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First published online January 3, 2006
Journal of Experimental Biology 209, 327-342 (2006)
Published by The Company of Biologists 2006
doi: 10.1242/jeb.01982
Neural responses of goldfish lateral line afferents to vortex motions
1 Institute for Zoology, University of Bonn, Poppelsdorfer Schloss, 53115
Bonn, Germany
2 Institute Alfred Fessard, Centre National de la Recherche Scientifique,
91198 Gif sur Yvette, France
Author for correspondence (e-mail:
jacob.engelmann{at}uni-bonn.de)
Accepted 11 November 2005
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Key words: posterior lateral line, particle image velocimetry, teleost fish, Carassius auratus
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). The smallest
functional unit of the lateral line is the neuromast, a sensory structure that
consists of hair cells whose ciliary bundles project into a gelatinous cupula.
Lateral line neuromasts occur freestanding on the skin (superficial
neuromasts) and in lateral line canals (canal neuromasts). Whereas superficial
neuromasts are sensitive to water velocity, canal neuromasts respond to the
acceleration of the water (Kalmijn,
1988). Lateral line neuromasts contain two populations of hair
cells that are antagonistically orientated
(Flock and Duvall, 1965;
Flock and Wersäll,
1962a). A single afferent may innervate multiple hair cells, all
of the same orientation (Münz,
1979).
Vortex motions are one type of natural hydrodynamic stimuli. They occur,
for instance, behind inanimate objects exposed to water currents (Vogel,
1994). Trout make use of vortex motions for station holding
(Sutterlin and Waddy, 1975)
and for the reduction of the costs of locomotion
(Liao et al., 2003). Vortex
motions are also caused by undulatory swimming fish
(Blickhan et al., 1992;
Cheng and Chahine, 2001;
Drucker and Lauder, 1999;
Linden and Turner, 2004). For
piscivorous animals, vortex motions may be important for prey detection and
hydrodynamic trail following (Hanke and
Bleckmann, 2004; Hanke et al.,
2000). Seals (Dehnhardt et al.,
2001) and some fish (Pohlmann
et al., 2004; Pohlmann et al.,
2001) most likely use vortex information to track down prey.
We investigated how posterior lateral line nerve (PLLN) fibers responded to a vortex ring that passed the fish laterally. During stimulation, we visualized and quantified the water motions that occurred across the surface of the fish's body with particle image velocimetry (PIV). We found that afferents of the PLLN of the goldfish, Carassius auratus, respond to vortex motions with reproducible changes in discharge rate followed by less reproducible, long-lasting changes in neural activity. Early response components correlated with the direction of water motions that occurred at the position of the neuromast recorded from. By contrast, neural activity that occurred after the vortex ring had passed the fish barely predicted the local direction of water motions.
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)
positioned on a vibration-isolated table (TMC, LINOS Photomics GmbH,
Göttinghen, Germany) and fixed in a stainless steel holder. For
artificial respiration, a tube was inserted into the fish's mouth. To prevent
lateral movements of the fish, a cord was attached to its tailfin and taped to
the tank wall. A plastic cylinder, glued on the head of the fish, prevented
water from entering the brain cavity and allowed a complete submersion of the
fish (the distance between the water surface and the dorsal fin of the fish
was at least 1 cm).
Stimulation
We stimulated the lateral line with a sphere (diameter 6 mm) that was
attached with a stainless steel shaft (length 11 cm, diameter 0.2 cm) to a
Ling vibrator (Model V101; Peabody, MA, USA). Sine waves (50 Hz, 100 ms
rise/fall time, duration 1 s) were generated (Superscope II; Somerville, MA,
USA) and transferred via an A/D converter (MacAdios, Somerville, MA,
USA) to a custom-made dB-attenuator whose output was fed into a power
amplifier (PA 25; ELDS, Royston, England) that drove the vibrator. The
displacement amplitude of the sphere, calibrated in air with a microscope
(Laborlux K; Leitz, Leica, Bensheim, Germany), was varied between 1 and 100
µm.
If a nerve fiber was encountered that was sensitive to water motions, the
location of the vibrating sphere was slowly changed along the x-axis
(along the fish's body). This was done manually by moving a sliding plate to
which the vibrator was mounted. While moving, the position of the sphere along
the length of the fish (x-position) changed, whereas its distance
(z-position) and its elevation (y-position) remained
constant (cf. Fig. 1). The
x-position where the vibrating sphere appeared to elicit the
strongest response was assumed to be the rostro-caudal position of the
neuromast recorded from (hereafter referred to as neuromast). The receptive
fields of 25 nerve fibers, in addition, were precisely determined off-line.
Receptive field organization was used to determine the exact position and
orientation of the neuromast. Since the vibration axis of the sphere was
always parallel to the rostro-caudal axis of the fish, afferents that
innervate neuromasts with dorso-ventrally oriented hair cells should have
biphasic (two peaks of excitation separated by a 180° phase shift)
response patterns if the sphere moves along the side of the fish. By contrast,
tri-phasic response patterns (three peaks of excitation separated by two
180° phase shifts) should be generated by afferents that innervate
neuromasts with horizontally (rostro-caudally) oriented hair cells
(Coombs et al., 1996). The
phase of the stimulus to which lateral line afferents couple differs by
180° for biphasic responses, while the responses of tri-phasic afferents
show two consecutive phase changes of 180° each. From the physics of the
flow field of the dipole stimulus it can be concluded that the neuromast
innervated by an afferent with a biphasic receptive field is situated at the
position where the phase shift occurs; likewise, the position of a neuromast
innervated by an afferent with a tri-phasic response is situated in-between
the position where the two phase shifts occur
(Coombs et al., 1996).
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If a unit that responded to a passing vortex ring could be held long enough, it was also tested for flow sensitivity. Water flow was generated with a propeller (Schottelantrieb 100; Aeronaut, Wernberg-Köblitz, Germany) coupled to a DC motor (Conrad Electronic, Wernberg-Köblitz, Germany) that was driven by a power supply (DIGI 35; Voltcraft, Conrad Electronic, Wernberg-Köblitz, Germany). Water velocity, measured with an anemometer (CTA 90C10; Dantec, Skovlunde, Denmark), was adjusted to 10±0.5 cm s-1. All fish were positioned with their heads towards the flow.
Recordings
We used KCl (3 mol l-1)-filled glass microelectrodes (impedance
50–150 M
) to record single unit activity from PLLN fibers. Unit
activity was amplified (VF 180 Micro Electrode Amplifier; Biologic, Micro
Electrode Amplifier, Echirolles, France; bandpass 0–1 kHz and 50 Hz
notch-filter), displayed on an oscilloscope (DL1300A; Yokogawa, Amersfoort,
The Netherlands) and stored on a DAT-recorder (Dtr 1802, Biologic) for
off-line analysis.
Data analysis
Stored responses were high-pass filtered (3 Hz) and fed through a window
discriminator (Model 121; WPI, Sarasota, FL, USA) that delivered a square
pulse for each action potential. These pulses were digitised by an A/D
converter (MacAdios; 12 bit, sampling rate 2 kHz) and stored on disk. Data
analysis was carried out with customized scripts in Igor Pro 3.15 (Wavemetrics
Inc., Lake Oswego, OR, USA) or MatLab (The MathWorks Cooperation, Natick, MA,
USA). Peri-stimulus–time histograms (PSTH) and raster plots were
computed to analyze afferent responses that were classified by criteria
described in the Results.
Particle image velocimetry (PIV)
A custom-made PIV system was used to visualize and quantify water motions.
Neutrally buoyant particles (Vestosint 1101, Hüls, Berlin,
Germany)–suspended in the water–were illuminated with a 1 mm-thick
light sheet that was generated with a constant wave laser pointer
(Schwäbisch Gmünd; HB Components, Schwäbisch Gmünd,
Germany). If not otherwise stated, the light sheet was in a vertical
(x–y) plane, oriented parallel to the lateral surface
of the fish (see Fig. 1A). Due
to the curvature of the fish's body, the distance between the light sheet and
the fish varied between 1 mm (minimal distance) and 3 mm. The illuminated
particles were filmed with a CCD camera (DMK 803; frame rate 25 Hz; The
Imagingsource, Bremen, Germany) and stored on a video recorder (EV-S9000E Pal;
Sony, Tokyo, Japan) together with the electrophysiological data and the
trigger used to open the valve. Videos were digitised (DC 30; MiroVideo,
Pinnacles System, Mountain View, CA, USA), stored on disk and converted to
avi-movies (Premiere 6.0; Adobe Systems, Mountain View, CA, USA).
Individual pictures were taken with an exposure time of 1/250 ms at a frame
rate of 25 Hz, i.e. the temporal precision of the PIV analysis was 
40 ms.
For the construction of PIV-images, movies of particle motions were imported
frame by frame in Davis 7 (LaVision, Göttingen, Germany), and successive
frames were analyzed by a time-series sequential cross-correlation. The
interrogation window size for this cross-correlation was 64x64 pixels.
To improve the analysis, an overlap among neighboring interrogation windows
was applied, which resulted in a window size of 32x32 pixels.
Application of a multi-pass filter further reduced the error of the calculated
vectors. This filter executed iterative (N=2) evaluations of the same
pair of images. In the first pass, a vector was computed and used as a
reference for the following pass. In the second pass, the interrogation window
of the first frame was shifted by half the amount of the reference vector and
in the opposite direction while the interrogation window of the second frame
was shifted in the direction by half of the amount of the reference vector.
Thus, the correlation in the second pass anticipates the main motion direction
of the particles and adjusts the interrogation area such that the maximum
number of particles is included. This enhances the precision of the PIV.
Finally, a median filter was used to compute the median vector for eight
neighboring interrogation windows. If the center vector (surrounded by the
eight interrogation windows) differed by >3x root-mean-square from
the median vector, the center vector was replaced by the averaged vector
obtained from the neighboring interrogation windows. After this computation,
the vector plots were post-processed. We used the same median filter and
smoothing as during the computation of the vector plots.
Neural responses to a vortex ring were correlated with the water motions. To do so, 5–10 PIV images were averaged and compared with the PSTHs of the respective neural responses. Some afferents continued to fire reproducible bursts after a vortex ring had passed the fish. To find out whether these bursts correlated with hydrodynamic events, vector plots of the particle motions recorded immediately before and during a certain burst were compared. The same procedure was applied to afferents that displayed late non-reproducible bursts. Fast Fourier transformations (FFTs) of the discharge rates of individual units were calculated and compared with the FFTs of the corresponding water motions.
Vector plots
Local flow-direction was obtained from vector orientation. The direction of
a vector pointing from rostral to caudal was defined as 0°, while that of
a vector pointing in the opposite direction was ±180°. Vectors
pointing in a dorsal direction were given a positive sign (0° to
+180°), while those pointing in a ventral direction were given a negative
sign (0° to –180°). Thus, vector angles less than 90° and
greater than –90° indicated water motions in the head-to-tail
direction, while those greater than 90° and less than –90°
indicated water motions in the tail-to-head direction. In all measurements in
which PIV data and neuronal data were simultaneously recorded, the laser sheet
was oriented in a vertical plane parallel to the fish.
Stimulus measurements
In addition to the PIV analysis, water velocities were measured with a
constant temperature anemometer (CTA 90C10; Dantec, Scovlunde, Denmark).
Compared with PIV data based on a low frame rate (25 Hz), anemometer
measurements have a higher temporal resolution. We calibrated the anemometer
by moving its probe, attached to a motor-driven arm, with a defined speed
through the experimental tank (10 trials/speed). During measurements, the
orientation of the sensitive element (wire) of the anemometer was vertical.
The wire was positioned 1–2 mm lateral (z-axis) from the fish
and 5 cm away (x-axis) from the tip of the pipette that generated the
vortex rings. During anemometer measurements, a fish was positioned in the
flow tank. The pressure components of a vortex ring stimulus were measured
with a hydrophone (type 8103; Brüel & Kjaer, Nærum, Denmark),
placed at the same position as the probe of the anemometer
(Fig. 3A).
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120 ms (from
160 ms to 280 ms; Fig. 3A).
Following this opening, a symmetrical reversion of flow direction, i.e. the
closure of the vortex ring, started (time 400–520 ms). During this
closure, particles moved towards the jet flow. Thereafter, another reversal in
flow direction occurred (not shown). Hydrophone recordings, done simultaneously with the PIV measurements, revealed that the vortex ring also caused high-frequency pressure pulses. At peak pressure (Fig. 3B), which was associated with maximum flow velocity (Fig. 3C), the vortex ring reached the laser sheet. After the high-frequency pressure pulses, a less defined large drop in hydrodynamic pressure occurred, which reached its minimum 1600 ms after valve opening. The edge of the hydrophone was placed at the same x- and z-distance from the pipette as the neuromast in the physiological experiments. Thus, the hydrophone interfered with the water motions of the vortex ring. It is noteworthy that the vector pattern remained fairly symmetrical and that the edge of the hydrophone did not reach the central jet flow (Fig. 3A).
Based on anemometer measurements (Fig. 3C), the first changes in flow velocity occurred after 160–180 ms; peak water velocities could be measured after 250–270 ms. Thereafter, water velocity declined, and 6 s after valve opening water motions were no longer detectable. Both anemometer and hydrophone measurements (see small s.d. of graphs in Fig. 3B,C) confirmed that the stimulus was reproducible from trial to trial. In contrast to water (particle) motions, pressure changes were less reproducible.
The reproducibility of the particle (water) motions was also evident when we calculated all particle velocities obtained from a single vertical row of integration windows. In such a row, particle (water) velocities in individual trials were indistinguishable from those based on averaged trials [40 ms before valve opening, the mean water velocity (vector length) was 1.2 cm s-1 (single trial) and 1.1 cm s-1 (averaged trials) (Wilcoxon test, Z=–1.376, P=0.169); 200 ms after valve opening, the mean particle (water) velocity (vector length) was 3.4 cm s-1 (single trial) and 3.0 cm s-1 (averaged trials) (Wilcoxon test, Z=–1.07, P=0.285)].
Forty milliseconds before valve opening, the orientation of vectors based on single trials (mean=56°) differed from the orientation of vectors based on averaged trials (mean=62°; Wilcoxon test, Z =–2.395, P=0.01). By contrast, 200 ms after valve opening, vector orientations based on single trials (mean=–59°) were indistinguishable from vector orientations based on averaged trials (mean=40°; Wilcoxon test, Z=–1.478, P=0.14). Thus, both vector length (particle velocities) and vector orientation (direction of particle motion) were reproducible from trial to trial. However, it should be mentioned that in the physiological experiments the vortex ring stimulus was altered by the presence of the fish. This was especially true in the experiments in which the lateral distance between the pipette tip and the fish was only 0.5 cm. However, as will be detailed below, the discharge patterns of the primary lateral line afferents evoked by the vortex stimulus remained fairly constant up to the lateral distance of 3.5 cm of the pipette tip. Therefore, the presence of the fish cannot have altered the vortex ring stimulus completely. Nevertheless, in the following, we prefer the term `vortex stimulus' instead of vortex ring stimulus.
Physiology
Single unit recordings were made from 96 afferents in the left
(ipsilateral) PLLN of 18 goldfish. Seventy-three afferents responded to water
motions; the remaining 23 afferents did not respond to the stimulus and were
discarded from further analysis. The ongoing activity of all afferents that
responded to water motions was determined, and the responses of these
afferents to vortex stimuli [N (total number of fish) = 16;
n (total number of cells) = 69] were investigated. If possible, we
also investigated the responses of these afferents (N=14;
n=41) to unidirectional water flow (10 cm s-1). Twenty-six
(63%) afferents significantly increased their discharge rate if exposed to
unidirectional water flow (Wilcoxon test, P
0.01) and were thus
classified as type I afferents (Engelmann
et al., 2000). The remaining 15 afferents (37%) were insensitive
to unidirectional water flow (Wilcoxon test, P0.01) and were thus
classified as type II afferents (Engelmann
et al., 2000). Ongoing activity of type I afferents
(19.3±10.6 spikes s-1) was not significantly different from
the ongoing activity of type II afferents (18.7±14.9 spikes
s-1; Mann–Whitney U-test, U=181;
Z=–0.379, P=0.72).
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All (n=69) but seven primary afferents responded to a vortex stimulus that passed the fish laterally. Four of the unresponsive afferents also failed to respond to a stationary dipole stimulus (duration 1 s, frequency 50 Hz, peak-to-peak displacement amplitude 100 µm) but responded to water motions caused by a pipette that was moved manually along the side of the fish. The remaining three afferents showed no responses to any of the hydrodynamic stimuli applied. In four afferents that responded to the vortex, even the initial responses were not reproducible across stimulus presentations. Therefore, these afferents were not further investigated. The remaining 58 afferents responded to the vortex with repeatable discharges. Controls (n=12) showed that the responses were caused by water motions and not by electrical or mechanical artifacts caused by valve opening.
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Afferents that responded with an initial increase in discharge rate were classified as E-afferents (n=34; Fig. 4A), while those that responded with an initial decrease in discharge rate were classified as I-afferents (n=24; Fig. 4B). Afferents responded with distinct temporal discharge patterns. To classify these discharge patterns, we analyzed the PSTHs (bin width 20 ms). To be scored as a response, neural activity had to differ from ongoing activity plus/minus three times its standard deviation–measured for 1 s immediately before valve opening–for at least 40 ms. Response duration was defined as the time between first and last threshold crossing. Responses to the vortex stimulus consisted of an initial reproducible component and a late less-reproducible component. The initial reproducible component was characterized by 1–3 predictable changes (increases or decreases; see above) in neural activity. We determined the maximum discharge rate and the latency of the initial response component.
The initial reproducible response component lasted for 300 ms. PIV
data (see below) revealed that the initial response component occurred while
the vortex stimulus passed the fish. By contrast, the late response component
coincided with the less-reproducible water motions that occurred after the
vortex stimulus had passed the neuromast; this was confirmed by calculating
the mean cross-correlation coefficient between every pair of five consecutive
responses for 12 randomly chosen cells (see cross-correlation data in
Fig. 4B, right).
Cross-correlation coefficients were 0.10±0.09 (mean ± s.d.) for
the 300 ms preceding valve opening (control), 0.32±0.08 for the 300 ms
following valve opening and 0.20±0.11 for the next 300 ms following
valve opening. Thus, for the time spans selected, reproducibility was highest
for the 300 ms directly following valve opening.
The late response component of E- and I-afferents lasted for 2 s (in
four cases for up to 6 s) and consisted of several bursts. As revealed by
cross-correlation analysis, the occurrence of these late bursts was usually
ill defined, i.e. they occurred at unpredictable times (e.g. Figs
4,
7,
8,
9,
12). However, in four
afferents, the late bursts were reproducible (e.g.
Fig. 11).
With respect to valve opening, E-afferents responded with a latency of 117±74 ms (n=34), I-afferents had a latency of 128±44 ms (n=24). Latencies of E- and I-afferents were not significantly different (Mann–Whitney U-test, U=306.5, Z=–1.603, P=0.11). Maximum discharge rates occurred later in I-afferents than in E-afferents; however, in terms of peak discharge rates, I- and E-afferents were not different (Table 1).
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Afferents were or were not sensitive to unidirectional water flow. There was no correlation between flow sensitivity and response type. Out of the 41 afferents tested, 26 were flow sensitive (16 E-afferents, eight I-afferents, two undefined) and 15 were flow insensitive (four E-afferents, six I-afferents, five undefined). Neither response duration (Mann–Whitney U-test, U=111; Z=–0.340, P=0.75; type I afferents, 810.1±823.6 ms; type II afferents, 874.8±659.8 ms) nor the duration of the initial response component (Mann–Whitney U-test, U=110; Z=–0.379, P=0.72; type I afferents, 102.2±68.3 ms; type II afferents, 94.0±67.4 ms) was significantly different in type I and type II afferents.
Lateral pipette tip distance and afferent responses
Due to the curvature of the fish, the distance between the opening of the
pipette tip and the fish was not constant along the length of the fish.
Therefore, we investigated the influence of the lateral distance of the
pipette tip (distance along the z-axis) on the responses of 10 E- and
four I-afferents (test range 0.5–5.5 cm).
Up to a lateral distance of 3.5 cm, the temporal response patterns of lateral line afferents remained fairly constant (Fig. 5A). A linear regression analysis revealed that the latency of the initial response component increased with increasing lateral tip distance (E-afferents, k=114.89+35.89z, r2=0.39, P<0.01; I-afferents, k=106.93+27.76z, r2=0.43, P<0.01; Fig. 6A). In E-afferents, both the latency of the first response peak (k=163.42+32.7z, r2=0.37, P<0.01; Fig. 6B; I-afferents were not investigated) and the latency of the maximum response peak (which may be identical with the first response peak; k=216.1+30.2z, r2=0.28, P<0.01) also increased with increasing lateral distance of the pipette tip. By contrast, neither the duration of the initial response component nor the duration of the total response changed in E-afferents (duration of the initial response component, d=98.8–6.2z, r2=0.05, P=0.12; duration of the total response, d=1915.4–82.8z, r2=0.01, P=0.43) and I-afferents (initial response, d=56.9–1.1z, r2=0.005, P=0.84; total response, d=1218.4+112.6z, r2=0.03, P=0.55). In E-afferents, there was no correlation between lateral tip distance and peak amplitude of the first response component (d=28.2–1.6z, r2=0.039, P=0.18). Thus, with increasing lateral tip distances, afferent responses were increasingly delayed, yet peak response amplitudes and response durations were not altered.
Neural responses and water motions
To investigate the relationship between neural activity and water motions,
we correlated PIV data with the neurophysiological data. The vector plots in
Figs 7,
8 are based on particle motions
recorded 40 ms before response onset, at the first and second crossing of
response threshold and 200 ms after the first threshold crossing, i.e. at the
time when the ill-defined response component occurred. The responses of an
E-afferent to the vortex stimulus are shown in
Fig. 7A. At the rostro-caudal
position of the neuromast (see gray bars in the fish drawings of
Fig. 7A), a water flow from
anterior to posterior correlates with an increase in neural activity. After
this initial increase in neural activity, flow direction started to reverse.
This reversal correlates with a decrease in neural activity, followed by
several less reproducible excitatory response components. The responses of an
I-afferent are depicted in Fig.
8. At the rostro-caudal position of the neuromast (see gray bars
in the fish drawings of Fig.
8A), water flow from anterior to posterior correlates with a
decrease in neural activity. After this initial decrease, flow direction
reversed. This reversal correlates with a strong increase in neural activity,
followed by less reproducible excitatory response components. Thus, the neural
responses reflect the directional sensitivity of lateral line afferents (hair
cells). The correlation between the direction of particle motions and
discharge rates was investigated in greater detail in six afferents that
innervated neuromasts whose rostro-caudal positions were precisely determined
off-line (see Materials and methods). For the time of the initial
increase/decrease and the following decrease/increase in neural activity, we
calculated the mean flow (vector) orientation for the PIV column depicted by
the gray bar (for an example, see Fig.
9). A change from a decrease to an increase (or vice
versa) in neural activity was accompanied by a 163.5±15.9°
(mean ± s.d.; n=6, Wilcoxon test, P<0.001) change
in flow direction. This shows that flow direction reversed between the first
and the second initial response component.
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We also analyzed whether the late response component (late bursts) also
correlated with flow patterns. In four cells, the late response component
consisted of reproducible bursts. However, in none of these cells did neural
activity predict flow direction (Wilcoxon test, n=4,
P0.2; e.g. Fig.
11). Thus, in contrast to the initial and reproducible response
components, there was no correlation between the occurrence of late and
reproducible bursts and flow direction. However, an FFT analysis revealed that
both discharge rates and water accelerations had prominent peaks at 3 and 8 Hz
(see Fig. 11C). This indicates
that the occurrence of late and reproducible bursts was partly due to
alterations in local flow direction.
In most cells, the late response component did not show any reproducible
bursts. In two of these cells, we investigated whether there was a correlation
between flow direction and neural activity. In the two cells analyzed, changes
in the initial response again correlated with a reversal in flow direction.
However, changes in flow direction occurred neither at the beginning nor at
the end of a late burst (a total of seven late bursts per cell were analyzed;
Wilcoxon test, P0.2 performed on averaged vector plots;
Fig. 12). Thus, in none of
these cells did neural activity predict flow direction.
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). In
agreement with Engelmann et al.
(2002), we found
flow-sensitive and flow-insensitive PLLN-afferents. Although we especially
searched for flow-insensitive (type II) afferents, the ratio between
flow-sensitive and flow-insensitive afferents was 26:15. This ratio is in line
with former studies (Engelmann et al.,
2002) and the finding that goldfish have much more superficial
than canal neuromasts (Puzdrowski,
1989).
In many studies, well-defined water motions, generated by a stationary
sphere that vibrated with a constant amplitude and frequency, were used as a
lateral line stimulus (Flock and
Wersäll, 1962b; Harris
and van Bergeijk, 1962; Kroese
et al., 1978; Bleckmann et al.,
1989). To generate more complex (and presumably more natural)
water motions, small objects passing the fish laterally were introduced as a
stimulus source (Bleckmann and Zelick,
1993; Mogdans and Goenechea,
1999; Müller et al.,
1996; Plachta et al.,
2003). In the present study, a vortex that passed the fish
laterally served as a hydrodynamic stimulus. Under natural conditions, many
fish are exposed to vortex rings or individual vortices that occur behind
stationary objects or in the wake of swimming fish
(Bleckmann et al., 1991;
Blickhan et al., 1992;
Cheng and Chahine, 2001;
Drucker and Lauder, 1999,
2000;
Rosen, 1959). Behavioral
sensitivity of fish to such vortices has been documented
(Tou, 1991). For piscivorous
fish, the detection of vortices may be of importance for prey detection and
hydrodynamic trail following (Hanke et
al., 2000; New et al.,
2001). Catfish (Pohlmann et al.,
2001,
2004) and seals
(Dehnhardt et al., 2001) may
use information preserved in vortices to track down prey. Thus, vortices are
of biological significance.
Neural responses to vortices
Peripheral lateral line units of goldfish responded with fairly predictable
discharges to the vortex stimulus. With four exceptions, the initial response
patterns were monophasic, biphasic or triphasic. Monophasic responses
consisted of one increase or decrease in neural activity that often was
followed by a weak decrease or increase in discharge rate. However, the second
change in neural activity did not match our threshold criteria. Biphasic
responses consisted of an increase in ongoing activity followed by a decrease
in discharge rate or vice versa. In triphasic responses, an
additional reproducible change in neural activity occurred. Thus, the initial
responses of goldfish lateral line afferents to the vortex stimulus compare
well with the initial responses of many PLLN-afferents to an object passing
the fish laterally (Mogdans and Bleckmann,
1998). With respect to the initial response component, different
lateral line afferents may show a reversed temporal response pattern to a
moving object or to a passing vortex. In addition, the initial reproducible
response pattern of most PLLN-afferents reversed if the direction of object
motion was reversed (Bleckmann and Zelick,
1993; Engelmann et al.,
2003; Mogdans and Bleckmann,
1998). Most likely, these findings can be explained by the
directionality of lateral line hair-cells (e.g.
Flock and Wersäll, 1962a;
Görner, 1963). Since
lateral line neuromasts contain two populations of hair cells that are aligned
in opposite directions, and since individual lateral line afferents innervate
only hair cells of the same alignment, one expects that different afferents
may respond in directly opposite ways to the same moving object stimulus. The
antagonistic orientation of hair cells in the sensory epithelium of a lateral
line neuromast also implies that the response patterns of lateral line
afferents invert when flow direction reverses.
If stimulated with water motions caused by a moving object, lateral line
units assumed to receive input from superficial neuromasts continued to fire
unpredictable bursts of spikes after the object had passed the fish laterally
(Bleckmann and Zelick, 1993;
Engelmann et al., 2003;
Mogdans and Bleckmann, 1998).
Moving objects not only generated initial reproducible water motions but also
late water oscillations that were less predictable. These late water
oscillations most likely caused the late ill-defined response bursts
(Mogdans and Bleckmann, 1998).
Using our stimulus, many type I and type II PLLN-afferents continued to fire
unpredictable bursts long after the vortex had passed the fish. Thus, both
flow-sensitive and flow-insensitive afferents responded similar to the vortex
stimulus.
Correlation of neural responses with PIV data
If one wants to correlate neural responses with the water motions that have
caused these responses, a precise determination of the position of the
neuromast is crucial. We did not attempt to determine the dorso-ventral
position of the neuromast since the water motions caused by the vortex
stimulus were fairly symmetrical across the dorso-ventral extent of the fish
(e.g. Fig. 2). Therefore, the
dorso-ventral position of the neuromast most likely had little influence on
the afferent responses. However, with respect to the long axis of the fish, we
precisely determined the position of the neuromast in 25 cases. In 12 of these
cases, we compared the PIV data with the neural data of afferents whose
receptive fields had been determined precisely off-line.
Our PIV measurements confirmed that the passing of the vortex stimulus from
rostral to caudal caused either an E- or an I-response in a given afferent
(see Figs 10,
11). This supports the
assumption that, all else being equal, the temporal response pattern of an
afferent depends on the orientation of the hair cells innervated by that
afferent. For the initial reproducible response component, our PIV
measurements show, in addition, that an inversion in flow direction caused an
inversion in the temporal characteristics of the neural response. To our
surprise, there was no or, at best, a weak correlation between the late
ill-defined response component and the water motions recorded simultaneously.
One possible explanation is that the distance between the laser sheet and the
surface of the fish was >1 mm. Due to reflections of the laser sheet and
the curvature of the fish, smaller distances were not possible. Since lateral
line cupulae have a length of <1 mm
(Teyke, 1990), we were unable
to monitor the water motions in their immediate vicinity. Hence, we cannot
rule out that the water motions responsible for the neural responses were not
always identical with the particle motions measured in the light sheet. The
lack of correlation between particle motions and the late response component
may also be due to undetected minor alterations in water velocity and/or flow
direction, i.e. changes exceeding the spatial and/or temporal (25 Hz)
resolution of our PIV system.
One can expect that the neural response of primary lateral line afferents
correlates well with the velocity and the direction of the water motions that
impinge on a neuromast (e.g. Flock, 1962;
Görner, 1963). However,
if we record from central lateral line units, i.e. from lateral line units
that may receive input from several neuromasts distributed across a larger
part of the fish's body, this method may be very helpful in uncovering the
complex spatio-temporal flow patterns that may be necessary to drive some
central units. Future experiments will show whether this prediction is
correct.
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Acknowledgments |
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Footnotes |
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* Authors contributed equally to this research 
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References |
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TOPSummaryIntroductionMaterials and methodsResultsDiscussionReferences |
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