Reproductive and diurnal rhythms regulate vocal motor plasticity in a teleost fish
Department of Neurobiology and Behavior, Cornell University, Ithaca, NY 14853, USA
* Author for correspondence (ahb3{at}cornell.edu)
Accepted 19 July 2009
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Key words: teleost, vocalization, pattern generator, circadian rhythm, seasonal plasticity
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Essentially the entire life history of the adult midshipman fish is
characterized by dramatic patterns of seasonal and daily periodicity in
reproductive behavior. From non-reproductive winters spent in deep waters off
the Pacific coastline, they migrate to tidal spawning grounds in the spring
where males excavate nests under rocks from which to attract females and guard
offspring (Bass, 1996
). Nesting
males court females primarily at night with long duration (
350 ms to
>1 h) advertisement calls known as `hums' that are generated by the
rhythmic contraction of muscles attached to the walls of the swim bladder
(Fig. 1Ai,Aiia)
(Bass et al., 1999
;
Brantley and Bass, 1994
;
Ibara et al., 1983
). The
multiharmonic hum has a highly stable fundamental frequency around 100 Hz at
ambient temperatures that does not vary across the duration of the call
(Fig. 1Aiia;
Fig. 2Ai) and shows almost no
amplitude modulation (Fig.
1Aiia). The hum contrasts sharply with the very brief
(50–100 ms), higher frequency (
110 Hz) and broadband agonistic
grunt produced singly by nesting parental males (type I), an alternative male
morphotype (type II) that either sneaks or satellite spawns, and females.
During agonistic encounters with other males, the grunt is also produced
repetitively as a `grunt train' by nesting males at rates of 1.5–3 Hz
for as long as several minutes (Fig.
1Aiib; Fig. 2Aii)
(Bass et al., 1999
;
Brantley and Bass, 1994
;
Cohen and Winn, 1967
;
McKibben and Bass, 1998
). A
second agonistic call, the `growl', is exclusive to the nest-building males
and most frequently recorded at night
(Bass et al., 1999
). Growls
are the most complex call; they overlap hums in duration (
200 ms to 5 s)
and are reiterative sequences of grunt- and hum-like signals
(Fig. 1Aiic,d;
Fig. 2Aiii). Only the nesting,
type I male morph employs all call types and thus has been the focus of the
present study.
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Fig. 1. Natural and fictive vocalizations of midshipman fish (Porichthys
notatus). Note that time scales differ between natural and fictive calls
to allow visualization of more complex waveforms in natural calls. (Ai)
Vocalizations are produced by the simultaneous contraction of a pair of vocal
muscles attached to the lateral walls of the swim bladder [modified from Bass
et al. (Bass et al., 2008 400 ms to >1 h. (Aiib) Agonistic
grunt trains are repetitions of brief grunts at a rate of 1.5–3 Hz.
(Aiic,d) Agonistic growls are the most complex vocalization with amplitude and
frequency modulation. They are an amalgam of brief grunts ( 50–150
ms) and longer duration, multiharmonic hums and range from 300 ms to several
seconds in duration. The grunt portion of the call in Aiid is clipped in the
original recording because of the proximity of the fish to the hydrophone.
(Bi) Sagittal view of the central network responsible for vocal production
[modified from Bass and McKibben (Bass and
McKibben, 2003
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Fig. 2. Interpulse intervals (IPIs) for individual natural and fictive
vocalizations. Shown here are the IPIs for representative examples of each
call type studied. Recording temperatures are indicated since the repetition
rate of natural sound pulses and the discharge frequency of the vocal motor
volley/fictive call are temperature sensitive
(Bass and Baker, 1991 50 ms duration) with an average IPI of 8.5 ms. (Aiii) A
natural growl (800 ms duration) can have considerable frequency modulation but
with a bimodal distribution: the shorter, faster grunt-like portion of this
growl has an IPI of 9 ms, while the longer, more regular hum-like portion
averages 13 ms. (Bi) Like the natural hum, a fictive hum (400 ms duration) can
have an extremely regular IPI (briefer at 10 ms than the natural one at
12 ms because of the higher recording temperature). (Bii) The IPI of a
fictive grunt averages 8.5 ms (like the natural one because of similar
recording temperatures). (Biii) The IPIs of this fictive growl or
`grunt–hum' (470 ms duration), like the natural one, are bimodally
distributed (between 8.5 and 10 ms, which is also briefer than the natural
call because of the higher temperature).
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Vocal motoneurons can be activated in a neurophysiological preparation of
midshipman and toadfish by electrical microstimulation in the forebrain's
preoptic area–anterior hypothalamus (POA–AH)
(Fig. 1Bi), the midbrain's
periaqueductal gray (PAG) (Fig.
1Bi) and the hindbrain's VPP
(Fig. 1Bi)
(Bass and Baker 1990
;
Goodson and Bass, 2000a
;
Goodson and Bass, 2000b
;
Goodson and Bass, 2002
;
Kittelberger et al., 2006
;
Remage-Healey and Bass, 2004
;
Remage-Healey and Bass, 2006
).
Electrical microstimulation in each of the above regions can produce a
rhythmic vocal motor volley known as a fictive vocalization that is readily
monitored with electrodes placed on ventral occipital nerve roots that form
the vocal nerve innervating the ipsilateral vocal muscle (see
Fig. 1Bi)
(Bass and Baker, 1990
).
Surgical isolation of the hindbrain–spinal region containing the
VPP–VPN–VMN circuitry further shows that this region alone can
produce and modulate the duration of fictive grunts with discharge frequencies
independent of the stimulus frequency (Bass
and Baker, 1990
; Remage-Healey
and Bass, 2004
; Remage-Healey
and Bass, 2006
; Kittelberger
et al., 2006
). Thus, the firing pattern of the vocal motor circuit
directly determines easily quantified temporal properties such as the
fundamental frequency/PRR and duration of natural calls that together with
amplitude modulation (AM) can be used to characterize fictive calls.
Midshipman fish behaviorally discriminate and neurally encode vocalizations
that vary in duration, frequency and AM; hence, the behavioral saliency of
these neuro-behavioral traits (Bass and
McKibben, 2003
).
Vocalizations play a crucial role in the seasonal reproductive behaviors of
midshipman and toadfish as they do in songbirds and anurans
(Bass and McKibben, 2003
;
Kelley and Brenowitz, 2002
).
Because of the one-to-one correlation between the temporal features of the
vocal motor volley/fictive call and natural calls, the fictive in
vivo preparation becomes a reliable measure of the probability of the
fish producing each type of natural vocalization in a particular physiological
condition. The simplest and briefest fictive call type, the grunt, has been
electrically and neurochemically (glutamate) evoked from midshipman at any
time of day or year (Bass and Baker,
1990
; Goodson and Bass,
2000a
; Remage-Healey and Bass,
2004
; Weeg et al.,
2005
; Kittelberger et al.,
2006
). However, long duration fictive calls with firing patterns
suggestive of natural growls and hums have only been occasionally recorded
(Goodson and Bass, 2000b
). Now
for the first time, using a new stimulation paradigm, we show that long
duration fictive growls and hums can indeed be readily evoked in parental
males, but almost exclusively at night and only when they are in reproductive
condition. Similarly, long duration fictive grunt trains have now been evoked
for the first time in reproductive males, although they can occur either
during the day or at night. Thus, as shown here, the seasonally and
nocturnally dependent vocal behaviors of midshipman fish are clearly supported
by periodic changes of basal activity in the vocal motor system. With this
analysis of the state dependence of long duration fictive calls and their
comparison with the natural calls, we can further dissect how either system or
local circuit changes in neurophysiology ultimately dictate the natural
rhythmicity of a behavior.
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Neurophysiological experiments
The fictive vocalization preparation used here has been thoroughly
described elsewhere (Bass and Baker,
1990
; Goodson and Bass,
2000a
; Remage-Healey and Bass,
2004
). Briefly, brain and rostral spinal cord with occipital nerve
roots were exposed by dorsal craniotomy under general anesthesia with 0.025%
benzocaine (Sigma) and a local injection at the wound site of a long-lasting
analgesic (0.25% bupivacaine; Abbot Laboratories, Chicago, IL, USA) with 0.01
mg ml–1 epinephrine (adrenaline; International Medication
Systems, El Monte, CA, USA). After surgery, fish were immobilized with an
intramuscular injection of pancuronium bromide (0.5 mg kg–1,
Astra Pharmaceutical, Westborough, MA, USA) and stabilized in a Plexiglas tank
with aged, chilled (16–17°C) saltwater perfused through the mouth.
One hour after surgery, an insulated tungsten electrode (125 µm diameter, 8
deg. tip angle, 5 M
impedance, 20 µm exposed tips; A-M Systems,
Sequim, WA, USA) was used to evoke the vocal/occipital nerve motor volley
(fictive vocalization) through delivery of 40 brief (30 ms) trains of 200 Hz
stimuli (0.1 ms pulse width, 50–75 µA positive current) at 1
s–1 via a WPI stimulus isolation unit (Model 850 S,
World Precision Instruments, Sarasota, FL, USA) to either the midbrain PAG
region which connects to the hindbrain pattern generator or the hindbrain VPP
region that projects to the VPN–VMN circuit
(Fig. 1Bi). The same low
current intensity was used for all fish at all time points, whether it was at
or above the call threshold for each individual. When only the threshold
current (minimum current to elicit a call) was used, the probability of
evoking long duration calls was much reduced (see Results). Well-documented
surface landmarks and depth measurements based on previous mapping studies of
the vocal motor system provided guides for electrode placement
(Goodson and Bass, 2002
;
Kittelberger et al., 2006
;
Remage-Healey and Bass, 2004
).
As noted earlier, fictive vocalizations reflect the firing properties of the
VPN–VMN circuit that directly determines a natural call's duration and
fundamental frequency (harmonic call)/pulse repetition rate (non-harmonic
call); hence, its designation as a fictive call/vocalization. Fictive calls
were recorded unilaterally from an occipital nerve with an extracellular
electrode (Teflon-coated silver wire with exposed ball tip; 50–100 µm
diameter) and digitized using MATLAB software designed by Dr Bruce Land
(Department of Neurobiology and Behavior, Cornell University). The two sides
of the brain fire together so that a unilateral recording represents bilateral
synchrony of the descending vocal motor volley
(Bass and Baker, 1991
) that
leads to the natural, simultaneous contraction of the paired vocal muscles
(Skoglund, 1961
;
Cohen and Winn, 1967
).
Neurophysiological and statistical analysis
Previously, fictive vocalization preparations performed during the day
typically evoked grunts with 15 brief (30 ms) stimulus trains presented at
one-second intervals (1 s–1) at each of several time-points
over the course of 120 min (Goodson and
Bass, 2000a
; Goodson and Bass,
2000b
; Goodson and Bass,
2002
; Remage-Healey and Bass,
2004
; Remage-Healey and Bass,
2006
; Remage-Healey and Bass,
2007
). However, it was found here during pilot studies with
reproductive males that they were highly responsive to a longer stimulation
time at night, consistent with the time that they mainly produce long duration
calls (Bass et al., 1999
;
Brantley and Bass, 1994
;
Ibara et al., 1983
). Thus, if
the number of stimulus trains was increased to 40 at every recording, long
duration calls could be readily evoked from some males by 60 min post-baseline
recordings. Hence, the first set of studies in this investigation delivered 40
brief stimulus trains at 1 s–1 at eight time-points
(baseline/0, 5, 15, 30, 45, 60, 90, and 120 min) to different groups of
reproductive and non-reproductive males at different times of the day.
It was also found during the course of these first experiments that at the 120 min time point, presentation of an additional 60 stimulus trains at 1 s–1, continuous with the initial 40, had an especially robust effect on the ability to evoke long duration calls at night in reproductive males. We subsequently tested reproductive males in the day and non-reproductive males day and night in the same way. To further evaluate the effect of the prolonged stimulation on evoking long calls before any slower physiological changes were incurred during the 120 min experiment, we compared these results with those of a separate group of reproductive animals that received 100 s of stimulation trains at baseline.
The minimum current or threshold for evoking fictive calls, call duration
and the ratio of the number of fictive growls/grunts were averaged for each
time point (5–120 min) and normalized against the baseline (0) of each
fish. As reported in the Results, natural and fictive growls are a hybrid of
grunt- and hum-like calls. For duration measurements of grunt–hums, the
duration of the initial grunt-like response (
3 pulses) and any subsequent
response (
3 pulses) were added for the complete value but did not include
the silent gap between the two. The repetition rates of the motor volley that
mimics the fundamental frequency of natural calls were determined by the
peak-to-peak interval between compound action potentials or `interpulse
interval' (IPI).
Call duration, grunt–hum probability and threshold change (reported as means with s.e.m.) were analyzed in JMP (7.0) using repeated-measures ANOVA followed by planned individual contrast post-hoc tests for between subjects comparisons from 30 to 120 min. Statistical analysis of baseline grunt duration, based on comparisons of mean values between each study group (see Results), was performed in Graphpad Prism (5.0) with a one-way ANOVA followed by Tukey's post-hoc tests. To expand the database for this analysis beyond the number of animals comprising the experimental groups (3–6) in the main body of this study, we included values from a larger sample size of animals treated identically at baseline (20 brief stimulus trains at 1 s–1 rather than the 40 stimulus trains at 1 s–1 used throughout the remainder of the study). A one-way ANOVA followed by Tukey's post-hoc tests was also used for duration change (log transformed) after presenting 100 stimulus trains (values normalized against the first 20 s of stimulation). Comparison of IPIs between fictive call types produced by the same fish was performed in Graphpad Prism (5.0) with paired t-tests, while unpaired t-tests were used for comparisons between the IPIs of fictive calls and the fundamental frequencies of natural calls. The IPI/frequency of a particular call type from any single fish is highly consistent, thus an average of 40 calls is not significantly different from one. A general linear mixed model was used to evaluate differences in duration between fictive grunts and growls, and between fictive grunts and natural grunts in order to account for a greater variation in call duration measured from individual fish. Statistical comparisons were always based on the mean values obtained for each animal in a group, not on the total call number for all animals in the group.
Photoperiod manipulation
We wanted to determine whether the nocturnal dependence of the male's
fictive grunt–hums and hums either reflected an endogenous rhythm or was
dependent upon external light cues. Thus, reproductive type I males shipped to
the lab in either July or August 2008 were subjected to 24 h of either dark or
light for 5 days after an initial exposure for 1–5 days to the 14 h L:10
h D cycle. These animals were then tested for the ability to produce long
duration fictive calls. Taking advantage of the midshipman's typical lack of
feeding during the first 1–2 weeks of acclimation to captive conditions
(Sisneros et al., 2009
), food
was withheld from these animals so as not to confound the effect of the
photoperiod regime with food entrainable rhythms. Of the six fish in each
treatment group, three were tested between 11:00 and 12:00 h EST of the
circadian day, while three were tested after 18:00 h EST of the circadian
night. Subjects of night experiments and all 24 h D fish were exposed to 30
min of white light during surgery with eyes covered, after which the rest of
the neurophysiology experiment was conducted in red light only, which does not
inhibit the nocturnal behavioral activity of midshipman fish (see
McKibben and Bass, 1998
).
Sound recordings
Recordings of midshipman vocalizations (courtesy of Margaret Marchaterre,
Department of Neurobiology and Behavior, Cornell University) were made
directly from spawning sites in the intertidal zone of Brinnon, Washington
using hydrophones (Bioacoustics Research Program, Cornell Laboratory of
Ornithology, Ithaca, NY) placed directly adjacent to nests, which are
excavations under large rocks (see Bass,
1996
; Bass et al.,
1999
; Bass and Clark,
2003
). Since the fundamental frequency/pulse repetition rate of
natural harmonic (hums and growls)/non-harmonic (grunts) calls and the
discharge frequency of fictive calls vary directly with ambient temperature
(Bass and Baker, 1991
;
Brantley and Bass, 1994
;
McKibben and Bass, 1998
),
temperature was also recorded (temperature loggers from DataLoggers, Onset
Computer, Pocasset, MA, USA). All sound recordings were made between dusk and
dawn when spawning and vocal activity peak
(Brantley and Bass, 1994
;
Bass et al., 1999
). Recordings
were digitized at 2 kHz and 16-bit resolution and waveforms visualized and
analyzed using Raven Pro 1.3 (Bioacoustics Program, Cornell Laboratory of
Ornithology).
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Diurnal and seasonal changes in call duration and frequency
The mean baseline fictive grunt duration of reproductive and
non-reproductive males reflects seasonal and daily changes in basal vocal
motor excitability. Baseline fictive grunt values were determined for separate
day and night groups of reproductive and non-reproductive males
(Fig. 3A). Mean grunt duration
of reproductive males tested at night was significantly greater
(P<0.05) than for all other groups (reproductive night:
88.79±9.28 ms; reproductive day: 57.16±5.33 ms; non-reproductive
night: 54.7±5.63 ms; non-reproductive day: 44.96±3.66 ms;
N=10 animals/group, 20 calls/animal).
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Fig. 3. Diel and seasonal variation in fictive calls. (A) A night versus
day comparison of mean baseline grunt duration in reproductive and
non-reproductive males. Asterisk, reproductive males at night have a
significantly higher fictive grunt duration than all other groups (see text).
(B) Call duration change over 120 min with 40 stimulus trains at each
recording. Reproductive males were housed on a 14 h L:10 h D cycle, and
non-reproductive in 10 h L:14 h D cycle (all N=3). There was a
significant, overall effect of reproductive state (see text). (C) 100 stimulus
trains (1 s–1) at baseline in reproductive males at night
versus 100 stimulus trains at 120 min in all groups (N=5 for
reproductive night; 3 each for reproductive day, non-reproductive night and
non-reproductive day; 6 each for 24 h D and baseline reproductive night).
Letters (a, b, c) denote significant differences (see text). (D) The call
threshold stimulus current significantly decreases in reproductive (14 h L:10
h D) males at night, but rises during the day (asterisks indicate significant
differences, see text).
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Fig. 4. Fictive call stimulus–response trains from a reproductive male housed
in 14 h L: 10 h D and tested at night. (Ai–iii) Example of the time- and
stimulation-dependent progression of fictive grunts to longer duration calls.
Shown here are 20 s excerpts from 40 stimulus trains with stimulus artifacts
(S.A., Ai) shown at 1 s intervals followed by the fictive call (see text for
details). (Bi–iii) As fictive grunts transition to fictive
grunt–hums and duration increases, mean firing frequency (20 calls, one
male) decreases. Recording temperature, 16.3°C.
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When a stimulus trial of 100 stimulus trains (1 s–1) was presented at 120 min, call duration increased dramatically in reproductive males at night compared with both reproductive males in the day and to non-reproductive males (day and night), coincident with the evocation of long duration growl-like calls (P<0.05) (Fig. 3C; Fig. 4Aiii). Most of the long duration calls had two components as sometimes observed with 40 stimulus trains at the 120 min time point (see above). However, the grunt-like part of the response was typically followed by a long hum-like response: the combined response resembling natural growls (Fig. 4Aiii; also see Fig. 1Aiid). Two of six reproductive males tested at night and given 100 stimulus trains at baseline were able to produce long duration calls as opposed to five of five at 120 min, suggesting both short term and long term activity-dependent changes in the vocal motor circuit. Non-reproductive males (day or night) increased call duration significantly less than all other groups (P<0.05) (Fig. 3C), reflecting the absence of fictive growls and hums. At night, reproductive males tested at 120 min produced significantly more long duration calls than either the reproductive males tested during the day at 120 min or the reproductive males tested during the night at baseline (Fig. 3C). Thus, long duration call production peaked in the group that permitted both short term and long term, activity-dependent changes to occur in vocal circuits already primed by a nocturnal, reproductive condition.
The IPI, which reflects the fictive call's discharge frequency, was also increased in the longer duration calls evoked with 100 stimulus trains at 120 min. The IPI analysis is shown in Fig. 2Bi–iii for single calls in comparison with single natural calls and in Fig. 4Bi–iii for a mean of 20 fictive calls to show cumulative results. The shift from grunts to growls that was potentiated by the 100 stimulus trains (Fig. 4A) was accompanied by the appearance of a bimodal distribution of IPIs, composed of the growl's faster grunt-like and slower hum-like components (Fig. 4B).
In sum, the facilitation of vocal motor excitability, as reflected in the increased production of long duration calls, depended upon reproductive state, time of day and degree of stimulation.
Diurnal and seasonal changes in call threshold
As shown above, fictive growls and hums are distinguished from grunts by
their physical attributes (duration, frequency, amplitude modulation) and by
the time of day and year at which they can be evoked. Fictive growls and hums
are also distinguished by a decreased response threshold (minimum current to
elicit a call), and a paradoxical dependence on increased stimulation
intensity. Amongst reproductive males, there was a conspicuous and significant
drop (25–40%) in call threshold (P=0.036) at night, compared
with the rise seen during the day (Fig.
3D) (90 min P=0.01 and 120 min P=0.0006) that
paralleled the steady, time-dependent increase in duration and IPIs
(Fig. 4). While fictive grunts
can follow a stimulus at the very low threshold current, fictive growls and
hums are elicited from reproductive males at night (and to a much lesser
degree during the day) with a slightly elevated stimulation current
(25–50 µA above threshold). Thus, in spite of the decrease in burst
threshold and this evidence for the vocal circuit's heightened excitability,
the likelihood of evoking the longer calls with every stimulus pulse was still
greater if the current remained slightly above threshold.
Fine temporal properties of fictive and natural calls
As we noted earlier, the fictive growl was designated as a
`grunt–hum' due to its hybrid nature, namely a grunt-like beginning
followed by a longer, hum-like portion with damped amplitude at either end.
Thus, both natural and fictive growls have two distinguishable parts that are
either continuous or separated by a sudden, brief change in amplitude
(Fig. 1Aiic,d,Biic,d; also see
Fig. 4Aiii) and exhibit a
bimodal distribution of IPIs (Fig.
2Aiii,Biii; also see Fig.
4Biii). The duration and mean frequency of natural growls can
range broadly even in one animal (e.g. 542 ms to 8 s; 59–116 Hz;
N=10 calls), with durations that obviously exceed our fictive
recordings. However, naturally brief growls (e.g.
Fig. 1Aiid) appear to be a
fundamental unit or pattern for the longer calls and the fictive growl is its
neural correlate. For reproductive males tested at night and presented with
100 stimulus trains at 120 min, the mean duration of fictive growls
(444.67±41.67 ms, N=6 animals, 5 calls/animal) was
significantly longer than that of the grunts evoked at baseline from the same
fish (67.36±6.81 ms; N=6 animals, 5 calls/animal;
P<0.0001). The mean frequency (at 16.4°C) of the hum-like
portions of the fictive growls was significantly lower than that of the grunts
(mean grunt frequency=106.84±1.81 Hz; mean hum
frequency=97.88±0.53 Hz; P=0.003).
Fictive hums alone, although rarely produced de novo (one animal,
3 calls, 1140±332.21 ms, continuous through two stimulus trains with
little amplitude modulation), resembled brief natural hums in IPIs
(Fig. 2Ai,Bi) [differences in
recording temperatures can account for different absolute values for IPIs of
both natural and fictive calls (see
Brantley and Bass, 1994
;
Bass and Baker, 1991
)]. The
more common hum-like portions of fictive growls also had a very regular, low
firing frequency (97.88±0.53 Hz; N=7 animals, 5–15
calls/animal) that was not significantly different (P=0.87) from that
of the natural hum (mean fundamental frequency=97.44±2.76 Hz 6;
N=5 animals, 1 call/animal; same recording temperature). IPIs
strikingly differentiated all fictive and natural hums from even the longest
fictive or natural grunts (
200 ms), which exhibit a higher, irregular IPI
(Fig. 2Ai,ii,Bi,ii) [see also
Brantley and Bass (Brantley and Bass,
1994
); Bass et al. (Bass et
al., 1999
) and Bass and Clark
(Bass and Clark, 2003
) for
natural grunts]. The distribution of IPIs (
10 ms) in all fictive hums,
either singular or part of a grunt–hum, was the tightest of any of the
natural or fictive calls (Fig.
2Bi). Fictive hums and the hum-like portions of fictive growls
were also similar to brief natural hums in duration [see Brantley and Bass
(Brantley and Bass, 1994
) for
hums as brief as 370 ms]. However, a statistical comparison is not warranted
because the duration of naturally produced hums is highly context dependent
(A.H.B. and M. Marchaterre, unpublished observations) while the evoked
correlates are strictly electrophysiological phenomona that reflect the state
of the pattern generator.
Unlike the fictive hums and growls, fictive grunt trains were easily triggered during both night and day trials but, like hums and growls, only in reproductive males. Natural grunt trains consist of individual grunts repeated at a rate of 1.5–3 Hz that can persist for several minutes (Fig. 1Aiib; see Introduction). After the 120 min recording period, free-running grunt trains were readily triggered with 3–20 s of stimulus trials in the hindbrain VPP region (Fig. 1Bi) and continued independently for more than 5 min without further stimulation, mimicking the natural call with a mean grunt repetition rate of 1.9±0.1 Hz (N=5 animals, one grunt train/animal). For individual grunts within the trains, the pulse repetition rate averaged 113±2.17 Hz, with a mean grunt duration of 46.56±7 ms (N=5 animals, 5 grunts/animal). This was not significantly different from the intra-grunt frequency (P=0.13) and duration (P>0.89) of grunts from natural grunt trains (mean frequency=108.52±1.563 Hz; mean duration=47±1.98 ms; N=5 animals, 5 grunts/animal). While fictive growls and hums could only be evoked from the midbrain's PAG region, which projects to the VPP (Fig. 1B1), grunt trains could only be evoked with stimulation in the VPP or VPN region.
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Fig. 5. Photoperiod-dependent plasticity of fictive calls. (A) Call duration change
in reproductive males subjected to 24 h of darkness (24 h D) versus
24 h of light (24 h L) (N=6 animals/group). Asterisks indicate
significant differences (see text). (B) The ratio of fictive grunt–hums
to grunts in reproductive males housed in 24 h D, 24 h L and 14 h L:10 h D
(same animals as in `reproductive night' test group). Asterisks indicate
significant differences (see text). (C) There was an insignificant trend for
call threshold in 24 h D males (day/night pooled) to fall, while call
threshold in 24 h L (pooled) animals rose (see text).
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Fig. 6. Photoperiod-dependent plasticity of stimulus–response trains.
(Ai–iii) Examples of the time- and stimulation-dependent progression of
fictive grunts to longer duration calls from a reproductive male housed in 24
h D and tested during the circadian day. (Bi–iii) Although fictive
grunt–hums appeared earlier in 24 h D males compared with 14 h L:10 h D
animals (compare with Fig.
4Ai,Bii), the overall firing frequency (mean 20 bursts, one male)
started low and increased slightly by 120 min (shown here for one animal
tested during the circadian night). Recording temperature, 16.3°C.
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Long duration fictive vocalization in midshipman fish
The evocation of fictive growls and hums, the neural correlates of the
natural, long duration calls used during the breeding season, depends upon
reproductive state and time of day. These calls are accompanied by several
distinct neurophysiological changes that reflect the altered state of the
vocal motor system at night in a reproductive male. First, either shortly
preceding or in tandem with the evocation of the first fictive growl or hum,
the call threshold drops by as much as 40% as these longer calls increase in
number and length. Second, in addition to the significant (up to 1000%)
increase from baseline duration with added stimulation, the firing rate
concomitantly falls. Third, fictive calls become more regular in their IPIs,
also like natural hums and the hum-like parts of growls. Interestingly, even
though the fictive grunt threshold significantly decreases in conjunction with
the first fictive hums, the kindling and evocation of these long duration
calls still rely upon a greater current intensity. This might reflect the
recruitment of neurons with lower input resistance, as in those exhibiting
more electrotonic coupling necessary for synchronous firing
(Christie et al., 1989
;
Christie and Jelinek,
1993
).
All of the above characteristics – duration increase, frequency and
call threshold decrease, and firing rate constancy – may be considered
the outcome of short term (40–100 stimulus trains at 1
s–1) and long term (120 min trials), activity-dependent
plasticity in the vocal motor circuit. Furthermore, this network or cellular
plasticity is itself susceptible to seasonal and daily modulation, such that
prolonged stimulation (100 stimulus trains) in a reproductive male during the
day evokes only a small fraction of the number of fictive hums that can be
elicited from another male at night. However, if the stimulation is not
increased from 40 to 100 stimulus trains, the potential to produce long
duration calls from reproductive males is not entirely revealed in any group.
This strongly suggests that activity-dependent plasticity in a circuit emerges
from behaviorally relevant network activity, or electrical stimulation of
sufficient duration to mimic naturally occurring network activation
(Buchanan, 1996
;
Parker and Grillner, 1999
).
Future experiments need to further explore the interaction between short and
long term activity-dependent changes that give rise to the vocal circuit
plasticity studied here. However, these initial studies clearly reveal the
dramatic effects of increased stimulation on the probability of evoking long
duration calls. Similarly, with prolonged stimulation in the motor cortex of
monkeys, muscle twitches evolve into complex movements reflecting natural
behaviors (Graziano et al.,
2005
).
In contrast with previous studies in midshipman (see Introduction), the
current experiments increased the number of stimulus trains from 15 to 40 (at
1 s–1) during each stimulus trial, but did not increase the
duration of the individual stimulus trains (30 ms). This may be one reason why
the recorded fictive hum rarely exceeded 1 s, while parental males will hum
without pause for up to an hour. In comparison, it is remarkable that the
spontaneous fictive grunt train fired independently for many minutes in
reproductive animals after only 3–20 s of hindbrain stimulation. It
would suggest that rhythmic, oscillatory-like output from the hindbrain vocal
circuit can produce the grunt train, while the hum relies upon added upstream
drive from the midbrain PAG and the forebrain's POA-AH that is a major
integration site for neuroendocrine and vocal mechanisms
(Goodson and Bass, 2002
).
The induction of different classes of long duration calls also shows site
specificity, namely stimulation in the midbrain PAG region for growls and hums
and the hindbrain VPP region for grunt trains. In general, the results are
consistent with earlier studies showing that multiple sites in the vocal motor
system can modulate the activity pattern of the pacemaker–motoneuron
circuit [see Results and other reviews by Goodson and Bass
(Goodson and Bass, 2002
) and
Kittelberger et al. (Kittelberger et al.,
2006
)]. However, the current study shows, for the first time in
the teleost fictive call preparation, the site-dependent induction of vocal
patterns that reflect the greatest divergence in vocal patterning. These new
results are further consistent with studies of the vocal brainstem in mammals,
including primates (e.g. Fenzl and
Schuller, 2005
; Jurgens and
Hage, 2007
).
Unlike teleosts, call patterning in tetrapods depends upon the integration
of vocal and respiratory mechanisms (Bass
and Baker, 1997
; Wild,
2004
; Zornik and Kelley,
2008
). Like studies in toadfishes and other vocal teleosts
(Bass and Baker, 1990
;
Bass and Baker, 1991
;
Barber and Mowbray, 1956
;
Packard, 1960
;
Skoglund, 1961
), recordings of
vocal motor volleys in frogs (in this case from a laryngeal branch of the
vagus nerve) essentially show a 1:1 correspondence between each complex
potential, muscle contraction and sound pulse
(Yamaguchi and Kelley, 2000
).
In vitro studies of isolated brain preparations from the terrestrial
frog Lithobates pipiens [formerly Rana pipiens (see
Frost, 2007
)] identify two
`semi-independent' call pattern generators, one at isthmal levels and one
(`the classical respiration generator') at caudal hindbrain–spinal
levels (Schmidt, 1992
). Recent
in vitro studies in Xenopus laevis, a fully aquatic frog
with a vocal circuit like that of terrestrial species (see
Zornik and Kelley, 2007
;
Zornik and Kelley, 2008
), show
that bath application of serotonin can evoke fictive responses that mimic the
temporal properties of natural vocalizations
(Rhodes et al., 2007
). In
vitro brain stimulation studies of frogs have been less conclusive. As
Zornik and Kelley point out, the temporal properties of the electrically
evoked responses are typically not independent of the stimulus frequency
(Zornik and Kelley, 2008
), in
contrast to studies like the current one of vocal fish
(Fig. 4A;
Fig. 6A; also see
Introduction). Rather, in studies of Xenopus, each electrical
stimulus pulse evokes a single complex potential in the nerve; responses that
mimic a natural call have only occasionally been obtained (see
Rhodes et al., 2007
). The
nuances of evoking fictive calls with electrical microstimulation in frogs and
in terrestrial vertebrates in general are likely dependent, in part, on a more
complex call circuitry that involves the integration of respiratory rhythms
(Bass and Baker, 1997
;
Zornik and Kelley, 2008
).
Steroid- and melatonin-dependent rhythmicity
What allows the observed neurophysiological changes in fictive calling to
occur in a night-time but not a noon-time brain, let alone in a reproductive
versus a non-reproductive animal? No doubt gonadal hormones play an
enormous role in the seasonal cycles of vocal activity, or any number of other
rhythmic behaviors. Indeed, increases in the degree of temporal encoding of
the higher harmonics of male hums by the peripheral auditory system of female
midshipman fish during the reproductive season can be induced in
non-reproductive females with either testosterone or estradiol treatments over
a period of about 3–4 weeks
(Sisneros et al., 2004b
). The
seasonal rhythmicity in vocal neurophysiology reported here is also
reminiscent of the steroid-dependent, morphometric changes in vocal nuclei in
songbirds (e.g. Arnold et al.,
1976
; Ball et al.,
2004
; Brenowitz,
2004
) and midshipman fish
(Forlano and Bass, 2005a
;
Forlano and Bass, 2005b
;
Bass and Forlano, 2008
). As in
songbirds, plasma levels of steroid hormones cycle with reproductive state in
midshipman, while androgen and estrogen receptors are found in the
midshipman's vocal control system in conjunction with the expression of brain
aromatase, which converts testosterone to estradiol (reviewed by
Bass and Remage-Healey, 2008
;
Forlano et al., 2006
).
While intramuscular injections of androgens in midshipman fish increase the
probability of evoking longer duration grunts, they do not evoke fictive
growls and hums with the temporal attributes described here
(Remage-Healey and Bass,
2004
). Thus, other aspects of reproductive state and time of day
are apparently key factors in the natural production of long duration calls
during the breeding season. In songbirds as well, there is evidence for
testis-independent effects on song production (without accounting for
centrally synthesized neurosteroids), since both sham-operated and castrated
sparrows under long day conditions have enlarged song control nuclei, and
exogenous melatonin decreases the size of telencephalic vocal nuclei
(Bernard et al., 1997
;
Bentley et al., 1999
).
Finally, the basal rate of the electric organ discharge (EOD) of weakly
electric fish increases at night independent of water temperature or breeding
status, although EOD rate in breeding males coupled with females is still the
greatest (Silva et al., 2007
;
Stoddard et al., 2007
). Thus,
steroid hormones, with their effect on the morphology as well as synaptic and
intrinsic firing properties of neurons, may be necessary, but not sufficient,
for the maximum upregulation of seasonally dependent vocal behaviors.
Diurnal changes in neuronal activity have been documented in brain regions
less typically linked to the motor components of reproductive behaviors, such
as the hippocampus (Barnes et al.,
1977
; Chaudhury et al.,
2005
). Excitatory postsynaptic potentials (EPSPs) in response to
perforant pathway stimulation, recorded in vivo in rats and monkeys
at different times of day, were as much as 30% larger in the dark phase than
the light phase of nocturnal rats, while the opposite effect was observed in
diurnal monkeys. Barnes and colleagues
(Barnes et al., 1977
)
hypothesized a circadian cycle of synaptic transmission in the hippocampus
that covaries with natural behavioral fluctuations, while Chaudhury and
colleagues (Chaudhury et al.,
2005
) concluded that an endogenous circadian oscillator modulates
long term potentiation in the mouse hippocampus.
Sometimes such rhythmic changes in behavior and neural systems can be
directly controlled by melatonin binding to regionally abundant receptors
(Whitfield-Rucker and Cassone,
2000
; Gahr and Kosar,
1996
; Musshoff et al.,
2002
; Rosenstein and Cardinali, 1990;
Wan et al., 1999
). For
example, melatonin applied to brain slices of the avian vocal circuit
decreases firing rate in a telencephalic vocal nucleus where the inhibitory G
protein-coupled melatonin 1 b receptor is expressed
(Jansen et al., 2005
). In
teleost fish, melatonin is rhythmically secreted from the retina and pineal
gland in intact and isolated preparations under various light conditions
(Bolliet et al., 1996
;
Cahill, 1996
;
Migaud et al., 2007
). Our
exposure of the midshipman to 24h D or 24h L for 5 days produced
neurophysiological results that correlate with the light-manipulated in
vivo melatonin rhythm found in several temperate teleost species [Migaud
et al., unpublished observations reported in Martinez-Chavez et al.
(Martinez-Chavez et al.,
2008
)] and in one subtropical species, the common dentex
(Pavlidis et al., 1999
).
Common dentex (Dentex dentex) acclimatized to 12 h L:12 h D and
thereafter exposed to 24 h D did not exhibit an endogenous melatonin rhythm
(low in the day, high at night); rather, levels were maintained as high as
during the natural night-time. If melatonin naturally enhances vocal circuit
function in the common dentex at night and 24 h D stimulates tonically high
levels as found in common dentex, then it may explain our ability to as easily
elicit fictive growls and hums from the 24 h D treated fish tested during the
circadian day as during the circadian night. Likewise, 24 h L can inhibit
melatonin production (and rhythmicity) altogether
(Martinez-Chavez et al.,
2008
), thus explaining the almost complete loss of long duration
fictive calling in our 24 h L fish during both natural day and night. Future
studies in midshipman need to assess shifting melatonin levels through natural
and manipulated photo regimes to more directly investigate the above
scenarios. Given the extensive GABAergic innervation of the vocal motor
nucleus (Marchaterre et al.,
1989
), and the evidence for melatonin modulation of GABAergic
activity in mammalian cortex (Musshoff et
al., 2002
; Wan et al.,
1999
), an interaction between this hormone and levels of
inhibition in the vocal motor circuit may contribute to the transition from
short grunts to long duration, lower frequency hums.
Future studies in midshipman need to assess shifting melatonin levels through natural and manipulated photo regimes to more directly investigate the above scenarios. This will include further evaluation of fluctuating fictive call threshold during natural day and night of both photo regimes. At this point, with a limited number of animals tested, there was only a trend for a persistent call threshold rhythm: lower in the natural night compared with day in constant darkness (24 h D), but not apparent in constant light (24 h L).
Concluding comments
The mechanisms underlying the observed neurophysiological changes in the
production of long duration fictive growls and hums from parental male
midshipman fish likely include a periodic modulation of both excitatory and
inhibitory activity in one or more vocal nuclei, as well as modulation of ion
channels [e.g. for the SCN (see Pennartz
et al., 2002
; Teshima et al.,
2003
; Meredith et al.,
2006
)]. Such natural fluctuations could be the downstream effects
of steroidal and/or non-steroidal (e.g. melatonin) hormone activation of
either local membrane or nuclear receptors, or even the product of local
oscillating clock gene transcription. Midshipman fish now offer the
opportunity to integrate the physiological mechanisms underlying stereotyped,
oscillatory-like vocalizations with the prevailing rhythms that shape them.
Lastly, given the shared origins of vocal pattern generators in fish and
tetrapods (Bass et al., 2008
),
the functional principles revealed by these and other studies will prove
informative to the vocal systems of vertebrates in general.
LIST OF ABBREVIATIONS
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