scholarly journals Neural representation of bat predation risk and evasive flight in moths: a modelling approach

2019 ◽  
Author(s):  
Holger R. Goerlitz ◽  
Hannah M. ter Hofstede ◽  
Marc W. Holderied
Keyword(s):  
Frequency Tuning ◽  
Sensory System ◽  
Safety Margin ◽  
Sensory Systems ◽  
Neural Representation ◽  
Multiple Predators ◽  
Echolocation Calls ◽  
Auditory Receptor ◽  
Multiple Characteristics ◽  
Similar Distance

AbstractMost animals are at risk from multiple predators and can vary anti-predator behaviour based on the level of threat posed by each predator. Animals use sensory systems to detect predator cues, but the relationship between the tuning of sensory systems and the sensory cues related to predator threat are not well-studied at the community level. Noctuid moths have ultrasound-sensitive ears to detect the echolocation calls of predatory bats. Here, combining empirical data and mathematical modelling, we show that moth hearing is adapted to provide information about the threat posed by different sympatric bat species. First, we found that multiple characteristics related to the threat posed by bats to moths correlate with bat echolocation call frequency. Second, the frequency tuning of the most sensitive auditory receptor in noctuid moth ears provides information allowing moths to escape detection by all sympatric bats with similar safety margin distances. Third, the least sensitive auditory receptor usually responds to bat echolocation calls at a similar distance across all moth species for a given bat species. If this neuron triggers last-ditch evasive flight, it suggests that there is an ideal reaction distance for each bat species, regardless of moth size. This study shows that even a very simple sensory system can adapt to deliver information suitable for triggering appropriate defensive reactions to each predator in a multiple predator community.

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

2021 ◽  
Author(s):  
Jan Clemens ◽  
Mala Murthy
Keyword(s):  
Frequency Tuning ◽  
Stimulus Change ◽  
Sensory System ◽  
Computational Modelling ◽  
Courtship Song ◽  
Highly Nonlinear ◽  
Divisive Normalization ◽  
Auditory Receptor ◽  
Receptor Neurons ◽  
Band Limited

Sensory neurons encode information using multiple nonlinear and dynamical transformations. For instance, auditory receptor neurons in Drosophila adapt to the mean and the intensity of the stimulus, change their frequency tuning with sound intensity, and employ a quadratic nonlinearity. While these computations are considered advantageous in isolation, their combination can lead to a highly ambiguous and complex code that is hard to decode. Combining electrophysiological recordings and computational modelling, we investigate how the different computations found in auditory receptor neurons in Drosophila combine to encode behaviorally-relevant acoustic signals like the courtship song. The computational model consists of a quadratic filter followed by a divisive normalization stage and reproduces population neural responses to artificial and natural sounds. For general classes of sounds, like band-limited noise, the representation resulting from these highly nonlinear computations is highly ambiguous and does not allow for a recovery of information about the frequency content and amplitude pattern. However, for courtship song, the code is simple and efficient: The quadratic filter improves the representation of the song envelope while preserving information about the song's fine structure across intensities. Divisive normalization renders the presentation of the song envelope robust to the relatively slow fluctuations in intensity that arise during social interactions, while preserving information about the species-specific fast fluctuations of the envelope. Overall, we demonstrate how a sensory system can benefit from adaptive and nonlinear computations while minimizing concomitant costs arising from ambiguity and complexity of readouts by adapting the code for behaviorally-relevant signals.

scholarly journals Neurophysiology goes wild: from exploring sensory coding in sound proof rooms to natural environments

2021 ◽  
Vol 207 (3) ◽  
pp. 303-319
Author(s):  
Heiner Römer
Keyword(s):  
Sensory System ◽  
Sensory Systems ◽  
Natural Environments ◽  
Sensory Coding ◽  
Noise Levels ◽  
Sensory Physiology ◽  
Sound Localisation ◽  
Physical Environments ◽  
History Of ◽  
Adaptive Behaviours

AbstractTo perform adaptive behaviours, animals have to establish a representation of the physical “outside” world. How these representations are created by sensory systems is a central issue in sensory physiology. This review addresses the history of experimental approaches toward ideas about sensory coding, using the relatively simple auditory system of acoustic insects. I will discuss the empirical evidence in support of Barlow’s “efficient coding hypothesis”, which argues that the coding properties of neurons undergo specific adaptations that allow insects to detect biologically important acoustic stimuli. This hypothesis opposes the view that the sensory systems of receivers are biased as a result of their phylogeny, which finally determine whether a sound stimulus elicits a behavioural response. Acoustic signals are often transmitted over considerable distances in complex physical environments with high noise levels, resulting in degradation of the temporal pattern of stimuli, unpredictable attenuation, reduced signal-to-noise levels, and degradation of cues used for sound localisation. Thus, a more naturalistic view of sensory coding must be taken, since the signals as broadcast by signallers are rarely equivalent to the effective stimuli encoded by the sensory system of receivers. The consequences of the environmental conditions for sensory coding are discussed.

scholarly journals Towards Using the Instrumented Timed Up-and-Go Test for Screening of Sensory System Performance for Balance Control in Older Adults

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 622 ◽  
Author(s):  
Thomas Gerhardy ◽  
Katharina Gordt ◽  
Carl-Philipp Jansen ◽  
Michael Schwenk
Keyword(s):  
Older Adults ◽  
System Performance ◽  
Fall Risk ◽  
Balance Control ◽  
Sensory System ◽  
Sensory Systems ◽  
Community Dwelling ◽  
Functional Mobility ◽  
Timed Up And Go ◽  
Community Dwelling Older Adults

Background: Decreasing performance of the sensory systems’ for balance control, including the visual, somatosensory and vestibular system, is associated with increased fall risk in older adults. A smartphone-based version of the Timed Up-and-Go (mTUG) may allow screening sensory balance impairments through mTUG subphases. The association between mTUG subphases and sensory system performance is examined. Methods: Functional mobility of forty-one community-dwelling older adults (>55 years) was measured using a validated mTUG. Duration of mTUG and its subphases ‘sit-to-walk’, ‘walking’, ‘turning’, ‘turn-to-sit’ and ‘sit-down’ were extracted. Sensory systems’ performance was quantified by validated posturography during standing (30 s) under different conditions. Visual, somatosensory and vestibular control ratios (CR) were calculated from posturography and correlated with mTUG subphases. Results: Vestibular CR correlated with mTUG total time (r = 0.54; p < 0.01), subphases ‘walking’ (r = 0.56; p < 0.01), and ‘turning’ (r = 0.43; p = 0.01). Somatosensory CR correlated with mTUG total time (r = 0.52; p = 0.01), subphases ‘walking’ (r = 0.52; p < 0.01) and ‘turning’ (r = 0.44; p < 0.01). Conclusions: Supporting the proposed approach, results indicate an association between specific mTUG subphases and sensory system performance. mTUG subphases ‘walking’ and ‘turning’ may allow screening for sensory system deterioration. This is a first step towards an objective, detailed and expeditious balance control assessment, however needing validation in a larger study.

General Principles for Sensory Coding

2018 ◽  
Author(s):  
Tatyana O. Sharpee
Keyword(s):  
Sensory System ◽  
Sensory Systems ◽  
Multiple Delays ◽  
Minimal Amount ◽  
Sensory Coding ◽  
Trade Offs ◽  
Almost All ◽  
Comprehensive Framework ◽  
State Of The Environment ◽  
The Impact

Sensory systems exist to provide an organism with information about the state of the environment that can be used to guide future actions and decisions. Remarkably, two conceptually simple yet general theorems from information theory can be used to evaluate the performance of any sensory system. One theorem states that there is a minimal amount of energy that an organism has to spend in order to capture a given amount of information about the environment. The second theorem states that the maximum rate with which the organism can acquire resources from the environment, relative to its competitors, is limited by the information this organism collects about the environment, also relative to its competitors. These two theorems provide a scaffold for formulating and testing general principles of sensory coding but leave unanswered many important practical questions of implementation in neural circuits. These implementation questions have guided thinking in entire subfields of sensory neuroscience, and include: What features in the sensory environment should be measured? Given that we make decisions on a variety of time scales, how should one solve trade-offs between making simpler measurements to guide minimal decisions vs. more elaborate sensory systems that have to overcome multiple delays between sensation and action. Once we agree on the types of features that are important to represent, how should they be represented? How should resources be allocated between different stages of processing, and where is the impact of noise most damaging? Finally, one should consider trade-offs between implementing a fixed strategy vs. an adaptive scheme that readjusts resources based on current needs. Where adaptation is considered, under what conditions does it become optimal to switch strategies? Research over the past 60 years has provided answers to almost all of these questions but primarily in early sensory systems. Joining these answers into a comprehensive framework is a challenge that will help us understand who we are and how we can make better use of limited natural resources.

scholarly journals An Artificial Vibrissa-Like Sensor for Detection of Flows

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 3892
Author(s):  
Moritz Scharff ◽  
Philipp Schorr ◽  
Tatiana Becker ◽  
Christian Resagk ◽  
Jorge H. Alencastre Miranda ◽  
...  
Keyword(s):  
Compressible Flow ◽  
Surface Texture ◽  
Large Deflection ◽  
Sensory System ◽  
Flow Characteristics ◽  
Elastic Beam ◽  
Sensory Systems ◽  
Tactile Sensors ◽  
Complex Receptor ◽  
Simulation And Experiment

In nature, there are several examples of sophisticated sensory systems to sense flows, e.g., the vibrissae of mammals. Seals can detect the flow of their prey, and rats are able to perceive the flow of surrounding air. The vibrissae are arranged around muzzle of an animal. A vibrissa consists of two major components: a shaft (infector) and a follicle–sinus complex (receptor), whereby the base of the shaft is supported by the follicle-sinus complex. The vibrissa shaft collects and transmits stimuli, e.g., flows, while the follicle-sinus complex transduces them for further processing. Beside detecting flows, the animals can also recognize the size of an object or determine the surface texture. Here, the combination of these functionalities in a single sensory system serves as paragon for artificial tactile sensors. The detection of flows becomes important regarding the measurement of flow characteristics, e.g., velocity, as well as the influence of the sensor during the scanning of objects. These aspects are closely related to each other, but, how can the characteristics of flow be represented by the signals at the base of a vibrissa shaft or by an artificial vibrissa-like sensor respectively? In this work, the structure of a natural vibrissa shaft is simplified to a slender, cylindrical/tapered elastic beam. The model is analyzed in simulation and experiment in order to identify the necessary observables to evaluate flows based on the quasi-static large deflection of the sensor shaft inside a steady, non-uniform, laminar, in-compressible flow.

scholarly journals Organizational sensory systems of Polish enterprises in the context of cooperative relationships

Management ◽  
2019 ◽  
Vol 23 (1) ◽  
pp. 50-60
Author(s):  
Michał Chomicki
Keyword(s):  
Sensory System ◽  
Sensory Systems ◽  
Economic Environment ◽  
Independence Tests ◽  
Cooperative Relationships ◽  
Theoretical Part ◽  
Chi Squared ◽  
The Relationship

Summary The aim of this paper is to indicate the relationship between the shape of organizational sensory systems of Polish companies and beneficialness of the shape of cooperative relations between these companies with particular kinds of cooperators. The theoretical part of this article was devoted to the identification of the role of cooperative relations in the contemporary economic environment and a brief description of the concept of organizational sensory system, including its influence on cooperation between companies. The survey used the respondents’ indications of frequency of monitoring of elements of organization and its environment and the indication of the beneficialness of the shape of cooperative relationships with suppliers, customers and co-opetitors (in the framework of coopetitive relations). The chi-squared independence tests were used to demonstrate dependencies. In conclusion, it turned out that there are only two statistically significant relations and both of them pertain to relationships with customers.

scholarly journals Complete neuroanatomy and sensor maps of Odonata wings for fly-by-feel flight control

2021 ◽  
Author(s):  
Joseph Fabian ◽  
Igor Siwanowicz ◽  
Myriam Uhrhan ◽  
Masateru Maeda ◽  
Richard Bomphrey ◽  
...  
Keyword(s):  
State Estimation ◽  
Flight Control ◽  
Sensory System ◽  
Distribution Patterns ◽  
Element Model ◽  
Sensory Systems ◽  
The Body ◽  
Dynamic State ◽  
Dynamic Strain ◽  
Wing Model

Fly-by-feel describes how flying animals capture aerodynamic information via their wings' sensory system to implement or enhance flight control. Traditional studies on animal flight emphasized controlling body stability via visual or inertial sensory inputs. In line with this, it has been demonstrated that wing sensory systems can provide inertial state estimation for the body. What about the state estimation of the wings themselves? Little is known about how flying animals utilize their wing sensory systems to monitor the dynamic state of their highly deformable wings. This study is a step toward a comprehensive investigation of how a flying animal senses aerodynamic and aeroelastic features of the wings relevant to flight control. Odonates: dragonflies and damselflies, are a great model for this because they have excellent flight performance and their wing structure has been extensively studied. Here, we developed a strategy to map the entire sensory system of Odonata wings via confocal microscopy. The result is the first complete map of a flying animal's wing sensory system, including both the external sensor morphologies and internal neuroanatomy. This complete search revealed over 750 sensors on each wing for one of the smallest dragonfly species and roughly half for a comparable size damselfly. We found over eight morphological classes of sensors, most of which resembled mechanosensors. Most sensors were innervated by a single neuron with an innervation pattern consistent with minimising wiring length. We further mapped the major veins of 13 Odonate species across 10 families and identified consistent sensor distribution patterns, with sensor count scaling with wing length. To explain the strain sensor density distribution along the major veins, we constructed a high-fidelity finite element model of a dragonfly wing based on micro-CT data. This flapping wing model revealed dynamic strain fields and suggested how increasing sensor count could allow encoding of different wing states. Taken together, the Odonate wing sensory system is well-equipped to implement sophisticated fly-by-feel flight control.

scholarly journals Encoding frequency contrast in primate auditory cortex

2014 ◽  
Vol 111 (11) ◽  
pp. 2244-2263 ◽  
Author(s):  
Brian J. Malone ◽  
Brian H. Scott ◽  
Malcolm N. Semple
Keyword(s):  
Auditory Cortex ◽  
Frequency Modulation ◽  
Carrier Frequency ◽  
Temporal Dynamics ◽  
Frequency Tuning ◽  
Modulation Depth ◽  
Average Rate ◽  
Spike Timing ◽  
Neural Representation ◽  
Response Dynamics

Changes in amplitude and frequency jointly determine much of the communicative significance of complex acoustic signals, including human speech. We have previously described responses of neurons in the core auditory cortex of awake rhesus macaques to sinusoidal amplitude modulation (SAM) signals. Here we report a complementary study of sinusoidal frequency modulation (SFM) in the same neurons. Responses to SFM were analogous to SAM responses in that changes in multiple parameters defining SFM stimuli (e.g., modulation frequency, modulation depth, carrier frequency) were robustly encoded in the temporal dynamics of the spike trains. For example, changes in the carrier frequency produced highly reproducible changes in shapes of the modulation period histogram, consistent with the notion that the instantaneous probability of discharge mirrors the moment-by-moment spectrum at low modulation rates. The upper limit for phase locking was similar across SAM and SFM within neurons, suggesting shared biophysical constraints on temporal processing. Using spike train classification methods, we found that neural thresholds for modulation depth discrimination are typically far lower than would be predicted from frequency tuning to static tones. This “dynamic hyperacuity” suggests a substantial central enhancement of the neural representation of frequency changes relative to the auditory periphery. Spike timing information was superior to average rate information when discriminating among SFM signals, and even when discriminating among static tones varying in frequency. This finding held even when differences in total spike count across stimuli were normalized, indicating both the primacy and generality of temporal response dynamics in cortical auditory processing.

scholarly journals Non-visual crypsis: a review of the empirical evidence for camouflage to senses other than vision

2008 ◽  
Vol 364 (1516) ◽  
pp. 549-557 ◽  
Author(s):  
Graeme D Ruxton
Keyword(s):  
Predation Risk ◽  
Empirical Evidence ◽  
Sensory System ◽  
Sensory Perception ◽  
Sensory Systems ◽  
Conclusive Evidence ◽  
Chemical Camouflage ◽  
Background Matching

I review the evidence that organisms have adaptations that confer difficulty of detection by predators and parasites that seek their targets primarily using sensory systems other than vision. In other words, I will answer the question of whether crypsis is a concept that can usefully be applied to non-visual sensory perception. Probably because vision is such an important sensory system in humans, research in this field is sparse. Thus, at present we have very few examples of chemical camouflage, and even these contain some ambiguity in deciding whether they are best seen as examples of background matching or mimicry. There are many examples of organisms that are adaptively silent at times or in locations when or where predation risk is higher or in response to detection of a predator. By contrast, evidence that the form (rather than use) of vocalizations and other sound-based signals has been influenced by issues of reducing detectability to unintended receivers is suggestive rather than conclusive. There is again suggestive but not completely conclusive evidence for crypsis against electro-sensing predators. Lastly, mechanoreception is highly understudied in this regard, but there are scattered reports that strongly suggest that some species can be thought of as being adapted to be cryptic in this modality. Hence, I conclude that crypsis is a concept that can usefully be applied to senses other than vision, and that this is a field very much worthy of more investigation.

scholarly journals Neural representation of spectral and temporal information in speech

2007 ◽  
Vol 363 (1493) ◽  
pp. 923-945 ◽  
Author(s):  
Eric D Young
Keyword(s):  
Neural Coding ◽  
Frequency Tuning ◽  
Neural Representation ◽  
Complex Sounds ◽  
Sound Levels ◽  
Language Communication ◽  
Frequency Components ◽  
The Central Nervous System ◽  
Stimulus Features ◽  
Central Auditory Neurons

Speech is the most interesting and one of the most complex sounds dealt with by the auditory system. The neural representation of speech needs to capture those features of the signal on which the brain depends in language communication. Here we describe the representation of speech in the auditory nerve and in a few sites in the central nervous system from the perspective of the neural coding of important aspects of the signal. The representation is tonotopic, meaning that the speech signal is decomposed by frequency and different frequency components are represented in different populations of neurons. Essential to the representation are the properties of frequency tuning and nonlinear suppression. Tuning creates the decomposition of the signal by frequency, and nonlinear suppression is essential for maintaining the representation across sound levels. The representation changes in central auditory neurons by becoming more robust against changes in stimulus intensity and more transient. However, it is probable that the form of the representation at the auditory cortex is fundamentally different from that at lower levels, in that stimulus features other than the distribution of energy across frequency are analysed.

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