Multi-channel acoustic recording and automated analysis of Drosophila courtship songs.

BACKGROUND: Drosophila melanogaster has served as a powerful model system for genetic studies of courtship songs. To accelerate research on the genetic and neural mechanisms underlying courtship song, we have developed a sensitive recording system to simultaneously capture the acoustic signals from 32 separate pairs of courting flies as well as software for automated segmentation of songs. RESULTS: Our novel hardware design enables recording of low amplitude sounds in most laboratory environments. We demonstrate the power of this system by collecting, segmenting and analyzing over 18 hours of courtship song from 75 males from five wild-type strains of Drosophila melanogaster. Our analysis reveals previously undetected modulation of courtship song features and extensive natural genetic variation for most components of courtship song. Despite having a large dataset with sufficient power to detect subtle modulations of song, we were unable to identify previously reported periodic rhythms in the inter-pulse interval of song. We provide detailed instructions for assembling the hardware and for using our open-source segmentation software. CONCLUSIONS: Analysis of a large dataset of acoustic signals from Drosophila melanogaster provides novel insight into the structure and dynamics of species-specific courtship songs. Our new system for recording and analyzing fly acoustic signals should therefore greatly accelerate future studies of the genetics, neurobiology and evolution of courtship song.

Mosquito (Aedes aegypti) flight tones: frequency, harmonicity, spherical spreading, and phase relationships.

Mosquito flight produces a tone as a side effect of wing movement; this tone is also a communication signal that is frequency-modulated during courtship. Recordings of tones produced by tethered flying male and female Aedes aegypti were undertaken using pairs of pressure-gradient microphones above and below, ahead and behind, and to the left and right over a range of distances. Fundamental frequencies were close to those previously reported, although amplitudes were lower. The male fundamental frequency was higher than that of the female and males modulated it over a wider range. Analysis of harmonics shows that the first six partials were nearly always within 1 Hz of integer multiples of the fundamental, even when the fundamental was being modulated. Along the front-back axis, amplitude attenuated as a function of distance raised to the power 2.3. Front and back recordings were out of phase, as were above and below, while left and right were in phase. Recordings from ahead and behind showed quadratic phase coupling, while others did not. Finally, two methods are presented for separating simultaneous flight tones in a single recording and enhancing their frequency resolution. Implications for mosquito behavior are discussed.

A scalable implementation of the recursive least-squares algorithm for training spiking neural networks.

Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a popular way to study computations performed by the nervous system. As the size and complexity of neural recordings increase, there is a need for efficient algorithms that can train models in a short period of time using minimal resources. We present optimized CPU and GPU implementations of the recursive least-squares algorithm in spiking neural networks. The GPU implementation can train networks of one million neurons, with 100 million plastic synapses and a billion static synapses, about 1,000 times faster than an unoptimized reference CPU implementation. We demonstrate the code's utility by training a network, in less than an hour, to reproduce the activity of > 66, 000 recorded neurons of a mouse performing a decision-making task. The fast implementation enables a more interactive in-silico study of the dynamics and connectivity underlying multi-area computations. It also admits the possibility to train models as in-vivo experiments are being conducted, thus closing the loop between modeling and experiments.

Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator.

The ability to optically image cellular transmembrane voltages at millisecond-timescale resolutions can offer unprecedented insight into the function of living brains in behaving animals. Here, we present a point mutation that increases the sensitivity of Ace2 opsin-based voltage indicators. We use the mutation to develop Voltron2, an improved chemigeneic voltage indicator that has a 65% higher sensitivity to single APs and 3-fold higher sensitivity to subthreshold potentials than Voltron. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, although with lower baseline fluorescence. In multiple in vitro and in vivo comparisons with its predecessor across multiple species, we found Voltron2 to be more sensitive to APs and subthreshold fluctuations. Finally, we used Voltron2 to study and evaluate the possible mechanisms of interneuron synchronization in the mouse hippocampus. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.

Adaptive auditory risk assessment in the dogbane tiger moth when pursued by bats.

Moths and butterflies flying in search of mates risk detection by numerous aerial predators; under the cover of night, the greatest threat will often be from insectivorous bats. During such encounters, the toxic dogbane tiger moth, Cycnia tenera uses the received intensity, duration and emission pattern of the bat's echolocation calls to determine when, and how many, defensive ultrasonic clicks to produce in return. These clicks, which constitute an acoustic startle response, act as warning signals against bats in flight. Using an integrated test of stimulus generalization and dishabituation, here we show that C. tenera is able to discriminate between the echolocation calls characteristic of a bat that has only just detected it versus those of a bat actively in pursuit of it. We also show that C. tenera habituates more profoundly to the former stimulus train ('early attack') than to the latter ('late attack'), even though it was initially equally responsive to both stimuli. Matched sensory and behavioural data indicate that reduced responsiveness reflects habituation and is not merely attributable to sensory adaptation or motor fatigue. In search of mates in the face of bats, C. tenera's ability to discriminate between attacking bats representing different levels of risk, and to habituate less so to those most dangerous, should function as an adaptive cost-benefit trade-off mechanism in nature.

Behavioral observations and sound recordings of free-flight mating swarms of Ae. Aegypti (Diptera: Culicidae) in Thailand.

Sound plays an important role in the mating behavior of mosquitoes, including Aedes aegypti (L). Males orient to the fundamental wing beat frequency of females, and both sexes actively modulate their flight tone before mating to converge at harmonic frequencies. The majority of studies on mosquito mating acoustics have been conducted in the laboratory using tethered individuals. In this study, we present the first free-flight recording of naturally forming Ae. aegypti swarms in Thailand. We describe mating behaviors and present results on the flight tone frequency and dynamics of wild pairs in free flight. To assess the importance of these behaviors in vector control programs, especially those using genetically modified mosquitoes, it will be critical to use methods, such as those described in this work, to measure mosquito mating behaviors in the field.

Neural Evolution of Context-Dependent Fly Song.

It is unclear where in the nervous system evolutionary changes tend to occur. To localize the source of neural evolution that has generated divergent behaviors, we developed a new approach to label and functionally manipulate homologous neurons across Drosophila species. We examined homologous descending neurons that drive courtship song in two species that sing divergent song types and localized relevant evolutionary changes in circuit function downstream of the intrinsic physiology of these descending neurons. This evolutionary change causes different species to produce divergent motor patterns in similar social contexts. Artificial stimulation of these descending neurons drives multiple song types, suggesting that multifunctional properties of song circuits may facilitate rapid evolution of song types.

Tiger moths and the threat of bats: decision-making based on the activity of a single sensory neuron.

Echolocating bats and eared moths are a model system of predator-prey interaction within an almost exclusively auditory world. Through selective pressures from aerial-hawking bats, noctuoid moths have evolved simple ears that contain one to two auditory neurons and function to detect bat echolocation calls and initiate defensive flight behaviours. Among these moths, some chemically defended and mimetic tiger moths also produce ultrasonic clicks in response to bat echolocation calls; these defensive signals are effective warning signals and may interfere with bats' ability to process echoic information. Here, we demonstrate that the activity of a single auditory neuron (the A1 cell) provides sufficient information for the toxic dogbane tiger moth, Cycnia tenera, to decide when to initiate defensive sound production in the face of bats. Thus, despite previous suggestions to the contrary, these moths' only other auditory neuron, the less sensitive A2 cell, is not necessary for initiating sound production. However, we found a positive linear relationship between combined A1 and A2 activity and the number of clicks the dogbane tiger moth produces.