763
Who, what, where? Recognition and localization of acoustic
signals by insects
Gerald Pollack
Insects, like all hearing animals, must analyze acoustic signals
to determine both their content and their location.
Neurophysiological experiments, together with behavioral tests,
are beginning to reveal the mechanisms underlying these
signal-analysis tasks. Work summarized here focusses on two
issues: first, how insects analyze the temporal structure of a
single signal in the presence of other competing signals; and
second, how the signal's location is represented by the
binaural difference in neural activity.
Addresses
Department of Biology, McGill University, 1205 Avenue Dr Penfield,
Montreal, Quebec H3A 1B1, Canada;
e-mail: [email protected]
Figure 1
Gryllodinus odicus Uv.
Pteronemobius heydeni Fish.
Tartarogryllus bucharicus B.-B.
Tartarogryllus tartarus obscurior Uv.
Current Opinion in Neurobiology 2000, 10:763–767
0959-4388/00/$ — see front matter
© 2000 Elsevier Science Ltd. All rights reserved.
Introduction
The questions posed in the title refer to some of the core
issues in animal communication. The recipients of a sensory signal need to know who produced the signal, what the
signal’s content is, and where the signal originated. Sound,
being both long-range and information-dense, is an excellent medium for communication. The information content
of the signal is represented by structural features of the
sound such as its spectrum and pattern of amplitude modulation. The recipient’s analysis of the message’s content
(who? what?) and of its location (where?) must be done in
real time, often when several signals arrive simultaneously
from different sources. These are daunting computational
tasks, and understanding how they are performed by nervous systems is a challenge for neurobiology.
Acoustic signaling is widespread among vertebrates but,
among invertebrates, hearing and acoustic communication
are well developed only in insects, in which they serve
behavioral functions such as detection of predators, location of mates, and location of hosts (for reviews, see [1–3]).
Insects offer several advantages as model systems for neuroethological studies, including robust behavior, easily
accessible nervous systems, and uniquely identifiable neurons that permit one to frame general questions about the
neural analysis of signals at the levels both of single nerve
cells and of the circuits they form [4,5]. In this review, I
will discuss some recent behavioral and neurophysiological
experiments carried out on insects that are directed at the
problems of signal recognition and localization.
Temporal pattern as a carrier of information
Insect songs generally consist of rhythmic sequences of
more-or-less similar brief sounds (sound pulses), and, with
Tartarogryllus burdigalensis Latr.
Oecanthus pellucens Scop.
Gryllus campestris L.
Gryllus bimaculatus Degeer
Modicogryllus pallipalpis Farb.
Gryllus truncatus Farb.
0.2 s
Current Opinion in Neurobiology
The diversity of temporal patterns of cricket songs. The songs
illustrated are those of several European and Asian species. From [8].
rare exception [6], lack the ‘melodies’ that characterize
many vertebrate communication signals. The ears of many
insects are capable of spectral analysis, and there are several examples in which a signal’s spectrum may be
informative (see [2,7] for reviews), but in most instances the
main information-carrier in an insect’s song is its temporal
structure — in other words, the durations and shapes of
sound pulses, the spacing between them, and their organization into higher-order groupings (Figure 1; [8]).
Behavioral experiments, using synthetic song models, have
outlined the properties of the temporal-pattern filters that
analyze the signals; however, the neuronal implementation
of these filters is understood only in broad outline.
Temporal-pattern filtering is mainly a central phenomenon;
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Neurobiology of behaviour
Figure 2
Figure 2
Selective attention to a single signal among many. S1, S2 and S3
represent three singers at different distances from the receiver, R.
Because of the differences in distance, their songs arrive at R at
different intensities, as illustrated in the oscillograms. The trace labeled
S1–3 shows what a microphone at the position of the receiver would
detect (i.e. the summation of the three signals). The bottom trace
represents the membrane potential of an interneuron, such as those
described in [15,16,17•], that receives both fast-acting excitation and
slow inhibition. Inhibition has lowered the neuron’s baseline membrane
potential below its resting level (resting membrane potential, rmp;
represented by the arrow), with the result that only the largest soundevoked excitatory postsynaptic potentials, produced by the loudest
sound pulses, are sufficient to bring the membrane potential above
threshold (dotted line). As a result, S1 and S2 are filtered out of the
neuron’s spiking response.
S1
S2
The anatomical relationships and relative response latencies of the different types of filter neurons suggest that
band-pass selectivity is synthesized by combining inputs
from lower-level low- and high-pass filters [9]. Recent work
suggests that even receptor neurons may, in some instances,
play a role in temporal-pattern filtering. Many insect songs
consist of long sequences of rapidly repeated sound pulses.
Such stimuli induce sensory habituation — a decline in
responses to successive sound pulses within the sequence.
The higher the pulse rate, the more pronounced the habituation; consequently, the receptor neurons act as low-pass
temporal filters [10••]. This mechanism can only operate in
species with songs that are conducive to habituation — long
sequences of rapidly repeated pulses. Such songs are, however, common. Despite these basic low-pass filter
properties of the receptor neurons, the general conclusion,
that strong temporal-pattern selectivity paralleling the
selectivity of behavioral responses emerges only at higher
levels of neural circuitry, remains essentially correct.
S3
R
S1
S2
S3
Providing high-quality input to the temporalpattern filters
S1–3
Threshold
rmp
Current Opinion in Neurobiology
receptor neurons and low-order interneurons generally
copy the temporal pattern of the stimulus with high fidelity. At higher levels, interneurons are found that respond
most strongly only to particular stimulus temporal patterns.
In the cricket Gryllus bimaculatus, for example, the first indication of temporal filtering is in brain neurons that are two
to three synapses removed from receptors. These neurons
show low-, high- or band-pass filter properties. The bandpass-filter neurons respond best to the same range of
temporal patterns that best evoke behavioral responses.
Insects often sing in aggregations [11–13] in which a listener may be within earshot of several singers. In some
species, individual signalers may avoid mutual interference by singing either in alternation or in synchrony with
others [12], but in other species the listener is faced with
the problem of teasing a single signal out of apparent
cacophony (the ‘cocktail party’ problem). Crickets and
katydids solve this problem with a form of selective attention [14–16,17•]. Some of their low-order auditory
interneurons receive mixed excitatory and inhibitory
input. The excitation has a rapid time course, allowing the
neurons to respond crisply and accurately to the pattern of
amplitude modulation. The inhibition, which is due in part
to a Ca2+-activated current [18] (most probably, a K+ current) is more leisurely, building up and, after the stimulus
has terminated, decaying over a period of several seconds.
The inhibition serves to down-regulate the neuron’s sensitivity such that signals of lower intensity are filtered out.
As a result, the temporal pattern of the most intense signal,
corresponding to the loudest (or nearest) singer, remains
relatively uncontaminated (Figure 2); thus a ‘clean’ copy of
Recognition and localization of acoustic signals by insects Pollack
This same mechanism explains the remarkable ability of
these insects to discriminate reliably between simultaneous
signals originating on the two sides [14,15,17•,19], a situation that they presumably encounter frequently in the field.
Each of the stimuli, when presented by itself, is detectable
by both ears, and so one might suppose that the simultaneous presence of many stimuli would result in their
obscuring each other’s temporal pattern. However, sound
intensity at the two ears will differ, depending on the direction of the sound source [20]. This auditory directionality,
together with the slow inhibition described above, enables
neurons on each side of the nervous system to ‘listen’ selectively to the sound played on their side. The result is that
distinct copies of the two songs can coexist in the nervous
system, one on each side. Presumably, these can then be
analyzed by recognizer circuits, also situated separately on
each side of the nervous system, with the behavioral outcome (preference for one or the other of the songs)
determined by comparing the outputs of the recognizers;
the side receiving the ‘best’ signal pattern wins [14,21].
The code for sound direction
In most instances of communication, simply recognizing
the signal is not enough — it must also be localized (e.g. so
that the recipient of a mate-attraction signal can approach
the sender). Sound localization in insects depends on comparison of sound intensity at the two ears (see [20] for a
review of the physical mechanisms responsible for generating binaural intensity differences).
Binaural cues
How is binaural intensity difference represented by auditory neurons? The intensity level of the stimulus affects
two aspects of neural responses: the response strength, that
is the number and/or rate of action potentials, increases
with increasing intensity; and the response latency
decreases with increasing intensity. Binaural differences in
either or both of these response properties might serve as
the code for localization (note that here we are speaking of
a binaural difference in the timing of neural activity, which
may amount to several milliseconds [22], not the time-difference in arrival of sound at the ears which, even for a
relatively large insect such as a field cricket, is at most
about 30 µs). Several recent studies, focusing on sound
localization by grasshoppers and crickets, have addressed
the code for sound direction.
Male grasshoppers turn towards the side from which a
female’s song is broadcast with exceptional acuity and
reliability [23]; a binaural intensity difference of only
1.5 dB, corresponding to a deviation of the source from
the midline by only a few degrees, is sufficient to evoke
turns in the correct direction with >80% reliability. This
performance is even more remarkable given that it is
essentially unaffected when the natural song, which lasts
Figure 3
t=0s
1.0
Relative response
the signal can be passed on to the higher-level filter
circuits for further processing.
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t=10s
0.8
Ipsilateral
Contralateral
0.6
0.4
0
10
20
30
(s)
Current Opinion in Neurobiology
Intensity-dependent habituation may reverse the sign of the binaural
difference in response strength. The inset shows a recording from the
auditory nerve of a cricket to a high-repetition-rate, high-intensity
sequence of sound pulses (bottom trace). The top trace shows
responses immediately after onset of stimulation, and the second trace
after 10 s of stimulation have elapsed. Responses to successive sound
pulses are quantified in the graph by integrating the nerve recording
over an appropriate time window surrounding each sound pulse. The
points show responses of a single nerve to stimuli played from the
ipsilateral and contralateral sides; this approximates the responses of
the two ears to a single stimulus played from one side. Initially, the
ipsilateral response is greater than the contralateral response, as a
result of auditory directionality. However, because stimulus intensity is
greater ipsilaterally, the ipsilateral response experiences greater
habituation and, after approximately eight seconds of stimulation, it falls
below the contralateral response. Modified from [10••].
approximately 1 s, is truncated to one quarter of its normal
length [24], thus severely limiting the grasshopper’s ability to use time-averaging of neural activity to increase
acuity. How, then, is binaural intensity difference encoded? This difference is, of course, accompanied by a
binaural difference in latency, which may be as much as
5 ms [22]. Are the turns driven by differences in response
strength (spike counts of receptor neurons) or in latency?
Ronacher and Krahe [25•] approached this question by
measuring the response variability of single receptor neurons and using these data to model the probability with
which bilateral pairs of receptor neurons would correctly
‘judge’ the sign of small binaural intensity differences.
They found that latency was more variable than spike
count and, as a result, the model’s performance was much
poorer (error rate up to 4.6 times as high) if the determination of sound direction was based on latency
comparison rather than comparison of spike counts.
However, even the spike-count difference was unable to
account for the performance of the grasshopper if only a
single pair of receptors was considered; performance of
the model comparable to that of the animal was obtained
only by pooling the spike counts from 6–13 pairs of receptors. Presumably, if the decision were based on binaural
latency comparison, input from an even larger number of
receptors would have to be pooled; however, Ronacher
and Krahe did not examine this.
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Neurobiology of behaviour
Habituation affects localization cues
Givois and Pollack [10••] studied the encoding of localization cues by auditory receptors of crickets, focusing on the
ways in which binaural differences are affected by the
temporal pattern of the stimulus. The song of the species
they studied, Teleogryllus oceanicus, consists of long-lasting
(of the order of minutes) trains of rapidly occurring sound
pulses. As described above, auditory receptors habituate
when challenged with such stimuli. The response decrement increases with increasing stimulus intensity, and this
has important consequences for sound localization.
Because intensity is greater at the ear ipsilateral to the
sound source, habituation is more pronounced in receptor
neurons serving that ear. As a result, the binaural difference in response strength decreases as habituation builds
up. Under extreme conditions, the difference may decline
to zero, or even reverse in sign (Figure 3). Clearly, this is
potentially problematic for sound localization. The cellular
basis for habituation has not yet been studied in insect
auditory receptors but, on the basis of findings in other
arthropod sensory systems, it seems likely that the causes
are fundamental features of nerve cell biology, for example
Na+-channel inactivation and Na+/K+-ATPase activity
[26,27]. Habituation may thus be an unavoidable consequence of the intense firing activity that typifies these
sensory neurons (firing rates of 300–500 Hz are not uncommon; K Imaizumi, G Pollack, unpublished data).
Binaural latency comparison may provide a way around the
localization problem imposed by habituation. Like response
strength, response latency also changes for rapidly repeated
sound pulses, becoming longer for successive sound pulses.
However, in contrast to the change in response strength, the
change in latency is independent of intensity [10••]. Binaural
latency difference thus remains constant, and is immune to
the effects of habituation. Interestingly, latency comparison
is the cue for sound direction in a recent robotic model of
cricket phonotaxis [28]. It remains to be seen, however,
whether crickets actually use latency difference as the main
cue for direction. The findings of Ronacher and Krahe [25•]
on grasshoppers, summarized above, suggest that binaural
latency difference may be encumbered by its own shortcoming, namely high variability. It is thus important to learn
which of the two possible cues, latency difference or
response-strength difference, dominates in directional decisions. Behavioral experiments currently underway in our
laboratory are directed at this question. We are exploiting the
fact that intensity differentially affects the habituation of
response strength and of response latency to uncouple the
binaural differences in these two potential cues; that is, we
establish conditions under which the response of one ear is
both stronger and later than that of the other ear. By observing the direction of behavioral responses under these
conditions, we hope to learn whether crickets attend mainly
to one or the other of these potential cues for direction.
Our preliminary results suggest that, despite the confounding effects of habituation, sound localization
depends mainly on response-strength difference. This has
interesting implications for our understanding of the forces
driving the evolution of song structure and song preferences. In crickets, songs are produced only by males, and
females analyze them not only to determine the speciesidentity of the singer, but also to evaluate his genetic
quality. Several studies suggest that females prefer songs
that are more energy-demanding to produce (i.e. which
have longer-duration sound pulses [29], longer-length
sequences of pulses [30], or higher pulse rates [31]), all of
which presumably reflect on the singer’s health, his ability
to acquire resources, and his overall genetic quality. These
female preferences, in turn, exert selective pressure favoring the evolution of longer pulses, higher pulse rates, and
longer-lasting pulse sequences. However, the song features that best demonstrate male quality are the same
features that most effectively produce habituation. This is
thus a potentially paradoxical situation; if songs were to
evolve so as to maximally demonstrate male quality, the
males singing them would be difficult to find. It is of little
use for a female to know that a prize male is out there
somewhere, but to be unable to locate him. It seems likely, instead, that the need for females to locate the singer
exerts a counteracting selective pressure, which limits the
duration rate and sequence-length of sound pulses.
Conclusions and prospects
A strong advantage of insects as model systems for the
study of signal analysis is that clear behavioral functions
can be ascribed to relatively few identified neurons. In
crickets, for example, three low-level interneurons on each
side of the nervous system have been shown, through
direct manipulation of their activity, to be important players in acoustic orientation responses [4,5]. This
experimentally favorable situation can now be exploited in
two ways. First, most of what we know of these neurons
comes from laboratory experiments performed under pristine and, therefore, entirely unrealistic acoustical
conditions. We need to know what challenges the neurons
face under natural conditions in which sound fields are corrupted by vegetation [21,32] and extraneous noises may
interfere with the signal of interest. This is crucial not only
to ensure that we are asking sensible questions in our laboratory experiments, but also to find out whether, and to
what extent, the basic properties of the neurons are affected by factors such as background noise (which is known to
affect responses in other systems [33]). With rare, but
important, exceptions [11,16], the behavior of auditory
neurons under field conditions has been essentially
neglected. Second, our understanding of the neural processing of acoustical signals rests mainly on traditional
analytical techniques, such as counting spikes and measuring latencies. Evidence in other systems, however, shows
that information may be encoded more subtly in the
detailed timing of action potentials [34]. This conclusion
stems from the application of analytical procedures derived
from systems analysis and information theory. Several laboratories are now beginning to apply these techniques to
Recognition and localization of acoustic signals by insects Pollack
insect auditory systems, and the next few years will
undoubtedly see new insights into the sorts of information
that individual neurons, and the animals that they serve,
extract from the sounds that surround them.
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