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First published online February 15, 2008
Journal of Experimental Biology 211, 773-779 (2008)
Published by The Company of Biologists 2008
doi: 10.1242/jeb.009795
Response properties of electrosensory units in the midbrain tectum of the paddlefish (Polyodon spathula Walbaum)
1 Center for Neurodynamics, Department of Biology, University of Missouri
– St Louis, St Louis, MO 63121, USA
2 Institute of Zoology, University of Bonn, Poppelsdorfer Schloss, 53115 Bonn,
Germany
* Author for correspondence (e-mail: hofmannm{at}umsl.edu)
Accepted 9 January 2008
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Summary |
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 TOP Summary INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Key words: electroreception, paddlefish, mesencephalic tectum, single unit
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INTRODUCTION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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).
Whereas some teleosts actively emit electric fields to probe their
environment, most electrosensory vertebrates only sense the weak ambient
fields that originate from other living organisms. This passive electrosensory
system has been well investigated at the level of the primary afferent fibers
and the hindbrain (dorsal octavolateral nucleus, DON). However, less is known
about the processing of electrosensory information at higher levels in the
brain.
Anatomical descriptions of ascending projections have shown that the major
target of hindbrain electrosensory neurons is the midbrain. There are three
major targets depending on the species. In teleosts, the most important target
is the electrosensory part of the torus semicircularis
(von der Emde, 1998). In
elasmobranchs, most fibers innervate the lateral mesencephalic nucleus.
However, the relationship between lateral mesencephalic nucleus and torus
semicircularis is not clear and they may be homologous. The tectum is also
innervated directly by DON fibers in elasmobranchs
(Boord and Northcutt, 1982;
Boord and Northcutt, 1988;
Northcutt and Boord, 1984). In
the paddlefish, all three mesencepalic targets receive direct input from the
hindbrain (Hofmann et al.,
2002).
There have been relatively few physiological investigations of the passive
electrosensory system in the midbrain. In elasmobranchs, Platt et al.
(Platt et al., 1974) and
Bullock (Bullock, 1979;
Bullock, 1984) described evoked
potentials in various midbrain areas in response to direct nerve shock and
electric field stimulations. Northcutt and Bodznick
(Northcutt and Bodznick, 1983)
identified the lateral mesencephalic nucleus in the dogfish as the main target
of ascending electrosensory information. Later, Bodznick
(Bodznick, 1991) found a
topographic map of electrosensory receptive fields in the tectum of a skate.
Single unit responses have been recorded in the midbrain of elasmobranchs
(Andrianov et al., 1984;
Schweitzer, 1986), the torus
semicircularis of catfish (Knudsen,
1976a; Knudsen,
1976b; Knudsen,
1978), and the tectum of a urodele, the axolotl
(Bartels et al., 1990).
However, these studies were mainly aimed at demonstrating the presence of
electrosensory information in the midbrain and its topographic representation
in the tectum. A detailed analysis of response properties to a variety of
stimulus waveforms and frequencies was not performed.
Paddlefish have the largest number of electroreceptors of any passive
electrosensory animal (Fig. 1).
The physiology of the electrosensory system has been extensively studied in
primary afferent fibers (Wojtenek et al.,
2001), and at the level of the hindbrain DON
(Hofmann et al., 2004;
Hofmann et al., 2005). In this
study, we analyzed the response properties of tectal units for comparison with
primary afferents and DON units.
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MATERIALS AND METHODS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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by the addition of stock salt. Before surgery the fish were
anesthetized with MS-222 (1:10 000). Local anesthesia (0.4% lidocaine, Sigma,
St Louis, MO, USA) was applied at the dorsal surface of the skull, and the
brain was exposed. Fish were then placed in the recording tank, immobilized
with 5–20 µl tubocuraine (Apothecon, Princeton, NJ, USA) and the
gills were irrigated through the mouth with fresh, aerated water.
Occasionally, local anesthesia with lidocaine was refreshed throughout the
experiment.
Stimulation
Electrical stimuli were delivered via silver wires at each end of the tank,
anterior and posterior to the fish, providing a quasi-homogeneous field across
the tank. In the figures the stimulus is displayed with respect to the
anterior electrode, i.e. if the stimulus goes positive, the anterior electrode
is positive with respect to the posterior electrode and vice versa.
Due to the geometry of the tank and the presence of the fish, the field was
probably not completely homogeneous. However, it allows stimulation of all
receptors simultaneously and avoids the necessity of locating the receptive
field for each unit with small local dipole electrodes. Stimuli were produced
by the computer and delivered through a USB audio interface (Burr Brown
PCM2902, Tucson, AZ, USA) that allowed DC output. The sampling rate was 22 050
s–1 and resolution was 16 bit. The signal was galvanically
isolated and converted to constant current by a linear stimulus isolator (A
395, WPI, Sarasota, FL, USA).
Electric fields applied to the tank were calibrated by measuring the voltage drop between two points in the middle of the tank parallel to the field lines. A sinusoidal stimulus at 5 Hz and different amplitudes was generated and the resulting field strength measured. We also changed the frequency to test for non-linearity between computer signal output and actual field strength in the tank. In the frequency and amplitude ranges used in this study, no non-linearity was present. While recording from higher multimodal areas, it was important that the experimental conditions excluded the stimulation of other modalities. Fortunately, stationary electrodes do not emit any physical signals other than electricity.
Recording
Tectal and DON units were recorded with tungsten electrodes (5–20
M
) or glass capillaries (1–10 M), filled with 3% lithium
chloride. Since tectal units showed no or little spontaneous activity, a
search stimulus was applied. This was usually a 5 Hz sinusoidal wave with 10
µV cm–1 peak-to-peak amplitude. Recordings were amplified
x1000 and filtered between 100 Hz and 5 kHz (AM Systems, Model 1700,
Carlsberg, WA, USA). The signal was digitized by a USB sound interface (Burr
Brown) and stored on a computer. The data were analyzed with Igor 5
(Wavemetrics, Portland, OR, USA), and standard dot plots, peri-stimulus time
histograms (PSTHs) and phase plots were computed.
Data analysis
For the spontaneous rate, we calculated the mean spike rate and the
coefficient of variation, which is the standard deviation of interspike
intervals divided by the mean interval. A value of 1 means that spikes are
generated randomly and lower values indicate that the spike train is more
regular.
To evaluate the response magnitude at different frequencies of a sinusoidal
electric field, two parameters were calculated. The first parameter was the
average spike rate during stimulation and the second parameter was the degree
of phase coupling. The latter was obtained by computing the normalized period
histogram of phase angles of spikes relative to the sine wave cycle with a bin
width of 10 degrees. Then, a value D was calculated
(Kajikawa and Hackett, 2005),
which is based on an estimate of entropy of the period histogram. This value
is 0 for random data and 1 if all spikes are in the same bin of the period
histogram. This method gives reliable results even if there is more than one
spike per period, which is often the case. The usual vector strength
calculations and Rayleigh tests were not used here since they are not reliable
if there is more than one spike per cycle or if spikes accumulate at two
different phase angles. The probability P for the significance of
synchrony was calculated according to Kajikawa and Hackett
(Kajikawa and Hackett, 2005).
Instead of calculating 1000 surrogate spike trains, we calculated 100, which
gives a probability resolution of 100, sufficient to detect significance
levels of P<0.01.
The mean phase angle of the spike trains was calculated according to
Goldberg and Brown (Goldberg and Brown,
1969). Phase angles were only calculated if the Rayleigh test
showed a significant phase coupling (z>4.6)
(Batschelet, 1981).
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RESULTS |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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Spontaneous rates
The spontaneous spike rate of tectal units was always very low
(2.20±2.22 Hz, N=48) compared with the ongoing spike rate of
DON units (27.6±11.7 Hz, N=71). Many units produced only a few
spikes and the interspike interval was highly variable. There was no
indication of an intrinsic rhythm. The mean coefficient of variation of tectal
units was 1.12±0.29, which means that the interspike interval was
random. In contrast, DON units showed a mean coefficient of variation of
0.21±0.206. This indicates that the spike trains were generated by a
regular mechanism. The difference between DON and tectum units was even more
apparent if the coefficient of variation was plotted against the spike rate
(Fig. 2A). This also shows that
it is unlikely that we recorded from afferent fibers in the tectum. There is
also strong evidence that we recorded from secondary units in the DON. It is
known that the spike trains of primary afferent fibers are driven by two
oscillators (Neiman and Russell,
2004). A fast Fourier transform (FFT) of their spike trains showed
two peaks, one corresponding to the spike generator and another at around 25
Hz that probably originates from the hair cells
(Fig. 2B). This 25 Hz
oscillation was absent in DON units (Fig.
2C) (see also Hofmann et al.,
2005).
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). Here, we focused on DON activity relevant for comparison
with that of tectal units. A 5 Hz sine wave caused the DON units to modulate
their firing rate around their spontaneous rate
(Fig. 3A). During the positive
phase of the sine wave, the ongoing activity was reduced at low stimulus
intensities and suppressed at higher intensities; during the negative phase
the spike rate was increased. In some units the phase relationship was
reversed and an increase in spike rate was observed during the positive phase
of the stimulus. However, there was no significant difference in overall spike
rate before and during stimulation (P>0.05, Wilcoxon paired-rank
test, N=37). In contrast, tectal units exhibited little spontaneous
activity and responses to a sine wave were mostly excitatory, i.e. the spike
rate was increased (P<0.0001, Wilcoxon paired-rank test,
N=42; Fig. 3B). Most
tectal units produced one to three spikes per cycle of the sine wave. However,
response activity was quite variable with some cycles failing to trigger
spikes whereas other cycles triggered two or three spikes. In most tectal
units, the response was uniform during prolonged stimulation
(Fig. 3B), although some units
had a delayed response starting a few seconds after stimulus onset
(Fig. 3C).
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In the tectum, spike rate change was more variable at higher amplitudes but, as in the DON, it was not a linear function of stimulus amplitude. Phase locking increased more systematically from the lowest amplitudes tested up to tenths of microvolts per centimeter, where it decreased again in some of the units. However, phase locking was much better (more than one order of magnitude) at amplitudes below 1 µV cm–1.
Response to different frequencies
Tectal and DON units were also tested at different frequencies of a uniform
sinusoidal field at 5–20 µV cm–1 peak-to-peak
amplitude. Since DON units had a spontaneous rate, any modulation that was
symmetrical around the spontaneous rate did not lead to an increase in overall
spike rate. Consequently, low stimulus frequencies that caused only minor
modulations resulted in only small changes in overall spike rate
(Fig. 7A). At frequencies above
ca 1 Hz some units increased their rate up to 10 Hz but some
decreased their rate. If the response was measured in terms of phase coupling
(D), DON units showed a linear relationship between frequency and
response magnitude below ca 5 Hz
(Fig. 7B). Above 10–20
Hz, modulation decreased steeply. The frequency tuning curves of DON units
were remarkably uniform with all units showing a similar frequency
response.
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DISCUSSION |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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),
they are probably not relevant for detecting small planktonic animals, the
primary food of the paddlefish. Here we used uniform stimulus fields, not with
the intention of simulating natural stimuli but for comparison with those used
in previous studies on the response properties of primary afferents and
hindbrain neurons. Furthermore, uniform fields are spatially uniform, i.e. the
field strength at a given point in time is the same around the animal.
The first obvious difference between tectal and DON units is that tectal units had little or no spontaneous activity. This has implications for neuronal coding. DON units with a spontaneous rate respond to electric field changes by modulating their spike rate. The mean spontaneous rate is higher (27.6 Hz) than the highest stimulus frequency the cells respond to (up to 20 Hz), which allows for accurate coding in the signal bandwidth. As a consequence, a sinusoidal signal causes modulation of the DON spike rate with no or little change in overall rate. This would be equivalent to a frequency modulation where the spontaneous rate is the carrier frequency. Tectal cells with low spontaneous activity cannot apply a rate code. Furthermore, the coefficient of variation is around 1, which suggests that spikes are generated at random intervals. Without stimulation, tectal units either generate spikes due to an internal Poisson-like process or they respond to the noise that is present in their synaptic input. If the latter is true, the spike train of tectal cells would represent the demodulated signal of the frequency modulated input from the DON units.
Like DON units, tectal units produced spikes phase locked to the sine wave.
However, the mean phase angle varied from unit to unit. In the DON, spikes
occurred during either the negative or the positive half-cycle, with most
units responding to the negative half-cycle. In all passive electrosensory
fishes with the exception of teleosts, primary afferent fibers respond with an
increase in spike rate when the electric field at the pore is negative
relative to the internal reference potential of the fish. Due to the high skin
impedance of freshwater fish, this reference potential is the average
potential of the fish's body (or head)
(Kalmijn, 1974). Recordings
from primary afferents of the paddlefish showed that fibers innervating the
rostrum respond with an increased rate if stimulated with a uniform field with
the cathode in front of the animal. Fibers innervating the gill cover,
however, respond to the same stimulus with a decrease in spike rate (M.H.H.
and L.A.W., unpublished observations). In this case, the opercular pore
openings are closer to the stimulus electrode behind the fish and the center
of the internal reference, which is somewhere around the mouth, is closer to
the electrode in front of the animal. This explains the two populations of
units in the DON with mean phase angles that differ by roughly 180 degrees. As
in the DON, tectal units were also highly phase coupled, but the mean phase
angle was variable from unit to unit and did not fall into two classes. Each
unit, however, had a characteristic phase angle that was mostly independent of
stimulus amplitude (see Fig.
5).
In contrast to the phase angle, the degree of phase coupling changed systematically with stimulus amplitude in both the DON and tectum. In the DON, phase coupling increased steeply between 0.3 and 3 µV cm–1, a range over which overall spike rate was unchanged. This suggests that in DON units, amplitude information is frequency modulated with the spontaneous rate being the carrier frequency. Tectal units appear to be more sensitive than DON units. Phase coupling was at least one order of magnitude higher at amplitudes below 1 µV cm–1.
Tectal and DON units were also different in their frequency response. DON units were remarkably similar when tested with sinusoidal waves at different frequencies. Although there were differences in spontaneous rate, the shape of the frequency response curve was nearly identical from unit to unit and the phase locking decreased proportionally with frequency below ca 5 Hz. Tectal units were more heterogeneous and did not show much attenuation at lower frequencies.
Due to the frequency response properties of primary afferents and DON units
that center on 10 Hz, the passive electrosensory system was thought to be
tuned to this frequency band. However, behavioral studies showed that best
frequencies are always lower (Peters and
Evers, 1985; Peters et al.,
1988). We have shown here that higher brain centers such as the
tectum have units with a frequency response tuning that agrees better with the
results of the behavioral studies. But, why do peripheral neurons attenuate
frequencies that are obviously relevant for the animal? It is known that the
filter curve for peripheral units can be described as a first derivative with
an additional low-pass filter (Hofmann et
al., 2004). In the special case of a sine wave, a derivative
filter would attenuate lower frequencies and shift the phase of the signal,
but would not change the waveform. However, if any other signal was applied,
its wave form would change. If we consider for example a monopolar DC electric
field that passes the animal, the electric field at a receptor would increase
while the source approaches and decrease afterwards. This is not a periodic
waveform, but just a transient increase in field strength that slowly goes
back to zero. Depending on stimulus polarity, this would result in either a
transient increase or a transient decrease in spike rate. A derivative filter
would convert this signal into a bipolar stimulus that would cause an increase
in spike rate followed by a decrease or vice versa. Thus, regardless
of stimulus polarity, DON units would always show a period of increased firing
in response to a monopolar moving stimulus. Furthermore, from the derivative
it is possible to calculate the distance of the source from the skin surface
(Hofmann and Wilkens, 2005).
We think that a major function of the derivative filter is to change the
waveform of such non-periodic events rather than to high-pass filter
sinusoidal signals. However, the side effect that low frequencies are
attenuated in the hindbrain is apparently compensated for in the tectum. This
is supported by the fact that tectal units respond better to lower frequencies
than DON units, which agrees better with behavioral studies
(Peters and Evers, 1985;
Peters et al., 1988). We can
only speculate about the mechanism involved, but we now know where it takes
place and can investigate whether perhaps a temporal integration could reverse
the effect of the peripheral differentiation.
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Acknowledgments |
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References |
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TOPSummaryINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONReferences |
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