A small, computationally flexible network produces the phenotypic diversity of song recognition in crickets.

How neural networks evolved to generate the diversity of species-specific communication signals is unknown. For receivers of the signals, one hypothesis is that novel recognition phenotypes arise from parameter variation in computationally flexible feature detection networks. We test this hypothesis in crickets, where males generate and females recognize the mating songs with a species-specific pulse pattern, by investigating whether the song recognition network in the cricket brain has the computational flexibility to recognize different temporal features. Using electrophysiological recordings from the network that recognizes crucial properties of the pulse pattern on the short timescale in the cricket Gryllus bimaculatus, we built a computational model that reproduces the neuronal and behavioral tuning of that species. An analysis of the model's parameter space reveals that the network can provide all recognition phenotypes for pulse duration and pause known in crickets and even other insects. Phenotypic diversity in the model is consistent with known preference types in crickets and other insects, and arises from computations that likely evolved to increase energy efficiency and robustness of pattern recognition. The model's parameter to phenotype mapping is degenerate - different network parameters can create similar changes in the phenotype - which likely supports evolutionary plasticity. Our study suggests that computationally flexible networks underlie the diverse pattern recognition phenotypes, and we reveal network properties that constrain and support behavioral diversity.

Physical linkage and mate preference generate linkage disequilibrium for behavioral isolation in two parapatric crickets.

Behavioral isolation is a potent barrier to gene flow and a source of striking diversity in the animal kingdom. However, it remains unclear if the linkage disequilibrium (LD) between sex-specific traits required for behavioral isolation results mostly from physical linkage between signal and preference loci or from directional mate preferences. Here, we test this in the field crickets Gryllus rubens and G. texensis. These closely related species diverged with gene flow and have strongly differentiated songs and preference functions for the mate calling song rhythm. We map quantitative trait loci for signal and preference traits (pQTL) as well as for gene expression associated with these traits (eQTL). We find strong, positive genetic covariance between song traits and between song and preference. Our results show that this is in part explained by incomplete physical linkage: although both linked pQTL and eQTL couple male and female traits, major effect loci for different traits were never on the same chromosome. We suggest that the finely tuned, highly divergent preference functions are likely an additional source of LD between male and female traits in this system. Furthermore, pleiotropy of gene expression presents an underappreciated mechanism to link sexually dimorphic phenotypes.

Demography and selection shape transcriptomic divergence in field crickets.

Gene flow, demography, and selection can result in similar patterns of genomic variation and disentangling their effects is key to understanding speciation. Here, we assess transcriptomic variation to unravel the evolutionary history of Gryllus rubens and Gryllus texensis, cryptic field cricket species with highly divergent mating behavior. We infer their demographic history and screen their transcriptomes for footprints of selection in the context of the inferred demography. We find strong support for a long history of bidirectional gene flow, which ceased during the late Pleistocene, and a bottleneck in G. rubens consistent with a peripatric origin of this species. Importantly, the demographic history has likely strongly shaped patterns of genetic differentiation (empirical FST distribution). Concordantly, FST -based selection detection uncovers a large number of outliers, likely comprising many false positives, echoing recent theoretical insights. Alternative genetic signatures of positive selection, informed by the demographic history of the sibling species, highlighted a smaller set of loci; many of these are candidates for controlling variation in mating behavior. Our results underscore the importance of demography in shaping overall patterns of genetic divergence and highlight that examining both demography and selection facilitates a more complete understanding of genetic divergence during speciation.

Hearing in Insects.

Insect hearing has independently evolved multiple times in the context of intraspecific communication and predator detection by transforming proprioceptive organs into ears. Research over the past decade, ranging from the biophysics of sound reception to molecular aspects of auditory transduction to the neuronal mechanisms of auditory signal processing, has greatly advanced our understanding of how insects hear. Apart from evolutionary innovations that seem unique to insect hearing, parallels between insect and vertebrate auditory systems have been uncovered, and the auditory sensory cells of insects and vertebrates turned out to be evolutionarily related. This review summarizes our current understanding of insect hearing. It also discusses recent advances in insect auditory research, which have put forward insect auditory systems for studying biological aspects that extend beyond hearing, such as cilium function, neuronal signal computation, and sensory system evolution.

Firing-rate resonances in the peripheral auditory system of the cricket, Gryllus bimaculatus.

In many communication systems, information is encoded in the temporal pattern of signals. For rhythmic signals that carry information in specific frequency bands, a neuronal system may profit from tuning its inherent filtering properties towards a peak sensitivity in the respective frequency range. The cricket Gryllus bimaculatus evaluates acoustic communication signals of both conspecifics and predators. The song signals of conspecifics exhibit a characteristic pulse pattern that contains only a narrow range of modulation frequencies. We examined individual neurons (AN1, AN2, ON1) in the peripheral auditory system of the cricket for tuning towards specific modulation frequencies by assessing their firing-rate resonance. Acoustic stimuli with a swept-frequency envelope allowed an efficient characterization of the cells' modulation transfer functions. Some of the examined cells exhibited tuned band-pass properties. Using simple computational models, we demonstrate how different, cell-intrinsic or network-based mechanisms such as subthreshold resonances, spike-triggered adaptation, as well as an interplay of excitation and inhibition can account for the experimentally observed firing-rate resonances. Therefore, basic neuronal mechanisms that share negative feedback as a common theme may contribute to selectivity in the peripheral auditory pathway of crickets that is designed towards mate recognition and predator avoidance.

Decision making and preferences for acoustic signals in choice situations by female crickets.

Multiple attributes usually have to be assessed when choosing a mate. Efficient choice of the best mate is complicated if the available cues are not positively correlated, as is often the case during acoustic communication. Because of varying distances of signalers, a female may be confronted with signals of diverse quality at different intensities. Here, we examined how available cues are weighted for a decision by female crickets. Two songs with different temporal patterns and/or sound intensities were presented in a choice paradigm and compared with female responses from a no-choice test. When both patterns were presented at equal intensity, preference functions became wider in choice situations compared with a no-choice paradigm. When the stimuli in two-choice tests were presented at different intensities, this effect was counteracted as preference functions became narrower compared with choice tests using stimuli of equal intensity. The weighting of intensity differences depended on pattern quality and was therefore non-linear. A simple computational model based on pattern and intensity cues reliably predicted female decisions. A comparison of processing schemes suggested that the computations for pattern recognition and directionality are performed in a network with parallel topology. However, the computational flow of information corresponded to serial processing.

Context-dependent coding and gain control in the auditory system of crickets.

Sensory systems process stimuli that greatly vary in intensity and complexity. To maintain efficient information transmission, neural systems need to adjust their properties to these different sensory contexts, yielding adaptive or stimulus-dependent codes. Here, we demonstrated adaptive spectrotemporal tuning in a small neural network, i.e. the peripheral auditory system of the cricket. We found that tuning of cricket auditory neurons was sharper for complex multi-band than for simple single-band stimuli. Information theoretical considerations revealed that this sharpening improved information transmission by separating the neural representations of individual stimulus components. A network model inspired by the structure of the cricket auditory system suggested two putative mechanisms underlying this adaptive tuning: a saturating peripheral nonlinearity could change the spectral tuning, whereas broad feed-forward inhibition was able to reproduce the observed adaptive sharpening of temporal tuning. Our study revealed a surprisingly dynamic code usually found in more complex nervous systems and suggested that stimulus-dependent codes could be implemented using common neural computations.

A neural mechanism for time-window separation resolves ambiguity of adaptive coding.

The senses of animals are confronted with changing environments and different contexts. Neural adaptation is one important tool to adjust sensitivity to varying intensity ranges. For instance, in a quiet night outdoors, our hearing is more sensitive than when we are confronted with the plurality of sounds in a large city during the day. However, adaptation also removes available information on absolute sound levels and may thus cause ambiguity. Experimental data on the trade-off between benefits and loss through adaptation is scarce and very few mechanisms have been proposed to resolve it. We present an example where adaptation is beneficial for one task--namely, the reliable encoding of the pattern of an acoustic signal-but detrimental for another--the localization of the same acoustic stimulus. With a combination of neurophysiological data, modeling, and behavioral tests, we show that adaptation in the periphery of the auditory pathway of grasshoppers enables intensity-invariant coding of amplitude modulations, but at the same time, degrades information available for sound localization. We demonstrate how focusing the response of localization neurons to the onset of relevant signals separates processing of localization and pattern information temporally. In this way, the ambiguity of adaptive coding can be circumvented and both absolute and relative levels can be processed using the same set of peripheral neurons.

Computational principles underlying recognition of acoustic signals in grasshoppers and crickets.

Grasshoppers and crickets independently evolved hearing organs and acoustic communication. They differ considerably in the organization of their auditory pathways, and the complexity of their songs, which are essential for mate attraction. Recent approaches aimed at describing the behavioral preference functions of females in both taxa by a simple modeling framework. The basic structure of the model consists of three processing steps: (1) feature extraction with a bank of 'LN models'-each containing a linear filter followed by a nonlinearity, (2) temporal integration, and (3) linear combination. The specific properties of the filters and nonlinearities were determined using a genetic learning algorithm trained on a large set of different song features and the corresponding behavioral response scores. The model showed an excellent prediction of the behavioral responses to the tested songs. Most remarkably, in both taxa the genetic algorithm found Gabor-like functions as the optimal filter shapes. By slight modifications of Gabor filters several types of preference functions could be modeled, which are observed in different cricket species. Furthermore, this model was able to explain several so far enigmatic results in grasshoppers. The computational approach offered a remarkably simple framework that can account for phenotypically rather different preference functions across several taxa.

Computational themes of peripheral processing in the auditory pathway of insects.

Hearing in insects serves to gain information in the context of mate finding, predator avoidance or host localization. For these goals, the auditory pathways of insects represent the computational substrate for object recognition and localization. Before these higher level computations can be executed in more central parts of the nervous system, the signals need to be preprocessed in the auditory periphery. Here, we review peripheral preprocessing along four computational themes rather than discussing specific physiological mechanisms: (1) control of sensitivity by adaptation, (2) recoding of amplitude modulations of an acoustic signal into a labeled-line code (3) frequency processing and (4) conditioning for binaural processing. Along these lines, we review evidence for canonical computations carried out in the peripheral auditory pathway and show that despite the vast diversity of insect hearing, signal processing is governed by common computational motifs and principles.

Time and timing in the acoustic recognition system of crickets.

The songs of many insects exhibit precise timing as the result of repetitive and stereotyped subunits on several time scales. As these signals encode the identity of a species, time and timing are important for the recognition system that analyzes these signals. Crickets are a prominent example as their songs are built from sound pulses that are broadcast in a long trill or as a chirped song. This pattern appears to be analyzed on two timescales, short and long. Recent evidence suggests that song recognition in crickets relies on two computations with respect to time; a short linear-nonlinear (LN) model that operates as a filter for pulse rate and a longer integration time window for monitoring song energy over time. Therefore, there is a twofold role for timing. A filter for pulse rate shows differentiating properties for which the specific timing of excitation and inhibition is important. For an integrator, however, the duration of the time window is more important than the precise timing of events. Here, we first review evidence for the role of LN-models and integration time windows for song recognition in crickets. We then parameterize the filter part by Gabor functions and explore the effects of duration, frequency, phase, and offset as these will correspond to differently timed patterns of excitation and inhibition. These filter properties were compared with known preference functions of crickets and katydids. In a comparative approach, the power for song discrimination by LN-models was tested with the songs of over 100 cricket species. It is demonstrated how the acoustic signals of crickets occupy a simple 2-dimensional space for song recognition that arises from timing, described by a Gabor function, and time, the integration window. Finally, we discuss the evolution of recognition systems in insects based on simple sensory computations.

Critical song features for auditory pattern recognition in crickets.

Many different invertebrate and vertebrate species use acoustic communication for pair formation. In the cricket Gryllus bimaculatus, females recognize their species-specific calling song and localize singing males by positive phonotaxis. The song pattern of males has a clear structure consisting of brief and regular pulses that are grouped into repetitive chirps. Information is thus present on a short and a long time scale. Here, we ask which structural features of the song critically determine the phonotactic performance. To this end we employed artificial neural networks to analyze a large body of behavioral data that measured females' phonotactic behavior under systematic variation of artificially generated song patterns. In a first step we used four non-redundant descriptive temporal features to predict the female response. The model prediction showed a high correlation with the experimental results. We used this behavioral model to explore the integration of the two different time scales. Our result suggested that only an attractive pulse structure in combination with an attractive chirp structure reliably induced phonotactic behavior to signals. In a further step we investigated all feature sets, each one consisting of a different combination of eight proposed temporal features. We identified feature sets of size two, three, and four that achieve highest prediction power by using the pulse period from the short time scale plus additional information from the long time scale.

Computational principles underlying the recognition of acoustic signals in insects.

Many animals produce pulse-like signals during acoustic communication. These signals exhibit structure on two time scales: they consist of trains of pulses that are often broadcast in packets-so called chirps. Temporal parameters of the pulse and of the chirp are decisive for female preference. Despite these signals being produced by animals from many different taxa (e.g. frogs, grasshoppers, crickets, bushcrickets, flies), a general framework for their evaluation is still lacking. We propose such a framework, based on a simple and physiologically plausible model. The model consists of feature detectors, whose time-varying output is averaged over the signal and then linearly combined to yield the behavioral preference. We fitted this model to large data sets collected in two species of crickets and found that Gabor filters--known from visual and auditory physiology--explain the preference functions in these two species very well. We further explored the properties of Gabor filters and found a systematic relationship between parameters of the filters and the shape of preference functions. Although these Gabor filters were relatively short, they were also able to explain aspects of the preference for signal parameters on the longer time scale due to the integration step in our model. Our framework explains a wide range of phenomena associated with female preference for a widespread class of signals in an intuitive and physiologically plausible fashion. This approach thus constitutes a valuable tool to understand the functioning and evolution of communication systems in many species.

Auditory processing at two time scales by the cricket Gryllus bimaculatus.

The acoustic display of many cricket species consists of series of pulses grouped into chirps, and thus information is distributed over both short and long time scales. Here we investigated the temporal cues that females of the cricket Gryllus bimaculatus used to detect a chirp pattern on a longer time scale than the fast pulse pattern. First, over a range of chirp and pause durations (100-400 ms), the duty cycle of the chirp pattern emerged as the most important cue for detection. The songs of males showed a distribution at lower duty cycles than preferred by females. The duty cycle also limited the responses of females at very short durations and pauses (below 80 ms). Second, by systematic variation of pulse and chirp periods of stimuli, an intermediate response field emerged that revealed the best responses of female crickets to patterns with amplitude modulations on both short and long time scales. On average, females also responded weakly to stimuli that contained amplitude modulations of only one time scale. Third, test patterns were constructed by addition of modulation frequencies rather than rectangular pulses. These tests showed that female crickets processed the chirp pattern in the time domain and tolerated noise levels up to a modulation depth of 50%. The combined evidence from all three approaches indicated inhibitory effects of unattractive patterns on both time scales. The fusion of short and long time scales during auditory processing by female crickets corresponded to a weighted AND-like operation of two processing modules, the pulse and the chirp filter.

Multiple arithmetic operations in a single neuron: the recruitment of adaptation processes in the cricket auditory pathway depends on sensory context.

Sensory pathways process behaviorally relevant signals in various contexts and therefore have to adapt to differing background conditions. Depending on changes in signal statistics, this adjustment might be a combination of two fundamental computational operations: subtractive adaptation shifting a neuron's threshold and divisive gain control scaling its sensitivity. The cricket auditory system has to deal with highly stereotyped conspecific songs at low carrier frequencies, and likely much more variable predator signals at high frequencies. We proposed that due to the differences between the two signal classes, the operation that is implemented by adaptation depends on the carrier frequency. We aimed to identify the biophysical basis underlying the basic computational operations of subtraction and division. We performed in vivo intracellular and extracellular recordings in a first-order auditory interneuron (AN2) that is active in both mate recognition and predator avoidance. We demonstrated subtractive shifts at the carrier frequency of conspecific songs and division at the predator-like carrier frequency. Combined application of current injection and acoustic stimuli for each cell allowed us to demonstrate the subtractive effect of cell-intrinsic adaptation currents. Pharmacological manipulation enabled us to demonstrate that presynaptic inhibition is most likely the source of divisive gain control. We showed that adjustment to the sensory context can depend on the class of signals that are relevant to the animal. We further revealed that presynaptic inhibition is a simple mechanism for divisive operations. Unlike other proposed mechanisms, it is widely available in the sensory periphery of both vertebrates and invertebrates.

Walking in Fourier's space: algorithms for the computation of periodicities in song patterns by the cricket Gryllus bimaculatus.

Is discrimination of the envelope of an acoustic signal based on spectral or temporal computations? To investigate this question for the cricket Gryllus bimaculatus, pattern envelopes were constructed by the addition of several sine waves and modified by systematic phase changes. The phonotactic response of female crickets towards such sinusoidal but also rectangular pulse patterns was quantified on a locomotion compensator. Envelope patterns that exhibited a modulation frequency of 25 Hz as the dominant frequency were attractive and although changes of phase modified the temporal pattern, the values of attractiveness remained unaffected. Removal of the 25-Hz component reduced the phonotactic scores. Patterns in which other frequency components exhibited a larger amplitude than the 25-Hz component were less attractive. However, the combination of an unattractive pulse period with the attractive modulation frequency of 25 Hz in a pattern revealed that such stimuli were unattractive despite the presence of the 25-Hz component. A comparison of the attractiveness of all patterns revealed that female crickets evaluated the duration of pulse period over a wide range of duty cycles. The combined evidence showed that pattern envelopes were processed in the time- and not in the spectral domain.

The origin of adaptation in the auditory pathway of locusts is specific to cell type and function.

We investigated the origin of spike frequency adaptation within a layered sensory network: the auditory pathway of locusts. Spike frequency adaptation as observed in an individual neuron may arise because of intrinsic or presynaptic adaptation mechanisms. To separate the contribution of different mechanisms, we recorded from the same cell during acoustic and intracellular current stimulation. We studied three identified neuron types that are representative for each network layer and participate in processing auditory patterns and localizing sound sources. By comparing current and acoustic stimulation, three distinct patterns of the distribution of adaptation mechanisms within the sensory network emerged: (1) balanced influence of both intrinsic and presynaptic adaptation mechanisms in an interneuron that summates over several receptor afferents (TN1), (2) predominantly inhibiting input as the source for spike frequency adaptation in a cell that transmits both pattern representation and directional information (BSN1), (3) primarily intrinsic, spike-triggered adaptation currents within an interneuron coding exclusively for direction (AN2). The time courses of spike frequency adaptation differed significantly between the cells types. Using the adaptation time constants, we were able to predict signal transmission properties for the different cells. We conclude that the adaptation mechanisms differ greatly among interneurons within this sensory pathway and are a function of their role in information processing.

Adaptation and selective information transmission in the cricket auditory neuron AN2.

Sensory systems adapt their neural code to changes in the sensory environment, often on multiple time scales. Here, we report a new form of adaptation in a first-order auditory interneuron (AN2) of crickets. We characterize the response of the AN2 neuron to amplitude-modulated sound stimuli and find that adaptation shifts the stimulus-response curves toward higher stimulus intensities, with a time constant of 1.5 s for adaptation and recovery. The spike responses were thus reduced for low-intensity sounds. We then address the question whether adaptation leads to an improvement of the signal's representation and compare the experimental results with the predictions of two competing hypotheses: infomax, which predicts that information conveyed about the entire signal range should be maximized, and selective coding, which predicts that "foreground" signals should be enhanced while "background" signals should be selectively suppressed. We test how adaptation changes the input-response curve when presenting signals with two or three peaks in their amplitude distributions, for which selective coding and infomax predict conflicting changes. By means of Bayesian data analysis, we quantify the shifts of the measured response curves and also find a slight reduction of their slopes. These decreases in slopes are smaller, and the absolute response thresholds are higher than those predicted by infomax. Most remarkably, and in contrast to the infomax principle, adaptation actually reduces the amount of encoded information when considering the whole range of input signals. The response curve changes are also not consistent with the selective coding hypothesis, because the amount of information conveyed about the loudest part of the signal does not increase as predicted but remains nearly constant. Less information is transmitted about signals with lower intensity.

Spike-frequency adaptation generates intensity invariance in a primary auditory interneuron.

Adaptation of the spike-frequency response to constant stimulation, as observed on various timescales in many neurons, reflects high-pass filter properties of a neuron's transfer function. Adaptation in general, however, is not sufficient to make a neuron's response independent of the mean intensity of a sensory stimulus, since low frequency components of the stimulus are still transmitted, although with reduced gain. We here show, based on an analytically tractable model, that the response of a neuron is intensity invariant, if the fully adapted steady-state spike-frequency response to constant stimuli is independent of stimulus intensity. Electrophysiological recordings from the AN1, a primary auditory interneuron of crickets, show that for intensities above 60 dB SPL (sound pressure level) the AN1 adapted with a time-constant of approximately 40 ms to a steady-state firing rate of approximately 100 Hz. Using identical random amplitude-modulation stimuli we verified that the AN1's spike-frequency response is indeed invariant to the stimulus' mean intensity above 60 dB SPL. The transfer function of the AN1 is a band pass, resulting from a high-pass filter (cutoff frequency at 4 Hz) due to adaptation and a low-pass filter (100 Hz) determined by the steady-state spike frequency. Thus, fast spike-frequency adaptation can generate intensity invariance already at the first level of neural processing.