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The Journal of Neuroscience, June 1, 2002, 22(11):4577-4590
Receptive Field Organization Determines Pyramidal Cell
Stimulus-Encoding Capability and Spatial Stimulus Selectivity
Joseph
Bastian1,
Maurice J.
Chacron2, 3, and
Leonard
Maler2
1 Department of Zoology, University of Oklahoma,
Norman, Oklahoma 73019, and Departments of 2 Cellular and
Molecular Medicine and 3 Physics, University of Ottawa,
Ontario, K1N 6N5 Canada
 |
ABSTRACT |
Sensory systems must operate over a wide range of spatial scales,
and single neuron receptive field (RF) organization may contribute to
the ability of a neuron to encode information about stimuli having
different spatial characteristics. Here we relate the RF organization
of sensory neurons to their ability to encode time-varying stimuli,
using linear stimulus estimation, measures of information transfer, and
more conventional analysis techniques. The electrosensory systems of
weakly electric fish are recognized as very tractable model systems for
studies of sensory processing because behaviorally relevant stimuli are
generated easily and related to known behaviors and because a
detailed anatomical database is available to guide the design and
interpretation of experiments. Receptive fields of neurons within the
first central electrosensory-processing region have an antagonistic
center-surround organization; the RF area varies with cell type, with
dendritic morphology, and with the spontaneous activity patterns of the
cell. Functional consequences of variations in center-surround
organization were assessed by comparing responses to two spatial
stimulus patterns that mimic naturalistic stimuli and that provide
input to the center alone or to the center plus surround. Measures of
the quality of stimulus estimation (coding fraction) and information
transmission (mutual information) as well as traditional measures of
responsiveness consistently demonstrate that, for cells having large
surrounds, the activation of both receptive field components degrades
the ability to encode time-varying stimuli. The loss of
coding efficiency with center-surround stimulation probably results
from cancellation of balanced excitatory and inhibitory inputs.
However, cells with small surrounds relative to centers perform well
under all spatial stimulus regimes.
Key words:
electroreception; electrolocation; electrocommunication; information theory; neural coding; pyramidal cells; stimulus
reconstruction; receptive fields
 |
INTRODUCTION |
Sensory neuron receptive field
properties vary widely and generally are thought to be matched or tuned
to the spatial and temporal characteristics of naturalistic stimuli,
allowing these to be detected or encoded while limiting responsiveness
to patterns that contain little useful information. This work focuses
on a population of primary sensory neurons, pyramidal cells, within the
electrosensory system of the gymnotiform fish Apteronotus leptorhynchus. The principal goal of these studies was to define the receptive field (RF) characteristics of pyramidal cells and to
compare their responses to stimuli applied in a manner mimicking either
signals received during communication or prey detection behaviors.
Weakly electric fish generate an electric field around the body via an
electric organ and continuously monitor this electric organ discharge
(EOD) field with electroreceptors scattered over the body surface (for
review, see Turner et al., 1999
). Electroreceptors designed to encode
the amplitude and the timing of the EOD (Scheich et al., 1973
) project
somatotopically to the first central electrosensory-processing center,
the electrosensory lateral line lobe or ELL, forming three complete
maps of the ipsilateral body surface (Heiligenberg and Dye, 1982
).
These afferents provide monosynaptic excitation and disynaptic
inhibition to the two principal ELL efferent neurons, the basilar and
nonbasilar pyramidal cells (Maler, 1979
; Maler et al., 1981
), which
also are referred to as E and I cells because they respond to increased
EOD amplitude with excitation and inhibition, respectively (Saunders
and Bastian, 1984
). The ELL receives massive synaptic input from higher
electrosensory centers as well (Sas and Maler, 1983
, 1987
). The
pyramidal cells extend elaborate apical dendrites into the ELL
molecular layers and receive both excitatory and inhibitory inputs from
higher centers. Previous studies demonstrated multiple roles for these
descending inputs, including gain control (Bastian,
1986a
,b
), positive feedback accentuation of stimulus features (for review, see Berman and Maler, 1999
), and modulation of RF
characteristics, including adaptive (plastic) optimization of common
mode rejection (for review, see Bastian, 1999
).
Recent studies also have demonstrated variations among ELL pyramidal
cells in terms of spontaneous firing properties and responses to simple
electrosensory stimuli. These variations are correlated highly with
pyramidal cell morphology, particularly apical dendritic structure
(Bastian and Courtright, 1991
; Bastian and Nguyenkim, 2001
). Hence
these physiological properties, which are measured easily, allow RF
characteristics to be related indirectly to pyramidal cell morphology.
Previous studies already have established that there are significant
physiological as well as anatomical differences among pyramidal cells
contingent on their locations within the multiple ELL somatotopic maps
(Shumway, 1989a
,b
), and it also has been demonstrated that different
maps are required for the correct performance of specific
communication behaviors (Metzner and Juranek, 1997
). This study focuses
on variations among pyramidal cells within maps, with the goal of
relating the firing characteristics of the cells and, by inference,
cell morphology to receptive field structure. In addition to defining
the spatial characteristics of pyramidal cell RFs, the functional
consequences of different RF organizations were determined. Responses
to stepwise and sinusoidal amplitude modulations (EOD AMs) as well as
random patterns of EOD AMs were studied. In conjunction with the
latter, stimulus reconstruction techniques (Rieke et al., 1996
;
Gabbiani and Koch, 1998
; Borst and Theunissen, 1999
) were used to
estimate the ability of pyramidal cells to encode detailed information
about the time course of electrosensory stimuli.
Previous investigations using stimulus reconstruction techniques showed
that tuberous electroreceptor afferents performed well, encoding from
40 to 80% of the information about stimulus time course (Wessel et
al., 1996
; Metzner et al., 1998
; Kreiman et al., 2000
). Pyramidal
cells, however, performed poorly, typically encoding <20% of the
stimulus (Gabbiani et al., 1996
; Metzner et al., 1998
; Gabbiani and
Metzner, 1999
). When the random AMs were applied in a manner that
stimulates RF centers and surrounds simultaneously, as is expected for
electrocommunication stimuli, we confirmed that a subset of pyramidal
cells performs poorly. However, when stimuli were presented
preferentially to RF centers, as occurs during electrolocation and
tracking of small prey (Nelson and MacIver, 1999
), significant
improvements in coding performance were seen.
 |
MATERIALS AND METHODS |
The weakly electric fish A. leptorhynchus was used
exclusively in these studies. Animals were housed in groups of 3-10 in 150 l tanks, temperature was maintained between 26 and 28°C, and water resistivity varied from 2000 to 5000
· cm. Experiments were
performed in a 39 × 44 × 12 cm deep Plexiglas aquarium with water recirculated from the animal's home tank. Animals were
respirated artificially with a continuous flow of aquarium water at a
rate of 10 ml/min. Surgical techniques were the same as described
previously (Bastian, 1996a
,b
), and all procedures were in accordance
with the University of Oklahoma animal care and use guidelines.
Recording and stimulation. Extracellular single-unit
recordings were made with metal-filled micropipettes constructed as
described by Frank and Becker (1964)
. Recording sites determined from
surface landmarks and recording depths were limited to the lateral and centrolateral ELL segments; pyramidal cells were identified on the
basis of recording depth and previously established firing characteristics (Saunders and Bastian, 1984
; Bastian and Courtright, 1991
). The EOD waveform was measured via silver-silver chloride wire
electrodes positioned near the animal's head and tail (Fig. 1E1, E2). The neural signals
and the head-to-tail EOD waveforms were amplified with World Precision
Instruments (Sarasota, FL) DAM50 preamplifiers with a gain of 1000 and
filters set at 300 Hz and 3 kHz. Spikes and EOD waveform zero crossings
were detected with window discriminators, and their times of occurrence
were measured with Cambridge Electronic Design (Cambridge, UK)
1401plus hardware and SpikeII software (resolution, 0.1 msec). The EOD waveform also was measured with a small
dipole pair of silver-silver chloride electrodes separated
by 2 mm, oriented perpendicular to the animal's skin, and positioned
within the receptive field of each cell. This dipole was used to
measure the changes in the local EOD amplitude resulting from the
various stimuli. This "local EOD" was amplified with a World
Precision Instruments DAM50 preamplifier (gain of 10,000; filters at
300 Hz and 3 kHz) and analog-to-digital converted with 10 kHz sampling
rate.

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Figure 1.
Stimulus generation. A,
Electrodes E1 and E2 near the animal's
head and tail measured the normal electric organ discharge waveform,
H-T EOD, and a sinusoidal Stimulus
waveform was synchronized to the zero crossings of the
H-T EOD (dotted lines). The stimulus
waveform was presented to the animal with two different geometries.
With global geometry the stimuli were applied via electrodes
G1 and G2, resulting in relatively
homogeneous stimulation of the body surface. With local
geometry a stimulus dipole applied the stimulus to
localized regions of the body surface. B, C, Period
histograms of the responses of a p-receptor afferent to sinusoidal
amplitude-modulated stimuli showing that, with correct calibration,
global and local stimuli result in similar electroreceptor afferent
responses.
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|
The electric organ of Apteronotus consists of modified
motoneurons; hence it remains intact during the neuromuscular blockade used in these experiments. Therefore, the spontaneous firing patterns that are described refer to activity in the presence of the animal's normal EOD but in the absence of any EOD modulations. Electrosensory stimuli consisted of amplitude modulations of the normal EOD produced by applying a train of sinusoidal waveforms to the fish. Each sinusoid
was triggered at the zero crossing of each EOD cycle (Fig.
1A, dashed lines) and had a period
slightly less than that of the EOD waveform; hence the train remained
synchronized to the animal's discharge and, depending on its polarity,
either added to or subtracted from the animal's own discharge. To
generate EOD AMs having different time courses, we multiplied
(MT3 multiplier; Tucker-Davis Technologies, Gainesville, FL) the train
of sinusoids by a square pulse (500 msec duration) to produce stepwise
AMs, a DC offset sine wave to generate sinusoidal AMs, or band-limited white noise to generate random AMs. The resulting signal was isolated from ground (World Precision Instruments A395 linear stimulus isolator), passed through a step attenuator for controlling amplitude, and then applied to the animal with either of two different geometries.
With global geometry the stimulus was applied to the tank via
silver-silver chloride electrodes ~19 cm lateral to either side of
the fish (Fig. 1, G1, G2). This stimulus produced a
relatively homogeneous change in EOD amplitude over the body surface
both ipsilateral and contralateral to the ELL-recorded from. The
amplitude of this field was set to 1.0 mV/cm without the fish in place, and this gradient served as the reference stimulus level (0 dB). The
typical global stimulus amplitude that was used to characterize cells
was
12 dB or ~250 µV/cm. With the second geometry, referred to as
local geometry, the stimulus signals were generated as described above
but delivered via a small stimulus dipole made from 76 µm stainless
steel wires insulated except for their tips and with a tip spacing of 2 mm (Fig. 1A, stimulus dipole). This
dipole, which exclusively activates small ipsilateral populations of
electroreceptors, was carried by a computer-controlled three-axis
positioning device that allowed for accurate placement of the stimulus
dipole at any selected site on, or lateral to, the skin surface.
A principal goal of these studies was to compare pyramidal cell
responses to stimuli applied with global geometry and with stimuli
applied only to the subregions of the receptive field of a cell (local
geometry). P-type electroreceptor afferents were used as the measuring
devices to calibrate the effectiveness of different stimulation
geometries. The local dipole typically was positioned 2-3 mm lateral
to the animal's skin; at this distance dipole currents ranging from
100 to 250 nA, depending on water resistivity, resulted in receptor
responses equivalent to those caused by the typical global stimulus of
250 µV/cm. Setting the product of dipole current and water
resistivity to 5 × 10
4 V · cm
resulted in a good match between global and local dipole stimuli;
Figure 1B,C shows phase histograms of the responses
of a p-receptor afferent to global and local stimuli of
12 dB,
respectively. Calibration experiments were done for 25 receptor
afferents in three fish. Receptor afferent locations spanned both the
dorsoventral and rostrocaudal extent of the middle two-thirds of the
body, which corresponded to the region containing the RFs of the
pyramidal cells that were studied. Responses were measured as vector
strengths of the phase histograms (see Data analysis). These averaged
0.074 ± 0.005 and 0.07 ± 0.005 (p = 0.55; Student's t test) for global and local stimulus
geometries, respectively.
Data analysis. At the start of each experiment the fish was
photographed from its lateral aspect; the outline of the fish was
digitized, scaled to its original size, and imported to MATLAB (The
MathWorks, Natick, MA). This image, along with the coordinates at which
the stimuli were applied, allowed for accurate reconstruction of the
spatial aspects of receptive fields. Records of spike times, times of
EOD zero crossings, times of stimulus presentation, and peak-to-peak
values of each successive EOD cycle, measured within the RF of a cell,
were exported from SpikeII as text files for subsequent analysis with
MATLAB. Pyramidal cell baseline firing frequencies and their tendencies
to produce short bursts of spikes were determined from activity in the
presence of the normal electric organ discharge. Pyramidal cells were
categorized as bursty or nonbursty, depending on whether or not they
produced clusters of spikes with short interspike intervals at rates
above those expected for a Poisson spike train of the same mean
frequency (Bastian and Nguyenkim, 2001
). Responses to stepwise AMs were accumulated as peri-stimulus time histograms (PSTHs) and quantified as
mean increases in firing frequency above baseline rates. Responses to
sinusoidal AMs were accumulated as period histograms, and responses were quantified as the vector strength or mean vector length
(Batschelet, 1981
; Mardia and Jupp, 1999
). This measure ranges from 0, when there is no phase relationship between the stimulus and response, to 1 with perfect phase locking.
Responses to random AMs were used to assess the ability of pyramidal
cells to encode detailed information about the time course of
electrosensory stimuli presented with global and local geometries. Random AMs were generated by multiplying the stimulus waveform by a
noise signal generated with a WG1 waveform generator (Tucker-Davis Technologies). Before multiplication, the noise signal was
low-pass-filtered (model 3382 eight-pole Butterworth filter;
Krohn-Hite, Avon, MA) with a cutoff frequency
(fc) typically equal to 10 Hz.
Then this signal with SD
was applied to the fish as
described above. Linear stimulus estimation techniques (Rieke et al.,
1996
) have been used previously to determine the accuracy with which
electroreceptor afferents (Wessel et al., 1996
; Kreiman et al., 2000
)
as well as pyramidal cells (Gabbiani et al., 1996
; Metzner et al.,
1998
; Gabbiani and Metzner, 1999
) encode time-varying stimuli presented with a geometry similar to the global geometry described above. These
techniques, described in detail by Gabbiani and Koch (1998)
and
Gabbiani and Metzner (1999)
, also were used in this study. Records of
spike times and peak-to-peak (p-p) amplitude of the EOD recorded within
the RF of the cell under study were imported to MATLAB and resampled at
2 kHz. Because the p-p amplitude of the EOD was measured from
successive EOD cycles, the original sampling frequency for this signal
is equal to a given fish's EOD frequency, which ranges from 600 to
~900 Hz. Resampling of the p-p EOD records to the higher frequency
was done by spline interpolation, and then the resampled record was
low-pass-filtered to remove any residual high-frequency noise.
The Wiener-Kolmogorov filter that minimized the mean square error
2 between the stimulus and the
reconstructed stimulus was computed from the resampled spike train and
EOD amplitude data as described by Gabbiani and Koch (1998)
. The
estimate of the original stimulus was obtained by convolution of the
spike train with this filter. The accuracy of the reconstruction was
quantified as the coding fraction (
= 1
/
), which ranges
from 0 for the case in which the estimate is no better than that
expected by chance to 1, where the estimate perfectly replicates the
stimulus. Stimulus estimation and coding fractions were calculated with
MATLAB algorithms described by Gabbiani and Koch (1998)
and available
at: http://www.klab.caltech.edu/~gabbiani/signproc.html.
In addition to coding fraction, a lower bound on the rate of mutual
information rate in bits per second (I) conveyed by
the spike train was determined as:
(Borst and Theunissen, 1999
), where
SNR(f) is the signal-to-noise ratio
computed at frequency f. It is given by:
where
Pss(f) and
Pnn(f) are
the power spectra of the stimulus and spike train, respectively, and
Psn(f) is the
cross-spectrum between the stimulus and the spike train (Gabbiani,
1996
; Rieke et al., 1996
). Mutual information rate in bits per spike
was calculated by dividing I by the firing rate of the cell
during the stimulation. Means are given as ±1 SE.
 |
RESULTS |
ELL pyramidal cell receptive fields
Pyramidal cell receptive fields were mapped by positioning a small
stimulus dipole 0.5-1 mm lateral to the fish at various rostrocaudal
and dorsoventral coordinates. The stimulus dipole delivered a
sinusoidally amplitude-modulated mimic of the animal's discharge that,
on the basis of electroreceptor afferent recordings, altered afferent
firing frequencies within a circular area having a radius of between 2 and 3 mm. Responses to this stimulus were summarized as phase
histograms, as shown in Figure
2A. When recording from
E cells (basilar pyramidal cells), we set the polarity of the stimulus
so that peak excitation occurred at the origin of the histogram, as
shown by the waveform below Figure 2A. Stimulus polarity was inverted for I cells (nonbasilar pyramidal cells).

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Figure 2.
Basilar pyramidal cell (E cell) receptive field
center mapped by defining the RF center boundaries. A,
Period histogram of the responses of the cell to sinusoidal AM (200 cycles) presented locally near the RF center. The
z-values are Rayleigh statistics, and values 4.5 indicate significant phase modulation (p
approximately 0.01). B, Period histogram typical
of responses at the RF center boundary. Open circles
indicate sites defining the best-fit elliptical area (176 mm2) estimating the RF center. C,
Period histogram typical of responses 2 mm beyond the RF center
boundary (filled circles). D-K,
Responses at sites within the antagonistic surround. L,
M, Responses at sites outside the antagonistic surround.
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The boundary of the RF center of a given cell was determined by
identifying from 6 to 14 locations at which phase histograms of the
responses of the cell were similar to responses from the RF center
(compare Fig. 2A,B) but showed obvious phase shifts with 1-2 mm changes in the dorsoventral or rostrocaudal direction (compare Fig. 2B,C). Phase shifts seen because of
moving the stimulus across the RF boundary averaged 98.6 ± 9.2°
(n = 31 measurement pairs from 14 cells). Then
receptive field center outlines were estimated by determining the
least-squares best-fit ellipse to these locations. An example of a RF
center estimated in this manner is shown by the gray area along with
the eight loci used for the estimation (Fig. 2, white
circles). No RF centers had borders extending to the contralateral
side of the body. At locations more distant from the RF center the
responses of the cell completely reversed polarity, as expected for
stimuli applied to the antagonistic surround (Fig.
2D); the regions of the body surface at which these "surround responses" could be evoked were, in some cells,
surprisingly large (Fig. 2E-K). All
ipsilateral locations tested within ~2.5-3 cm from the center
boundary of this cell gave surround responses. It was not determined
whether the surrounds of pyramidal cells extended to the contralateral
side of the body. The Rayleigh statistic (z) was used to
determine whether the stimulus caused significant modulation of the
activity of the cell; these are indicated for each histogram, and
values >4.5 (p
0.01) were taken to indicate significant responses. Only when the stimulus dipole was moved greater
than ~3 cm from the nearest RF center boundary did the cell cease
responding to the EOD AM (Fig. 2L,M).
Pyramidal cell receptive field center areas were found to vary with
pyramidal cell type, E (basilar) versus I (nonbasilar), as well as with
characteristics of the spontaneous firing patterns of the cells. Cells
were characterized as either bursty or nonbursty, depending on whether
or not autocorrelations of their spontaneous activity differed
significantly from that expected for a Poisson spike train and, as
described previously (Bastian and Nguyenkim, 2001
), the majority of
both E and I cells had bursty firing patterns. Of the sample of 33 cells for which RF center maps were produced, 27 had relatively low
spontaneous rates and bursty firing patterns (Fig.
3A,B). Receptive field center
areas were estimated from the best-fit ellipse for each cell; the mean
areas for the different cell types are shown in Figure 3C.
Among the bursty cells, mean center areas were significantly larger for
the E cells compared with the I cells, averaging 192 ± 21 and
142 ± 11 mm2, respectively
(p = 0.05; t test). The
high-frequency nonbursty pyramidal cells were seen less frequently (6 of 33 cells), and the average RF center area was intermediate between
that of the bursty E and I cells (Fig. 3C). Although the
mean area of the RF centers of nonbursty cells was not significantly
different from that of the bursty E or I cells, the shapes of the
centers did differ. The ratio of the major to minor axis of the
best-fit ellipse was calculated for each cell; these averaged 2.99 ± 0.22 and 1.89 ± 0.21 for bursty and nonbursty cells,
respectively (p < 0.002; t test).
Hence the RF centers of bursty cells are more elongate in the
rostrocaudal direction and flattened in the dorsoventral direction
compared with those of the nonbursty cells. Overall, the major axes of
the best-fit ellipses were well aligned with the long axis of the fish.
The orientation of the major axes varied over a range of 10 to
21°
relative to a line running from the tip of the snout through the center
of the tail (mean deviation,
1.65 ± 6.01°).

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Figure 3.
Summary of pyramidal cell RF center areas
determined by mapping center-surround boundaries. A,
Mean spontaneous firing frequencies of bursty E cells
(E), bursty I cells
(I), and nonbursty (NB) E
and I pyramidal cells. B, Mean burst indices (percentage
of bursts unexpected, given a Poisson spike train) of E and I cells; by
definition, NB cells have burst indices of zero. C, Mean
RF areas for E, I, and nonbursty cells. Error bars = ±1 SEM.
D, Scatter plot illustrating the correlations among
pyramidal cell RF center area, spontaneous firing rate, and burst
indices. Filled circles and squares
indicate E and I cells; open circles and
squares indicate nonbursty E and I cells,
respectively.
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It was shown previously that spontaneous firing characteristics of
pyramidal cells are correlated with the morphology of a cell,
especially the size of the apical dendrite arbor (Bastian and
Courtright, 1991
; Bastian and Nguyenkim, 2001
). The lowest-frequency bursty cells are found most superficially within the ELL pyramidal cell
layer, and these cells have the most extensive apical dendrites. Cells
with higher spontaneous rates are less bursty, found deeper within the
pyramidal cell layer, and have smaller dendritic arbors. The
highest-frequency cells, which are typically nonbursty, have the
smallest dendritic arbors, and these comprise a distinct morphological category termed deep basilar pyramidal cells. Receptive field center
areas of bursty E and I cells are plotted against spontaneous firing
rate and burst indices in Figure 3D (filled
circles and squares, respectively). Areas were
correlated negatively with the spontaneous firing rates of the cells
(r =
0.51; p = 0.007) and correlated
positively with their tendency to fire bursts of spikes
(r = 0.41; p = 0.035). Hence those
cells with low spontaneous firing frequencies and high burst indices
had the largest RF centers. The nonbursty cells differed, having larger
RF center areas than the highest-frequency bursty cells (Fig.
3D, open symbols). Given the relationships
between spontaneous firing characteristics and cell morphology, this
result suggests that RF center areas also may be related to the
morphologies of the cells.
Estimation of antagonistic surround areas
As shown in Figure 2, extensive areas of the body surface
apparently contribute to the RF antagonistic surround of pyramidal cells. The large size of these surrounds precluded efficient
determination of their area by directly searching for boundaries as
described above. As an alternative, the stimulation dipole was
positioned sequentially at 55 sites, each separated by 1 cm over a grid
extending 10 cm in the rostrocaudal and 4 cm in the dorsoventral
directions. The distance of the stimulus dipole lateral to the fish
ranged from a minimum of ~2 to a maximum of ~5 mm because of the
curved surface of the animal. Increasing the lateral distance between the surface of the fish and the stimulus dipole is expected to increase
the area of skin stimulated by the dipole, and receptor afferent
recordings showed that at a lateral distance of 3 mm the standard
dipole stimulus altered afferent firing frequencies within a circular
area having a radius of ~5 mm.
At the RF center of each cell and at each of the 55 stimulation sites,
responses to 20 sec presentations of a 4 Hz sinusoidal EOD AM were
summarized as phase histograms, and the direction of the mean vector
and the Rayleigh statistic (z-value) were computed for each
histogram. The mean vector direction determined from stimulation within
the RF center was taken as a reference direction. The directions of the
mean vectors determined at each of the remaining stimulation sites were
compared with the reference direction, and the z-values for
those that differed by more than ±90° were given a negative value.
Thus Rayleigh statistics from stimulation sites within the RF center
remain positive, whereas those obtained from sites in the surround
region are negative. Then the two-dimensional array of
z-values was interpolated to 1-mm-grid spacing
(two-dimensional linear interpolation) for improved visualization and
displayed as a surface superimposed on the outline of the fish, with
regions of different colors indicating different z-values.
The numbers of spikes within each phase histogram ranged between ~80
and 400, depending on the firing rate of a given cell; for this range
of spike counts z-values >4.5 indicate significant phase
coupling to the EOD AM (p < 0.01). Therefore,
±4.5 was taken as the z-value limits to identify areas
within which the dipole stimulus caused significant changes in the
firing pattern of a cell.
Figure 4, A and B,
shows RF maps for mid-frequency E and I cells recorded from neighboring
ELL regions of the same fish. The red region of Figure
4A indicates the area within which the stimulus caused significant responses in-phase with stimuli applied to the RF
center, and the blue areas within the inner and outer white contour
lines show the areas within which the cell gave significant out-of-phase responses (estimated surround areas). The color map for
the I cell, Figure 4B, was inverted to emphasize that
the cell responded to falling EOD amplitude applied to its RF center. For comparison, the RF centers also were outlined via the technique described in conjunction with Figure 2, and these are shown by the
white ellipses along with the stimulation sites to which the ellipses
were fit (Fig. 4B, filled circles). The
increase in RF size seen when the mapping is done with the stimulus
dipole further lateral to the fish is expected, given that the
effective area of the stimulus expands with increasing distance of the
dipole lateral to the fish, and this effective area is shown by the
gray circle above the distance calibration. Although the majority of cells had antagonistic surrounds as large or larger than their centers,
some of the highest-frequency and nonbursty cells had very small
surrounds. Figure 4, C and D, shows the RF maps
obtained from a nonbursty E cell (27 spikes/sec spontaneous rate),
using the standard stimulus strength as well as a stimulus 6 dB greater in amplitude. Receptive field center areas were comparable with that of
the E cell of Figure 3A, but essentially no antagonistic surround was seen with the standard stimulus. Increasing stimulus strength by a factor of 2 recruited only small increases in the surround area.

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Figure 4.
Pyramidal cell receptive field maps based on
responses to sinusoidal AMs presented over an array of grid points.
A, An E cell (18.8 sp/sec spontaneous rate; RF center
area, 629 mm2; surround area, 3295 mm2). White ellipse
shows RF center area (138 mm2) mapped as the
best-fit ellipse to boundary points shown as black
circles. B, An RF map for an 18.6 sp/sec I cell
recorded from the same animal; center and surround areas, 296 and 3416 mm2, respectively. RF center areas determined from
boundary points, 124.8 mm2. C, D, RF
maps for a 27 sp/sec nonbursty E cell mapped with the standard stimulus
intensity and with a 6 dB (~2×) increase in amplitude, respectively.
RF center and surround areas, 560 and 17 mm2,
respectively, for the standard dipole stimulus; areas were increased to
591 and 227 mm2, respectively, with the stronger
stimulus. Color maps were set to saturate at z-values of
±10. The gray circle indicates the spatial extent of
the above-threshold stimulus attributable to the standard stimulus
intensity determined from p-receptor afferent recordings.
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The relative sizes of RF centers and antagonistic surrounds mapped in
this manner varied with pyramidal cell type (E, I, or nonbursty, NB)
and with the spontaneous firing rates of the cells. Figure
5A-C summarizes RF dimensions
for a population of 10 E cells, 11 I cells, and 7 NB cells. The average
firing frequencies for the E and I cells did not differ, but as
described above, the nonbursty cells have significantly higher
spontaneous rates (Fig. 5A). As was found by using
the perimeter-mapping technique, the RF centers of E cells are
significantly larger than those of the I cells, whereas the RF centers
of the NB cells are of intermediate size (Fig. 5B). The
dimensions of RF antagonistic surrounds varied oppositely; the mean
surround area of I cells was approximately threefold greater than that
of either the E cells or the nonbursty cells (Fig. 5C).

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Figure 5.
Summary of RF dimensions mapped with
dipole stimulus positioned over an array of grid points.
A, Mean spontaneous firing rates of the sample of E
cells (E), I cells
(I), and nonbursty (NB) E
and I cells selected for similar local EOD modulation.
B, Mean RF center areas; E cell and NB cell RF center
areas > mean I cell center area; p < 0.02;
one-way ANOVA and Tukey-Kramer multiple comparison tests.
C, Mean RF surround areas; I cell RF surround area > E and NB cell RF surrounds; p < 0.02; one-way
ANOVA and Tukey-Kramer multiple comparisons. Error bars = ±1 SEM.
D, E, Summaries of RF center and surround areas,
respectively, of cells having different spontaneous firing rates
(correlation coefficients: D, r = 0.143, p = 0.39; E,
r = 0.51, p = 0.001).
Filled circles and squares indicate E and
I cells, respectively; open circles and
squares indicate nonbursty E and I cells.
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|
Although a standard stimulus strength was used for these RF mapping
experiments, the relative change in local EOD amplitude caused by the
stimulus did vary. This variation occurs not only because the EOD
amplitudes of individual fish are usually different but also because
local EOD amplitudes measured at different sites on the body surface
vary (Bastian, 1981a
; Rasnow and Bower, 1996
). The cells described in
Figure 5A-C represent a subset of the total sample that was
studied. These data were selected to insure that the local EOD
modulations measured within the RF center were within the same range
(25-75%) and that the mean modulation did not vary significantly
between the E and I cell samples. The mean local EOD modulations
averaged 51 ± 6.5 and 43 ± 3.2% (p > 0.27; t test) for the E and I cells, respectively. The
mean local EOD modulation for the nonbursty cells was higher, 82 ± 21%, because in several cases stronger stimuli were used in an
attempt to reveal potentially higher threshold surround regions.
Analysis of the total populations of 18 E, 13 I, and 7 NB cells and
ignoring differences in local EOD modulation revealed the same pattern
of significant differences in RF dimensions as summarized in Figure
5A-C.
Figure 5D shows that the dimensions of RF centers mapped
with this technique are independent of the spontaneous firing frequency of the cells. That the negative correlation between RF center area and
spontaneous rate seen with the perimeter mapping technique of Figures 2
and 3 was not reproduced in these data may reflect the lower resolution
of this latter technique. Antagonistic surround areas, however, were
related to the spontaneous firing rate of the cells (Fig.
5E) and also to the burst indices of the cells (data not
shown). The correlation coefficient relating the log of surround areas
of all cells that were studied and their spontaneous rates was
0.51
(n = 38; p = 0.001), but this
correlation is primarily attributable to the relationship between the
spontaneous frequency and surround dimensions of the E cells (Fig.
5E, filled and open circles). Removal
of the I cells (Fig. 5E, filled squares) from this analysis had minimal effects on this correlation
(r =
0.5 for E cells alone), and analysis of the I
cells separately revealed no correlation between their spontaneous rate
and surround dimensions.
The uniformly large antagonistic surrounds of the I cells as well as
the variable surround areas of the E cells may be explained, at least
in part, by differences in the ELL interneuronal circuitry. The center
response of the I cells (reduced firing frequency) results from
receptor afferent activation of inhibitory interneurons located
immediately ventral to a given I cell via axons of these inhibitory
interneurons. The surround response (increased firing frequency)
results from gap junction inputs from dendrites of the same class of
interneurons. The interneurons responsible for the surround are,
however, located at greater distances from a given I cell. The large
size of the I cell surrounds may result from the fact that these
dendritic processes ramify over long distances (>100 µm) and thus
represent receptor afferents distant from the RF center. In addition,
the interneurons also make gap junction contacts among themselves,
allowing receptor afferents from large regions of the body to
contribute to the surround of a given cell (Maler, 1979
; Maler et al.,
1981
; Mathieson et al., 1987
).
The more heterogeneous sizes of antagonistic surrounds of E cells may
result from the variability in their position within the ELL lamina.
The deep basilar pyramidal cells, which have high firing frequencies
and small antagonistic surrounds, are found below the ELL laminae
within which most inhibitory interneuronal synapses occur (Maler et
al., 1981
; Bastian and Courtright, 1991
; Maler and Mugnaini, 1994
).
Hence both their high firing frequencies and small antagonistic
surrounds may be, at least in part, attributable to reduced inhibitory
interneuronal input.
Functional consequences of receptive field organization: responses
to stepwise AMs
The functional significance of the variation in relative sizes of
pyramidal cell RF centers and surrounds was assessed by comparing
responses of an individual cell to stimuli of the same effective
amplitudes, as judged by receptor afferent recordings, but presented
with different geometries. Global stimulus geometry results in
simultaneous activation of receptor afferents over most of the body
surface and therefore provides approximately equivalent input to the
center and surround simultaneously. Stimuli presented via the local
dipole, however, activate areas smaller than the typical RF center;
hence with local geometry the RF center can be stimulated without
activating the surround. These two stimulus geometries mimic spatial
aspects of electrosensory stimuli that normally are experienced by the
fish under natural conditions. Electrocommunication signals generated
by one animal and received by another result in spatially extensive
activation of receptor afferents similar to the effects of globally
presented stimuli. Electrolocation stimuli, especially those generated
by small electrolocation targets, cause spatially restricted receptor
afferent activation as results from the local stimulus geometry. Hence
differences in pyramidal cell responses to these two categories of
stimuli also may indicate differential processing of communication
versus electrolocation stimuli.
Examples of nonbursty high-frequency (27 sp/sec) and bursty
low-frequency (12 sp/sec) E cell responses to stepwise local increases in EOD amplitude (
12 dB) are summarized in the PSTHs of Figure 6, A and B,
respectively. Both cells responded with large initial increases in
firing frequency, which adapted rapidly. The mean increases in firing
frequency above background rates, measured over the 500 msec stimulus
duration, were similar (25 sp/sec). Presenting the stimulus with the
global geometry, which causes RF centers and antagonistic surrounds to
receive the same change in EOD amplitude, had opposite effects on the
responses of these cells. The mean response of the high-frequency cell
was approximately doubled from 25 to 66 sp/sec, whereas that of the
low-frequency cell was reduced from 25 to 9 sp/sec (Fig.
6C,D, respectively). These opposite signed changes in
response contingent on stimulus geometry were maintained over a wide
range of stimulus intensities, as shown in Figure 6E.
For the high-frequency cell, global stimuli always evoked stronger
responses than the equivalent local stimulus (Fig.
6E, open and filled circles,
respectively). The opposite pattern is characteristic of low-frequency
cells; global stimuli typically evoke weaker responses compared with
the local stimuli (Fig. 6E, open and
filled triangles, respectively).

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Figure 6.
Responses of pyramidal cells to stepwise electric
organ discharge (EOD) AMs. A, B, Responses of a high-
and low-frequency E cell to 12 dB stepwise increases in EOD AM
presented with local geometry. C, D, Responses of the
cells of A and B to global presentation
of stepwise AMs. E, Responses of the cells of
A and B to local and global EOD AMs of
various amplitudes.
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|
The effects of changing stimulus geometry on the responses of 69 pyramidal cells are summarized in Figure
7. The difference between the responses
of each cell to local and global geometries is plotted against the
spontaneous firing rate of the cells. Low-frequency cells typically
show positive response differences, indicating that the local stimulus
is the more effective, as shown in the example of Figure
6B,D,E.

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Figure 7.
Scatter plot relating differences in responses to
local versus global stepwise AMs to the spontaneous firing frequencies
of the cells. Filled circles and squares
indicate E and I cells, respectively; open circles and
squares indicate nonbursty E and I cells,
respectively.
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|
The negative correlation (r =
0.56; p < 0.001) indicates that cells with higher firing rates are relatively
more sensitive to global stimuli, and for cells with spontaneous rates
above ~20 sp/sec the sensitivity to the global geometry exceeds that to the local, resulting in negative response differences. Separate analysis of the bursty E and I cells (Fig. 7, filled circles
and squares, respectively) showed that both types behaved
similarly. Seven nonbursty E and three nonbursty I cells also were
recorded in this experiment (Fig. 7, open circles and
squares, respectively), and these usually showed negative
response differences being more sensitive to global rather than to
local stimuli. Response differences also were correlated significantly
with measures of the burstiness of the cells, as expected, given the
correlation between burstiness and spontaneous rate (data not shown).
The large reductions in the responses of the low-frequency, bursty
pyramidal cells seen when stimulus geometry was switched from local to
global indicates that the antagonistic surrounds of these cells provide
more powerful inhibition compared with that of the higher-frequency
cells. The observations that the highest-frequency cells give stronger
responses to global stimuli may reflect the fact that local stimuli do
not stimulate the entire extent of the RF center of the cell. Switching
to global geometry may provide additional input to center without
recruiting a strong antagonistic surround.
Responses to sinusoidal AMs
A second set of experiments was performed by using sinusoidal EOD
AMs identical to those used in RF-mapping studies. Examples of
responses of high- and lower-frequency pyramidal cells to local and
global presentation of these stimuli are shown in the phase histograms
of Figure 8. As with stepwise AMs,
responsiveness of the high- and low-frequency cells changed oppositely,
contingent on stimulus geometry; high-frequency cells increased
responsiveness with the switch from local to global (Fig.
8A,C), whereas low-frequency cells decreased
responsiveness (Fig. 8B,D). Furthermore, in many of
the low- to medium-frequency cells global sinusoidal AMs evoked no
response at all (Fig. 8D) despite the fact that the
stimulus was well above threshold for receptor afferents. Responses to sinusoidal AMs were quantified as the mean vector (r) of the
phase histogram. Figure 8E summarizes the responses
of these two cells to a series of stimulus amplitudes and shows that
the response differences resulting from changes in geometry are
maintained over a wide range of intensities. In addition, some
low-frequency cells that gave statistically significant responses to
weaker AMs (less than approximately
20 dB) became unresponsive with increased stimulus amplitude (Fig. 8E, open
triangles). This suggests that for some cells the thresholds for
RF centers may be lower than that of the surrounds.

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Figure 8.
Responses of high- and low-frequency pyramidal
cells to 4 Hz sinusoidal EOD AMs. A, B, Period
histograms of a high-frequency E cell and low-frequency I cell
responses to local stimulation (stimulus amplitude, 12 dB). C,
D, Responses of the cells of A and
B to 12 dB sinusoidal AMs presented globally.
E, Responses of the cells of A and
B to sinusoidal AMs of various amplitudes presented with
global and local geometries.
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|
The difference in mean vectors for the responses of a given cell to
local and global stimuli was used to gauge the effects of changing
stimulus geometry; Figure 9 summarizes
these mean vector differences for 44 pyramidal cells of various
spontaneous firing frequencies. As seen with stepwise EOD AMs, the
difference in responsiveness was correlated negatively with the
spontaneous rate of the cells (r =
0.77;
p < 0.001). The low-frequency cells typically gave
stronger responses to local versus global stimuli (positive mean vector
difference), whereas the highest-frequency cells behaved oppositely.
Separate analyses of E and I cells (Fig. 9, filled
circles and squares) showed that these behaved
similarly. The nonbursty E and I cells (Fig. 9, open circles
and squares, respectively) either showed small positive mean
vector differences, indicating more similar responses to local and
global geometries, or negative differences, indicating stronger
responses to the global geometry.

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Figure 9.
Scatter plot relating differences in responses
(mean vector differences) to local versus global sinusoidal AMs to
spontaneous firing frequencies of the cells. Filled
circles and squares indicate E and I cells,
respectively; open circles and squares
indicate nonbursty E and I cells.
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Responses to random AMs: information rates and
stimulus estimation
Previous studies of both electroreceptor afferents and ELL
pyramidal cells in the related fish Eigenmannia showed that,
whereas single receptor afferents performed well as encoders of
time-varying stimuli, pyramidal cells performed very poorly (Gabbiani
et al., 1996
; Metzner et al., 1998
; Gabbiani and Metzner, 1999
).
Stimulus presentation in these previous studies was similar to the
global geometry used here in that the RF center and surrounds were
activated simultaneously. Given the differences in RF structure seen
contingent on pyramidal cell type as well as differences in responses
seen with local versus global stimulation, it seemed likely that
encoding abilities might vary among pyramidal cells and also might
improve with the local stimulus geometry, which more closely resembles stimuli generated by prey.
Random AMs (RAM) were presented with either global or local geometry,
and stimulus reconstructions were produced as described in Materials
and Methods. The coding fractions (
) were used to assess the
accuracy of the reconstruction of stimuli presented with the two
geometries, and the mutual information rates in bits/spike were used to
determine whether changes in coding fraction could be accounted for by
changes in firing frequency. The RAM bandwidth was within the range of
frequencies expected for electrolocation stimuli caused by small prey
items, usually 0-10 Hz but occasionally 0-5 Hz (Nelson and MacIver,
1999
). Contrast levels (SD of modulated EOD amplitude/mean EOD
amplitude measured at the RF center) ranged from 3 to 26%.
Figure 10, A1 and
A2, contrasts stimulus reconstructions obtained from a
low-frequency (8 sp/sec) E cell with global and local stimulus
presentation, respectively. The time course of the EOD amplitude
modulation measured in the RF center is shown in gray along with the
stimulus estimate (in black). The times of spike occurrence are
indicated by the vertical black lines, and the optimal filter used for
the reconstruction is shown immediately below the spike trains. Figure
10A1 shows that, as found previously (Gabbiani et
al., 1996
; Metzner et al., 1998
; Gabbiani and Metzner, 1999
), some
pyramidal cells perform very poorly as stimulus encoders when the
geometry is global. Significant improvements are seen, however, when
the RF center is stimulated alone (Fig. 10A2). The improvement is partly attributable to changes in the optimal filter waveform but also may reflect changes in firing frequency, which increased from 7.3 to 8.3 sp/sec with the application of the local stimulus. However, mutual information rates for the cell of Figure 10,
A1 and A2, also increased from 0.06 bits/spike to
0.59 bits/spike with changes from global to local geometry, indicating
that increased spike rate is probably a minor contributor to the
improved coding fraction. Additionally, an obvious change in the firing
pattern of this cell occurred when the geometry was changed to local; spikes showed an increased tendency to occur in clusters or bursts, increasing the spike train coefficient of variation from 1.14 to 1.33. The increased coefficient of variation also suggests that local stimuli
are more effective in driving these cells.

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Figure 10.
Examples of reconstructions of random EOD
amplitude modulations presented with either global or local stimulus
geometry. Gray lines, Stimulus waveforms; variations in
p-p EOD amplitude were measured within the RF center of the cell.
Black lines, Reconstruction waveforms. Vertical
lines, Times of spike occurrence. Bottom insets,
Optimal filters; alignment to individual spike times is indicated by
the vertical dotted line. A1, A2, Global
and local stimulation, respectively, of a low-frequency E cell.
B1, B2, Global and local stimulation, respectively, of a
medium-frequency I cell. C1, C2, Global and local
stimulation, respectively, of a high-frequency NB E cell.
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|
Figure 10, B1 and B2, contrasts the responses of
a medium-frequency (16.5 sp/sec) I cell to the different stimulus
geometries. Again, coding fraction increased substantially with local
stimulation. This was accompanied by an increase in spike frequency,
from 15.5 to 19 sp/sec, and an increase in mutual information, from
0.19 to 0.48 bits/spike. As in the case of the low-frequency E cell, the improvement in coding fraction was correlated with substantial changes in the optimal filter as well as increased clustering of spikes.
In some cases the highest-frequency pyramidal cells, which also have
nonbursty patterns of spontaneous firing, showed opposite changes in
coding fraction contingent on stimulus geometry, as is shown by Figure
10, C1 and C2. The spontaneous firing rate of the
cell was 37.7 sp/sec. Both the coding fraction and the mutual information rate determined from the responses of this cell to global
stimuli, 0.51 and 0.50 bits/spike, respectively, were far higher than
those typically seen with the lower-frequency cells. Furthermore,
switching to local geometry reduced rather than increased the coding
fraction and mutual information rate (
= 0.36, I = 0.36 bits/spike) as well as reducing firing
frequency from 44 to 38 sp/sec.
Figure 11 summarizes the
stimulus-encoding performance of 11 E, 11 I, and 5 high-frequency
nonbursty cells with global (G) and local (L) stimulus geometries. On
average, coding fraction and mutual information rates of the low- to
medium-frequency E and I cells were significantly greater with
local versus global stimulation (Fig. 11A,B,
light and dark gray bars). Neither mean firing
rates nor stimulus contrast differed significantly among these data
(Fig. 11C,D, light and dark gray
bars). On average, changing stimulus geometry did not result in
significant differences in either mean coding fraction or information
rates for the nonbursty cells (Fig. 11A,B,
black bars) although, as mentioned above, some nonbursty
cells showed reduced rather than increased coding fractions with local
stimulation. Although the sample size for nonbursty cells is small
(n = 5), the available data suggest that these cells
provide the best estimates of stimulus time course independent of
stimulus geometry. However, the mutual information per spike is not as
high as typically is seen for the lower-frequency cells with local
stimulation; hence their high coding fractions must be attributable in
large part to their higher firing frequencies (Fig. 11C,
black bars).

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Figure 11.
Summary of comparisons of coding fraction and
mutual information determined from reconstructions of random AM stimuli
presented with global (G) or local
(L) geometry. A, Mean coding
fractions of both E and I cells are significantly greater for stimuli
presented with local geometry (p values 0.001; t tests), but not different for NB cells
(p = 0.76). B, Mean mutual
information rates of both E and I cells are significantly greater for
stimuli presented with local versus global geometry
(p values 0.004; t tests),
but not different for NB cells (p = 0.65).
Neither mean spike rates during stimulation (C)
nor mean stimulus contrasts (D) varied
significantly contingent on stimulus geometry for E, I, or NB cells.
Error bars = ±1 SEM.
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As seen with stepwise and sinusoidal AM stimulation, the changes in
coding fraction and mutual information seen with global versus local
stimulation are correlated with the spontaneous activity patterns of
the cells. Figure 12A
shows that the coding fraction improvement, measured as local minus
global coding fraction, is most striking for the lowest-frequency
cells, which are those that also have the largest inhibitory surrounds,
as shown in Figure 5E. Coding fractions seen with local
stimulation are relatively constant (Fig. 12C), averaging
0.29 ± 0.02 for all of the cells that were studied, and
uncorrelated with spontaneous rate. Hence the strong negative
correlation of Figure 12A reflects the fact that,
with global stimulation, coding fraction is very poor for the
lowest-frequency cells but improves for cells having higher spontaneous
rates and smaller antagonistic surrounds (Fig. 12E). The changes in mutual information contingent on stimulus geometry show
a similar correlation with the spontaneous firing rates of the cells
(Fig. 12B). As with coding fraction, the largest
improvements contingent on the switch to local stimulation occur for
the low-frequency cells, and, as seen with responses to stepwise AMs
and sinusoidal AMs, some of the highest-frequency cells show superior
performance for global rather than for local stimulation (Fig.
12B, points below dashed zero
line). The relationships between the spontaneous rate of a cell
and mutual information with local and global stimulation are shown in
Figure 12, D and F, respectively. As with coding
fraction, mutual information per/spike is very poor for low-frequency
cells under global stimulation but improves for cells with increased firing rates (Fig. 12F). However, the opposite trend
is seen for local stimulation in which there is a significant negative
correlation between information rates and the baseline firing frequency
of the cells (Fig. 12D). Given the relatively flat
relationship between coding fraction and spontaneous rate (Fig.
12C), reduced mutual information per spike is expected with
increasing firing frequency.

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Figure 12.
Variations of coding fraction and mutual
information rates with spontaneous firing rates of the cells. Increases
in coding fraction (A) and mutual information
rates (B) seen with local versus global
stimulation are correlated negatively with the spontaneous firing rates
of the cells (A, r = 0.67,
p < 0.001; B, r = 0.82, p < 0.001). C, Coding
fractions determined from local RF center stimulation are not
correlated significantly with spontaneous rate (r = 0.33; p = 0.10). D, Mutual
information rates in bits per spike are significantly lower for
higher-frequency pyramidal cells (r = 0.55;
p = 0.003). E, F, Both coding
fraction and mutual information rates increase significantly with
increasing pyramidal cell spontaneous rate (E,
r = 0.83, p < 0.001;
F, r = 0.73, p < 0.001). Filled circles and squares
indicate E and I cells, respectively; open circles and
squares indicate nonbursty E and I cells,
respectively.
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DISCUSSION |
The application of information theory and the methods of
statistical signal estimation and detection (Rieke et al., 1996
; Borst
and Theunissen, 1999
; Dayan and Abbott, 2001
) have contributed greatly
to our understanding of how the size of an RF of a sensory neuron
determines its coding properties. For the two-dimensional RFs found in
visual, somatosensory, and electrosensory systems the coding for
stimulus location is independent of RF size (Abbott and Dayan, 1999
;
Zhang and Sejnowski, 1999
; Lewis and Maler, 2001
). However, this
independence does not hold for all stimulus attributes; coding for the
spread of a stimulus is optimized with smaller RFs, whereas estimates
of stimulus intensity are optimized with a large RF size (Lewis and
Maler, 2001
). These theoretical analyses have assumed a two-dimensional
Gaussian RF structure that is a reasonable approximation of the RF
centers of pyramidal cells (Fig. 2). It is, however, well documented
that RFs of neurons at lower stages of sensory processing have an
antagonistic center-surround organization. Under various naturalistic
stimulus conditions different parts or all of the RF of a sensory cell
are expected to be influenced. The effects of varying the RF components
stimulated on the encoding performance of a neuron have yet to be
studied in detail.
Here we address the effects of the antagonistic surround of a sensory
neuron on its ability to encode time-varying stimulus intensity. As is
the case for other senses, the electrosensory system must operate over
a wide range of spatial scales. Isolated prey are expected to produce
stimuli for which the spatial scale is similar to or smaller than the
RF centers measured in this study (Nelson and MacIver, 1999
).
Electrocommunication signals produce spatially extensive stimuli that
will activate ELL pyramidal cell RF centers and surrounds, and, under
natural conditions, electric fish will have to encode or detect both
local and global sensory inputs. We use both traditional methods of
sensory physiology as well as quantitative measures of the quality of
stimulus estimation (coding fraction) and information transmission
(mutual information). These assays consistently demonstrate that, for
the low-frequency cells having relative large surrounds, simultaneous
activation of both RF components degrades the ability to encode the
time-varying intensity of a stimulus. However, under these global
stimulus conditions such cells are known to act as feature detectors
(Gabbiani et al., 1996
; Metzner et al., 1998
; Gabbiani and Metzner,
1999
). We show that these low-frequency cells perform much better as encoders of local stimuli and additionally that the highest-frequency cells perform well as encoders under both global and local stimulus conditions. Hence our results demonstrate that different categories of
ELL pyramidal cells are capable of stimulus encoding under both
stimulus regimes.
Our results confirm and extend those of previous studies of the related
fish Eigenmannia, which also determined that many pyramidal
cells were very poor encoders of stimuli applied with global geometry
(Gabbiani et al., 1996
; Metzner et al., 1998
; Gabbiani and Metzner,
1999
). However, these previous studies did not use input localized to
pyramidal cell RF centers; hence improvements in coding fraction
contingent on local stimulus geometry could not be detected. In
addition, the previous recordings were restricted to the more
superficial large pyramidal cells (Metzner et al., 1998
); hence the
high-frequency deep pyramidal cells could not be studied.
Both the RF mapping data as well as the differences in responsiveness
to stepwise and sinusoidal EOD AMs under local and global conditions
indicate that the size and effectiveness of antagonistic surrounds are
related to the spontaneous firing rate of a cell. Previous studies
established relationships between spontaneous activity patterns and
pyramidal cell anatomy; specifically, low-frequency cells were found to
be located more superficially within the ELL lamina and to have much
larger apical dendritic trees (Bastian and Courtright, 1991
). Hence it
is expected that the low-frequency cells with large surrounds also will
be found more superficially within the ELL and have larger apical
dendrites. These latter morphological features determine the amount of
descending electrosensory feedback that a cell receives as well as
their expression of intracellular calcium release channels (Berman and
Maler, 1999
). It is therefore possible that variations in
stimulus-encoding abilities also are related to these morphological and
biochemical differences. Because feedback inputs also are known to
influence the RFs of ELL pyramidal cells (Bastian, 1986a
,b
; Shumway and
Maler, 1989
), we propose that changes in feedback activity may function
to optimize the coding efficiency of the pyramidal cell population for
electrolocation versus communication signals.
It is well known that ELL pyramidal cells also show significant
morphological and physiological differences contingent on which of the
three ELL maps within which they reside (Shumway, 1989a
,b
).
Additionally, selective ablation experiments demonstrated that
different ELL maps are necessary and sufficient for the production of
different EOD modulation behaviors (Metzner and Juranek, 1997
), and
under global stimulus conditions pyramidal cells, particularly I cells,
from the different maps show differential performance in feature
detection tasks (Metzner et al., 1998
). Hence map-specific cell
properties are correlated with the ability to perform specific behaviors. Future studies should include comparisons of
stimulus-encoding performance of pyramidal cells having similar firing
characteristics from all three ELL maps by using both global and local
stimulus geometries. Map-specific stimulus-encoding characteristics may point to ELL subdivisions specialized to process electrolocation signals.
Comparisons with previous studies of RF organization
The receptive field center areas determined in this study are
approximately twofold larger than previous estimates of those of a
related fish, Apteronotus albifrons. This is probably
attributable to methodological rather than species differences. The
previous measurements were made with small stimuli moving parallel to
the long axis of the fish (Bastian, 1981b
). Many pyramidal cells, particularly those with low spontaneous rates, are rapidly adapting and
respond only as the moving target crosses the RF boundary. Therefore,
RF center areas determined from responses to moving targets not only
are underestimated but also show apparent shifts in their location
depending on the direction of target movement. A subset of the cells of
this study also was mapped with the dipole moving in a pattern similar
to that used in previous studies, and, as expected, the phasic nature
of the responses of the cells resulted in underestimates of the true
extent of the RF centers.
One previous study, of the related fish Eigenmannia
virescens, also used stationary patterns of EOD modulation and
found RF center areas between ~45 and 55 mm2 for pyramidal cells from comparable
regions of the ELL (Shumway, 1989a
). These dimensions
compare reasonably well with the mean RF center areas measured for
Apteronotus, considering that the fish used in
the latter study were approximately one-half as large as those used here.
Previous anatomical and physiological studies indicated the presence of
pyramidal cell antagonistic surrounds (Maler, 1979
; Maler et al., 1981
;
Bastian, 1981b
; Shumway, 1989a
,b
), but no studies before this have
estimated their areas, which can be surprisingly large. Three
components of the ELL circuitry likely contribute to these surrounds:
intrinsic inhibitory interneurons, monosynaptic and disynaptic
inhibitory inputs projecting to the ELL from higher centers, and
inhibitory commissural neurons. The anatomy and physiology of these are
well described (for review, see Berman and Maler, 1999
). Additional
studies that use localized pharmacological inactivation of specific
pathways are needed to determine the contributions of each to the
extensive antagonistic surrounds.
Behavioral considerations
P-type electroreceptor afferents fire at exceptionally high
spontaneous rates, 10-20 times higher than ELL pyramidal cells, and
information conveyed by these afferent spike trains subserves two
categories of behavior: electrocommunication and electrolocation. Electrocommunication signals result when an individual fish senses the
discharge of another (or others). The discharges of an individual and
conspecifics sum; each fish senses a composite signal that shows
a pattern of amplitude modulations or "beats" of a time course
depending on the harmonic relationships among the EODs. One or more
individuals then typically produce an EOD modulation of a type dictated
by the social context. For example, individuals having discharges of
similar frequencies may produce jamming avoidance responses, which are
slow frequency changes that increase the frequency difference between
the EODs. This shifts the AMs caused by the interacting EODs to higher
frequencies that do not jam or interfere with electrolocation (for
review, see Heiligenberg, 1991
). Alternatively, an animal may produce
"chirps": brief rises in EOD frequency seen in agonistic or
reproductive situations (Hagedorn, 1986
). The jamming avoidance
responses as well as all electrocommunication behaviors are similar in
that they produce spatially extensive stimuli (global stimulation). It
may be that for these behaviors detailed information about the time
course of a stimulus is less important than the time of occurrence of specific events; hence feature detection may suffice.
Electrolocation signals, particularly those generated by small aquatic
prey, differ in that the region of skin influenced is relatively small
(local stimulation). Prey organisms produce electric images ~1 cm in
diameter at the time of detection and, given the relative fish-prey
velocity at the time of detection, the bandwidth of this signal is
~4.5 Hz (Nelson and MacIver, 1999
). Images of this dimension are well
matched to the RF center sizes seen in this study, and this signal
bandwidth is within the range in which the encoding capabilities of the
pyramidal cell are maximum. After detection, which often occurs with
the prey near the dorsal surface of the animal's trunk, the fish
execute a series of swimming movements that bring the prey toward the
mouth for capture. Analysis of these movements indicates that the fish
tracks the prey's position rather than producing a ballistic strike
(MacIver et al., 2001
). Detailed information about the time-varying
local EOD amplitude resulting from changes in the fish-prey position
may be necessary for successful prey-tracking behavior. Although
pyramidal cells show improved stimulus-encoding performance for local
stimuli, it is not yet understood why coding fractions do not exceed a maximum of ~0.5. It may be that movement of the local stimulus also
is required to reveal the maximum stimulus-encoding ability of the
pyramidal cells. Ultimately, experiments focusing on higher order-processing regions will be required to determine how well individual neurons are able to recover information from populations of
antecedent cells. Neurons within the optic tectum are particularly attractive candidates for such studies because they not only
participate in electrosensory processing (Bastian, 1982
) but also are
involved in generating motor commands that lead to coordinated swimming movements (Yuthas, 1985
).
 |
FOOTNOTES |
Received Feb. 11, 2002; revised March 13, 2002; accepted March 15, 2002.
This research was supported by National Institutes of Health Grant
NS12337 (J.B.), by the Natural Sciences and Engineering Research
Council (M.J.C.), and by the Canadian Institutes of Health Research
(L.M.). We thank Brent Doiron and Dr. André Longtin for
helpful discussions.
Correspondence should be addressed to Joseph Bastian, Department of
Zoology, University of Oklahoma, 730 Van Vleet Oval, Norman, OK 73019. E-mail: jbastian{at}ou.edu.
 |
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