Biology subjects

Clemens, J.

Publications and source records attributed to Clemens, J..

17 recordsLinked to original sources

bioRxiv2026

A shared circuit architecture for multiscale signal recognition in crickets

Communication signals often contain behaviorally relevant structure on multiple temporal scales. Short-timescale features are commonly thought to be recognized first and then integrated into longer-timescale representations. Whether a shared circuit can instead recognize multiple timescales remains unclear. Cricket calling songs provide a tractable test because millisecond-scale pulses are grouped into chirps lasting hundreds of milliseconds. We combined female phonotaxis with a mechanistic model of the identified pulse-recognition network to ask whether this circuitry can also generate chirp selectivity. In Gryllus bimaculatus, the model, originally parameterized from pulse-scale electrophysiology and behavior, recovered the main boundaries of chirp preference without fitting to chirp behavior. Coincidence detection generated the minimum chirp-duration requirement, whereas suppressive computations in the networks input neuron shaped the upper boundaries for chirp duty cycle and period. Across 14 species, varying these suppressive computations captured major differences in chirp tuning. These findings reveal a temporally interleaved serial circuit in which long-timescale selectivity begins upstream of completed short-timescale selectivity, offering an alternative to both conventional short-first hierarchies and parallel pathways.

neuroscience↗

bioRxiv2026

Abdominal-B neurons selectively drive vibrations in Drosophila

Male Drosophila courtship includes two communication signals: airborne song and substrate-borne vibrations. While the neural control of song has been extensively characterized, little is known about the circuits underlying vibration production. Here, we identify neurons expressing the Hox gene abdominal-B (abdB) as a driver of vibration production. Optogenetic activation of abdB neurons selectively elicited vibrations in both males and females without inducing courtship song, whereas silencing these neurons did not impair vibration production during natural courtship. The vibration-driving abdB neurons are neither doublesex-nor fruitless-positive, defining a previously unrecognized component of the courtship circuit. Although abdB activation produced only stimulus-locked vibrations, co-activation of the persistence-promoting neuron cluster pCd converted this transient signal output into sustained vibration trains. Together, our results identify a dedicated pathway for vibration production and show that signal identity and persistence can be independently specified by distinct circuit components.

neuroscience↗

bioRxiv2025

Drosophila males integrate song and pheromones usingcontext-specific strategies

Animals need to integrate sensory information from multiple modalities to interact with their environment and with others. In male Drosophila, multiple sensory cues modulate social behaviors such as courtship and aggression, but the strategies by which multimodal cues are combined to inform social behavior are not known. Here, we focus on how courtship song and taste cues are integrated to shape the social behavior of male flies. By combining cue manipulations with computational modeling, we assessed the individual and combined contributions of song and taste. Our results reveal three context-specific integration strategies. Overall social interactions were driven by a linear combination of song and taste. Aggression was driven by song, independent of taste cues. Courtship was controlled by a nonlinear integration of song and female taste cues, with female taste flipping the valence of song from suppressing to enhancing courtship. Our results show how context-specific integration strategies allow animals to recognize social scenarios and produce flexible, context-appropriate behaviors.

neuroscience↗

bioRxiv2025

Control of walking direction by descending and dopaminergic neurons in Drosophila

Animals need to fine-control the speed and direction of locomotion to navigate complex and dynamic environments. To achieve this, they integrate multimodal sensory inputs with their internal drive to constantly adjust their motor output. This integration involves the interplay of neuronal populations across different hierarchical levels along the sensorimotor axis - from sensory, central, and modulatory neurons in the brain to descending neurons and motor networks in the nerve cord. Here, we characterize two populations of neurons that control distinct aspects of walking on different hierarchical levels in Drosophila. First, we use in-vivo electrophysiological recordings to demonstrate that moonwalker descending neurons (MDN) integrate antennal touch to drive changes in walking direction from forward to backward. Second, we establish DopaMeander as an important component in the control of forward walking through a combination of optogenetic activation, silencing, connectomics, and in-vivo recordings. These dopaminergic modulatory neurons drive forward walking with increased turning, and the activity of individual neurons is correlated with ipsiversive turning. Hence, MDN and DopaMeander control opposite regimes of walking on different hierarchical levels. Computational models reveal that their activity predicts key parameters of spontaneous walking. Moreover, we find that both MDN and DopaMeander are gated out during flight. This suggests that neuronal populations across levels of control are modulated by the behavioral state to minimize cross-talk between motor programs.

neuroscience↗

bioRxiv2025

Sex-specific behavioral feedback modulates sensorimotor processing and drives flexible social behavior

How the brain enables individuals to adapt behavior to their partner is key to understanding social exchange. For example, courtship behavior involves sensorimotor processing of signals that can result in behavioral dialogue between partners, such as stereotyped movements and singing. The courtship behavior of Drosophila melanogaster males with their partners, which are usually female but can also be male, involves singing. To investigate how behavioral feed-back and sensorimotor processing contribute to flexible social interactions, we compared the courtship behavior and singing of male D. melanogaster towards males and females. Quanti-tative analysis of their interactions revealed that while underlying courtship and song rules are unaffected by the sex of the partner, the behavioral dynamics and song sequences differ by partner sex. This divergence stems from sex-specific behavioral feedback: females decelerate to song, while males orient towards the singer. Moreover, optogenetic manipulations reveal that the partners responses are driven by sex-specific neural circuits that link song detection with arousal and social decisions. Our findings demonstrate that flexible social behaviors can arise from fixed sensorimotor rules through a context-dependent selection facilitated by the partners behavioral feedback. More broadly, our results reveal compositionality as a key mechanism for achieving behavioral flexibility during complex social interactions such as courtship.

neuroscience↗

bioRxiv2025

Attuning to song duels facilitates song-matching in nightingales

Complex vocal communication requires precise, flexible adjustments to vocal-motor commands for the production of coherent responses to auditory inputs. The mechanisms underlying how such sensorimotor integration controls vocal production is poorly understood. Here, we investigate the dynamics of territorial vocal duels and song-matching in common nightingales (Luscinia megarhynchos). Using a combination of field observations, playback experiments and accelerometry, we find that wild nightingales readily modified the acoustic features of their song, matched the rivals song and engaged more vigorously against vocal opponents with a shared song repertoire. Furthermore, we demonstrate that neurons in the sensorimotor nucleus HVC are tuned to specific song stimuli, potentially enabling context-specific integration of auditory information to facilitate matched song production. These findings highlight the crucial role of song recognition in allowing nightingales to adjust their vocalizations in response to specific social situations, demonstrating the complexity and adaptability of their communication system. Moreover, this study provides a new framework and model system for investigating online sensorimotor processing during dynamic vocal interactions.

neuroscience↗

bioRxiv2024

A neural circuit for context-dependent multimodal signaling in Drosophila

Many animals, including humans, produce multimodal displays by combining acoustic with visual or vibratory signals [1-4]. However, the neural circuits that coordinate the production of multiple signals in a context-dependent manner are unknown. Multimodal behaviors could be produced by parallel circuits that independently integrate the external cues that trigger each signal. We find that multimodal signals in Drosophila are driven by a single circuit that integrates external sensory cues with internal motivational state and circuit dynamics. Drosophila males produce air-borne song and substrate-borne vibration during courtship and previous studies have identified neurons that drive courtship and singing, but the contexts and circuits that drive vibrations and coordinate multimodal signaling were not known [5-11]. We show that males produce song and vibration in distinct, largely non-overlapping contexts and that brain neurons that drive song also drive vibrations with cell-type specific dynamics and via separate pre-motor pathways. This circuit also coordinates multimodal signaling with ongoing behavior, namely locomotion, to drive vibrations only when the males vibrations can reach the female. A shared circuit facilitates the control of signal dynamics by external cues and motivational state through shared mechanisms like recurrence and mutual inhibition. A proof-of-concept circuit model shows that these motifs are sufficient to explain the behavioral dynamics. Our work shows how simple motifs can be combined in a single neural circuit to select and coordinate multiple behaviors.

neuroscience↗

bioRxiv2024

Taming a behavioral monster: Resonant song recognition and the evolution of acoustic communication in crickets

Rare behavioral phenotypes--behavioral monsters--can challenge hypotheses about the evolution of the neural networks that drive behavior. In crickets, the diversity of song recognition behaviors is thought to be based on the modification of a shared neural network. We here report on a cricket with a novel resonant song recognition pattern that challenges this hypothesis. Females of the species Anurogryllus muticus respond to pulse patterns with the period of the male song, but also to song at twice the period. To identify the mechanisms underlying this multi-peaked recognition, we first explored minimal models of resonant behaviors. Though all of the three simple models tested (autocorrelation, rebound, resonate and fire) produced some kind of resonant behavior, only a single-neuron model with an oscillating membrane qualitatively matched the Anurogryllus behavior with regard to both period and duty cycle tuning. Surprisingly, the rebound model, a minimal model of the core mechanism for song recognition in crickets, fails to reproduce the preference for higher duty cycles observed in the behavior, questioning the universality of the core algorithm. However, the behavior is reproduced with a network model that contains all computations from the song recognition network of crickets, revealing the importance of an additional computation not part of the core mechanism: Following the core rebound mechanism in which post-inhibitory rebounds give rise to the resonant period tuning, feed-forward inhibition further shapes the tuning, resulting in the observed behavioral profile. Overall, this shows how unusual behavioral phenotypes can evolve by combining different nonlinear computations at the level of single cells and networks.

neuroscience↗

bioRxiv2023

Flexible control of vocal timing in bats enables escape from acoustic interference

In natural environments, background noise can degrade the integrity of acoustic signals, posing a problem for animals that rely on their vocalizations for communication and navigation. A simple behavioral strategy to combat acoustic interference would be to restrict call emissions to periods of low-amplitude or no noise. Using audio playback and computational tools for the automated detection of over 2.5 million vocalizations from groups of freely vocalizing bats, we show that bats (Carollia perspicillata) can dynamically adapt the timing of their calls to avoid acoustic jamming in both predictably and unpredictably patterned noise. This study demonstrates that bats spontaneously seek out temporal windows of opportunity for vocalizing in acoustically crowded environments, providing a mechanism for efficient echolocation and communication in cluttered acoustic landscapes. One Sentence SummaryBats avoid acoustic interference by rapidly adjusting the timing of vocalizations to the temporal pattern of varying noise.

animal behavior and cognition↗

bioRxiv2021

Quadratic and adaptive computations yield an efficient representation of song in Drosophila auditory receptor neurons

Sensory neurons transform stimuli through multiple adaptive and nonlinear computations. In Drosophila, auditory receptor neurons adapt to the mean and intensity of acoustic stimuli, shift their frequency tuning with sound intensity, and employ a quadratic nonlinearity. Although each of these computations is thought to improve sensory encoding, their combination could produce a highly ambiguous neural code from which behaviorally relevant information is difficult to extract. Here, we combine electrophysiology and computational modeling to determine how these computations jointly encode natural acoustic signals such as courtship song. We show that a model consisting of a quadratic filter followed by divisive normalization accurately reproduces population responses to both artificial and natural sounds. The model further localizes adaptive temporal filtering to antennal mechanics and variance adaptation to divisive normalization downstream of the receptor mechanics. For arbitrary broadband stimuli, these computations generate an ambiguous representation from which carrier frequency and amplitude cannot be reliably recovered. In contrast, the representation of courtship song is simple and robust. Quadratic filtering enhances encoding of the song envelope while preserving a straightforward temporal code for the carrier through frequency doubling. Divisive normalization removes slow intensity fluctuations arising during social interactions while preserving the rapid envelope fluctuations that define song structure. Together, our results show that adaptive and nonlinear computations that appear to complicate sensory coding for arbitrary stimuli instead generate a robust and easily decoded representation of behaviorally relevant signals by exploiting their natural statistics.

neuroscience↗

bioRxiv2021

Fast and accurate annotation of acoustic signals with deep neural networks

Acoustic signals serve communication within and across species throughout the animal kingdom. Studying the genetics, evolution, and neurobiology of acoustic communication requires annotating acoustic signals: segmenting and identifying individual acoustic elements like syllables or sound pulses. To be useful, annotations need to be accurate, robust to noise, and fast. We here introduce DAS, a method that annotates acoustic signals across species based on a deep-learning derived hierarchical presentation of sound. We demonstrate the accuracy, robustness, and speed of DAS using acoustic signals with diverse characteristics from insects, birds, and mammals. DAS comes with a graphical user interface for annotating song, training the network, and for generating and proofreading annotations. The method can be trained to annotate signals from new species with little manual annotation and can be combined with unsupervised methods to discover novel signal types. DAS annotates song with high throughput and low latency, allowing realtime annotations for closed-loop experimental interventions. Overall, DAS is a universal, versatile, and accessible tool for annotating acoustic communication signals.

neuroscience↗

bioRxiv2020

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 models 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 arise from computations that likely evolved to increase energy efficiency and robustness of pattern recognition. The models 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.

neuroscience↗

bioRxiv2020

Sex-specific speed-accuracy tradeoffs shape neural processing of acoustic signals

Speed-accuracy tradeoffs - being fast at the risk of being wrong - are fundamental to many decisions and natural selection is expected to resolve these tradeoffs according to the costs and benefits of behavior. We here test the prediction that females and males should integrate information from courtship signals differently because they experience different payoffs along the speed-accuracy continuum. We fitted a neural model of decision making (a drift-diffusion model of integration to threshold) to behavioral data from the grasshopper Chorthippus biguttulus to determine the parameters of temporal integration of acoustic directional information used by male grasshoppers to locate receptive females. The model revealed that males had a low threshold for initiating a turning response, yet a large integration time constant enabled them to continue to gather information when cues were weak. This contrasts with parameters estimated for females of the same species when evaluating potential mates, in which response thresholds were much higher and behavior was strongly influenced by unattractive stimuli. Our results reveal differences in neural integration consistent with the sex-specific costs of mate search: Males often face competition and need to be fast, while females often pay high error costs and need to be deliberate.

neuroscience↗

bioRxiv2020

Litterbox - A gnotobiotic zeolite-clay system to investigate Arabidopsis-microbe interactions

Plants are colonised by millions of microorganisms representing thousands of species with varying effects on plant growth and health. The microbial communities found on plants are compositionally consistent and their overall positive effect on the plant is well known. However, the effects of individual microbiota members on plant hosts and vice versa, as well as the underlying mechanisms remain largely unknown. Here, we describe Litterbox, a highly controlled system to investigate plant-microbe interactions. Plants were grown gnotobiotically on zeolite-clay, an excellent soil replacement that retains enough moisture to avoid subsequent watering. Plants grown on zeolite phenotypically resemble plants grown under environmental conditions. Further, bacterial densities on leaves in the Litterbox system resembled those in temperate environments. A PDMS sheet was used to cover the zeolite, thereby significantly lowering the bacterial load in the zeolite and rhizosphere. This reduced the likelihood of potential systemic responses in leaves induced by microbial rhizosphere colonisation. We present results of example experiments studying the transcriptional responses of leaves to defined microbiota members and the spatial distribution of bacteria on leaves. We anticipate that this versatile and affordable plant growth system will promote microbiota research and help in elucidating plant-microbe interactions and their underlying mechanisms.

plant biology↗

bioRxiv2018

Shared Song Object Detector Neurons in Drosophila Male and Female Brains Drive Divergent, Sex-Specific Behaviors

Males and females often produce distinct responses to the same sensory stimuli. How such differences arise - at the level of sensory processing or in the circuits that generate behavior - remains largely unresolved across sensory modalities. We address this issue in the acoustic communication system of Drosophila. During courtship, males generate time-varying songs, and each sex responds with specific behaviors. We characterize male and female behavioral tuning for all aspects of song, and show that feature tuning is similar between sexes, suggesting sex-shared song detectors drive divergent behaviors. We then identify higher-order neurons in the Drosophila brain, called pC2, that are tuned for multiple temporal aspects of one mode of the males song, and drive sex-specific behaviors. We thus uncover neurons that are specifically tuned to an acoustic communication signal and that reside at the sensory-motor interface, flexibly linking auditory perception with sex-specific behavioral responses.

neuroscience↗

bioRxiv2017

Fast Intensity Adaptation Enhances the Encoding of Sound in Drosophila

To faithfully encode complex stimuli, sensory neurons should correct, via adaptation, for stimulus properties that corrupt pattern recognition. Here, we investigate sound intensity adaptation in the Drosophila auditory system, which is largely devoted to processing courtship song. Mechanosensory neurons (JONs) in the antenna are sensitive not only to sound-induced antennal vibrations, but also to wind or gravity, which affect the antennas mean position. Song pattern recognition therefore requires adaptation to antennal position (stimulus mean) in addition to sound intensity (stimulus variance). We discover fast variance adaptation in Drosophila JONs, which corrects for background noise over the behaviorally relevant intensity range. We determine where mean and variance adaptation arises and how they interact. A computational model explains our results using a sequence of subtractive and divisive adaptation modules, interleaved by rectification. These results lay the foundation for identifying the molecular and biophysical implementation of adaptation to the statistics of natural sensory stimuli.

neuroscience↗

bioRxiv2017

Reported Drosophila Courtship Song Rhythms Remain Data Analysis Artifacts

From 1980 to 1992, a series of influential papers reported on the discovery, genetics, and evolution of a periodic cycling of the interval between Drosophila male courtship song pulses. The molecular mechanisms underlying this periodicity were never described. To reinitiate investigation of this phenomenon, we performed automated segmentation of songs, but failed to detect the proposed periodicity [Arthur BJ et al. (2013) BMC Biol 11:11; Stern DL (2014) BMC Biol 12:38]. Kyriacou CP et al. [(2017) PNAS 114:1970-1975] report that we failed to detect song rhythms because i) our flies did not sing enough and ii) our segmenter did not identify many of the song pulses. Kyriacou et al. manually annotated a subset of our recordings and reported that two strains displayed rhythms with genotype-specific periodicity, in agreement with their original reports. We cannot replicate this finding and show that the manually-annotated data, the original automatically segmented data, and a new data set provide no evidence for either the existence of song rhythms or song periodicity differences between genotypes. Furthermore, we have re-examined our methods and analysis and find that our automated segmentation method was not biased to prevent detection of putative song periodicity. We conclude that there is currently no evidence for the existence of Drosophila courtship song rhythms.\n\nSignificance statementPrevious studies have reported that male vinegar flies sing courtship songs with a periodic rhythm of approximately 55 seconds. Several years ago, we showed that we could not replicate this observation. Recently, the original authors have claimed that we failed to find rhythms because 1) our flies did not sing enough and 2) our software for detecting song did not detect all song events. They claimed that they could detect rhythms in song annotated by hand. We report here that we cannot replicate their observation of rhythms in the hand-annotated data or in any dataset and that our original methods were not biased against detecting rhythms. We conclude that song rhythms cannot be detected.

animal behavior and cognition↗