Brainstem lateral line responses to sinusoidal wave stimuli in still and running water
Institut für Zoologie, Universität Bonn, Poppelsdorfer Schloß, D-53115 Bonn, Germany
* Author for correspondence (e-mail: kroether{at}uni-bonn.de )
Accepted 11 March 2002
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Summary |
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Key words: lateral line, medial octavolateralis nucleus, neuromast, hydrodynamic stimuli, background noise, goldfish, Carassius auratus
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Introduction |
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The sensory organs of the lateral line are the neuromasts, which can be
distributed across the entire fish body
(Northcutt, 1989). Each
neuromast consists of a patch of hair cells underneath a gelatinous cupula.
Two types of neuromast can be distinguished: superficial neuromasts (SN),
which occur freestanding on the surface of the skin, and canal neuromasts
(CN), which are recessed in subepidermal canals (e.g.
Münz, 1979
;
Webb, 1989
;
Song and Northcutt, 1991
).
Neuromast function has been studied in a still-water environment in various
ways: by direct observation of cupula motion (Denton and Gray,
1988,
1989
), or by recording from
lateral line hair cells (e.g. Harris et
al., 1970
), or by recording neural activity of primary afferent
fibers in response to the water motions caused by a stationary vibrating
sphere, i.e. a dipole stimulus (e.g.
Münz, 1985
;
Kroese and Schellart, 1992
;
Coombs and Janssen, 1990
;
Coombs and Montgomery, 1992
;
Montgomery and Coombs, 1992
;
Wubbels, 1992
;
Montgomery et al., 1994
). The
latter studies revealed that the response of the fibers innervating
superficial neuromasts is approximately proportional to the relative velocity
of the fish and the surrounding water; thus superficial neuromasts function as
velocity detectors. Lowest displacement thresholds are in the frequency range
20-60 Hz. In contrast, the response of fibers innervating canal neuromasts is
largely proportional to net water acceleration; thus canal neuromasts function
as acceleration detectors. In addition, canal neuromasts function as high-pass
filters and have minimal displacement thresholds in the frequency range 60-120
Hz.
Afferent fibers that innervate superficial and canal neuromasts exhibit
different sensitivity to running water
(Engelmann et al., 2000;
Voigt et al., 2000
). Fibers
innervating superficial neuromasts are flow-sensitive, with increased ongoing
discharge rates in running water. In contrast, fibers innervating canal
neuromasts are flow-insensitive, i.e. with comparable ongoing discharge rates
in still and running water.
Engelmann et al. (2000)
were the first to record the responses of primary lateral line afferent fibers
to a stationary vibrating sphere in running water. They found in goldfish that
fibers innervating superficial neuromasts respond highly sensitively to a
vibrating sphere only in still water. In running water responses were masked,
because superficial neuromasts were permanently stimulated by the background
water flow. Responses of fibers innervating canal neuromasts to the vibrating
sphere were barely affected by running water, indicating that canal neuromasts
act as high-pass filters. Thus, in addition to the morphological separation,
there is a clear functional separation of the peripheral lateral line.
The sensory information that is represented by the activity of primary
afferent fibers is processed by neurons in the medial octavolateralis nucleus
(MON) in the fish brainstem (Puzdrowski,
1989; New et al.,
1996
). Studies using vibrating sphere stimuli have shown that many
MON units exhibit primary-like responses and receptive fields; the latter may
be explained by the processing of peripheral input through a lateral
inhibitory network (Coombs et al.,
1998
). Receptive fields that are completely unlike those of
primary afferents can also be found among MON units
(Mogdans and Kröther,
2001
). Studies in which the lateral line was stimulated with water
motions generated by a moving object indicate that MON neurons integrate
information from many neuromasts, which may be distributed across large
portions of the lateral line periphery
(Mogdans et al., 1999
;
Mogdans and Goenechea, 2000
).
Thus, there are at least two channels in the lateral line brainstem, one to
process local hydrodynamic information generated, for example, by a vibrating
source, and another to process more complex water motions such as those
generated by a moving source (Mogdans and
Goenechea, 2000
). However, the extent to which the functional
separation of the lateral line periphery
(Engelmann et al., 2000
) is
maintained in the brainstem is unknown. To answer this question, we studied
how the responses of goldfish MON units to a stationary vibrating sphere are
affected by running water.
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Materials and methods |
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Stimulation
Sinusoidal water motions were generated by a stationary vibrating sphere (8
mm diameter). The sphere was attached to a minishaker (LDS V101) by a
stainless steel rod (2 mm diameter, 17 cm length). The shaker was driven using
a 50 Hz signal (duration 1 s, rise/fall time 100 ms) generated by a computer
(Power Macintosh) and read through a 14-bit D/A converter at a rate of 8 kHz
(Instrunet 100B, GWI). Signals were power-amplified (LDS PA25e) and attenuated
(custom-built attenuator) before being passed to the minishaker. The
minishaker was mounted to a sliding bar assembly outside the tank, which
allowed adjustment of sphere elevation and location along the side of the
fish. The axis of sphere vibration was parallel to the long axis of the fish.
The distance between the sphere and the fish was 6-7 mm. For calibration,
sphere vibration in water was filmed using a video camera (see
Mogdans and Kröther,
2001). Peak-to-peak (pp) displacements at the skin of the
fish were calculated using the equation given by Harris and van Bergeijk
(1962
). According to this
equation, a sphere displacement of 100 µm, for example, resulted in a water
displacement of 8.8 µm at the surface of the fish.
Water flow was generated using a model ship's propeller (8 cm diameter
driven by a d.c. motor (Conrad Electronics) connected to a power supply
(Voltcraft Digi 35, Conrad Electronics). The ship's propeller was suspended
from a holder and moved the water on the side of the flow tank that was
opposite to the side containing the fish. The water was passed through a flow
collimator (15 cmx13 cm row of straws, 5 mm diameter, 15 mm length)
before reaching the fish. Water velocities were calibrated without the fish in
the experimental tank using particle image velocimetry (see
Hanke et al., 2000). Water
velocities generated at the site of the fish ranged from 1.7 cm s-1
to 19.4 cm s-1.
Data acquisition
Neural activity from single units in the MON was recorded with glass
micropipettes filled with an indium alloy (Small Parts Inc.) and plated with
platinum chloride (1-4 µm tip diameter, 2-4 M impedance). Electrodes
were advanced through the plastic cylinder that was mounted on top of the
animal's head and placed on the surface of the brainstem with a
micromanipulator. Electrodes were advanced through brain tissue in small (2-10
µm) steps using a motorized microdrive (Nanostepper NPC, Science Products
Trading). Recorded activity was amplified (DAM 80, WPI), filtered (0.30-1
kHz), fed through a noise eliminator (Hum Bug, Quest Scientific), and passed
through a window discriminator (WPI 121), which generated a 5 V pulse for each
action potential above a selected level. Pulses were digitized (Instrunet
Model 100B, 14-bit resolution, 8 kHz sampling rate), monitored and stored on a
Power Macintosh using data acquisition software (SuperScope II, GWI). Original
recordings were stored on a digital tape recorder (ZA5ES, Sony in combination
with DTR 1802, Biologic).
Stimulation protocol
To search for lateral line units, the sphere was vibrated with a constant
pp displacement of 2700 µm and positioned at various locations along
the side of the fish. A water flow velocity of 15.5 cm s-1 was also
used. In addition, units were searched by moving the minishaker and thus the
attached sphere manually along the side of the fish. If a unit responded to
any of these stimuli, we tested whether it responded to airborne sound
(clapping hands, shouting) or to vibrations generated by tapping against the
tank walls. Units that responded to sound or vibration were assumed to receive
input from the inner ear and were not investigated further.
Units that responded to the moving sphere and/or to running water but not to the vibrating sphere were also not investigated further. In units which responded to the vibrating sphere the receptive field was determined crudely by moving the vibrating sphere along the side of the fish and monitoring response strength by listening to the audiomonitor. The sphere was then placed where the strongest response (in some cases, the strongest reduction of neural activity) was elicited. With the sphere at this location, the unit's level-response function was measured in 2-5 dB steps in still water. For each displacement amplitude tested, unit responses to 20 repetitions of the 50 Hz stimulus, presented at a repetition rate of 0.4 Hz, were recorded. Then, water flow was initiated (flow velocity 15.5 cm s-1) and the level-response function was measured in running water. Finally, the level-response function was measured again in still water to check that the unit's responsiveness had not changed. Then, the displacement amplitude was adjusted to 2700 µm pp and the unit's response to the vibrating sphere was recorded in still water and in water running at flow velocities between 1.7 and 19.4 cm s-1.
To measure unit responsiveness to running water, the nonvibrating sphere was placed at least 10 cm behind the fish and water flow was initiated by starting the motor driving the model ship's propeller. After approximately 10 s, neural activity was recorded for 60 s (20 consecutive data traces, each of 3 s duration), during which the water velocity remained constant. Then, flow velocity was increased to a higher value and unit activity was recorded again for 20x3 s. Using this protocol, unit activity was recorded with flow velocities between 1.7 and 19.4 cm s-1.
To test for transient effects on unit responses caused by the onset and end of the water flow, unit activity was recorded for 1-2 min while the water was still, then flow was turned on and activity was recorded for another 2-4 min, after which the motor driving the model ship's propeller was turned off and unit activity was recorded for an additional 2-4 min.
Data analysis
Data were obtained from 46 lateral line units. Responses to the vibrating
sphere were quantified by the average firing rates (spikes s-1)
during sphere vibration, the average phase angle (degrees) of each spike with
respect to the signal delivered to the vibrator, the degree of phase-locking
(synchronization coefficient R) and the Rayleigh statistic
Z. Average firing rate was determined from the number of spikes
elicited during the 20 stimulus presentations and compared with the average
ongoing firing rate during a 1 s period, starting 1 s after sphere vibration
had ended. Spike numbers during these 1 s periods were averaged across the 20
stimulus traces. Previous measurements of the water motions generated by our
vibrating sphere showed that the time waveforms of the water motions
reproduced the electrical signal that was delivered to the vibrator and that
water motions after stimulus end did not last longer than approximately
200-300 ms (Plachta et al.,
1999).
The time of occurrence of each action potential during stimulus
presentation was determined with respect to each cycle of the 50 Hz signal and
used to calculate the corresponding phase angles. From these data, the mean
phase angle and the synchronization coefficient R (vector strength,
after Goldberg and Brown,
1969) were calculated. The direction of the vector describes the
average phase angle to which a unit responds and its magnitude describes the
strength of phase-locking. A vector strength of 1 indicates that all spikes
occured at the same phase angle. The Rayleigh statistic Z was used to
determine whether measures of vector strength were statistically significant:
Z=R2N, where N=total number of spikes
(Batschelet, 1981
). Z
values above 4.6 indicate a probability of 0.01 or less that spikes were
randomly distributed during a vibration cycle.
To further characterize unit responses, the slopes of the level-response functions (ongoing rates subtracted) were determined at the steepest part of each function. To determine threshold, evoked rates (ongoing rates subtracted) were normalized and threshold was defined as the displacement amplitude that elicited 10 % of the maximum response when a unit responded with an increased rate, or 10 % of the minimum response when a unit responded with a decreased rate.
In 30 units, responses to running water were quantified by the average
firing rates (spikes s-1) during each 60 s period of constant water
velocity (see Stimulation protocol). To compare neural activity in still and
running water, the number of spikes during each 3 s trace was determined.
Spike counts for the 20 traces that were recorded at a given water velocity
were compared with spike counts for 20 traces recorded in still water
(Wilcoxon-test, P0.01). 16 units were lost before this test was
completed, and their responses to running water were quantified by the units'
ongoing activity in running water (see above) with the vibrating sphere (2700
µm displacement) placed 6-7 mm away from the fish. Units were defined as
flow-sensitive if discharge rates increased or decreased with increasing flow
velocity and, from a particular unit-specific flow velocity on, were
significantly different (P
0.01) from the discharge rates in still
water. In three units, which were clearly flow-sensitive at velocities between
4 and 12 cm s-1, discharge rates in running water were comparable
to those in still water at the highest flow velocities tested.
For each unit, discharge rates measured in the presence of a constant water flow were plotted as a function of flow velocity and a linear regression was fitted to the data (data points above rate saturation were excluded). The slope of the regression line was used as a measure of the degree of flow sensitivity (Fig. 1A).
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One unit apparently did not show increased or decreased activity in the presence of a constant water flow. However, plotting the peri-stimulus time (PST) histogram (bin width 1 s) revealed a transient response to the onset of the water flow. The unit was thus considered flow-sensitive.
Masking of responses to the vibrating sphere
To determine whether the responses of a given unit to the vibrating sphere
were affected by running water, level-response functions measured in still and
running water were compared. For this analysis, ongoing discharge rates were
subtracted from stimulus-evoked discharge rates. Firing rates and
synchronization coefficients (R values) were then plotted as a
function of sphere displacement and linear regressions were fitted to the data
(Fig. 1B,C). Data points below
threshold and above saturation and R values that were not
statistically significant (Z4.6) were omitted for this analysis.
Regressions obtained under still and running water conditions were compared by
analysis of covariance (ANCOVA, P
0.01). Responses to the
vibrating sphere in running water were defined as masked if the regression
fitted to firing rates or to the synchronization coefficients or both had
shallower slopes or were shifted towards lower values compared to the
corresponding regressions in still water.
To determine the degree of masking, level-response functions for both spike rates (ongoing rates subtracted) and synchronization coefficients were integrated (Fig. 1B,C). Integrals of response functions measured in running water were expressed as a percentage of the integrals of response functions measured in still water. In a few cases this method yielded negative percentages because the ongoing rates in running water, on average, were slightly greater than evoked rates. Since in these cases masking was complete, the per cent integral was set to zero.
Five units were lost before level-response functions in still and running
water were completely measured. In these units, regression analysis was not
possible and masking was determined by comparing firing rates in response to a
given displacement amplitude in still and running water using the
Wilcoxon-test (P0.01).
To test for differences between unit populations (see Results), regression
line slopes and per cent integrals were compared using the MannWhitney
U-test for independent samples (P0.01).
Verification of recording sites
In 11 fishes, a total of 19 electrolytic lesions were placed at
physiologically characterized recording sites by passing a small current for
26 s through the electrode tip. Fish were deeply anesthetized with MS-222
(tricaine methane sulfonate) and perfused intracardially with a physiological
salt solution (Oakley and Schafer,
1978) followed by 4% glutaraldehyde solution in 0.1 mol
l-1 phosphate buffer (pH 7.4). Brains were removed, postfixed and
cut at 15 µm in a transverse plane parallel to the electrode penetrations.
Sections were stained with Cresyl-Violet, analyzed under a microscope and
lesions reconstructed with the aid of a computer (Macintosh PPC) and Photoshop
4.0 software. 17 lesioned recording sites were identified in transverse
sections of the brain. All lesions were located dorsally in the MON, just
below the cerebellar crest, indicating that recordings were made in the crest
cell layer (New et al., 1996
).
Representative sections through the brainstem of a goldfish with a lesion in
the MON have been published previously (e.g.
Mogdans and Goenechea, 2000
;
Mogdans and Kröther,
2001
).
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Results |
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Analysis of PST histograms revealed a variety of patterns comparable to
those described previously (Mogdans and
Goenechea, 2000; Mogdans and
Kröther, 2001
). If displacement values were used that caused
rate saturation, responses were either sustained for the duration of the
stimulus (N=20) or adapting (N=24), i.e. after an initial
response peak, discharge rates returned to pre-stimulus levels. 30 units had
robust phase-locking, R>0.5. In 16 units, phase-locking was rather
weak, R
0.5. Due to fairly shallow rate-level slopes, on average,
maximum evoked rates were only approximately twice as large as ongoing rates
(Table 1).
Sensitivity to running water
Sensitivity to running water was determined by recording ongoing unit
activity in running water with the non-vibrating sphere placed 10 cm behind
the fish. 31 units (67 %) were flowsensitive, i.e. ongoing rates in running
water were significantly different from those in still water. In 17 of these
units discharge rate increased (Fig.
2A), and in 11 units discharge rate decreased with increasing
water velocity (Fig. 2B). In
three units, discharge rate initially increased with increasing water velocity
to a maximum and then decreased (Fig.
2A, broken lines). 15 units (33 %) did not respond to running
water at any of the velocities tested and were thus considered
flow-insensitive (Fig. 2C).
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Transient effects caused by the onset and end of water flow were studied in 12 units. In 10 units, discharge rates increased (N=6) or decreased (N=4) shortly after water flow was initiated and remained at an elevated (or reduced) level of activity for the time period during which water was flowing (Fig. 3A). In three of these units, increases and decreases in discharge rate were more strongly pronounced during a transient period shortly after flow onset than during the remaining time of water flow (Fig. 3B). When the water flow was turned off, discharge rates returned to levels that were comparable to those in still water. One unit responded to the onset of water flow with a transient increase, and another with a transient decrease in discharge rate, i.e. neural activity returned to still-water levels while the water was still flowing (Fig. 3C).
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Responses to the vibrating sphere in running water
Three main types of units were distinguished on the basis of their
responses to running water and the masking of the responses to the vibrating
sphere by running water.
Type I units (N=27) were flow-sensitive, i.e. they exhibited increased or decreased levels of activity in running water (see Fig. 2A,B). The responses of type I units to the vibrating sphere were masked by runnning water either in terms of spike rate (N=17) or both spike rate and phase-coupling (N=10). In Fig. 4, data are shown from a type I unit that responded to the vibrating sphere in still water with an increase in discharge rate. With increasing displacement amplitude of the vibrating sphere, the number of spikes increased, whereas the degree of phase-locking to the stimulus (synchronisation coefficient R) remained low (Fig. 4, left). In running water, ongoing discharge rate was increased. The response to the vibrating sphere, however, was no longer apparent (Fig. 4, right). Consequently, level-response functions measured in running water differed from those measured in still water in terms of both spike rate and phase-locking.
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Type II units (N=7) were flow-insensitive, i.e. they did not respond to running water (e.g. Fig. 2C). In addition, the responses of type II units to the vibrating sphere were not masked in any respect by running water. Data from a type II unit are shown in Fig. 6. This unit responded to the vibrating sphere in still water with an increase in discharge rate (Fig. 6, left). With increasing displacement amplitude, both the number of spikes during stimulus presentation and the degree of phase-locking to the stimulus increased. In running water, ongoing discharge rate, evoked discharge rate and phase-locking to the vibrating sphere stimulus were not different from the respective values in still water (Fig. 6, right).
Data from another type II unit are shown in Fig. 7. This unit responded to the vibrating sphere in still water with a decrease in discharge rate (Fig. 7, left). With increasing displacement amplitude of the vibrating sphere, the number of spikes during stimulus presentation decreased. Phase-coupling was low for all displacement amplitudes applied. As in the previous example, ongoing discharge rate, evoked discharge rate and phase-locking in running water were not different from the respective measurements in still water (Fig. 7, right).
Type III units (N=7) were, like type II units, flow-insensitive. However, in contrast to type II units, the responses of type III units to the vibrating sphere stimulus were masked in running water either in terms of spike rate (N=2), or in terms of phase-coupling (N=3), or both (N=2). Data from a type III unit are shown in Fig. 8. The unit responded to the vibrating sphere in still water with an increase in discharge rate (Fig. 8, left). With increasing displacement amplitude of the vibrating sphere, both the number of spikes during stimulus presentation and the degree of phase-locking to the stimulus increased. Ongoing activity in running water was not different from the rate in still water (Fig. 8, right). Nevertheless, discharge rate and phase-coupling to the vibrating sphere stimulus in running water were lower than under still-water conditions.
Fig. 9 summarizes the differences between type I, type II and type III units. Firstly, all type I units were flow-sensitive whereas type II and type III units were not. This is evident from a comparison of the absolute slopes of the regression lines that were used as a measure of flow-sensitivity (see Materials and methods). Median slopes were 0.33 spikes cm-1 per cm s-1 increase in flow velocity (range 0.01-0.73), 0.06 spikes cm-1 per cm s-1 (range 0.004-0.07) and 0.04 spikes cm-1 per cm s-1 (range 0.008-0.23) for type I, type II and type III units, respectively (Fig. 9A). The slopes of type I units were significantly greater than those of type II and type III units (Mann-Whitney U-test, P<0.001). The slopes of the regression lines of type II units were not different from those of type III units (P=0.34). Secondly, the responses of type I and type III units to the vibrating sphere were masked in running water, whereas the responses of type II units were not different in still and running water. This is evident by comparing the integrals of the level-response functions in running water with those in still water. This measure was used to quantify the degree of masking (see Materials and methods). In terms of spike rate, median integrals of type I, II and III units in running water were 21 % (range 0-58 %), 108 % (range 101-125 %) and 29 % (range 6-96 %) of the integrals in still water (Fig. 9B). The percentages obtained from type II units were different from those obtained from type I and type III units (U-test, P<0.001). The percentages from type I units were not different from those of type III units (P=0.29). In terms of phase-coupling, similar results were obtained. Median integrals of type I, II and III units in running water were 77 % (range 45-117 %), 92 % (range 78-117 %) and 73 % (range 35-129 %) of the integrals in still water. Masking of phase-coupling was weaker than masking of spike rate. The statistical analysis did not yield significance (type II versus type I, P=0.032; type II versus type III, P=0.11), but masking was nevertheless evident (Fig. 9C). The percentages from type I units were not different from those of type III units (P=0.84).
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Five units had response properties different from those of the three main unit types described above. Data from one of these units are shown in Fig. 10. In this unit, ongoing discharge rate increased in the presence of running water (flow-sensitive unit). Moreover, the discharge rate elicited by the vibrating sphere was also increased in running water. Consequently, the response to the vibrating sphere was not masked by running water. However, in terms of phase-coupling, the unit's response was masked. Data from the second unit are shown in Fig. 11. In still water, the unit responded to the vibrating sphere with an increase in discharge rate. In the presence of running water, ongoing discharge rate was decreased (flow-sensitive unit). Nevertheless, responses to the vibrating sphere were comparable in still and running water, at least for large displacement amplitudes. Consequently, the ratio between evoked and ongoing discharge rate was increased in running water. The third unit responded with an increase in discharge rate in response to the vibrating sphere (data not shown). In running water, ongoing discharge rate was slightly increased (flow-sensitive unit). Nevertheless, the unit's response to the vibrating sphere was not masked in running water. The fourth unit (data not shown) responded only to the onset of water flow with a transient increase of discharge rate. Consequently, the response to the vibrating sphere was not masked. In the fifth unit, masking of the response to the vibrating sphere by running water depended on sphere location (see below and Fig. 12C).
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Masking of responses to the vibrating sphere at different receptive
field locations
The main goal of this study was to investigate the effects of running water
on unit responses to a stationary sphere. Therefore, receptive fields were not
measured in detail. However, a crude analysis revealed that many units had
receptive fields that consisted of a region from which stimulation with the
vibrating sphere caused an increase in discharge rate (excitatory region) and
another region from which stimulation with the vibrating sphere caused a
decrease in discharge rate (inhibitory region)
(Mogdans and Kröther,
2001). In eight units, the effect of running water was measured
with the sphere positioned at two different locations within the receptive
field.
In five units the response to the vibrating sphere was masked in running water, but masking did not depend on the location of the sphere. Data from one such unit are shown in Fig. 12A. In still water, stimulation with the vibration sphere in the head region caused a decrease, whereas stimulation near the trunk caused an increase, in discharge rate. In running water, both the inhibitory and the excitatory responses were masked. In two units, responses to the vibrating sphere were not masked in running water, and again the effect was independent of sphere location. Data from one such unit are shown in Fig. 12B. In still water, stimulation with the vibrating sphere near the caudal peduncle and in the trunk region caused an increase in discharge rate. Neither of these responses was masked in running water.
One unit was recorded in which masking depended on the location of the sphere within the receptive field (Fig. 12C). In still water, this unit responded with an increase in discharge rate when the sphere was placed near the operculum. In running water, the response was not masked. When the vibrating sphere was near the tip of the snout, the unit responded with a decrease in discharge rate, but in contrast to the previous location, the response was masked in running water.
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Discussion |
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Flow-sensitive and flow-insensitive cells in the MON
Comparing ongoing activity of MON cells in still and running water allowed
us to distinguish between flow-sensitive (type I) and flow-insensitive (type
II and type III) units. In this respect, MON cells were comparable to primary
lateral line afferents, which are also either sensitive (type I) or
insensitive (type II) to running water
(Engelmann et al., 2000;
Voigt et al., 2000
).
Flow-sensitive afferents of type I probably innervate superficial neuromasts,
whereas flow-insensitive type II afferents probably innervate canal neuromasts
(Engelmann et al., 2000
).
Thus, it is tempting to speculate that flow-sensitive cells in the MON receive
input predominantly from fibers innervating superficial neuromasts and that
flow-insensitive MON cells receive input predominantly from fibers innervating
canal neuromasts.
Flow-sensitive afferent fibers always responded to running water with a
burst-like increase in discharge rate
(Engelmann et al., 2000). This
was probably because even a laminar water flow generated micro-turbulences
close to the skin of the fish. Since we used an almost identical tank to the
one in that study, comparable micro-turbulences must have been present.
Nevertheless, MON cells did not show burst-like activity in running water. In
addition, more than one-third of our flow-sensitive MON cells responded with a
decrease in discharge rate to running water
(Fig. 2). There are at least
two explanations for this: (i) the peripheral effects caused by
microturbulences are filtered at the level of the MON through an
as-yet-unknown central mechanism, and/or (ii) a reduction of ongoing discharge
rate in running water is due to inhibitory inputs onto MON cells mediated by
interneurons (New et al.,
1996
).
Two MON cells responded only for 1 or 2 min after flow onset
(Fig. 3C). Measurements with a
constant-temperature anemometer showed that a constant water velocity in the
flow tank was reached within approximately 10 s after the ship' propeller was
turned on, so these cells did not respond to the water acceleration associated
with the onset of the water flow. Perhaps these neurons were filtering stimuli
of long duration. Neurons with such properties are suited to cancel unwanted
responses to background flow information generated, for instance, in swimming
fish. Previous studies have demonstrated the ability of MON cells for adaptive
cancellation of responses to stimuli coupled to the fish's own ventilatory
movements (Montgomery and Bodznick,
1994,Montgomery and Bodznick,
1994
).
Effects of running water on MON unit responses to a vibrating
sphere
The responses of type I MON units to a vibrating sphere were masked in
running water in terms of spike rate, or both spike rate and phase-coupling.
Thus, the responses of type I MON cells were comparable to the dipole
responses of type I afferent fibers, which are also masked by running water
(Engelmann et al., 2000). This
further supports the idea that type I MON cells receive input from type I
afferents and thus process hydrodynamic information received by superficial
neuromasts.
The responses of type II MON cells to a vibrating sphere were not masked in
running water. Spike rates and phase-coupling were comparable in still and
running water. Thus the responses of type II MON cells were comparable to the
dipole responses of type II afferents, which are not masked by running water
(Engelmann et al., 2000). This
supports the assumption that type II MON cells receive input from type II
afferent fibers and thus process hydrodynamic information received by canal
neuromasts.
Theoretically, type II MON responses may result from the processing of input from a superficial neuromast with a vertical orientation, i.e. perpendicular to the direction of the flow. This neuromast should not respond to flow, provided that the flow is perfectly laminar. It should, however, still respond to a vibrating sphere, as this stimulus has spatial non-uniformities in the vertical dimension. Consequently, a central cell receiving input from this neuromast would be flow-insensitive and not masked, i.e. it would behave like a cell receiving input from a canal neuromast.
The responses of type III MON cells to a vibrating sphere were masked in
running water even though these cells were flow-insensitive. Thus, type III
cells had response properties intermediate between those of type I and type II
cells. This can be explained if type III cells received input from both type I
and type II afferents, i.e. if superficial and canal neuromast input converged
at the level of the MON. Excitatory input from type II afferents (canal
neuromasts) would explain why type III MON cells are flow-insensitive.
Additional inhibitory input from type I afferents (superficial neuromasts)
would explain the masking of type III MON responses. However, type III
responses can also be explained by the processing of superficial neuromast
information alone. A central cell may receive input from at least two
oppositely oriented populations of hair cells located in different superficial
neuromasts. In this case, the excitatory and inhibitory effects caused in the
respective afferent fibers will be cancelled at the level of the central cell
and the cell will thus be rendered flow-insensitive. Since the response to the
vibrating sphere in running water is masked already at the level of the
periphery (Engelmann et al.,
2000), the central cell's response will also be masked.
Some units exhibited responses unlike those of the main three response types: they were flow-sensitive but the responses to the vibrating sphere were not masked in running water (Figs 10, 11). A plausible explanation for this behavior is that these units received excitatory input from both type I and type II afferents, i.e. from both superficial and canal neuromasts.
Eight units were held long enough to test the effects of running water on the responses elicited from two different sphere locations. In seven units responses were either masked or not masked, and were independent of sphere location, suggesting that these units received input from only one type of neuromast. However, we found one cell in which responses to the vibrating sphere were masked by running water in one part but not in another part of the receptive field. This suggests that this cell received information from both superficial neuromasts and canal neuromasts located in different parts of the lateral line periphery.
Central lateral line pathways
The peripheral lateral line exhibits a clear morphological and functional
separation, having two types of receptive organs, the superficial and canal
neuromasts, with different morphological and biomechanical properties (for
reviews, see Bleckmann, 1994;
Coombs and Montgomery, 1999
).
Behavioral data strongly suggest that the two types of neuromasts have
different functions. Superficial neuromasts appear to be necessary for
rheotaxis behavior (Baker and Montgomery,
1999
; Montgomery et al.,
1997
). In contrast, canal neuromasts may mediate orienting
behavior and thus may be essential for the localization of a hydrodynamic
source (Coombs et al., 2001
).
This dual role of the two lateral line subsystems suggests a largely separate
processing of superficial and canal neuromast information. In addition, all
previous physiological studies indicated that superficial and canal neuromasts
are innervated by different populations of afferent fibers (e.g.
Kroese and Schellart, 1992
;
Coombs and Janssen, 1990
;
Coombs and Montgomery, 1992
;
Montgomery and Coombs, 1992
;
Wubbels, 1992
), suggesting
that information from superficial and canal neuromasts reaches the brain
via separate channels. The data from the present study support the
idea that the peripheral separation of superficial and canal neuromast input
is largely maintained at the first site of sensory integration in the lateral
line brainstem.
The idea that separate channels for the processing of superficial and canal
neuromast input exist throughout the ascending lateral line pathway is further
supported by studies in which a moving object was used as a lateral line
stimulus (Mogdans and Bleckmann,
1998). Two types of primary afferents can be distinguished, based
on their response to a moving object: fibers that respond with unpredictable
bursts of activity to the wake generated by the moving object, and fibers that
do not respond to the wake. Fibers of the first type probably innervate
superficial neuromasts whereas fibers of the second type innervate canal
neuromasts. In the brain, responses to moving objects similar to those in the
periphery can be found. As seen both at the level of the medulla
(Mogdans et al., 1997
) and in
the midbrain torus semicircularis
(Wojtenek et al., 1998
), one
population of lateral line neurons responds with a short burst of activity to
a passing moving object but not to the object's wake, whereas other neurons
respond to the wake, which suggests that they process input from canal and
superficial neuromasts, respectively.
Even though there is strong evidence for largely separate processing of
superficial and canal neuromast information, interactions between the two
subsystems cannot be ruled out. There are three possible candidates for the
convergence of superficial and canal neuromast input at the level of the MON:
(i) flow-insensitive type III units that have response properties intermediate
to those of type I and II units (c.f. Fig.
8), (ii) flow-sensitive units that respond about equally well to
the vibrating sphere in still and running water (cf. Figs
10,
11), and (iii) units in which
dipole responses are masked at one location in the receptive field but not at
another (cf. Fig. 12C). In
addition, both in the medulla and in the midbrain, many neurons exhibit
responses to a moving object (Bleckmann and
Zelick, 1993; Müller et
al., 1996
; Mogdans et al.,
1997
; Wojtenek et al.,
1998
), which can hardly be explained by processing input
exclusively from superficial or from canal neuromasts.
Another aspect of hydrodynamic information processing by MON neurons
deserves consideration. Whereas most MON cells readily respond to the complex
water motions generated by a moving object, only a small proportion of MON
cells responds to the water motions generated by a stationary vibrating sphere
(Mogdans and Goenechea, 2000).
Many MON cells that do respond to a vibrating sphere, do so only at vibration
amplitudes that are substantially greater than those needed to elicit
responses from primary afferents (e.g.
Coombs et al., 1998
;
Engelmann et al., 2000
;
present study). Cells of the first type may be part of a pathway for the
processing of complex hydrodynamic information that stimulates large parts of
the lateral line periphery. In contrast, cells of the second type may be part
of a pathway that processes local hydrodynamic information. However, this does
not exclude the possibility that cells which respond to a stationary dipole
stimulus are also involved in the processing of more complex water
motions.
Finally, the understanding of hydrodynamic information processing by
brainstem lateral line neurons is complicated by the fact that many MON cells
receive input from both the anterior and the posterior lateral line, i.e. from
afferent fibers that innervate neuromasts on both the head and the trunk. This
can be seen in measurements of receptive fields that may extend from as far
rostral as the tip of the snout to as far caudal as the tail fin
(Coombs et al., 1998;
Mogdans and Kröther,
2001
). Stimulation in one part of the receptive field can be
excitatory whereas stimulation in an adjacent part can be inhibitory
(Mogdans and Kröther,
2001
). Moreover, responses to hydrodynamic stimuli in running
water may depend on the location of the stimulus within a unit's receptive
field (this study). One of the challenges of lateral line research is to
understand the intricate network that underlies the processing of hydrodynamic
information in the fish brainstem.
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