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First published online May 2, 2008
Journal of Experimental Biology 211, 1657-1667 (2008)
Published by The Company of Biologists 2008
doi: 10.1242/jeb.013516
Electrocommunication signals in free swimming brown ghost knifefish, Apteronotus leptorhynchus
Department of Biology and Centre for Neural Dynamics, University of Ottawa, Ottawa, ON, K1N 6N5, Canada
* Author for correspondence (e-mail: ginettejhupe{at}gmail.com)
Accepted 14 March 2008
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Summary |
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 TOP Summary INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Key words: electrocommunication, weakly electric fish, chirps, abrupt frequency rises, behaviour
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INTRODUCTION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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). A central goal of ethologists is to uncover why animals
produce signals and reveal what functional significance they serve. We can
examine the conditions under which an animal produces a given signal, or
particular combination of signals, to shed light on factors that may influence
or induce particular signalling behaviour (causes). In studying behaviours
that may reflect signalling motivation, we can also observe any behavioural
consequences of signal production in order to reveal the social relevance of
different signal types (effects). Characterization of the actions associated
with signal production has provided a means of evaluating whether
communication occurs and has helped reveal the functions of signals in many
animal systems (e.g. Hopkins,
1974; Crawford et al.,
1986; Seyfarth and Cheney,
2003; Partan and Marler,
2005; Wong and Hopkins,
2007). Here, we take this approach to study electrocommunication
signals in a species of weakly electric fish.
Brown ghost knifefish, Apteronotus leptorhynchus, are native to
freshwater systems of South America and like all weakly electric fish, they
both produce and detect electric signals
(Moller, 1995). The strength
of the generated electric signal is in the range of a few millivolts and is
produced in a species-specific manner by specialized electrocytes that make up
the electric organ. Because of its origin, the electric discharge produced by
these fish is called the electric organ discharge, EOD. The EOD of A.
leptorhynchus is emitted as a continuous quasi-sinusoidal wave. The EOD
frequency (EODf) of A. leptorhynchus is sexually dimorphic and
individually specific; males emit in the range of 800–1000 Hz, whereas
females emit in the range of 600–800 Hz
(Zakon et al., 2002;
Zupanc, 2002;
Dunlap and Larkins-Ford,
2003a). The fish are able to sense this self-generated signal and
other electric signals in their environment via electroreceptors
distributed over their skin surface. They use this combined motor-sensory
system to navigate through their surroundings and find prey, a behaviour
termed electrolocation (Nelson and
MacIver, 1999; von der Emde,
2006). Weakly electric fish are also thought to use their electric
sense for communication, specifically electrocommunication
(Hagedorn and Heiligenberg,
1985; Zakon et al.,
2002; Zupanc,
2002; Turner et al.,
2007), the focus of this study.
Although the EOD is highly regular over time
(Moortgat et al., 1998),
stereotyped amplitude and frequency modulations are common in social
situations. It is believed that these modulations serve as communication
signals (Larimer and MacDonald,
1968). These modulations have classically been categorized into
two broad categories: rises and chirps. Rises are characterized by an increase
in the fish's EODf followed by an eventual decrease back to the baseline
frequency, lasting from tens of milliseconds to minutes
(Tallarovic and Zakon, 2002;
Tallarovic and Zakon, 2005).
Chirps are a second type of EOD modulation that tend to be shorter in duration
(
20 ms), and are the most commonly studied signal type
(Zakon et al., 2002).
Chirps have traditionally been defined as brief frequency excursions, and
several subtypes have been identified. Although there remains controversy
surrounding the categorization of chirps, we will be using the categorization
scheme outlined by Zupanc and colleagues
(Engler et al., 2000;
Engler and Zupanc, 2001;
Zupanc et al., 2006). Type 2
chirps are the most common type of chirp produced by A.
leptorhynchus. They are 15–20 ms in duration and have frequency
excursions of about 50–100 Hz. Type 1 chirps occur much less often than
Type 2 chirps and they are characterized by a larger frequency excursion than
Type 2 chirps, and a similarly short duration. Other longer duration chirp
types have been described, called Types 3–6; however, these were found
to be produced at very low rates (Engler
et al., 2000; Engler and
Zupanc, 2001; Zupanc et al.,
2006) and were not observed in the current study. Although chirps
were first described in A. leptorhynchus by Larimer and MacDonald
(Larimer and MacDonald, 1968),
40 years later very little is known about the social significance of these or
other electrocommunication signals. Various experimental paradigms, involving
both isolated fish (`chirp chamber' studies) and artificially interacting
fish, have led to a number of conclusions regarding chirping behaviours (e.g.
Zupanc and Maler, 1993;
Triefenbach and Zakon, 2003;
Kolodziejski et al., 2007).
Although fundamental to our current understanding of chirping behaviour, there
is a need to test if these behavioural patterns persist in naturally
interacting fish (Dunlap and Larkins-Ford,
2003b).
The objective of the current study is to examine chirping in pairs of
freely interacting male and female A. leptorhynchus and characterize
the behaviours associated with the production of these signals. In addition to
chirps, we observed that the fish commonly produce a type of frequency rise
known as an abrupt frequency rise (AFR), a signal type that was first
described by Engler and Zupanc (Engler and
Zupanc, 2001) and also documented by Tallarovic and Zakon
(Tallarovic and Zakon, 2005).
This signal consists of a series of brief events, each with a frequency
increase and subsequent decrease, produced in rapid succession, with variable
duration and repetition number. Our observations of freely swimming fish allow
us to analyze the behaviours that are associated with the production of
different signal types. We characterized the behaviours associated with chirp
and AFR production in A. leptorhynchus using three approaches. First,
we examine the temporal sequence of signal production in order to reveal
potential patterning, both within a fish and between fish. Second, we examine
the relationship between signal production and aggressive encounters
(attacks). Finally, we relate signalling with inter-fish distance to
characterize further the behaviours associated with signal production in
free-swimming A. leptorhynchus.
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MATERIALS AND METHODS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Experimental regime
We examined signal production in 21 different pairs of fish. For each trial
only novel pairings were used; the two fish selected were housed in separate
tanks and had not met following shipment.
Table 2 presents, for each of
the 21 trials, the identity of the two fish used, the difference in EODf
between the interacting fish (the difference frequency, Df), the type of sex
pairing, and Type 1 chirp, Type 2 chirp, AFR and attack counts for both of the
fish examined.
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Trials were performed in the dark in a 9.5 l tank measuring 30.0x17.0x13.5 cm. The water in the test tank was replaced with heated (26–27°C) water with a conductivity of 100–120 µS, between every trial or every second trial. To begin each trial, one fish (`fish 1' as listed in Table 2) was transferred from its home tank into the test tank. After 20 min a second fish (`fish 2') was added to the tank. Immediately upon introduction of the second fish into the test tank, 5 min electrical and video recordings of the interaction were taken. After 5 min of interaction both fish were returned to their respective home tanks. No effects of ordering on chirp or attack rates were found (paired t-test: P=0.72 and P=0.81, respectively). Fish were identified based upon their anatomical differences and EODf.
Video and electrical recordings
The EODs were recorded using two pairs of Teflon-coated silver-wire
electrodes (diameter: 0.38 mm, insulated to the tip; WPI, Inc., Sarasota, FL,
USA) positioned in opposite corners of the tank
(Fig. 1A) and an AM Systems
(Carlsborg, WA, USA) differential amplifier, model 1700 (amplified 10x,
low frequency cut-off of 10 Hz, high frequency cut-off of 5 kHz). The signals
were acquired at a sampling rate of 10 kHz using custom programs in Igor Pro
(Wavemetrics, Inc., Portland, OR, USA). A grounded Teflon-coated silver-wire
electrode (insulated to the tip) was attached to one corner of the test tank.
The trials were recorded from above using a Sony video camera (model DCR-TRV
260) equipped with infrared illumination.
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Chirps were categorized as either Type 1 or Type 2 by visual inspection. A
given fish produced at most two clearly distinct chirp types, which were
distinguishable based upon their frequency excursion. Type 1 chirps had large
frequency excursions whereas Type 2 chirps had notably smaller frequency
excursions, comparable to the descriptions outlined by Zupanc and colleagues
(Zupanc et al., 2006). All
AFRs were lumped into one category and these were variable in terms of
frequency excursion, repetition number, and duration. The electrical
recordings from each trial were converted into an audio format. These audio
files were played and chirps were counted
(Dulka and Maler, 1994;
Dunlap, 2002) and the timing of
each recorded for each of the first five trials. These counts were compared to
the chirp counts obtained from spectrogram analysis to assure the reliability
of our method (regression: R2=0.9998,
P<0.001).
Behavioural analysis
From the recorded videos of the interactions we noted the times of all
observable attacks. Attacks included all open jawed biting behaviours and all
high-speed lunges directed at a conspecific
(Heiligenberg, 1973). For each
trial we also tracked the position of each fish in the tank, again as viewed
from above, using Videopoint software (Lenox, MA, USA). Frames of every 200 ms
were analyzed. The distance from the head of one fish to the head of the other
fish was used as a functional indication of the distance between the two fish,
because most bites and lunges were initiated by, and largely directed at, this
region.
Characterization of signal patterning
To characterize the temporal patterning of signal production we created
correlograms relating the production of one signal with the production of a
second signal type. For each trial, we created signal-centred histograms in
which the counts pertaining to a second signal type were plotted in 200 ms
bins, for 4 s prior to and following the production of the first reference
signal. The histograms were then averaged over all trials to create
correlograms for each comparison. Those that differed significantly from a
flat distribution (the null distribution expected if signals are not
temporally correlated), determined using repeated measures ANOVA (RM ANOVA) on
ranks (P<0.05), were analyzed on a bin by bin basis (see
Statistical analysis section). Trials in which fish produced less than 10 of a
particular signal were omitted from the correlogram analysis. Although some
fish were used in multiple trials, we are assuming independence between trials
because all trials involve novel pairings.
To assure that the patterns we observed between two time series were not due to patterning within a given signal time series, we created `reversed' time series for one of the two signals being considered for each correlogram, and recalculated the averaged correlograms in the same fashion as for the unmodified time series. To create reversed time series, we simply switched the first half of one trial (time=0–150 s) with the second half of the same trial (time=150–300 s). This reversed time series has the same autocorrelation function as the original, but is not temporally linked to the production of any other signal. In all cases, the reversed-time-series correlograms were not significantly different than the ones expected if all events occur randomly (RM ANOVA on ranks: P>0.05 for all cases), thus verifying that all patterns we observed in the correlograms were not artifacts of non-random patterning in the individual signals.
In a similar way, we created correlograms plotting the attack rate of one fish centered at a given signal type, for 4 s before and after, again in 200 ms bins. The same statistical analyses were performed to identify relationships between attack rate and signal production.
Statistical analyses
Summary data are expressed as means ± s.e.m., unless otherwise
indicated. Linear regressions were used to characterize different parameters
(EODf, Df and time) associated with average signal production rates. In all
cases, an F-test was performed on the slope with P<0.05
as the threshold for statistical significance.
With respect to the correlograms, to determine significance on a bin-by-bin basis, we calculated a P value for each bin in each correlogram. To do this, for each correlogram we randomly shuffled one of the two signal (or attack) time series being considered and created a histogram relating this shuffled time series with the un-shuffled one. We repeated this procedure one thousand times and used the resulting distributions of counts in each bin to directly calculate a P value for any particular bin count in a given comparison. We then determined, for each bin, the fraction of all fish in all trials having significant P values (less than 0.05 or greater than 0.95) and plotted these below the corresponding averaged correlogram.
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RESULTS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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).
They show comparable amplitude decreases and frequency excursions. We did not
observe any chirps with a duration greater than 15-20 ms. In the spectrogram,
they may appear to last longer than this because of time smearing resulting
from the spectrogram overlap parameters (compare for example the oscillogram,
instantaneous frequency plot, and spectrogram of the Type 2 chirp shown in
Fig. 1B,C,D); these parameters
were optimized to provide sufficient resolution of both time and
frequency.
In addition to these chirps, AFRs were produced in abundance by the fish
under these experimental conditions. Two representative AFRs are shown in
Fig. 1F; both are produced by
the lower frequency of the two interacting fish (the third harmonics are shown
on the spectrogram). At the time of the AFRs, the higher frequency fish's EOD
signal is weak, allowing us to better illustrate the lower frequency fish's
frequency modulations. The AFRs shown here consist of distinct and consecutive
frequency rises produced in rapid succession. We recorded a total of 1046 AFRs
during the dyadic interactions. They are of variable duration, lasting from
tens to hundreds of milliseconds (mean duration: 404±4.3 ms). Although
this signal type has been described as an AFR in only one study prior to this
(Engler and Zupanc, 2001), we
believe that it is the same signal type that Tallarovic and Zakon
(Tallarovic and Zakon, 2005)
describe as a short duration rise. We have found that AFRs are produced
extensively during A. leptorhynchus social interactions. Furthermore,
our results suggest that these signals are produced in a context-dependent
fashion (see following sections), lending strength to the proposition that
they are a distinct class of electrocommunication signals produced by A.
leptorhynchus.
Long term changes in frequency, as well as frequency jamming behaviours
(Tallarovic and Zakon, 2005)
were observed infrequently, and were very variable in terms of frequency
excursion and duration. We observed 48 frequency rises which, unlike AFRs,
involved more gradual frequency modulations (over seconds and tens of
seconds), and hence fit into the category of a gradual frequency rise [GFR
(Tallarovic and Zakon, 2002;
Serrano-Fernández,
2003; Tallarovic and Zakon,
2005)]. These longer, more gradual frequency rises, were produced
infrequently during our studies and thus will not be discussed further.
Signalling rates as a function of gender, EODf and Df
Many researchers have pointed out that there is a need to compare the
behaviour of fish observed under artificial experimental conditions with that
of freely interacting fish (e.g. Dunlap
and Larkins-Ford, 2003b). In this section, we compare the mean
chirp rates of free swimming fish with those reported previously using chirp
chambers and other experimental conditions. We examine how the chirp rates are
influenced by gender, EODf and the difference in EODf of the interacting fish
(the difference frequency, Df). For comparison, we analyze AFR production in
the same manner.
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; Dye,
1987; Dulka and Maler,
1994; Dulka et al.,
1995; Dunlap and Larkins-Ford,
2003a; Kolodziejski et al.,
2004). We found a similar pattern in free-swimming conditions:
males produce significantly more chirps (Type 1 and Type 2 chirps) than
females (Fig. 2A,B;
Mann–Whitney rank sum test: T17=262,
P=0.01; and T17=162.5, P<0.001,
respectively). Furthermore, we found that under our conditions both genders
predominantly produce Type 2 chirps, similar to previously reported behaviour
in isolated fish (Engler et al.,
2000), in chirp chamber studies
(Engler and Zupanc, 2001) and
in fish interacting electrically (Zupanc
et al., 2006). Because Type 1 chirps were produced so
infrequently, it is difficult to gain any further insight into the factors
controlling their production. So, we will focus mainly on Type 2 chirps in the
following sections, and restrict this to chirps produced by males because
females chirped so infrequently. Contrary to the sexual dimorphism seen with respect to chirping, we found no sexual dimorphism in the average AFR rates of males and females tested under these conditions (Fig. 2C; Mann–Whitney rank sum test: T17=333.5, P=0.42).
Effect of EOD frequency and difference frequency
Previous studies have shown that chirp production rates in males are
proportional to the EOD frequency (EODf) and inversely proportional to the
difference frequency (Df) between a playback signal and EODf
(Zupanc and Maler, 1993;
Bastian et al., 2001;
Dunlap, 2002;
Dunlap and Larkins-Ford,
2003b; Kolodziejski et al.,
2007). We found that Type 2 chirp rates were not significantly
correlated with EODf in males (regression: R2=0.10,
P=0.12). However, we found that Type 2 chirp rates were negatively
correlated with Df, independent of the sign of Df
(Fig. 3A; regression:
R2=0.20, P=0.03). Interestingly, although males
chirped with a comparable mean rate when paired with males or with females
(137.8±42.5 vs 130.9±42.5 chirps per trial,
respectively), the mean Df was smaller for trials in which males were paired
with another male (47.1±8.4 Hz) than when paired with a female
(144.6±24.7 Hz). From Fig.
3A we can see that for any given Df, males tend to chirp at lower
rates when paired with a male than when paired with a female.
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A similar analysis of AFR rates revealed no relationship with EODf
(regression: R2=0.03, P=0.32). However, when all
fish are considered together we find that AFR rates are negatively correlated
with the absolute Df (Fig. 3B;
regression: R2=0.14, P=0.01). In general, in
agreement with previous studies (Zupanc
and Maler, 1993; Bastian et
al., 2001; Dunlap,
2002; Dunlap and Larkins-Ford,
2003b; Kolodziejski et al.,
2007), our results suggest that fish tend to produce chirps and
AFRs predominantly when interacting with a fish whose EODf is similar to its
own.
Signalling rates over time: chirp rates increase with time
Many studies have reported that the chirp rates of male and female A.
leptorhynchus tend to habituate over time, both in chirp chambers
(Dunlap, 2002;
Dunlap and Larkins-Ford,
2003b) and in fish communicating through a perforated barrier
(Dunlap and Larkins-Ford,
2003b). Contrary to this, over a similar time period, we found
that the Type 2 chirp rates of free-swimming male fish did not decrease;
instead, they increased significantly as the trial progressed
(Fig. 4A; regression:
R2=0.71, P=0.002). During this same time period,
attack counts decreased significantly (Fig.
4B; regression: R2=0.63, P=0.05);
although the greatest decrease in attack rate occurred over the first minute
of the interaction. This suggests a negative relationship between Type 2 chirp
rates and attack rates; as chirp rates increase, attack rates decrease. We
will investigate this relationship further in a following section. In contrast
to Type 2 chirp rates, Type 1 chirp and AFR rates did not change significantly
with time (regression: R2=0.08, P=0.44;
R2=0.29, P=0.11, respectively).
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;
Zupanc and Maler, 1993;
Engler and Zupanc, 2001;
Zupanc et al., 2006). Zupanc
et al. (Zupanc et al., 2006)
quantified this bursty chirping behaviour in male fish, interacting between
adjacent PVC tubes, using inter-chirp interval histograms. They found that
chirps tend to follow one another at a preferred latency of approximately 500
ms.
We performed a similar analysis on the signals produced by male and female
free-swimming interacting A. leptorhynchus in order to reveal
patterns in the signalling of individual fishes. With respect to male Type 2
chirps, we found a pattern of `burstiness' and a preferred latency period
comparable to those reported by Zupanc and colleagues
(Zupanc et al., 2006).
Fig. 5 shows an interchirp
interval histogram for all males across all trials. It suggests that males
tend to produce chirps in a bursty fashion with a preferred latency of
400–600 ms. Fig. 6A (top
panel) shows the averaged auto-correlogram corresponding to the male Type 2
chirp sequences (unlike the interchirp interval histogram, this analysis
considers both first order and higher order inter-chirp latencies). Because
the pattern in the auto-correlogram deviates from a flat (null or random)
distribution, it clearly indicates that males chirp in a non-random fashion
(RM ANOVA: 
240=266.2, P<0.001). The
lower panel shows the fraction of comparisons in which a given bin count (in
the correlogram) is significantly greater than (black line
P>0.95), or less than (grey line P<0.05) that expected
by chance. In a large number of cases the chirp rates are much less than
expected in the period immediately following a chirp event (grey line). This
is followed by a period with an increased tendency to chirp, indicated by the
peaks in the auto-correlogram and bottom panel (black line).
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AFRs are also produced in a non-random fashion. The AFR auto-correlogram
and bottom panel (Fig. 6B) show
that the probability of AFR production is reduced for a short time following
the first AFR and increases to a peak at a preferred latency of 400–800
ms (RM ANOVA: 240=241.7, P<0.001). This
suggests that AFRs, like chirps, tend to be produced in bursts, with a similar
preferred latency.
Interestingly, not only are signals correlated in time with themselves, the
patterns of two distinct signal types produced by a given fish are also
correlated. The probability that an individual fish produced an AFR just
before or after it produced a Type 2 chirp is significantly lower than chance
(Fig. 6C; RM ANOVA:
240=169.1, P<0.001) and this trend is
significant in about 40% of individuals
(Fig. 6C lower panel, grey
line). Overall, this patterning suggests that the fish tend to produce these
different signals under different conditions, at different times during an
interaction. In the following sections we show that there are different
contextual factors associated with the production of the different signal
types.
Signal production between two interacting fish is not independent
A previous study of A. leptorhynchus males interacting
electrically but confined to separate tubes, has provided evidence for a
so-called `echo response' (Zupanc et al.,
2006), such that chirps produced by one fish followed chirps
produced by another with a preferred latency. We investigate the relationship
between chirp rates in physically interacting fish by means of an inter-signal
cross-correlogram, a histogram describing Type 2 chirp production in one fish
at different times before and after another fish's Type 2 chirp. The
cross-correlogram for male–male interactions is significantly different
from that expected if the two fish chirped independently
(Fig. 7A; RM ANOVA:
240=100.4, P<0.001). The fish tend not
to chirp at the same time: the chirp rate of one fish at the time when the
other is chirping (t=0) is much less than expected by chance in more
than 70% of trials (Fig. 7A
lower panel, grey line). In addition, the chirp rates in adjacent time bins
are significantly greater than expected by chance (illustrated by the peaks in
the black line, Fig. 7A lower
panel), reflecting an `echo response' at a 200–600 ms latency.
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240=114.1,
P<0.001), but rather, are produced concurrently. This suggests
that either the two fish are responding at a very short latency with AFRs in
response to their partner's AFRs, or that shared conditions or features of the
interaction trigger AFR production in both fish at the same time (both fish
may produce AFRs during aggressive situations for example).
In addition to interactions with signals of the same type, we also found a
relationship between the patterning of AFRs of one fish relative to Type 2
chirps produced by the other fish. As indicated by the trend in the averaged
correlogram (Fig. 7C; upper
panel), one fish tends not to produce AFRs at the same time as the other fish
is producing Type 2 chirps (RM ANOVA: 240=105.7,
P<0.001). Although this trend is significant in a smaller
proportional of fish considered, the rate of AFR production in one fish was
consistently lower than expected at the time the other fish produces
chirps.
Overall, this signal patterning analysis provides a quantitative measure of the temporal interactions in chirp behaviour. Further, it reinforces the idea that Type 2 chirps and AFRs are true communication signals that are produced in bursty temporal patterns, influence the signalling behaviour of interacting conspecifics, and tend to be produced at different times during social interaction.
Attack rates are correlated with signalling
Many researchers have referred to chirps as aggressive signals
(Bullock, 1969;
Maler and Ellis, 1987;
Dunlap and Larkins-Ford,
2003b; Triefenbach and Zakon,
2003). In order to investigate this possibility, we have
quantified the temporal relationships between attack behaviours and signal
production using cross-correlograms. Fig.
8A (top panel) shows that a fish's own attack rate is decreased
near the time it produces a Type 2 chirp (RM ANOVA:
240=166.5, P<0.001). When we look at
the bin-by-bin analysis (bottom panel), it is clear that in more than 40% of
fish, attack rates are significantly lower than expected just prior to and
following a Type 2 chirp (grey line).
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When we consider interactions between fish, we see that chirping in one
fish is associated with a decreased attack rate by the other fish
(Fig. 8B; RM ANOVA:
240=76.8, P<0.001) and the trend is
significant in over half of the trials considered. Fish tend to chirp after
periods of low aggression, when both its own attack rate and that of the
interacting conspecific are lower than expected.
Contrary to the relationships observed for chirps, attack rate is highest
at the time of AFR production in both the signalling fish
(Fig. 9A; RM ANOVA:
240=138.1, P<0.001) and in the fish
with which it was interacting (Fig.
9B; RM ANOVA: 240=115.4,
P<0.001). In other words, a fish tends to produce AFRs at the same
time that it attacks (significant in about three-quarters of fish considered,
Fig. 9A; black line, lower
panel), but also when it is being attacked
(Fig. 9B), suggesting that AFRs
may be aggressive signals used frequently during agonistic encounters.
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DISCUSSION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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).
Because appropriate context is critical for the production of natural
behaviours, such studies must be undertaken in the most natural context that
is feasible under the given experimental constraints. In A.
leptorhynchus, various experimental settings have been used to
investigate putative electrocommunication signals, but none before the present
study has provided a detailed temporal analysis of signalling between two
freely interacting wave-type fish. Using spectrograms to separate the signals
of each individual fish and cross-correlation analyses, we have provided
further quantitative evidence for the existence of electrocommunication, as
well as a first step towards understanding the meaning of the underlying
signals. A complete neuroethological description of any physiological process
requires both a neural and behavioural description of the phenomenon.
Descriptions of the behavioural relevance of the electrocommunication signals
produced by A. leptorhynchus, such as we are presenting here, will be
necessary for elucidating the roles of neural circuits and modulators involved
in electrosensory processing and signal production.
Signalling behaviour: free-swimming versus constrained fish
Our study in free swimming A. leptorhynchus showed that some
features of chirp behaviour are preserved between these and other experimental
conditions. One feature of chirping that we confirm, and is consistent across
many experimental regimes, is the sexual dimorphism in chirp rates
(Maler and Ellis, 1987;
Dye, 1987;
Dulka and Maler, 1994;
Dulka et al., 1995;
Dunlap and Larkins-Ford,
2003a). Male chirp rates are much higher than female chirp rates
(Fig. 2). A second
relationship, previously described and confirmed in our study, is the effect
of difference frequency, Df, on chirp rates (Maler and Zupanc, 1993;
Bastian et al., 2001;
Dunlap and Larkins-Ford,
2003b; Kolodziejski et al.,
2007). There is an inverse relationship between Type 2 chirp rates
of freely interacting male A. leptorhynchus and the difference in
frequency between its own EODf and that of the fish with which it is paired
(Fig. 3). This relationship
persists when absolute Df is considered
(Bastian et al., 2001). This
implies that in any given pairing the lower and higher frequency fish tend to
chirp at approximately the same rate; a rate influenced by the magnitude of
the difference in the EODf of the two fish. This strong relationship between
Df and Type 2 chirp rate can explain why the relationship between EODf and
chirp rate is less apparent. Another point to consider with respect to the
relationship between Df and chirp rates is how these signals are detected or
perceived by conspecifics. Type 2 chirps and AFRs are produced most often when
Dfs are small, and interestingly, this is also the range in which
electroreceptor afferents most effectively encode small Type 2-like chirps
(Benda et al., 2006). Our
results clearly indicate that although fish chirp at the highest rate to fish
whose EODf is similar to its own, they also respond to chirps when the Df is
much greater. Thus there are likely to be additional mechanisms involved in
the detection and encoding of chirps in cases when the Df is large (G.J.H.,
J.E.L. and J. Benda, manuscript in revision).
An important difference between the chirping behaviour of fish tested under
previous experimental conditions and our results involves how chirp rates
change with time. Fig. 4 shows
that the rate of Type 2 chirp production increases significantly with time.
This increase is contrary to what has been reported for chirp production in
the past (Dunlap and Larkins-Ford,
2003b). It is possible that the decrease in chirp rates, reported
in such studies, is at least in part a result of the fish habituating to
unrealistic stimuli. In our experiments, the fish do not decrease chirp rates
over time, presumably because multimodal sensory cues are present because of a
dynamic interaction involving a real fish. Importantly, Dunlap and
Larkins-Ford (Dunlap and Larkins-Ford,
2003b) report that chirp rates actually decrease in free-swimming
fish. We suggest that this difference may be attributable to their use of a
much larger tank in which the fish could separate themselves
(Dunlap and Larkins-Ford,
2003b), whereas we used a relatively small tank which forced
interaction.
Differences in chirping behaviour with that observed in previous studies
suggest that simply being able to physically interact changes the chirping
behaviour of A. leptorhynchus. Bullock
(Bullock, 1969) used different
stimulation techniques and fish models to evoke chirping in A.
leptorhynchus and found that visual cues influenced chirping behaviour.
Our study provides further evidence that interactions are an important aspect
of shaping the natural signalling behaviour.
Perhaps the most important difference between the electrocommunication behaviour of freely interacting fish compared to those tested using previous experimental designs is the abundance of AFRs that we observed. It appears that features of natural, aggressive physical interactions are necessary to motivate AFR production in this species. Thus, these behavioural considerations will be necessary in future studies aimed at understanding the meaning of AFRs and the biophysical basis of their generation.
Behavioural correlates
Communication signals, by definition, must transfer some form of
information from the sender to the receiver
(Bradbury and Vehrencamp, 1998;
Griffin, 2001). Evaluating
this transfer of information is an obvious difficulty confronting ethologists
because we are limited to drawing conclusions based upon an animal's
observable behaviours. Thus, communication can be evaluated in terms of how an
individual's behaviour is affected by signals emitted by another. It is
important to ask what behaviours can be monitored in freely swimming fish that
may also be related to signal production. As a step towards solving this
problem, we have characterized signal production, attacks and inter-fish
distance using correlation analyses.
Signal patterning
Our study has shown that in A. leptorhynchus, both chirps and AFRs
are produced in a nonrandom, bursty fashion (Figs
5,
6). Also, through
cross-correlation analysis, we provide evidence that the signals produced by
one fish influence signal production in an interacting conspecific
(Fig. 7). The echo response
reported here has been observed in both pulse
(Moller, 1995) and in
wave-type weakly electric fish (Zupanc et
al., 2006); in both cases, the fish tend to respond with a
species-specific preferred latency. In A. leptorhynchus, the latency
is much longer than processing by a reflexive sensory-to-motor neural pathway
would suggest (Heiligenberg,
1991), so it is possible that higher level decision making is
involved in shaping this electrocommunicatory behaviour. In future studies,
experimental design can be controlled more specifically to determine the
nature of this decision-making process.
Signalling and attack behaviours
Additionally, our results suggest that different types of signals are
produced under different contexts and hence probably serve distinct social
roles. In the A. leptorhynchus literature, chirps are often referred
to as aggressive signals. These assertions are based on experiments which show
that males tend to chirp more in response to EOD mimics similar in frequency
to their own (Maler and Ellis,
1987; Bastian et al.,
2001), and thus more representative of male–male
interactions (because of the sexual dimorphism in EODfs). Thus, because
male–male interactions tend to be aggressive in nature, it has been
suggested that Type 2 chirps are agonistic signals (Zupanc et al., 2002).
Although chirps do occur during aggressive encounters, here we show that on a
smaller time scale, chirps do not often occur during attack behaviours. Our
analyses of attack rates (Figs
8,
9) suggest that Type 2 chirps
are produced when fish are not attacking, and may be used at a distance by
fish to deter aggressive behaviours.
Contrary to chirps, it appears that AFRs are aggressive signals, given that
they are specifically produced during attacks when the fish are in close
proximity. Aggressive signals are produced by a number of weakly electric fish
species. For example, in 1974, Hopkins temporally correlated the observable
behaviours of Eigenmannia (a related wave-type gymnotiform) with the
patterns of electric signals they produce. He found that short duration
interruptions were correlated with aggressive attack and threat behaviours. In
this species, the number of interruptions contained in a bout is a reliable
predictor of the likeliness that the animal will attack; the more
interruptions produced the greater the probability of attack
(Hopkins, 1974). Additionally,
in a number of pulse species, transient pulse accelerations are associated
with attacks and other aggressive behaviours
(Carlson, 2002).
Our results agree with a previous study by Bullock
(Bullock, 1969) who reported
that A. leptorhynchus were often observed chirping in between bouts
of attacks. In addition, a very recent study by Triefenbach and Zakon
(Triefenbach and Zakon, 2008)
has shown that gradual frequency rises and chirps tend to be produced under
different contexts. When two fish are competing for a single tube shelter,
they found that chirps tend to be produced when fish are not actively engaged,
whereas gradual rises tend to be produced when fish are actively engaged in
contact behaviours (Triefenbach and Zakon,
2008). Our results corroborate these and further show that these
relationships are preserved at time scales as small as 200 ms.
Signalling and inter-fish distance
Fish confined to PVC tubes will only chirp in response to a conspecific
when their PVC tubes are within 10–15 cm of each other
(Zupanc et al., 2006).
Further, they speculate that this limited communication distance is a
consequence of a fish's limited ability to detect conspecific signals.
Similarly, we found that freely interacting fish tend to chirp when they are
on average 12.5 cm apart (head-to-head distance;
Fig. 10A) but found many
chirps are produced at distances even greater than this. It is not clear,
however, that such a comparison is straight-forward because the distances
reported under our conditions were dynamic whereas those of Zupanc et al.
(Zupanc et al., 2006) were
static. Nonetheless, these distances are within the range of those found to be
behaviourally relevant for electrocommunication
(Knudsen, 1975).
Conclusions
In this study, we found that allowing fish to freely interact changed their
chirping behaviour, suggesting that many cues are involved in shaping
electrocommunication signalling. It also allowed us to relate chirp production
with features of social interaction, such as attack rates and interfish
distances, not accessible using previous more-constrained methods.
Furthermore, observing chirping in freely interacting fish revealed that AFRs,
a relatively uncharacterized type of frequency rise, are produced in
abundance. We found that both chirps and AFRs are produced in a non-random
fashion and that production rates are influenced by the signalling behaviour
of interacting conspecifics. Moreover, chirps and AFRs are also produced under
different behavioural contexts: chirps tend to be produced in the time between
attacks, whereas AFRs tend to be produced while the fish are in close
proximity, during attacks. These results emphasize the importance of
experimental context in studying communication signals. In addition, they
provide more clues to guide future studies aimed at understanding the
physiological mechanisms underlying the detection, interpretation and
production of electrocommunication signals.
LIST OF ABBREVIATIONS
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Acknowledgments |
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References |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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