-up for delivering visual stimuli is located inside a sealed Faraday
cage. Four monitors are located at 20·cm to the sides, in front and
above the animal (the upper monitor is not shown). Stimulus signals
generated by PC1 were directed to any one of the four monitors
through a selector switch located outside the Faraday cage. A second
computer (PC2) was used in combination with PC1 to record the
response of the crab. (B) The looming stimulus was a simulated
projection of an approaching object from one of the monitor screens.
The simulation corresponded to a black square object of 5·cm that
approached from a distance of 70·cm at a constant velocity of
20·cm·s–1 (see Materials and methods).
systems used during the experiments were located outside the
Faraday cage. In this way, a range of different stimuli could be
selected and presented to different parts of the visual field
without distressing the animal, while behavior or neuronal
activity was being recorded.
Visual simulations generated by computer may differ in
many ways from the visual input experienced under natural
conditions. Thus, for example, the refreshing rate of a monitor
screen may impose a severe constraint on the study of the visual
system of animals with a high flicker fusion frequency. We did
not measure the fusion frequency in Chasmagnathus, but are
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confident that it is lower than the refresh rate of our monitors.
Flicker fusion in other crabs (the fiddler crab Uca pugilator)
was found to be below 50·Hz (Layne et al., 1997) and in the
crayfish, responses to looming stimuli corresponding to real
approaching objects or to filmed representations projected at
24·frames·s–1, rendered identical results (Glantz, 1974). We
found no response differences in Chasmagnathus when
comparing a black sheet of cardboard moving overhead with
the computer-generated image (V.M. and D.T., unpublished
observations).
The simulated looming stimulus used in the present study
consisted of a 5·cm black square, which approached over a
distance of 70·cm at a constant speed of 20·cm·s–1 (Fig.·1B).
Thus, for the crab’s eye the stimulus had an apparent size
subtending an angle of 4° at its stationary initial position and
expanded until covering the entire screen (77° width, 62°
height). It should be noted that this definition is somehow
arbitrary, because different properly scaled combinations of
sizes, speeds and distances of the object can generate identical
image expansions (Gabbiani et al., 1999). Thus, for example,
a 5·cm object that approaches from 70·cm at a speed of
20·cm·s–1 cannot be distinguished on the bases of its image
expansion from an object of 10·cm that approaches from
140·cm at 40·cm·s–1. Despite this uncertainty, the animal would
still be able to estimate the time remaining before colliding with
the approaching object. Such information can be extracted from
the rate of expansion of the image and is independent of the
combination of parameters that generated that particular
expansion. Indeed, the estimation of the collision time can be
obtained by determining the ratio between retinal image size at
a given instant and the rate of expansion of the image, provided
that the object approaches at a constant velocity (Lee, 1976;
Rind and Simmons, 1999).
Throughout the experiments expansions were always directly
towards the animal. In addition to the black looming stimulus,
in some experiments we also used the following stimuli: (i) a
white looming stimulus over a black background; (ii) a receding
stimulus with an opposite but otherwise similar kinetic to the
looming one; (iii) a stimulus that consisted of a black square
subtending 17° (6·cm sides), which moved parallel to the animal
at a constant speed of approximately 48°·s–1 (18·cm·s–1 on the
screen); (iv) a gradual darkening without motion components.
This was generated by reducing the light intensity at the screen
from 2.1⫻10–2·mW·cm–2 (corresponding to the white
background) to 0.03⫻10–2·mW·cm–2 (corresponding to the
black looming stimulus at full expansion). The time course of
the luminance change approximated that produced by the black
looming stimulus.
Escape response
The locomotor activity of the crab was investigated in a
walking simulator device consisting of a floating styrofoam
ball that could be freely rotated by the animal from a standing
position (Fig.·2). The method is a variation of that previously
used to investigate the orientation of walking in insects (e.g.
Dahmen, 1980). The crab was attached to a weightless rod
THE JOURNAL OF EXPERIMENTAL BIOLOGY
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D. Oliva, V. Medan and D. Tomsic
Yc
Xc
ϕc
Y2
Flexible
sheet
X2
Y1
X1
Fig.·2. Measurement of the escape response. Locomotor activity was
studied in a walking simulator device consisted of a styrofoam ball
that could be freely rotated by the animal. The crab was held in
position by a weightless rod attached to its carapace that could move
freely up and down within a vertical guide located above the crab.
Both the rod and the guide sleeve had square cross-sections, which
prevented the animal from rotating around its yaw axis. The horizontal
position of the floating ball was stabilized by four contact points
separated by 90° and provided by two optical mice and two flexible
sheets. Locomotion was assessed by recording the rotations of the ball
with the two mice according to the method described in the text (see
also Fig.·1).
through a piece of rubber glued to its dorsal carapace. The rod
was introduced inside a metal guide, positioned vertically
above the ball, where it could slide up and down with little
friction. This allows the animal to feel its own weight and thus
to adopt their natural posture while performing on the ball. The
rod and the guide both had square sections, which prevented
rotational movements and thus opened the visual feedback
loop. Because crab eyes possess a panoramic field of view, but
the visual sensitivity may be different around the eye (e.g.
Sandeman, 1978), opening the feedback loop allowed us to
vary the location of the visual input while preventing the
complications of the crab responding to the visual
consequences of its own actions (Land and Layne, 1995b). On
the other hand, crabs have their eyes mounted on top of
movable stalks, which they move to stabilize the optic flow that
results from its own movements. However, they have never
been observed to move the eyes in such a way as to bring the
image of a target to bear upon a special part of the retina, i.e.
they do not fixate and track objects of interest (Barnes and
Nalbach, 1993; Sandeman, 1978). In a series of preliminary
experiments we compared the escape response to looming
stimuli between crabs with free and immobilized eyestalks, and
found no difference in any response parameter. Therefore, there
was no need for immobilizing the eyes during behavioral
experiments in the present study.
The styrofoam ball (16·cm in diameter) was floating within
a bowl-shaped container partially filled with water. Horizontal
displacements of the ball were prevented by four set points
provided by two optical mice and by two flexible sheets located
at right angles from each other. The rotation of the ball was
recorded by the two mice that have their optical reading
systems protected by transparent acetate sheets, which also
ensure smooth movements of the ball.
Recording and reconstruction of the locomotor pathway
During normal walking, crabs may perform translatory as
well as rotational movements. On the walking simulator these
actions turn into corresponding displacements of the ball
beneath the crab. In the case of pure translation, the path of the
ball is a straight line whose direction is opposite to that of the
crab’s intended locomotion. Pure rotation by the crab causes
rotation of the ball about a vertical axis through the crab, again
in the opposite direction to the crab’s intention. Combinations
of translation and rotation result in circular movements by the
ball, where the center of rotation is at a distance from the crab
itself. Translatory and rotatory movements were extracted by
the method shown in Fig.·2. A system of orthogonal
coordinates centered in the crab defined the Yc and Xc axes,
which corresponded, respectively, to the anteroposterior and
lateromedial axes of the crab. Attempts of the animal to move
forward or backward displaced the surface of the sphere
beneath the crab along the Yc axis, and this movement was
recorded by monitoring Y-axis movements (Y1) of mouse 1.
Attempts of the animal to move sideways displaced the surface
along the Xc axis, and this movement was recorded by
monitoring Y-axis movement of mouse 2 (Y2). Rotational
movements (␸c) were recorded by monitoring the X-axis of
both mice. Thus pure forward–backward translatory
movements over time t corresponded to ⌬Yc(t)=␣1⌬Y1(t),
sideways translatory movements to ⌬Xc(t)=␣2⌬Y2(t), and
rotational movements to ⌬␸c(t)=␤1⌬X1(t)=␤2⌬X2(t), where ␣1,
␣2, ␤1 and ␤2 are constants that were obtained by calibration
of the equipment. Signals from the mice were acquired using
the recording facilities of the commercial software generating
the visual stimuli (Presentation 5.3, Neurobehavioral Systems
Inc., Albany, CA, USA). Mice data were taken at each frame
update (16.7·ms), which ensured accurate correspondence
between the recorded response times and the stimulus features
(size, border speed, etc) at each screen update. Two
Presentation programs were run in two separate PCs. PC1,
which generated the visual stimuli, was used to record one of
the mice, as well as to trigger the recording of the second mouse
in PC2 (Fig.·1A). Thus, the program that generated the visual
stimulus synchronized the recording of the two mice just before
stimulus onset. The data recorded by mice 1 and 2 during a trial
generated two Presentation files, which contained a list of the
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Looming detection in crabs
Results
The crab response to looming stimuli
To analyse the time course of the escape response in
Chasmagnathus we began with responses elicited by looming
stimuli approaching from the side of the crab, because these
escapes are executed in a single direction and do not contain a
rotational component (see below) (see also Land and Layne,
1995b). An example of the escape response developed by the
crab can be seen in Movie 1 in supplementary material. As
A
Accumulated distance (cm)
Electrophysiology
Intracellular recordings from interneurons in the optic lobe
were performed in the intact living animal according to
methods previously described (Berón de Astrada et al., 2001).
Briefly, the crab was firmly held in an adjustable clamp. The
eyestalks were cemented to the carapace at an angle of
approximately 70° from the horizontal line, which corresponds
to their normal position. A tangential cut performed with a
sharp scalpel was made to remove a small piece of thin cuticle
(about 500·␮m in diameter) from the tip of the eyestalk without
causing damage to the ommatidial area. The crab was
positioned in the center of the arrangement of monitors within
the Faraday cage. The clamp with the crab was held in position
using a magnetic holding device. The glass microelectrode was
then positioned and advanced through the opening in the
cuticle. Microelectrodes (borosilicate glass; 1.2·mm outer
diameter, 0.68·mm inner diameter), were pulled on a BrownFlaming micropipette puller (P-77; Sutter Instrument, Novato,
CA, USA) yielding tip resistances of 40–60·M⍀ when filled
with 3·mol·l–1 KCl. A bridge balance amplifier was used for
intracellular recordings (Axoclamp 2B; Axon Instruments,
Union City, CA, USA). The output of the amplifier was
monitored on an analogue oscilloscope, digitized at 10·kHz
(Digidata 1320; Axon Instruments) and recorded in a computer
for subsequent analysis. All intracellular recordings were
performed at the membrane resting potential.
The monitors located inside the Faraday cage generated a
significant level of electrical noise in the recordings, but we
were able to prevent the noise in two ways: (i) by placing a
wire mesh just in front of each one of the screens, and (ii) by
wrapping the headstage, the electroholder and part of the glass
electrode with a dense, properly grounded, metal wire mesh.
Note that after electrophysiological recordings, the crabs
remained healthy and no subsequent behavioral differences
were observed with respect to non-treated animals.
100
75
50
25
0
Normalized accumulated distance
times associated with each data record and frame update. The
files were then combined and analyzed off-line to obtain the
profile of the escape response.
A recording trial lasted 10·s and, when repeated, trials were
recorded at either 1 or 3·min intervals. In all trials the stimulus
remained stationary for 30·s at its initial position before starting
to increase in size. Behavior was always monitored by visually
observing the animal through a small hole in the curtain at the
front of the cage.
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0
1
2
4
6
8
10
8
10
Decelerated
escape
B
0.8
Escape
running
0.6
0.4
Escape
start
0.2
0
Still
0
2
4
6
Time (s)
Stimulus (3.5 s)
Fig.·3. The escape response to looming stimuli. (A) Each trace
corresponds to the distance covered by a different animal during 10·s,
starting from the beginning of the stimulus presentation at the right
side. Different animals run different distances. However, when
normalized to the maximum value, the time courses of all responses
are remarkably similar (B). The response then can be divided into four
distinguishable phases (for further details see the text and Movie 1 in
supplementary material). The dotted line signals the time at which the
virtual object would collide with the animal. N=18, one trial per crab.
shown in Fig.·3A, the same looming stimulus elicits escape
responses of different magnitude in different animals (running
distances may vary from 20 to 100·cm). Nevertheless, when the
individual responses are normalized to the maximal value, their
time courses look remarkably similar (Fig.·3B). In all cases
four distinguishable response phases can be recognized. First,
despite the fact that the stimulus has begun to loom, the crab
remains still, indicating that it has not yet perceived the
stimulus as a threat. Second, there is a well-defined moment at
which the escape run is triggered. Third, from the starting point
of the escape until the end of the stimulus expansion, there is
a response phase characterized by high-speed running of up to
35·cm·s–1. Fourth, at the end of the stimulus expansion the crab
immediately decelerates, in such a way that by the end of the
10·s recording period it is slowly walking or has stopped. On
a few occasions, the animals had been walking before the start
of image expansion; those trials were not included in the
analysis.
THE JOURNAL OF EXPERIMENTAL BIOLOGY
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D. Oliva, V. Medan and D. Tomsic
0.5
30
0.4
1.5
20
0
3.5
2.5
0.3
15
0.2
10
0.1
5
Fig.·4. Threshold of escape response to looming stimuli.
Individual responses from different crabs are displayed
from the beginning of stimulus expansion up to 0.5·s
following the time of virtual collision (same dataset as
shown in Fig.·3). The time at which each response was
initiated (response latency) was projected onto the curve
that describes the angular size of the stimulus, which
identifies the apparent stimulus size at the time the crab
initiated the escape response. The inset shows at higher
magnification the part of the responses corresponding to the
time enclosed by the horizontal rectangle. See the text for
further details.
0
0
0
1
2
3
4
Time (s)
Repeated responses
Escape responses to repeated visual stimulation can be
affected by habituation (e.g. Tomsic et al., 1998; Tomsic et
al., 2003). Therefore, before measuring the crab’s response to
repeated presentation of the stimulus approaching from
different visual regions (see below), we decided to evaluate
the extent to which repetitions of the same looming stimulus
affect the performance of the escape response in
Chasmagnathus. Fig.·5A shows the mean response distance
100
Mean accumulated distance (cm)
Response threshold
We defined the time of response initiation as the first point
at which the normalized curve of accumulated distance begins
to increase (Fig.·4), which corresponds to a movement of
approximately 0.01·cm, or less than 0.1% of the accumulated
distance for any run (Fig.·4, inset). These latency values of
individual responses were then projected to intercept the curve
that describes the apparent size of the object (Fig.·4), to
determine the angular size reached by the stimulus at the time
each escape was initiated. Similarly, we obtained the retinal
speed reached by the stimulus at escape initiation by projecting
the latency values onto the curve that describes the rate of
image expansion (not shown). Analysis of the data in Fig.·4
(same data set of Fig.·3, N=17) revealed that the stimulus used
in the present study triggered the escape response at a mean (±
s.e.m.) of 2.41±0.07·s following the beginning of its expansion.
At that point the stimulus size on the screen was 4.8±0.3·cm
and its edges moved at a speed of 2.32±0.4·cm·s–1,
corresponding to an apparent size of 13.9±1° and a retinal
speed of 14±2°·s–1, respectively. Thus, at the initial response
time the apparent size of the stimulus had increased by about
10° (from 4° at its initial stationary size) in about 2.4·s. Note
that the object simulated here departed from 70·cm away and
travelled at a speed of 20·cm·s–1, which means that it took 3.5·s
to virtually collide with the crab. Because the response started
2.4·s after the stimulus began to move, the animals responded
approximately 1·s before the collision. We repeated the same
experiment at different times of the year and, despite
differences in response intensity related to seasonal variations,
found an identical response initiation time (mean ±
s.e.m.=2.43±0.07·s, N=14). Therefore, the time at which crabs
decide to initiate escape to this stimulus appears to be very
consistent among different individuals.
1 min stimulus interval
A
3.0
80
2.5
60
2.0
1.5
40
1.0
20
0.5
0
0
100
3 min stimulus interval
B
3.0
80
2.5
60
2.0
Response latency (s)
Stimulus angular size (deg.)
25
Normalized accumulated distance
0.005
1.5
40
1.0
20
Latency
Distance
0.5
0
0
0
2
4
6
Trial number
8
10
Fig.·5. Responses to repeated looming stimulation. (A) Repeated
presentations of the same looming stimulus at 1·min intervals produce
a progressive reduction of the escape distance (open squares, left axis)
and an increase in response latency (filled circles, right axis) (N=14
crabs). (B) Repeated stimulation with longer inter-trial intervals
(3·min) causes less changes to the escape distance and did not affect
the response latency (N=15 crabs). Broken lines indicate the value of
the mean response latency at first trial.
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Looming detection in crabs
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A
70 cm
60
B
C
3
Mean latency (s)
50
Mean distance (cm)
Fig.·6. Directional sensitivity of the
escape response. The looming stimulus
was presented to each animal once in
each of the four different visual regions
corresponding to the position of the
monitors, and the sequence of
presentation was varied among animals.
(A) Polar plots show the trajectories of
the escape responses to the stimulus
approaching from each one of the four
screens: upper left, stimulus above;
upper right, stimulus in front; lower left,
stimulus at left side, lower right,
stimulus at right side. Black circles
denote the direction of escape for each
animal. (B) Response distance of the
responses shown in A. (C) Latency to
initiate the escape of the responses
shown in A. Values are mean response
scores ± s.e.m.; N=10 crabs, one trial at
each stimulus location.
40
30
20
2
1
10
0
0
Above
Front
(open squares, left axis) run by a group of 14 crabs, upon 10
presentations of the looming stimulus separated by 1·min. The
figure also shows the mean response latency (as described
above) for the same animals (filled circles, right axis). The
result indicates that repeated stimulations caused a
progressive reduction in the running distance and an increase
in response latency. Given that 1·min is a quite short intertrial interval, the result may have been caused by motor
fatigue rather than by a central process of habituation.
Consequently, we repeated the experiment with a different
group of 15 crabs but using an inter-trial interval of 3·min.
The result revealed that despite subtle changes in the running
distances across trials (a sensitization effect is apparent at trial
2) there were no differences in the latency of response
(Fig.·5B). Therefore, in the latter condition repeated
responses to the same stimulus are always launched at
approximately the same time.
Left
Right
Above
Front
Left
Right
Directional tuning of escape
Individual trajectories of escape responses recorded on the
walking simulator to the virtual looming stimulus approaching
from four different visual regions are shown in Fig.·6. Each
animal was presented with one stimulus from each monitor
using an inter-trial interval of 3·min and the sequence of
presentations was varied among different animals. The crabs
escape sideways to the left or right with equal probability when
confronted with stimuli in their dorsal visual field, but always
run in the opposite direction to an expanding stimulus when it
is presented in horizontal directions of view. Escape paths in
response to lateral stimuli are longer than those elicited by
frontal or dorsal stimuli (Fig.·6B). These differences may
reflect variations of resolving power across the visual field
(Nalbach and Nalbach, 1987; Sandeman, 1978) or the fact that
crabs’ preferred running direction is sideways. For instance, for
frontal stimuli we recorded the largest rotational components
THE JOURNAL OF EXPERIMENTAL BIOLOGY
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D. Oliva, V. Medan and D. Tomsic
M1 neuron
M2 neuron
10 mV
Angular size of Mean spike
stimulus (deg.) frequency (Hz)
Trial
120
120
80
80
40
40
0
0
60
30
0
60
30
0
1
2
4
Time (s)
6
1
2
4
Time (s)
6
Fig.·7. Response of an M1 and an M2 type of movement detector neuron to the looming stimulus appearing from the right visual field. Traces
exemplify individual responses from each neuronal type. The time of spike occurrence shown below the traces illustrates the consistency of the
response for each neuron to nine presentations of the stimulus, separated by 1·min (the traces correspond to the last trial of these series).
Peristimulus time histograms show the mean spike rate obtained from the nine trials. Data are divided into 100-ms bins and are plotted as means
± s.e.m. Angular size of the looming object is given in the lower traces of each panel. Arrowheads mark the beginning of the stimulus expansion;
long arrows mark the moment at which the synaptic activity or the spike rate of neurons had clearly increased above resting level.
of escape runs, indicating that crabs attempted to rotate in order
to run sideways. Response latencies, however, may be
determined by the resolving power of the crabs’ eyes: the crabs’
response latency was consistently longer for dorsal, compared
with lateral or frontal stimuli (P<0.01, Fig.·6C). Interommatidial angles in the eyes of Chasmagnathus increase
towards the dorsal visual field (V.M., unpublished) and a
looming stimulus needs to expand further in the dorsal,
compared to equatorial, visual field in order to stimulate a
similar number of facets.
Identification of neurons responsive to looming stimuli
Movement detector neurons (MDNs) from the lobula of the
crab are easily recognized by their high sensitivity to moving
objects in comparison to stationary changes in brightness
(Berón de Astrada and Tomsic, 2002; Tomsic et al., 2003).
Previous studies distinguished MDNs with dendrites that
arborize in a single layer of the lobula from neurons that
arborize in two layers (Berón de Astrada and Tomsic, 2002;
Sztarker et al., 2005). Based on morphological
characterizations and physiological analyses of responses to
laterally moving objects, more recent studies revealed the
existence of at least four clearly distinguishable subclasses of
MDN (Medan et al., 2004) (V.M. and D.T., unpublished). We
evaluated the response to the looming stimulus in the four
different cell types and found that two of them, which we name
M1 and M2 (see below), respond to an expanding image in a
robust and reliable way. Representative responses of these two
neurons are shown in Fig.·7, together with their consistency in
terms of the times of neuronal spikes upon nine presentations
of the looming stimulus separated by 1·min (the traces
correspond to trial 9 of each experiment). The response in both
M1 and M2 neurons consists of a depolarization accompanied
by spiking activity that progressively increases as the image of
the virtual object grows over the retina of the animal (see also
Figs·8, 9). Despite the fact that stimulus repetition appears to
reduce the total number of elicited spikes (particularly in M2),
and that the occurrence of spikes may slightly vary among trials
(likely due to the fact that the animal is alive and hence its
internal state is continuously changing), the general response
THE JOURNAL OF EXPERIMENTAL BIOLOGY
Looming detection in crabs
A
Flash
B
C
Lateral motion
873
Looming
20 mV
M1
1s
Angular size of
stimulus (deg.)
M2
60
30
0
1
2
Time (s)
4
6
Fig.·8. Response of an M1 and an M2 neuron to (A) a flash of light, (B) a laterally moving object and (C) an approaching object. (A) The
horizontal open bar below the traces represents 1·s duration of light stimulation (200·mW·m–2 at the crab eye). (B) The black bar represents 1·s
motion of a black square object moving laterally to the crab. (C) The curved line represents the time course of expansion of the looming stimulus
as described in Fig.·7. Arrows in the traces mark the approximate moment at which the neurons began to respond to the looming stimulus by
increasing their synaptic activity or spike rate above resting level.
profile of both types of neurons to the looming stimulus is
preserved across trials. These profiles can be better appreciated
from the peristimulus histograms of Fig.·7 (see also Figs·8, 9
and 11), corresponding to averaged data (± s.e.m.) of the nine
repetitions organized into 100·ms bins. The histograms suggest
the existence of two peaks in spike rate: a small one that occurs
immediately after the start of stimulus movement, and a second
that builds up during the approach. Interestingly enough, these
two peaks were also observed in the LGMD1-DCMD neurons
of the locust when a stimulus that subtends >5° at the eye
approaches the eye, and they were taken as an indication that
these neurons follow angular acceleration of the image much
more closely than angular velocity or angular size of the image
(Rind and Simmons, 1992).
In Fig.·8, recordings of an M1 and an M2 neuron from
different animals illustrate their responses to (A) a flash of
light, (B) a black rectangle moved laterally and (C) the
looming stimulus. In both types of neurons the response to
the pulse of light consists of a discrete IPSP or EPSP
(occasionally a single spike), always associated with the onset
and the offset of the light, whereas to tangential motion the
two neurons respond with a train of spikes riding on top of a
large and rather sustained EPSP. The response in both M1 and
M2 neurons to the looming stimulus consists of a
depolarization accompanied with spiking activity that
progressively increases as the image of the virtual object
grows over the retina of the animal (see also Fig.·9). Despite
these similarities, the two neurons present substantial
differences. Type M1 neurons comprise a group of 14 units
with a well-documented morphology (Sztarker et al., 2005).
Briefly, these neurons are homogeneously distributed across
the lobula, where they extend their dendrites tangentially
along a single layer, in such a way that each neuron collects
information from a different and restricted part of the
retinotopic mosaic. Physiological measurements revealed that
the neurons have their receptive field oriented toward
different parts of the visual space, each neuron encompassing
less than 90°. Therefore, although the neuronal assemble
allows assessment of visual information from the whole
panorama, each element processes information from a
restricted part of the animal’s visual field (Medan et al., 2004)
(V.M. and D.T., unpublished). These neurons had previously
been named monostratified movement detector neurons (MMDNs) (Sztarker et al., 2005) but, in order to separate them
from a second group of monostratified neurons described
below, we term them here simply M1. By contrast, the group
of M2 neurons is formed by a yet-undetermined number of
elements, although the similarities in cell morphology
observed over several independent intracellular stainings
indicate there may possibly be only one unit of this type. This
neuron possesses a very large dendritic tree that extends in a
single layer all the way through the lobula, thus collecting
information from the entire retinotopic mosaic. Physiological
measurements revealed that the receptive field of this neuron
is extremely large, covering the entire visual space (Medan et
al., 2004) (V.M. and D.T., unpublished). We call these
neurons monostratified 2 or M2.
From electrophysiology, the two neuronal types are readily
distinguishable because M1 do not fire spontaneously whereas
M2 fires at a constant rate of about 6·Hz. At the end of the
stimulus expansion M2 usually stops firing and occasionally
shows a clear hyperpolarization that may last for several
hundred milliseconds before regaining spontaneous activity
(Figs·8, 9).
THE JOURNAL OF EXPERIMENTAL BIOLOGY
874
D. Oliva, V. Medan and D. Tomsic
M1 neurons
M2 neurons
30 mV
Angular size Mean spike
of stimulus frequency
(deg.)
(Hz)
A
10 mV
60
40
20
0
60
40
20
0
60
30
0
60
30
0
Angular size Mean spike
of stimulus frequency
(deg.)
(Hz)
B
60
40
20
0
60
30
0
60
40
20
0
60
30
0
Angular size Mean spike
of stimulus frequency
(deg.)
(Hz)
C
60
40
20
0
60
40
20
0
60
30
0
60
30
0
Mean spike
frequency
(Hz)
D
60
40
20
0
60
40
20
0
Mean spike
frequency
(Hz)
E
60
40
20
0
Gradual
darkening
0
1
2
3
4
Time (s)
5
6
7
60
40
20
0
0
1
2
3
4
Time (s)
5
6
7
Fig.·9. Response of M1 and M2 neurons to different types of movement. (A–E) Results with (A) the black looming stimulus, (B) the black
receding stimulus, (C) the white looming stimulus, (D) the laterally moving stimulus and (E) the gradual darkening. Sample recordings from a
single M1 and a single M2 neuron illustrate the type of responses of these neurons to the five different stimuli. Peristimulus time histograms
show the mean spike rate recorded from 11 M1 and 13 M2 neurons from different animals (one trial per stimulus per neuron). Data are divided
into 100-ms bins and are plotted as means ± s.e.m. The angular size of the looming and receding object is given in the bottom traces of each
panel. Arrowheads signal the beginning of the stimulus expansion; black bars represent 1·s motion of a black square object moving laterally to
the crab. The darkening bar in E represents a gradual darkening of the screen without motion components.
THE JOURNAL OF EXPERIMENTAL BIOLOGY
Looming detection in crabs
Temporal relation between the neuronal and the behavioral
response to the looming stimulus
Before a visual interneuron can be considered to be involved
in the detection of stimuli that trigger an escape response, it
must satisfy two initial criteria: firstly, it must respond to the
same stimuli that trigger the escape behavior and secondly, its
activity must precede the behavioral response. The M1 and M2
neurons that we recorded from satisfy both of these criteria.
60
Behavior
M1
M2
50
50
40
40
30
30
20
20
10
10
Mean spike number
60
Mean distance (cm)
Neuronal and behavioral responses to looming, receding and
laterally moving stimuli
We evaluated the responses of M1 and M2 neurons to visual
stimuli consisting of a black looming, a white looming, a black
receding, a laterally moving black square, and a motionless
darkening of the screen. Recordings were taken from the right
lobula, stimuli were presented at the screen located to the right
of the crab, and in the case of M1 only neurons with the
receptive field oriented towards that side were used. Fig.·9
shows representative responses of one neuron from each type
to the five visual stimuli, and averaged data (± s.e.m.) from 11
M1 and 13 M2 neurons organized into 100·ms bins. The black
receding stimulus (Fig.·9B) evokes in M1 neurons a small but
consistent response at the beginning of the image contraction,
which is usually absent in M2 elements. In both neuron types
the white looming object (Fig.·9C) elicits a weak response that
slightly increases with the approach of the virtual object.
Lateral displacements of the black square (Fig.·9D) produce a
considerable response, which is often sustained through the
motion period. Dimming of the screen without motion
components generates a gradual response in M2 but only a
sharp response at the time of maximal darkness in M1 neurons
(Fig.·9E). The black looming stimulus (Fig.·9A) is the one that
generates the strongest responses. This can be appreciated by
comparing the mean spike frequency reached in response to the
different stimuli (peristimulus histograms in Fig.·9), as well as
the total number of spikes elicited by the stimuli (Fig.·10).
The stronger responses obtained to the black looming
stimulus (A) in comparison with the lateral motion of the
square (D) could be attributed to the fact that the number of
elementary motion detectors stimulated at the end of the
looming expansion is grater than that stimulated by the lateral
moving square. However, larger moving squares that the one
used in the present study do not necessarily elicit stronger
responses (V.M. and D.T., unpublished). More likely then, the
strong response to looming stimuli relates to the increase in the
velocity of image expansion that, as it was proposed in the
locust, may reduce effects of neuronal inhibition (Simmons and
Rind, 1992).
In order to begin exploring the relation between the activity
of M1 and M2 neurons with the escape response, we evaluated
the behavioral reactions to the various stimuli we used. Fig.·10
shows that there is good correspondence between the visual
stimuli that elicit an escape behavior and those that are effective
at exciting the M1 and M2 neurons. The black looming
stimulus is the most powerful, while the black receding one is
the weakest.
875
0
Gradual
darkening
0
A
B
C
D
E
Fig.·10. Comparison of the behavioral and the neuronal responses to
(A) a black approaching object (B) a black receding object, (C) a white
approaching object, (D) an object moving laterally, and (E) a gradual
darkening of the screen. Behavioral responses are shown as the mean
response distances covered during 10·s following the beginning of the
stimulus (left axis). Responses of M1 and M2 neurons to the same set
of stimuli were assessed by counting the number of elicited spikes
during the period of stimulation (right axis). In M2 neurons the
spontaneous rate of firing was subtracted from the response. To obtain
the behavioral and the electrophysiological data, crabs were presented
with only one stimulus of each type separated by 3·min. In both
behavioral and electrophysiological experiments the sequence of
presentation was varied among animals. Bars represent mean response
scores ± s.e.m. Behavior, N=14 crabs; neurons: M1, N=11; M2, N=13.
Comparison of the temporal profile of the crab escape response
with those of M1 and M2 neurons to the black looming
stimulus is shown in Fig.·11. Behavior is shown as the mean
running speed from 14 animals (one run per crab), organized
into 100·ms bins. Neuronal responses are shown as the mean
spike frequency of 19 records obtained from 10 M1 and 18
records from 13 M2 neurons (no more than 2 records per
neuron per crab were considered), which are also organized
into 100·ms bins. Note that the time axes for the records shown
in Figs·7–9 and 11 are different from those in Figs·3 and 4; the
start of the looming motion indicated by arrowheads in Fig.·11
corresponds to time zero in Figs·3 and 4. As described above,
the escape response starts (dotted line in Fig.·11) approximately
2.4·s after the stimulus begins to move. Clearly, at the moment
of escape initiation, both M1 and M2 neurons have
significantly increased their firing activity above their resting
discharge. However, there is a delay of approximately 120·ms
between the responses of MDNs and the behavioral reaction
(Tomsic et al., 2003), so that the behaviorally relevant
discharge level occurs 120·ms before the first movement of the
animal can be detected (see arrows in Fig.·11).
The escape speed of crabs increases with the angular size of
the stimulus (Fig.·11A), whereby running speed continues to
increase up to the moment when the stimulus stops expanding
(broken line). At the end of expansion, when the stimulus was
moving at angular velocities above 200°·s–1, crabs reached an
averaged escape velocity per bin of 24.5·cm·s–1. Interestingly,
THE JOURNAL OF EXPERIMENTAL BIOLOGY
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D. Oliva, V. Medan and D. Tomsic
Mean running
speed (cm s–1)
30
A
Behavior
20
10
0
M1 mean spike
frequency (Hz)
80
B
60
M1
40
20
0
M2 mean spike
frequency (Hz)
80
C
60
M2
40
20
Angular size of
stimulus (deg.)
0
D
80
60
40
20
0
0
Angular velocity
(deg. s–1)
250
1
2
3
4
5
6
7
1
2
3
4
Time (s)
5
6
7
E
200
150
100
50
0
0
the run suddenly decelerates almost immediately following the
end of expansion. This matching between the dynamic of the
approaching image and that of the escape suggests that the
response is under feedback control.
Discussion
The great challenge to investigate the computational and
neural processes that underlie the behavioral decision of
reacting to looming stimuli arises from the scarcity of
experimental models in which both the behavioral and the
neuronal responses can be studied in the same animal. In
this paper we introduce a new experimental model, which
presents some advantages for investigating the processes of
looming detection, escape decision and escape control, at
Fig.·11. Temporal relationship between the neuronal and the
behavioral response to the looming stimulus. Peristimulus
time histograms show (A) the mean (± s.e.m.) running speed
of the animals and (B,C) the mean (± s.e.m.) spike rate of
M1 (B) and M2 (C) neurons, calculated over 100-ms bins
and plotted against time during the object approach. (D)
Angular size and (E) speed of expansion of the looming
object. Arrowheads mark the beginning of the stimulus
expansion; the dotted line marks the moment at which the
escape behavior was initiated; the broken line indicates the
moment when the stimulus reached its maximum expansion
and velocity; the vertical solid line marks the point in time
at which collision would have occurred; arrows in B and C
point to the neuronal activity 120·ms before the first
movement of the animals. Behavioral data are from 14 crabs
(one trial per crab). Neurophysiological data are from 19
trials recorded from a total of 10 M1 neurons and 18 trials
from 13 M2 neurons, each neuron from a different animal
(i.e. no more than 2 records per crab were included).
both behavioral and neuronal levels. The advantages can be
summarized as follows: (i) a robust and reliable response
that can be elicited by computer-generated looming stimuli
in all tested animals; (ii) the response magnitude, timing
and direction are easy to record and to quantify; (iii) the
response of identified neurons to looming stimuli can be
recorded intracellularly in the intact animal; (iv) the
response of these neurons seems to encode properties of the
visual stimuli that trigger the escape response. Our results
reveal that in many aspects, looming-sensitive neurons of
the crab remarkably resemble those studied in the locust
(see below), a finding that is relevant to the question of
whether analysis of retinal image expansions is performed
by similar or different computational principles across
species.
THE JOURNAL OF EXPERIMENTAL BIOLOGY
Looming detection in crabs
Reaction to looming stimuli in crabs
Semiterrestrial crabs possess a highly developed visual
system and display conspicuous visual guided behaviors (e.g.
Cannicci et al., 1997; Zeil and Hemmi, 2006). In nature,
Chasmagnathus is preyed upon by different species of seabirds
(Spivak and Sanchez, 1992), the most important being the gull
Larus atlanticus, which is a specialized crab feeder (Escalante,
1966; Copello and Favero, 2001). The strategies used by this
gull to approach and capture Chasmagnathus have barely been
studied. Yet, they seem to be varied, the most important being
walking and surface seizing (Copello and Favero, 2001).
Depending on the attack strategy and on the different stages of
an attack, visual cues vary widely for the crab prey. How do
the animals then detect the danger and elicit the appropriate
response faced with such a variety of visual cues? Fiddler crabs
appear to employ a multistage predator avoidance strategy
depending on the level of risk, whereby this risk may be
assessed by different detector systems, sensitive to different
aspects of predator-associated visual cues (Hemmi, 2005b). A
similar hypothesis has recently been proposed to explain the
range of evasive behaviors, from steering to diving, elicited by
looming stimuli in the locust (Santer et al., 2006).
Parameters of the looming stimuli that determine the escape
decision
Depending on their velocity, size, distance and movement
direction, approaching objects generate images that move and
expand over the observer’s retina with different dynamics.
Thus, the way in which the image changes contains significant
information about object behavior, even though biological
constraints may limit access to some of this information
(Hemmi and Zeil, 2005). But which one of the various
parameters that define the expanding image is used by the
animal? Behavioral experiments performed in different species
of crabs and in crayfish have suggested different possibilities,
including an increase in the apparent size of the stimulus
(Glantz, 1974; Nalbach, 1990b), a threshold in retinal speed
(Hemmi, 2005b), or a combination of these factors (Land and
Layne, 1995a; Hemmi, 2005b). For instance, the critical
stimulus parameter to initiate the escape in the crab Heloecius
or to trigger the defense reaction in the crayfish is the increase
in angular size (Nalbach, 1990b; Glantz, 1974). In Heloecius
the apparent angular size of the stimulus had to increase above
5.6° from its initial value (discussed in Hemmi, 2005b) while
in the crayfish the required increase was about 8° (Glantz,
1974). In Chasmagnathus, the looming stimulus used in the
present study launched the escape response when the image
reached an apparent angular size of 13.9° and a retinal speed
of 14°·s–1. Therefore, at the response onset the apparent angular
size of the stimulus had increased by approximately 10° (from
4° at the initial position up to 13.9° at the time of response
onset), which is not far from the values reported in Heloecius
and the crayfish. It should be stressed, however, that the value
obtained corresponded to the average time at which most
Chasmagnathus decided to initiate the escape, and not to the
minimum threshold for detecting visual motion stimuli. In fact,
877
our electrophysiological recordings show clearcut neuronal
responses when the stimulus subtends less than 4.5° (i.e. an
increase of 0.5° from the initial value) and moved at a retinal
speed below 1.4°·s–1 (see arrows in Figs·7, 8).
When compared with field studies, the mean threshold
values found in Chasmagnathus appear to be much higher than
those reported for fiddler crabs (Hemmi, 2005b; Land and
Layne, 1995a). Several reasons may account for the difference:
First, fiddler crabs possess a region of maximal vertical
resolution around the eyes’ equator, which is not common to
other groups like grapsid crabs (Zeil et al., 1986). Thus, stimuli
moving close to the level of the horizon might indeed be more
readily perceived in fiddler crabs than in Chasmagnathus.
Second, the discrepancy may arise from the fact that the values
we report in the present study correspond to the averaged
thresholds from several animals, whereas in fiddler crabs the
reported values corresponded to the minimum individual
threshold detected among many animals. In fact, when looking
at individual responses we found escape reactions that were
triggered when the stimulus had an apparent angular size of
only 5.7° and moved at a retinal speed of 2.3°·s–1. Lower
thresholds would have been difficult to obtain in our current
experiments since the initial size of the stimulus was already
4°. Interestingly, the lowest behavioral thresholds we observed
were from those few animals (hence excluded from the general
analysis) that were slowly walking at the time the looming was
initiated, which suggests that the locomotion state may have a
facilitatory effect on the responsiveness to danger visual
stimuli.
A third possibility to explain the difference in thresholds
between fiddler crabs and Chasmagnathus relates to the fact
that crabs display different responses according to their
assessment of the risk of predation (Hemmi, 2005a). In fact,
crabs respond to a predator in three different stages: freeze,
home run and, ultimately, refuge entry. Thus, a stimulus
approaching from a long distance, such as those used in field
studies with fiddler crabs, initially elicits a startle response. But
as the stimulus comes closer (or initiates its approach from a
shorter distance, as in our study), the probability and the
strength of the escape increase. It has been proposed that the
different stages of the escape response are mediated by two
distinct detector systems, sensitive to different aspects of
predator-associated visual cues (Hemmi, 2005b). Differential
activation of these two distinct, but complementary, predator
response systems was suggested to explain the discrepancy
between the threshold values found in fiddler crabs and in the
crab Heloecius (Hemmi, 2005b). This explanation could also
account for the discrepancy between the values found in fiddler
crabs and Chasmagnathus.
To determine which one of the parameters that characterize
a visual stimulus is used by the animal to identify it as an
impending threat, and then initiate the escape, requires a
comprehensive study employing a wide range of visual stimuli.
The present study shows that regardless of the differences in
response strength in different animals (Figs·3, 4) or in the same
animal, depending on the number of exposures (Fig.·5B), the
THE JOURNAL OF EXPERIMENTAL BIOLOGY
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time course for the response remains invariant. Provided
stimuli are separated by at least 3·min, temporal parameters
such as the response latency can thus be assessed by repeatedly
recording the responses to diverse looming stimuli in the same
animal.
Neuronal responses to looming stimuli and the escape
response
In this study we show that two subclasses of movement
detector neurons from the crab’s lobula, here termed M1 and
M2, respond to the looming stimulus in a way that closely
matches the time course of expansion and, equally important,
their activity correlates with the magnitude (speed) of the
elicited escape response (Fig.·11). This is particularly clear in
the case of M1 neurons, the discharge rate of which correlates
with each phase of the behavioral output. During the first part
of the stimulus approach M1 is silent and the crab remains still.
Then, at a certain point of the expansion the neuron begins to
increase its firing rate, and soon afterwards the crab starts to
run. The increase in running speed of the crab during the
stimulus approach faithfully follows the increment in the firing
rate of M1 until the moment of maximum stimulus expansion,
when the neuron abruptly stops firing and the animal
immediately decelerates its run. However, before the relation
of M1 neurons with the escape response can be generalized,
more experiments using looming stimuli of different sizes and
with different velocities of approach are needed.
The directional component of the escape response of crabs
is known to be controlled by continuous visual feedback (Land
and Layne, 1995a; Land and Layne, 1995b). The close
correlation between the time course of image expansion and the
speed of running suggests that the velocity of the escape may
also be controlled by a visual feedback, which could operate
through M1 neurons. However, because we do not know the
postsynaptic target of M1 neurons, their involvement in the
circuit that commands the escape response to looming stimuli
remains speculative.
Comparison of the looming sensitive neurons of the crab and
the locust
The visual nervous system of insects and crustaceans are
thought to be homologous (Strausfeld, 2005), and the recent
finding of a lobula plate neuropil in Chasmagnathus gave
further support to this idea (Sztarker et al., 2005). In the present
study we found that the looming-sensitive neurons of the crab
resemble those of the locust in many aspects. In both animals
these neurons collect visual information from a large portion
of the retinotopic mosaic through a large dendritic tree located
in the lobula, and their axons project to the midbrain.
Functionally, these neurons respond vigorously to the approach
of dark objects towards the eye, with a response that continues
to increase as the object comes closer, as would occur during
imminent collision or during the strike of a predator. In both
animals the neurons are excited by translatory movements,
their response wanes to a repetitive stimulus and they are
almost insensitive to wide field image motion. In addition, they
respond more strongly to black than white expanding stimuli
or image contraction (e.g. Berón de Astrada and Tomsic, 2002;
Medan et al., 2004; Rind, 1987; Rind and Simmons, 1999) (see
results in the present paper).
In both locust and crabs there are two identified classes of
looming-sensitive neurons. Class M1 and class M2 of the crab
share features with class LGMD1 and class LGMD2,
respectively, of the locust. Like LGMD1, M1 do not fire in the
absence of visual stimulation, whereas LGMD2 as M2 both
have a significant resting spike discharge. The spontaneous
firing of LGMD2 and M2 generates in these neurons a faster
discharge rate than in LGMD1 and in M1 during object
approach and, unlike in LGMD1 and M1, they often exhibit a
hyperpolarization and reduction in spike rate at the end of
approach. The response of LGMD1 to approaches of objects
that subtend >5° at the eye usually comprise two peaks in the
spike rate (Rind and Simmons, 1992), and this feature is also
apparent in M1 neurons. During contraction of a dark image
both M1 and LGMD1 are often strongly excited for a brief
time, but such excitation is not found in M2 and LGMD2. In
addition, recordings from M1 and LGMD1 usually show an
abundant, sharp postsynaptic activity, which is not common to
M2 and LGMD2. To further appreciate the functional analogies
between the neurons from the crab and the locust, compare the
records of this paper with those previously published (Simmons
and Rind, 1997).
Despite the likeness in their general morphology and
similarity in their functional properties, the looming-sensitive
neurons of the crab and the locust differ in some important
aspects. In the locust, we know most about the LGMD1 neuron
and its involvement in the animal’s escape response. There is
only one single bilateral pair of these neurons, each one
covering the entire view of the eye ipsilateral to its lobula
projections. By contrast, the M1 class of the crab comprises 14
bilateral pairs (Sztarker et al., 2005), with receptive fields that
are distributed over the extensive visual field of the crab’s eye.
Assuming that the system of M1 neurons of the crab, like the
LGMD1 of the locust, participates in the escape behavior to
looming stimuli, it is reasonable to speculate about the
differences between the two looming-sensitive systems and the
characteristics of the behaviors with which they are involved.
Tethered flying locusts respond to an approaching object
with steering manoeuvres and eventually by switching to
gliding, which is thought to be a last-ditch effort to evade a fast
aerial predator (Santer et al., 2006). Thus, the gliding response
appears to represent a true fixed action pattern that is not
influenced by visual feedback. The control of such an all-ornone type of response does not require fine directional
adjustments and, therefore, could be achieved by a single pair
of neurons such as the LGMD1. In contrast, the response to
approaching objects in crabs consists of a run, in which
direction and speed are clearly influenced by continuous visual
feedback (Land and Layne, 1995b). In the absence of a nearby
shelter crabs run on a straight path away from the approaching
object, but readily change directions upon changes of its
direction of approach (e.g. Nalbach, 1990a; Land and Layne,
THE JOURNAL OF EXPERIMENTAL BIOLOGY
Looming detection in crabs
1995b). This fine directional tuning might require a system of
looming-sensitive neurons with differently oriented receptive
fields, i.e. an array such as that provided by the 14 pairs of M1
neurons found in Chasmagnathus.
In the locust, the exact mechanism by which the LGMD1
neuron encodes information about looming stimuli remains
contentious. Two current models predict how the output firing
of the LGMD1 represents a looming stimulus. One hypothesis
states that the LGMD1 acts as an angular threshold detector.
According to this model, postsynaptic multiplication of
excitatory and inhibitory inputs that converge onto the
LGMD1 produces a peak that occurs with a fixed delay after
the looming object reaches a fixed threshold angular size
(Gabbiani et al., 1999; Gabbiani et al., 2002). Accordingly,
peak firing occurs before collision (Hatsopoulos et al., 1995;
Gabbiani et al., 1999; Gabbiani et al., 2002). Another model
suggests that presynaptic inhibition shapes looming responses
of the LGMD1 (Rind, 1996), which produces a peak firing
rate after the object motion ceases (Rind and Simmons, 1999).
Thus, the debate between the two hypotheses mainly concerns
whether or not the peak of LGMD1 firing rate is the ‘essential
functional variable’ (see Rind and Santer, 2004) that triggers
the locust escape. It was shown recently that high-frequency
(>150·Hz) LGMD1 spikes (measured at its postsynaptic
DCMD neuron) are involved in triggering the glide response,
but the analyses could not identify any feature of the LGMD1
response alone that was reliably associated with glides in all
trials (Santer et al., 2006). This was because, for a glide to be
triggered, the high-frequency spikes must be timed
appropriately within the wingbeat cycle to coincide with wing
elevation. This means that the locust’s escape behavior can
vary in response to the same looming stimulus, so a predator
cannot exploit predictability in the locust’s collision
avoidance behavior (Santer el al., 2006). The lack of
predictability also makes it more complicated to relate a
certain threshold of the looming expansion with the actual
behavioral output.
At variance with the gliding response of the locust, which is
measured in terms of the probability of occurrence (Santer et
al., 2005; Santer et al., 2006), the escape run of the crab is a
graded response, the magnitude of which can be measured in
terms of the distance or the speed of the run. The onset of the
crab’s escape response occurs much earlier than the peak firing
rate of the M1 neurons, but their activity appears to convey
information on the speed of the escape run.
We thank Angel Vidal for technical assistance and Drs M.
Berón de Astrada and J. Sztarker for fruitful discussions and
corrections to this manuscript. We also wish to thank two
anonymous reviewers for providing valuable comments on an
earlier version of the manuscript. This work was supported by
doctoral fellowships from the National Research Council of
Argentina (CONICET) to D.O. and to V.M., and from the
following research grants to D.T.: Universidad de Buenos
Aires, grant number X 173; ANPCYT, grant number PICT
12300/02.
879
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