Responses of Trigeminal Ganglion Neurons during Natural Whisking Behaviors in the Awake Rat

Leiser, Steven C.; Moxon, Karen A.

doi:10.1016/j.neuron.2006.10.036

Cited by 116 publications

(115 citation statements)

References 72 publications

(94 reference statements)

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“…It has been reported that rat free-whisking (i.e., with no contacts) generates a sensory signal [40], [41]. This signal is analogous to the self-generated signal observed in our whisking robot.…”

Section: Possible Neural Substrates Of a Contact Detection Scheme supporting

confidence: 79%

Adaptive Cancelation of Self-Generated Sensory Signals in a Whisking Robot

et al. 2010

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Article:Anderson, S.R., Pearson, M.J., Pipe, A. et ReuseUnless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. Abstract-Sensory signals are often caused by one's own active movements. This raises a problem of discriminating between selfgenerated sensory signals and signals generated by the external world. Such discrimination is of general importance for robotic systems, where operational robustness is dependent on the correct interpretation of sensory signals. Here, we investigate this problem in the context of a whiskered robot. The whisker sensory signal comprises two components: one due to contact with an object (externally generated) and another due to active movement of the whisker (self-generated). We propose a solution to this discrimination problem based on adaptive noise cancelation, where the robot learns to predict the sensory consequences of its own movements using an adaptive filter. The filter inputs (copy of motor commands) are transformed by Laguerre functions instead of the oftenused tapped-delay line, which reduces model order and, therefore, computational complexity. Results from a contact-detection task demonstrate that false positives are significantly reduced using the proposed scheme.Index Terms-Force and tactile sensing, internal model, learning and adaptive systems, neurorobotics, noise cancelation.

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Section: Possible Neural Substrates Of a Contact Detection Scheme supporting

confidence: 79%

Adaptive Cancelation of Self-Generated Sensory Signals in a Whisking Robot

et al. 2010

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“…At the present time, it is not clear from ganglion recordings whether these parameters can be measured independently [16,33]. In contrast, it seems more likely that the rat would be able to measure axial force (F x in figure 1c) independently of the bending moment [34].…”

Section: Methods For Radial Distance Determinationmentioning

confidence: 72%

Radial distance determination in the rat vibrissal system and the effects of Weber's law

Solomon

Hartmann

2011

Phil. Trans. R. Soc. B

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Rats rhythmically tap and brush their vibrissae (whiskers) against objects to tactually explore the environment. To extract a complex feature such as the contour of an object, the rat must at least implicitly estimate radial object distance, that is, the distance from the base of the vibrissa to the point of object contact. Radial object distance cannot be directly measured, however, because there are no mechanoreceptors along the vibrissa. Instead, the mechanical signals generated by the vibrissa's interaction with the environment must be transmitted to mechanoreceptors near the vibrissa base. The first part of this paper surveys the different mechanical methods by which the rat could determine radial object distance. Two novel methods are highlighted: one based on measurement of bending moment and axial force at the vibrissa base, and a second based on measurement of how far the vibrissa rotates beyond initial contact. The second part of the paper discusses the application of Weber's law to two methods for radial distance determination. In both cases, Weber's law predicts that the rat will have greatest sensing resolution close to the vibrissa tip. These predictions could be tested with behavioural experiments that measure the perceptual acuity of the rat.

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“…On the other hand, it has been shown that in rats sensory signals are generated by whisking movements. Specifically, a study by Leiser and Moxon reported that trigeminal ganglion cells of the rat fired during active whisking in air with no object contacts but were silent when the whiskers were at rest (Leiser and Moxon, 2007). The implication of this result is that whisker sensory signals may include self-generated artefacts during whisking.…”

Section: The Cerebellum Viewed As An Adaptive Filter and Forward Modelmentioning

confidence: 99%

“…The weights of the adaptive filter in the noise cancellation scheme (figure 6a) are adjusted by removing the correlations in the clean signal from the reference noise, implemented via the LMS rule. In the context of whisking, the self-generated noise is thought to be caused by the movement of the whisker, either by inertia of the whisker base in the follicle or the whisker musculature pressing and activating the mechanoreceptors (Leiser and Moxon, 2007). Ultimately, this activation is caused by the motor command to the whisker plant.…”

Section: The Cerebellum Viewed As An Adaptive Filter and Forward Modelmentioning

confidence: 99%

The Robot Vibrissal System: Understanding Mammalian Sensorimotor Co-ordination Through Biomimetics

Prescott

Mitchinson

Lepora

et al. 2015

Sensorimotor Integration in the Whisker System

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SummaryWe consider the problem of sensorimotor co-ordination in mammals through the lens of vibrissal touch, and via the methodology of embodied computational neuroscienceÑusing biomimetic robots to synthesize and investigate models of mammalian brain architecture. The chapter focuses on five major brain sub-systems and their likely role in vibrissal system functionÑsuperior colliculus, basal ganglia, somatosensory cortex, cerebellum, and hippocampus. With respect to each of these we demonstrate how embodied modelling has helped elucidate their likely function in the brain of awake behaving animals. We also demonstrate how the appropriate co-ordination of these sub-systems, with a model of brain architecture, can give rise to integrated behaviour in a life-like whiskered robot.

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Responses of Trigeminal Ganglion Neurons during Natural Whisking Behaviors in the Awake Rat

Cited by 116 publications

References 72 publications

Adaptive Cancelation of Self-Generated Sensory Signals in a Whisking Robot

Adaptive Cancelation of Self-Generated Sensory Signals in a Whisking Robot

Radial distance determination in the rat vibrissal system and the effects of Weber's law

The Robot Vibrissal System: Understanding Mammalian Sensorimotor Co-ordination Through Biomimetics

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