99 research outputs found
Scene analysis in the natural environment
The problem of scene analysis has been studied in a number of different fields over the past decades. These studies have led to a number of important insights into problems of scene analysis, but not all of these insights are widely appreciated. Despite this progress, there are also critical shortcomings in current approaches that hinder further progress. Here we take the view that scene analysis is a universal problem solved by all animals, and that we can gain new insight by studying the problems that animals face in complex natural environments. In particular, the jumping spider, songbird, echolocating bat, and electric fish, all exhibit behaviors that require robust solutions to scene analysis problems encountered in the natural environment. By examining the behaviors of these seemingly disparate animals, we emerge with a framework for studying analysis comprising four essential properties: 1) the ability to solve ill-posed problems, 2) the ability to integrate and store information across time and modality, 3) efficient recovery and representation of 3D scene structure, and 4) the use of optimal motor actions for acquiring information to progress towards behavioral goals
Active Control of Acoustic Field-of-View in a Biosonar System
Echolocating bats can actively change the area scanned by their biosonar sensory system (“field of view”), and they do so according to the complexity of the environment and depending on the distance to the target
A cognitive framework for object recognition with application to autonomous vehicles
Autonomous vehicles or self-driving cars are capable of sensing the surrounding environment so they can navigate roads without human input. Decisions are constantly made on sensing, mapping and driving policy using machine learning techniques. Deep Learning – massive neural networks that utilize the power of parallel processing – has become a popular choice for addressing the complexities of real time decision making. This method of machine learning has been shown to outperform alternative solutions in multiple domains, and has an architecture that can be adapted to new problems with relative ease. To harness the power of Deep Learning, it is necessary to have large amounts of training data that are representative of all possible situations the system will face. To successfully implement situational awareness in driverless vehicles, it is not possible to exhaust all possible training examples. An alternative method is to apply cognitive approaches to perception, for situations the autonomous vehicles will face. Cognitive approaches to perception work by mimicking the process of human intelligence – thereby permitting a machine to react to situations it has not previously experienced. This paper proposes a novel cognitive approach for object recognition. The proposed cognitive object recognition algorithm, referred to as Recognition by Components, is inspired by the psychological studies pertaining to early childhood development. The algorithm works by breaking down images into a series of primitive forms such as square, triangle, circle or rectangle and memory based aggregation to identify objects. Experimental results suggest that Recognition by Component algorithm performs significantly better than algorithms that require large amounts of training data
Auditory temporal resolution of a wild white-beaked dolphin (Lagenorhynchus albirostris)
Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Journal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology 195 (2009): 375-384, doi:10.1007/s00359-009-0415-x.Adequate temporal resolution is required across taxa to properly utilize amplitude modulated acoustic signals. Among mammals, odontocete marine mammals are considered to have relatively high temporal resolution, which is a selective advantage when processing fast traveling underwater sound. However, multiple methods used to estimate auditory temporal resolution have left comparisons among odontocetes and other mammals somewhat vague. Here we present the estimated auditory temporal resolution of an adult male white-beaked dolphin, (Lagenorhynchus albirostris), using auditory evoked potentials and click stimuli. Ours is the first of such studies performed on a wild dolphin in a capture-and-release scenario. The white-beaked dolphin followed rhythmic clicks up to a rate of approximately 1125-1250 Hz, after which the modulation rate transfer function (MRTF) cut-off steeply. However, 10% of the maximum response was still found at 1450 Hz indicating high temporal resolution. The MRTF was similar in shape and bandwidth to that of other odontocetes. The estimated maximal temporal resolution of white-beaked dolphins and other odontocetes was approximately twice that of pinnipeds and manatees, and more than ten-times faster than humans and gerbils. The exceptionally high temporal resolution abilities of odontocetes are likely due primarily to echolocation capabilities that require rapid processing of acoustic cues.We wish to thank the Danish Natural Science Research Council for major financial support (grant no. 272-05-0395)
The Cercal Organ May Provide Singing Tettigoniids a Backup Sensory System for the Detection of Eavesdropping Bats
Conspicuous signals, such as the calling songs of tettigoniids, are intended to attract mates but may also unintentionally attract predators. Among them bats that listen to prey-generated sounds constitute a predation pressure for many acoustically communicating insects as well as frogs. As an adaptation to protect against bat predation many insect species evolved auditory sensitivity to bat-emitted echolocation signals. Recently, the European mouse-eared bat species Myotis myotis and M. blythii oxygnathus were found to eavesdrop on calling songs of the tettigoniid Tettigonia cantans. These gleaning bats emit rather faint echolocation signals when approaching prey and singing insects may have difficulty detecting acoustic predator-related signals. The aim of this study was to determine (1) if loud self-generated sound produced by European tettigoniids impairs the detection of pulsed ultrasound and (2) if wind-sensors on the cercal organ function as a sensory backup system for bat detection in tettigoniids. We addressed these questions by combining a behavioral approach to study the response of two European tettigoniid species to pulsed ultrasound, together with an electrophysiological approach to record the activity of wind-sensitive interneurons during real attacks of the European mouse-eared bat species Myotis myotis. Results showed that singing T. cantans males did not respond to sequences of ultrasound pulses, whereas singing T. viridissima did respond with predominantly brief song pauses when ultrasound pulses fell into silent intervals or were coincident with the production of soft hemi-syllables. This result, however, strongly depended on ambient temperature with a lower probability for song interruption observable at 21°C compared to 28°C. Using extracellular recordings, dorsal giant interneurons of tettigoniids were shown to fire regular bursts in response to attacking bats. Between the first response of wind-sensitive interneurons and contact, a mean time lag of 860 ms was found. This time interval corresponds to a bat-to-prey distance of ca. 72 cm. This result demonstrates the efficiency of the cercal system of tettigoniids in detecting attacking bats and suggests this sensory system to be particularly valuable for singing insects that are targeted by eavesdropping bats
Functional correlates of skull shape in Chiroptera: feeding and echolocation adaptations.
Morphological, functional and behavioural adaptations of bats are among the most diverse within mammals. A strong association between bat skull morphology and feeding behaviour has been suggested previously. However, morphological variation related to other drivers of adaptation, in particular echolocation, remains understudied. We assessed variation in skull morphology with respect to ecology (diet and emission type) and function (bite force, masticatory muscles and echolocation characteristics) using geometric morphometrics and comparative methods. Our study suggests that variation in skull shape of 10 bat families is the result of adaptations to broad dietary categories and sound emission types (oral or nasal). Skull shape correlates with echolocation parameters only in a subsample of insectivorous species, possibly because they (almost) entirely rely on this sensory system for locating and capturing prey. Insectivores emitting low frequencies are characterised by a ventrally tilted rostrum, a trait not associated with feeding parameters. This result questions the validity of a trade-off between feeding and echolocation function. Our study advances understanding of the relationship between skull morphology and specific features of echolocation and suggests that evolutionary constraints due to echolocation may differ between different groups within the Chiroptera
Implications of sensory ecology for species coexistence: biased perception links predator diversity to prey size distribution
Hearing and evasive behaviour in the greater wax moth, Galleria mellonella (Pyralidae)
Greater wax moths (Galleria mellonella L., Pyraloidea) use ultrasound sensitive ears to detect clicking conspecifics and echolocating bats. Pyralid ears have four sensory cells, A14. The audiogram of G. mellonella has best frequency at 60 kHz with a threshold around 47 dB sound pressure level. A1 and A2 have almost equal thresholds in contrast to noctuids and geometrids. A3 responds at + 12 to + 16 dB relative to the A1 threshold. The threshold data from the A-cells give no indication of frequency discrimination in greater wax moths. Tethered greater wax moths respond to ultrasound with short-latency cessation of flight at + 20 to + 25 dB relative to the A1 threshold. The behavioural threshold curve parallels the audiogram, thus further corroborating the lack of frequency discrimination. Hence, the distinction between bats and conspecifics is probably based on temporal cues. At a constant duty cycle (percentage of time where sound is on) the pulse repetition rate has no effect on the threshold for flight cessation, but stimulus duration affects both sensory and behavioural thresholds. The maximum integration time is essentially the same: 45 ms for the A1-cell and 50–60 ms for the flight cessation response. However, the slopes of the time-intensity trade-off functions are very different: − 2.1 dB per doubling of sound duration for the A1-cell threshold, and − 7.2 dB per doubling of sound duration for the behavioural threshold. The significance of the results for sexual acoustic communication as well as for bat defence is discussed
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