Wing movements underlying sound production in calling, rivalry, and courtship songs of the cricket Gryllus bimaculatus (DeGeer)

Lin, Chu-Cheng; Hedwig, Berthold

doi:10.1016/j.jinsphys.2021.104299

Cited by 5 publications

(6 citation statements)

References 51 publications

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“…Courtship song in G. bimaculatus consists of 12–15 ms long sound pulses repeated at ~ 3.75 Hz and is dominated by frequencies of 12–16 kHz intercalated with a series of low-amplitude 4.6–4.9 kHz sound pulses (Libersat et al 1994 ; Lin and Hedwig 2021 ). B-DARN1 was presented with courtship song in recording 1; it responded with an elevated rate of ‘background’ AP firing (approximately 10–20 AP s −1 ) likely tied to the low-amplitude pulses of the song (Fig.…”

Section: Resultsmentioning

confidence: 99%

An auditory-responsive interneuron descending from the cricket brain: a new element in the auditory pathway

2022

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Crickets receive auditory information from their environment via ears located on the front legs. Ascending interneurons forward auditory activity to the brain, which houses a pattern recognition network for phonotaxis to conspecific calling songs and which controls negative phonotaxis to high-frequency sound pulses. Descending brain neurons, however, which are clearly involved in controlling these behaviors, have not yet been identified. We describe a descending auditory-responsive brain neuron with an arborization pattern that coincides with the ring-like auditory neuropil in the brain formed by the axonal arborizations of ascending and local interneurons, indicating its close link to auditory processing. Spiking activity of this interneuron occurs with a short latency to calling song patterns and the neuron copies the sound pulse pattern. The neuron preferentially responds to short sound pulses, but its activity appears to be independent of the calling song pattern recognition process. It also receives a weaker synaptic input in response to high-frequency pulses, which may contribute to its short latency spiking responses. This interneuron could be a crucial part in the auditory-to-motor transformation of the nervous system and contribute to the motor control of cricket auditory behavior.

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Section: Resultsmentioning

confidence: 99%

An auditory-responsive interneuron descending from the cricket brain: a new element in the auditory pathway

2022

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“…Cricket data at the nymph stage were not recorded since they do not chirp, i.e., their wings which enable crickets to produce sound are not fully developed. The female cricket's sounds were also not recorded as they do not produce any chirps (Jonsson et al, 2021 ; Lin and Hedwig, 2021 ). Therefore, this research processed sound signals in relation to the male crickets at the adult and mature stages.…”

Section: Methodsmentioning

confidence: 99%

“…The denoised .wav files were subsequently saved in a separate folder and, the metadata associated with these files were documented in the CSV file (as shown in Figure 2 , top right). The cricket species are known to produce three types of chirps/songs: aggression, courtship, or calling songs (Alexander, 1961 ; Miyashita et al, 2016 ; Lin and Hedwig, 2021 ). In this step, the extracted sound clips were annotated with the guidance of an entomologist, the domain expert.…”

Section: Methodsmentioning

confidence: 99%

“…For instance, crickets produce sounds to signify/mean certain behavior/activities (e.g., courtship, calling, aggression, etc.) (Alexander, 1961 ; Miyashita et al, 2016 ; Lin and Hedwig, 2021 ). The loud calling songs are meant to attract distant females, soft courtship songs initiate sexual behavior with nearby females, and aggression songs are produced when fighting for mates and territories.…”

Section: Introductionmentioning

confidence: 99%

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A convolutional neural network with image and numerical data to improve farming of edible crickets as a source of food—A decision support system

Kyalo,

Tonnang,

Egonyu

et al. 2024

Front. Artif. Intell.

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Crickets (Gryllus bimaculatus) produce sounds as a natural means to communicate and convey various behaviors and activities, including mating, feeding, aggression, distress, and more. These vocalizations are intricately linked to prevailing environmental conditions such as temperature and humidity. By accurately monitoring, identifying, and appropriately addressing these behaviors and activities, the farming and production of crickets can be enhanced. This research implemented a decision support system that leverages machine learning (ML) algorithms to decode and classify cricket songs, along with their associated key weather variables (temperature and humidity). Videos capturing cricket behavior and weather variables were recorded. From these videos, sound signals were extracted and classified such as calling, aggression, and courtship. Numerical and image features were extracted from the sound signals and combined with the weather variables. The extracted numerical features, i.e., Mel-Frequency Cepstral Coefficients (MFCC), Linear Frequency Cepstral Coefficients, and chroma, were used to train shallow (support vector machine, k-nearest neighbors, and random forest (RF)) ML algorithms. While image features, i.e., spectrograms, were used to train different state-of-the-art deep ML models, i,e., convolutional neural network architectures (ResNet152V2, VGG16, and EfficientNetB4). In the deep ML category, ResNet152V2 had the best accuracy of 99.42%. The RF algorithm had the best accuracy of 95.63% in the shallow ML category when trained with a combination of MFCC+chroma and after feature selection. In descending order of importance, the top 6 ranked features in the RF algorithm were, namely humidity, temperature, C#, mfcc11, mfcc10, and D. From the selected features, it is notable that temperature and humidity are necessary for growth and metabolic activities in insects. Moreover, the songs produced by certain cricket species naturally align to musical tones such as C# and D as ranked by the algorithm. Using this knowledge, a decision support system was built to guide farmers about the optimal temperature and humidity ranges and interpret the songs (calling, aggression, and courtship) in relation to weather variables. With this information, farmers can put in place suitable measures such as temperature regulation, humidity control, addressing aggressors, and other relevant interventions to minimize or eliminate losses and enhance cricket production.

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“…some members of the Eneopterinae: Robillard et al, 2013). It has also been shown in Gryllus bimaculatus that calling song and aggressive song are produced by similar wing movements, indicating that both song types are probably generated by the same neuronal network, but courtship song is produced using a different wing movement and is probably under different motor control (Lin and Hedwig, 2021b).…”

Section: Sound Productionmentioning

confidence: 97%

Acoustic signalling in Orthoptera

Hall

Robinson

2021

Advances in Insect Physiology

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Acoustic communication is one of the most well-known behavioural traits of the Orthoptera. Orthopteran insects and the sounds they produce are both extremely diverse, and speciesspecific sounds are an extremely important tool in orthopteran taxonomy and systematics. For most species, acoustic signalling is the most important means of communication. It plays a vital role in mating, mate choice, intrasexual competition, interspecific interactions with predators and parasitoids, and the divergence of populations and species. The enormous diversity of the orthopterans has provided researchers with a wealth of model systems for studying anatomy, physiology, neurobiology, bioacoustics, communication, life-history traits, behaviour, evolutionary ecology, and speciation, all areas in which acoustic communication is important. We first reviewed orthopteran sound signalling nearly 20 years ago (Robinson and Hall, 2002), since when there has been an enormous amount of further work. This second review will look mainly at research published since that first review.

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Wing movements underlying sound production in calling, rivalry, and courtship songs of the cricket Gryllus bimaculatus (DeGeer)

Cited by 5 publications

References 51 publications

An auditory-responsive interneuron descending from the cricket brain: a new element in the auditory pathway

An auditory-responsive interneuron descending from the cricket brain: a new element in the auditory pathway

A convolutional neural network with image and numerical data to improve farming of edible crickets as a source of food—A decision support system

Acoustic signalling in Orthoptera

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