Article

Texture-induced vibrations in the forearm during tactile exploration

Institute of Neuroscience, Université Catholique de Louvain Brussels, Belgium.
Frontiers in Behavioral Neuroscience (Impact Factor: 3.27). 07/2012; 6:37. DOI: 10.3389/fnbeh.2012.00037
Source: PubMed

ABSTRACT

Humans can detect and discriminate between fine variations of surface roughness using active touch. It is hitherto believed that roughness perception is mediated mostly by cutaneous and subcutaneous afferents located in the fingertips. However, recent findings have shown that following abolishment of cutaneous afferences resulting from trauma or pharmacological intervention, the ability of subjects to discriminate between textures roughness was not significantly altered. These findings suggest that the somatosensory system is able to collect textural information from other sources than fingertip afference. It follows that signals resulting of the interaction of a finger with a rough surface must be transmitted to stimulate receptor populations in regions far away from the contact. This transmission was characterized by measuring in the wrist vibrations originating at the fingertip and thus propagating through the finger, the hand and the wrist during active exploration of textured surfaces. The spectral analysis of the vibrations taking place in the forearm tissues revealed regularities that were correlated with the scanned surface and the speed of exploration. In the case of periodic textures, the vibration signal contained a fundamental frequency component corresponding to the finger velocity divided by the spatial period of the stimulus. This regularity was found for a wide range of textural length scales and scanning velocities. For non-periodic textures, the spectrum of the vibration did not contain obvious features that would enable discrimination between the different stimuli. However, for both periodic and non-periodic stimuli, the intensity of the vibrations could be related to the microgeometry of the scanned surfaces.

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Available from: Jean-Louis Thonnard
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    • "To test whether our fitted and optimized filters might be an artifact of our approach rather than reflect the integration properties of S1 neurons, we also optimized filters on a distorted data set. During natural interaction with surfaces, the amplitude of elicited vibrations decreases as their frequency increases, leading to roughly a power–law relationship (Manfredi et al., 2014; Wiertlewski et al., 2011; Delhaye et al., 2012). When we re-optimized the filters to stimuli with a distorted frequency composition, we found that the resulting filters did not match the ones observed in cortex (green bars inFigure 5B–D): The PC signal was weighted more heavily, was integrated over longer timescales, and was mostly excitatory, in contrast to what we observed in both the cortical filters and the ones optimized on our natural texture data set. "
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    ABSTRACT: The sense of touch comprises multiple sensory channels that each convey characteristic signals during interactions with objects. These neural signals must then be integrated in such a way that behaviorally relevant information about the objects is preserved. To understand this integration process, we implement a simple computational model that describes how the responses of neurons in somatosensory cortex - recorded from awake, behaving monkeys - are shaped by the peripheral input, reconstructed using simulations of neuronal populations that reproduce natural spiking responses in the nerve with millisecond precision. First, we find that the strength of cortical responses is driven by one population of nerve fibers (rapidly adapting) whereas the timing of cortical responses is shaped by another (Pacinian). Second, we show that input from these sensory channels is integrated in an optimal fashion that exploits the disparate response behaviors of the different fiber types.
    Full-text · Article · Dec 2015 · eLife Sciences
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    • "It is thought that this effect is mediated by the central nervous system, since imperceptible vibration applied to the wrist is unlikely to have reached the fingertip and increased the sensitivity of mechanoreceptors in the fingertip pad skin: Vibration loses more than 90% of its power as it travels 1–2 cm on the skin and approximately 99% of the power with a 6-cm travel due to the skin's viscoelastic properties (Manfredi et al. 2012). While suprathreshold vibration may travel between the fingertip and wrist and activate remote mechanoreceptors (Delhaye et al. 2012; Libouton et al. 2012), the likelihood of activating remote mechanoreceptors becomes slim with subthreshold vibration, especially when the vibrating probe is surrounded by a ring, thus blocking the spread of vibration (Verrillo 1962) in the previous studies (Enders et al. 2013; Hur et al. 2014; Lakshminarayanan et al. 2015). In addition, manipulating the distance between fingertip and vibration location (e.g., fingertip–palm vs. fingertip–forearm ) did not influence the results (Enders et al. 2013; Hur et al. 2014; Lakshminarayanan et al. 2015). "
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    ABSTRACT: Random vibration applied to skin can change the sense of touch. Specifically, low amplitude white-noise vibration can improve fingertip touch perception. In fact, fingertip touch sensation can improve even when imperceptible random vibration is applied to other remote upper extremity areas such as wrist, dorsum of the hand, or forearm. As such, vibration can be used to manipulate sensory feedback and improve dexterity, particularly during neurological rehabilitation. Nonetheless, the neurological bases for remote vibration enhanced sensory feedback are yet poorly understood. This study examined how imperceptible random vibration applied to the wrist changes cortical activity for fingertip sensation. We measured somatosensory evoked potentials to assess peak-to-peak response to light touch of the index fingertip with applied wrist vibration versus without. We observed increased peak-to-peak somatosensory evoked potentials with wrist vibration, especially with increased amplitude of the later component for the somatosensory, motor, and premotor cortex with wrist vibration. These findings corroborate an enhanced cortical-level sensory response motivated by vibration. It is possible that the cortical modulation observed here is the result of the establishment of transient networks for improved perception.
    Preview · Article · Nov 2015
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    • " this study , we have only considered the strength and frequency composition of skin vibrations close to the location of contact with the texture on the fingertip . However , high - frequency skin vibrations elicited at the fingertip propagate the full length of the finger ( Manfredi et al . 2012 ) and have been recorded as far away as the wrist ( Delhaye et al . 2012 ) . Skin vibrations also decay in a frequency - dependent manner , a mechanism that , at least on the finger , amplifies frequencies in the PC response range ( Manfredi et al . 2012 ) . Given the exquisite sensitivity of PC fibers to high - frequency vibrations ( with thresholds below 1 ␮m around 250 Hz ) , texture - elicited vibrations"
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    ABSTRACT: Sensory systems are designed to extract behaviorally relevant information from the environment. In seeking to understand a sensory system, it is important to understand the environment within which it operates. In the present study, we seek to characterize the natural scenes of tactile texture perception. During tactile exploration, complex high-frequency vibrations are elicited in the fingertip skin, and these vibrations are thought to carry information about the surface texture of manipulated objects. How these texture-elicited vibrations depend on surface microgeometry and on the biomechanical properties of the fingertip skin itself remains to be elucidated. Here, we record skin vibrations, using a laser Doppler vibrometer, as various textured surfaces are scanned across the finger. We find that the frequency composition of elicited vibrations is texture-specific and highly repeatable. In fact, textures can be classified with high accuracy based on the vibrations they elicit in the skin. As might be expected, some aspects of surface microgeometry are directly reflected in the skin vibrations. However, texture vibrations are also determined in part by fingerprint geometry. This mechanism enhances textural features that are too small to be resolved spatially, given the limited spatial resolution of the neural signal. We conclude that it is impossible to understand the neural basis of texture perception without first characterizing the skin vibrations that drive neural responses, given the complex dependence of skin vibrations on both surface microgeometry and fingertip biomechanics.
    Full-text · Article · Feb 2014 · Journal of Neurophysiology
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