Automated audiovisual behavior recognition in wild primates
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ABSTRACT:
SUBMITTER: Bain M
PROVIDER: S-EPMC8589313 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Automated observation and analysis of behavior is important to facilitate progress in many fields of science. Recent developments in deep learning have enabled progress in object detection and tracking, but rodent behavior recognition struggles to exceed 75-80% accuracy for ethologically relevant behaviors. We investigate the main reasons why and distinguish three aspects of behavior dynamics that are difficult to automate. We isolate these aspects in an artificial dataset and reproduce effects with the state-of-the-art behavior recognition models. Having an endless amount of labeled training data with minimal input noise and representative dynamics will enable research to optimize behavior recognition architectures and get closer to human-like recognition performance for behaviors with challenging dynamics.
| S-EPMC10366600 | biostudies-literature
Project description:Many species of primates use tools and manipulate objects. Environmental objects, such as sticks and branches, are used in locomotion, display, conflict, nesting, and foraging. This study presents observations regarding endangered male Hainan gibbons (Nomascus hainanus) selecting sticks and then throwing and catching them repeatedly. This act of Hainan gibbons was termed as "juggling" behavior. This study is the first record of branch use of this kind in free-living gibbons. While it is impossible to experiment on this only remaining population of Hainan gibbons, the deliberate acquisition and then throwing and catching of a stick raises myriad questions regarding their function. The study determined that the juggling behavior of Hainan gibbons, in the process of their brachiation, helps them accurately judge the distance and support strength of an object. It was also found that an adult individual's proficiency in juggling behavior was much higher than that of a youth. Of all gibbon species, the juggling behavior of Hainan gibbon has a high degree of behavior refinement. Gibbons have the longest forearm than any other primates, which helps them in such performances-a unique mechanism that allows them to perform such unique activities, including juggling.
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Project description:BackgroundLocomotion behaviors of Caenorhabditis elegans play an important role in drug activity screening, anti-aging research, and toxicological assessment. Previous studies have provided important insights into drug activity screening, anti-aging, and toxicological research by manually counting the number of body bends. However, manual counting is often low-throughput and takes a lot of time and manpower. And it is easy to cause artificial bias and error in counting results.ResultsIn this paper, an algorithm is proposed for automatic counting and analysis of the body bending behavior of nematodes. First of all, the numerical coordinate regression method with convolutional neural network is used to obtain the head and tail coordinates. Next, curvature-based feature point extraction algorithm is used to calculate the feature points of the nematode centerline. Then the maximum distance between the peak point and the straight line between the pharynx and the tail is calculated. The number of body bends is counted according to the change in the maximum distance per frame.ConclusionExperiments are performed to prove the effectiveness of the proposed algorithm. The accuracy of head coordinate prediction is 0.993, and the accuracy of tail coordinate prediction is 0.990. The Pearson correlation coefficient between the results of the automatic count and manual count of the number of body bends is 0.998 and the mean absolute error is 1.931. Different strains of nematodes are selected to analyze differences in body bending behavior, demonstrating a relationship between nematode vitality and lifespan. The code is freely available at https://github.com/hthana/Body-Bend-Count .
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Project description:Interventions: Single arm:None
Primary outcome(s): Overall accuracy;Mean intersection over union (mIoU)
Study Design: Single arm
| 2691192 | ecrin-mdr-crc
Project description:Recent achievements in hearing aid development, such as visually guided hearing aids, make it increasingly important to study movement behavior in everyday situations in order to develop test methods and evaluate hearing aid performance. In this work, audiovisual virtual environments (VEs) were designed for communication conditions in a living room, a lecture hall, a cafeteria, a train station, and a street environment. Movement behavior (head movement, gaze direction, and torso rotation) and electroencephalography signals were measured in these VEs in the laboratory for 22 younger normal-hearing participants and 19 older normal-hearing participants. These data establish a reference for future studies that will investigate the movement behavior of hearing-impaired listeners and hearing aid users for comparison. Questionnaires were used to evaluate the subjective experience in the VEs. A test-retest comparison showed that the measured movement behavior is reproducible and that the measures of movement behavior used in this study are reliable. Moreover, evaluation of the questionnaires indicated that the VEs are sufficiently realistic. The participants rated the experienced acoustic realism of the VEs positively, and although the rating of the experienced visual realism was lower, the participants felt to some extent present and involved in the VEs. Analysis of the movement data showed that movement behavior depends on the VE and the age of the subject and is predictable in multitalker conversations and for moving distractors. The VEs and a database of the collected data are publicly available.
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Project description:ObjectivesPeople with Schizophrenia (SZ) show deficits in auditory and audiovisual speech recognition. It is possible that these deficits are related to aberrant early sensory processing, combined with an impaired ability to utilize visual cues to improve speech recognition. In this electroencephalography study we tested this by having SZ and healthy controls (HC) identify different unisensory auditory and bisensory audiovisual syllables at different auditory noise levels.MethodsSZ (N = 24) and HC (N = 21) identified one of three different syllables (/da/, /ga/, /ta/) at three different noise levels (no, low, high). Half the trials were unisensory auditory and the other half provided additional visual input of moving lips. Task-evoked mediofrontal N1 and P2 brain potentials triggered to the onset of the auditory syllables were derived and related to behavioral performance.ResultsIn comparison to HC, SZ showed speech recognition deficits for unisensory and bisensory stimuli. These deficits were primarily found in the no noise condition. Paralleling these observations, reduced N1 amplitudes to unisensory and bisensory stimuli in SZ were found in the no noise condition. In HC the N1 amplitudes were positively related to the speech recognition performance, whereas no such relationships were found in SZ. Moreover, no group differences in multisensory speech recognition benefits and N1 suppression effects for bisensory stimuli were observed.ConclusionOur study suggests that reduced N1 amplitudes reflect early auditory and audiovisual speech processing deficits in SZ. The findings that the amplitude effects were confined to salient speech stimuli and the attenuated relationship with behavioral performance in patients compared to HC, indicates a diminished decoding of the auditory speech signals in SZs. Our study also revealed relatively intact multisensory benefits in SZs, which implies that the observed auditory and audiovisual speech recognition deficits were primarily related to aberrant processing of the auditory syllables.
| S-EPMC8683777 | biostudies-literature
Project description:Primate offspring often depend on their mothers well beyond the age of weaning, and offspring that experience maternal death in early life can suffer substantial reductions in fitness across the life span. Here, we leverage data from eight wild primate populations (seven species) to examine two underappreciated pathways linking early maternal death and offspring fitness that are distinct from direct effects of orphaning on offspring survival. First, we show that, for five of the seven species, offspring face reduced survival during the years immediately preceding maternal death, while the mother is still alive. Second, we identify an intergenerational effect of early maternal loss in three species (muriquis, baboons, and blue monkeys), such that early maternal death experienced in one generation leads to reduced offspring survival in the next. Our results have important implications for the evolution of slow life histories in primates, as they suggest that maternal condition and survival are more important for offspring fitness than previously realized.
| S-EPMC7821045 | biostudies-literature
Project description:Automated speech recognition (ASR) systems, which use sophisticated machine-learning algorithms to convert spoken language to text, have become increasingly widespread, powering popular virtual assistants, facilitating automated closed captioning, and enabling digital dictation platforms for health care. Over the last several years, the quality of these systems has dramatically improved, due both to advances in deep learning and to the collection of large-scale datasets used to train the systems. There is concern, however, that these tools do not work equally well for all subgroups of the population. Here, we examine the ability of five state-of-the-art ASR systems-developed by Amazon, Apple, Google, IBM, and Microsoft-to transcribe structured interviews conducted with 42 white speakers and 73 black speakers. In total, this corpus spans five US cities and consists of 19.8 h of audio matched on the age and gender of the speaker. We found that all five ASR systems exhibited substantial racial disparities, with an average word error rate (WER) of 0.35 for black speakers compared with 0.19 for white speakers. We trace these disparities to the underlying acoustic models used by the ASR systems as the race gap was equally large on a subset of identical phrases spoken by black and white individuals in our corpus. We conclude by proposing strategies-such as using more diverse training datasets that include African American Vernacular English-to reduce these performance differences and ensure speech recognition technology is inclusive.
| S-EPMC7149386 | biostudies-literature
Project description:BackgroundRhesus macaques are widely used in biomedical research. Automated behavior monitoring can be useful in various fields (including neuroscience), as well as having applications to animal welfare but current technology lags behind that developed for other species. One difficulty facing developers is the reliable identification of individual macaques within a group especially as pair- and group-housing of macaques becomes standard. Current published methods require either implantation or wearing of a tracking device.New methodI present face recognition, in combination with face detection, as a method to non-invasively identify individual rhesus macaques in videos. The face recognition method utilizes local-binary patterns in combination with a local discriminant classification algorithm.ResultsA classification accuracy of between 90 and 96% was achieved for four different groups. Group size, number of training images and challenging image conditions such as high contrast all had an impact on classification accuracy. I demonstrate that these methods can be applied in real time using standard affordable hardware and a potential application to studies of social structure.Comparison with existing method(s)Face recognition methods have been reported for humans and other primate species such as chimpanzees but not rhesus macaques. The classification accuracy with this method is comparable to that for chimpanzees. Face recognition has the advantage over other methods for identifying rhesus macaques such as tags and collars of being non-invasive.ConclusionsThis is the first reported method for face recognition of rhesus macaques, has high classification accuracy and can be implemented in real time.
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Project description:Laboratory training and testing of auditory recognition skills in animals is important for understanding animal communication systems that depend on auditory cues. Songbirds are commonly studied because of their exceptional ability to learn complex vocalizations. In recent years, mounting interest in the perceptual abilities of songbirds has increased the demand for laboratory behavioural training and testing paradigms. Here, we describe and demonstrate the success of a method for auditory discrimination experiments, including all the necessary hardware, training procedures and freely-available, versatile software. The system can run several behavioural training and testing paradigms, including operant (go-nogo, stimulus preference, and two-alternative forced choice) and classical conditioning tasks. The software and some hardware components can be used with any laboratory animal that learns and responds to sensory cues. The peripheral hardware and training procedures are designed for use with songbirds and auditory stimuli. Using the go-nogo paradigm of the training system, we show that adult zebra finches learn to recognize and correctly classify individual female calls and male songs. We also show that learning the task generalizes to new stimulus classes; birds that learned the task with calls subsequently learned to recognize songs faster than did birds that learned the task and songs at the same time.
| S-EPMC3156469 | biostudies-literature