J Comp Physiol A (2010) 196:315–320
DOI 10.1007/s00359-010-0514-8
SHORT COMMUNICATION
The structure and size of sensory bursts encode stimulus
information but only size affects behavior
Gary Marsat • Gerald S. Pollack
Received: 9 December 2009 / Revised: 11 February 2010 / Accepted: 19 February 2010 / Published online: 7 March 2010
Ó Springer-Verlag 2010
Abstract Cricket ultrasound avoidance is a classic model
system for neuroethology. Avoidance steering is triggered
by high-firing-rate bursts of spikes in the auditory command neuron AN2. Although bursting is common among
sensory neurons, and although the detailed structure of
bursts may encode information about the stimulus, it is as
yet unclear whether this information is decoded. We
address this question in two ways: from an information
coding point of view, by showing the relationship between
stimulus and burst structure; and also from a functional
point of view by showing the relationship between burst
structure and behavior. We conclude that the burst structure
carries detailed temporal information about the stimulus
but that this has little impact on the behavioral response,
which is affected mainly by burst size.
Keywords Sensory coding Ultrasound avoidance
Bursting Temporal coding Cricket
Introduction
Echolocating bats hunt flying insects using ultrasonic
probes, and crickets, like many nocturnally flying insects,
respond to ultrasound stimuli with avoidance responses.
G. Marsat
Department of Cellular and Molecular Medicine,
University of Ottawa, Ottawa, ON K1H 8M5, Canada
G. S. Pollack (&)
Department of Biology, McGill University,
Montreal, QC H3A 1B1, Canada
e-mail: gerald.pollack@mcgill.ca
AN2 is a first-order, ultrasound-tuned, bilaterally paired
auditory interneuron that serves as a command neuron for
avoidance steering during flight (Nolen and Hoy 1984).
Responses of AN2 to long-lasting, dynamic stimuli consist,
after a rapid adaptation phase, of both isolated spikes,
separated by relatively long and variable interspike intervals, and of bursts, consisting of groups of spikes separated
by short intervals (\6.5 ms). Recent work showed that
bursts, but not isolated spikes, in AN2 signal the occurrence of salient peaks in ultrasound amplitude and result in
behavioral responses (Marsat and Pollack 2006).
Although bursts in sensory neurons are known to function as feature detectors (Gabbiani et al. 1996), it is unclear
whether they should be considered as unitary, all-or-none
events, or whether the fine structure of bursts carries
additional information about the features they encode
(Krahe and Gabbiani 2004). Recent studies suggest that
some stimulus information can be encoded in the burst
structure, either in the size of the burst or the pattern of
interspike intervals (Kepecs et al. 2002; Kepecs and
Lisman 2003; Oswald et al. 2007; Arganda et al. 2007;
Eyherabide et al. 2008, 2009). These analyses show that
this information is present in the spike train and thus is
potentially available to a decoder, but it is unknown whether the information is actually used by post-synaptic networks. We used combinations of neural and behavioral
recordings to clarify this issue. We show that information
about the size and shape of the amplitude envelope of an
auditory stimulus is encoded both in the burst size and
interspike-interval structure of the response of AN2. We
consider the network between AN2 and the motor output as
a whole and show that this decoder uses the information
encoded in the burst size but that the behavioral output is
not influenced by the interspike-interval structure of the
burst.
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Materials and methods
Experimental procedures are described in detail in Marsat
and Pollack (2006); the results presented here are from the
same dataset. Briefly, adult Teleogryllus oceanicus were
tethered dorsally and placed ventral-side up in a wind
stream to elicit flight behavior. Abdominal steering
movements associated with ultrasound avoidance were
monitored by casting a shadow of the abdomen onto a
photocell array, the voltage output of which varied roughly
linearly with lateral displacement of the abdomen. Signals
were digitized for off-line analysis (16 bits; 10 kHz sampling rate, PCI-6251 AD/DA board, National Instruments,
Austin, TX). Behavior recordings of abdomen movements
were high-pass filtered with a cutoff frequency of 0.5 Hz
and averaged across repetitions of the same stimulus to
calculate burst-triggered averages (see below). Twenty to
forty minutes after the behavioral assay, the cricket was
prepared for in vivo electrophysiology (see Marsat and
Pollack 2005). AN2 was recorded extracellularly from the
cervical connectives with stainless-steel hook electrodes.
Recordings were amplified with a Grass P15 amplifier
(Astro-Med, West Warwick, RI) and digitized as described
above. Sound stimuli (duration 15 s) had carrier frequency
of 30 kHz and Gaussian amplitude envelopes (low-passfiltered at 200 Hz; standard deviation 6 dB). Stimuli were
generated digitally at sampling rate of 120 kHz. Mean
stimulus level was 85 dB SPL, corresponding to approximately 20–25 dB above threshold.
Analysis included the data from crickets in which AN2
frequently fired bursts of more than three spikes in
response to these stimuli (n = 14 out of 22 neurons). Our
analysis relies on comparing the timing of the behavioral
and neural responses to the same stimulus waveform (for
details see Marsat and Pollack 2006). The bursting
response contains very little noise thus it is highly reproducible from trial to trial (Fig. 1; also see Marsat and
Pollack 2006) but the behavioral response is more noisy.
To remove the noise from the behavioral response, we
average responses to 20–30 repetitions of the stimulus. We
deduce the relative timing between AN2 bursts and the
averaged behavioral response by referring both of these to
the shared stimulus timing.
We excluded from our analyses the first second of
responses (both behavioral and physiological), during
which AN2’s firing rate and behavioral responses adapt in
order to satisfy the ergodicity requirement of the analysis
(Marmarelis and Marmarelis 1978). While insects respond
quickly to the onset of ultrasound, the insect can remain
within hearing distance of a hunting bat for several seconds
(Simmons 2005); thus the adapted response is behaviorally
relevant. Spike trains, expressed as series of ones (for time
points at which spikes occur) and zeros, were down-
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Fig. 1 Exemplars of neural and behavioral responses to RAM
stimuli. Stimuli consist of an ultrasonic carrier (30 kHz, not shown)
and a random amplitude modulation (RAM; standard deviation: 6 dB)
envelope. Neural responses of AN2 to the stimulus excerpt shown on
top are displayed as a raster plot where black dots represent bursting
responses and grey dots isolated spikes. The behavioral response
(bottom) is quantified as the amplitude of the lateral displacement of
the abdomen (arbitrary units; see ‘‘Materials and methods’’). We
show two segments of recording in the same cricket that exemplify
the relationship between stimulus, neural response and behavior. We
underlined a prominent peak in the stimulus that gives rise to large
neural and behavioral responses
sampled to 2 kHz. The points where isolated spikes
occurred were set to 0 so as to keep only spikes within
bursts (ISI B 6.5 ms, as determined from ISI histograms;
see Marsat and Pollack 2006). Burst structure was classified according to the criteria described in the results and
figures. The timings of the first spike of the bursts in a
given category were used to calculate the corresponding
burst-triggered average (BTA) of the stimulus amplitude or
of the behavioral response. BTAs were characterized
by three measures: maximum (amplitude of the peak),
half-width (the width at half maximum) and total power,
which is essentially the area under the peak of the BTA
(see inset in Fig. 2a). Total power was calculated as:
Pe
t¼b ðBTAðtÞ MinÞ; where b is the time of the local
minimum preceding the peak of the BTA, e the time of the
minimum after the peak and Min is the minimum value of
the BTA between b and e, inclusive (see Fig. 2a, inset). We
also measured the onset slope of the BTA by fitting a linear
function through the steepest portion of the rising phase.
Matrices of data were created where each entry contains
the value of the measure being analyzed (e.g., the maximum) for the BTA of a single experiment and the corresponding independent variable (e.g., number of spikes in
the burst). These datasets contained only 186 entries out of
the 266 possible entries (14 experiments 9 19 categories)
because very large bursts did not occur in some experiments. For each of these datasets the linear best fit between
the variables was calculated along with the R2 value and
the probability that the slope is not different from zero. All
analyses were performed with Matlab 2008 (Mathworks,
Natick, MA) including the curve fitting toolbox.
J Comp Physiol A (2010) 196:315–320
317
a
d
b
e
c
f
Fig. 2 Average stimulus amplitude envelope and behavioral response
associated with bursts of different structure. Burst were divided in
groups based either on their mean interspike interval (a, d), their
duration (b, e) or the number of spikes they contain (c, f). The figures
display the shapes of the average amplitude modulations that precede
the bursts in one of these groups (a–c) or the average behavioral
response that follows them (d–f). Zero on the x axes represents the
timing of the first spike in the burst and on the y axes, the mean sound
amplitude (a–c) or behavioral response (d–f). The inset in a illustrates
the calculation of the stimulus power measure used later (Figs. 3, 4),
which is essentially calculating the area under the curve (shaded area)
Results
Visual inspection of the response of AN2 to amplitude
modulated ultrasound stimuli suggests that peaks in sound
amplitude with different modulation patterns can trigger
bursts of different size and structure (Fig. 1). Small bursts
of two or three spikes are most common but longer bursts
containing many spikes also occur. The features of the
stimulus that trigger these large bursts seem to be large or
broad peaks in amplitude (e.g., the underlined portion of
the stimulus in Fig. 1). Most importantly we observe that
peaks in amplitude that lead to large bursts also lead to
large steering movements in the behaving animal (Fig. 1).
In order to explore these qualitative observations, we
classified each recorded burst based either on its duration
(time between first and last spike), the number of spikes, or
the mean interval between spikes. These groups of bursts
were then used to calculate averages of the stimulus that
preceded them and of the behavioral response that followed. These burst-triggered averages characterize the
relationship between the amplitude and temporal features
of the stimulus or behavioral response (i.e., their shapes)
and bursting.
All three burst characteristics vary systematically with
the preceding stimulus peak. Interspike interval is shorter
(i.e., instantaneous firing rate is higher) the larger and
narrower the amplitude peak that triggers the burst
(Fig. 2a; Table 1). Similarly, longer bursts or bursts with
more spikes, are correlated with larger and broader peaks
in the stimulus (Fig 2b, c; Table 1). Note that different
bursts can be triggered by stimuli with only subtle, but
statistically significant (Table 1), differences in shape. This
is, for example, the case of bursts with short to medium
durations (Fig. 2b) which are correlated to slight changes
in the descending phase of the BTA 4–6 ms before burst
onset. We can also observe a clear relationship between
two aspects of the burst and the subsequent behavioral
response (Fig. 2d–f): behavioral responses increase with
increasing burst duration and increasing spike count
(Table 1).
To explore more quantitatively the relationship between
the structure of bursts and of the stimulus, we plot three
characteristics of the burst-triggered averages as a function
of both number of spikes and burst duration (Fig. 3). The
ratio of these reflects the average firing rate within the
burst. We sorted the responses into 19 groups, as indicated
by the 19 rectangles in each panel of Fig. 3. For each
group, we plot the half-width, the maximum, and the total
power of the preceding amplitude peak (Fig. 3a–c). We
also display the result of a similar analysis, taking the
maximum of the spike triggered average of the behavior as
a quantification of the strength of the steering response
(Fig. 3d). We find only weak correlations between the
stimulus maximum or half-width and the burst duration or
number of spikes (Table 1). If we consider the overall
power contained in the peak of the burst triggered average,
a clear correlation is observed with both burst duration and
number of spikes. Furthermore, the strength of the behavioral response is also correlated with these two aspects of
the bursts.
This analysis does not allow separating which aspect of
burst structure is best correlated with different aspect of the
stimulus. The main issue comes from the fact that the
duration of the burst is correlated with the number of spikes
it contains. Due to this correlation the shaded squares
representing each group of bursts are located on a diagonal.
However, the breadth of this diagonal shows that for a
given number of spikes, or a given duration, the burst can
vary due to a difference in average ISI. Therefore, we
re-evaluated the correlations as a function of two new
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Table 1 Regression analysis of correlations between burst structure, stimulus structure and behavior
Number of spikes
Burst duration (ms)
2
Burst size
Burst density
p
R2
0.02
<1025
0.27
[0.1
0.01
<1025
0.29
0.39
<1025
0.39
[0.1
0.007
0.25
<1025
0.31
[0.1
0.005
p
R
0.1
[0.1
[0.1
0.008
Stimulus power
<1025
Behavior magnitude
<1025
2
p
R
0.0003
\0.04
\0.01
0.05
0.3
<1025
0.3
<1025
p
R
Stimulus maximum
\10-5
Stimulus half-width
2
The 4 columns represent the categorizing parameter of the bursts (see ‘‘Results’’ for details) and the 4 rows the burst-triggered average (BTA)
parameters quantified. The goodness of fit of the linear regression between the two variable (quantified by the R2 value) and the probability that
the slope of the linear fit is not different from zero (i.e., no correlation) are given. Bold characters highlight cells with stronger correlations
(R2 [ 0.2)
a
c
b
d
Fig. 3 Correlations between burst structure, stimulus structure and
behavior. Each panel quantifies one aspect of the burst-triggered
average (BTA): its half-width (a) maximum (b) or total power (c) for
the stimulus BTA and overall magnitude (quantified as the peak’s
maximum) for the behavioral-response BTA (d). 19 burst categories
were defined based on the number of spikes they contain (x axes) and
their duration (y axes). The definitions of the 19 different categories
are shown at the edge of the color-coded squares. The darkness of the
square is proportional to the value of the measure examined in each
panel. Note that the top-most squares include all bursts of more than
17 ms and the right-most squares all bursts of 8 spikes and more. The
arrows in the top-left corners of the panels illustrate two other
dimensions along which burst structure varies: the burst density (see
left panels) is the burst duration divided by the number of spikes and
it increases from the top-left quadrant to the bottom-right whereas the
burst size (burst duration 9 number of spikes) increases from the
bottom-left to the top-right quadrant
independent variables: the burst size, defined as the product
of the number of spikes in the burst and the duration of the
burst, and the burst density defined as the inverse of the
average interval between spikes of a burst. The arrows in
the top-left corners of the plots (Fig. 3) roughly show the
directions along which these variables change. An interesting situation occurs when considering burst density as a
variable: the half-width of the burst-triggered average is
negatively correlated with burst density, but the maximum
is positively correlated (Figs. 3a, b, 4a; note that in Fig. 4
we plot the data as a function of the mean burst ISI because
of the clear meaning of this measure, but that mean ISI is
inversely proportional to burst density). No strong correlations were found between stimulus half-width or power
and burst size (Fig. 4a). A broad but not very intense peak
in stimulus amplitude would give rise to a low density
burst, whereas a narrow but intense peak will give rise to a
dense burst. This means that for a burst of a given size the
burst density can allow to distinguish between broad and
narrow stimulus peaks of similar overall power. However,
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J Comp Physiol A (2010) 196:315–320
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Fig. 4 Correlations between
burst size or density and the
stimulus or the behavior.
a Correlations between three
characteristics of the stimulus
BTA and the density (blue) or
size (red) of the associated
bursts. Note that burst density is
expressed as mean ISI, i.e.,
(burst density)-1. Each dot
represents the data for a single
category of burst (i.e., density
and size) in each experiment;
the lines show the best linear fit.
Correlation statistics are listed
in Table 1. b Behavioral
response correlates with burst
size but not burst density. Each
dot represents the maximum of
the BTA of the behavioral
response calculated for a single
category of burst (density or
size) in each experiment; see
Table 1 for statistics. Points
shown in color are results for
four representative cells
the overall power contained in the peak is not correlated
with burst density but only with burst size (Fig 4a). Most
importantly, the strength of the behavioral response is also
correlated with burst size but not density (Fig. 4b;
Table 1). We showed previously (Marsat and Pollack
2006) that the strength of the behavioral response was
influenced by the average burst rate of a neuron. The
correlations we show here are not determined by average
burst rate because for a given neuron, thus a given burst
rate, the correlations described are clearly present (see
colored points in Fig 4b). We performed similar analyses
of the behavioral response while using different aspects of
the BTA of steering movements, onset slope or half-width,
to quantify the magnitude of the behavioral response but
also failed to find a correlation between these measures and
burst density (data not shown; R2 \ 0.008 in all cases).
Discussion
Our analysis reveals that the structure of the burst can carry
information about the shape of the stimulus that it encodes.
In particular we observed a correlation between the size of
the burst and the intensity of the stimulus: broader and/or
higher peaks in ultrasound amplitude elicit longer bursts
containing more spikes. This finding corroborates results in
other systems. Similar to AN2, burst size in grasshopper
auditory receptors signals the overall intensity of the
amplitude peak (i.e., height and/or breadth; Eyherabide
et al. 2008, 2009). In the visual system of cats, burst size is
correlated with stimulus orientation (cortex; DeBusk et al.
1997; Martinez-Conde et al. 2002) or the slope of stimulus
upstrokes (Kepecs et al. 2002; Kepecs and Lisman 2003).
The number of spikes in bursts of tactile neurons of
the leech vary according to the velocity of the stimulus
(Arganda et al. 2007).
The above-mentioned studies stress the importance of
the size of the burst (i.e., number of spikes and/or burst
duration) as the information-carrying variable within a
burst. An alternate, but not exclusive, approach focuses on
the relevance of the interval between spikes of a burst for
information coding. Previous studies on neural coding
noted that the intervals between successive spikes (i.e.,
relative timing), rather than their absolute timing, carry
more information about the stimulus (de Ruyter Van
Steveninck and Bialek 1988). Furthermore, short interspike
intervals such as occur in bursts, carry information more
efficiently than long ones (Reich et al. 2000). Interval
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codes within bursts are therefore a potentially important
aspect of information coding in these neurons. Such a code
has been found in the sensory neurons of the electric fish
which produce bursts most often limited to two spikes.
Oswald et al. (2007) showed that the interspike interval of
these doublets reliably encodes the amplitude of the stimulus peak. Our results indicate that the interspike intervals
in AN2 bursts are correlated with stimulus features. For a
burst of a given number of spikes, the average interval in
the burst could provide the information to discriminate
between a tall, narrow stimulus peak and a shallow, broad
peak.
The ultimate goal of our study was not only to determine
whether the two neural codes detailed above can be
observed in AN2, but also whether the information they
encode is actually used by the post-synaptic network.
Indeed, a neural code is only relevant to sensory processing
if it is decoded post-synaptically. This question has been
addressed mostly with modeling studies showing that burst
size/duration (Kepecs and Lisman 2004) or burst interspike
intervals (Izhikevich et al. 2003) can be decoded by synapses exhibiting mixtures of depression and facilitation.
The question, however, has not been addressed experimentally. The results we present here provide insights into
this problem by considering the network between AN2 and
the motor output as a whole. By correlating the behavioral
response and bursts of different sizes (i.e., number of
spikes) and densities (i.e., average ISI) we observe that
behavior varies only as a function of burst size, not burst
density. In other words, features of the stimulus that affect
burst size, also affect behavior whereas features affecting
burst density but not burst size do not appear to affect
behavior. Our results suggest that in this system, a code
based on burst size contains more behaviorally relevant
information whereas an interval code, although potentially
present, has less obvious relevance.
We do not know why the information present in the
burst density seems unused. One possibility is that any
influence of burst density on behavior is too subtle for our
measures to detect. Another possibility is that the apparent
encoding of burst density is merely a byproduct of burst
generation in AN2, and that a mechanism is not present
post-synaptically to decode it. However, our results have
behavioral implications. We hypothesize that the overall
intensity of a bat echolocation pulse as perceived by the
cricket can carry information about its distance. The
information carried by the pulse shape (for example
breadth) might be harder to interpret as it varies with time
across bat species and might be harder to relate to the
imminence of an attack. This hypothesis implies that,
because pulse intensity is an indicator of the closeness of
the predator, it is encoded in the burst structure and affects
behavior: stronger pulses lead to more spikes and stronger
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J Comp Physiol A (2010) 196:315–320
steering movements. On the other hand, if pulse shape is
not as clearly related to the magnitude of the threat, then
selection might not have favored mechanisms to decode
this irrelevant information.
Acknowledgments This work was supported by a Canadian Institutes for Health Research operating Grant (G.S.P.) and fellowship
(G.M.) and a Natural Sciences and Engineering Research Council of
Canada Discovery Grant (G.S.P.).
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