Biology subjects

Delhaye, B. P.

Publications and source records attributed to Delhaye, B. P..

9 recordsLinked to original sources

bioRxiv2026

Interaction forces reflect the perception of texture during active exploration

AO_SCPLOWBSTRACTC_SCPLOWWe are constantly exploring the world around us through touch. Active touch depends on coordination of movement and force, yet the forces used during natural exploration and their relationship with perception is largely unexplored. Here we measured exploration forces together with fingertip motion while 17 participants explored 14 textures and rated their perceived hardness, slipperiness, or roughness. Exploration strategies differed systematically across tasks: hardness judgments involved relatively stationary pressing with larger and more variable normal forces, whereas slipperiness and roughness judgments relied more on sweeping movements. Within tasks, interaction forces covaried with perceptual ratings: harder textures elicited larger maximum tangential forces, consistent with diagonal pressing, while more slippery textures were explored with faster fingertip motion and lower forces. Estimated dynamic friction was negatively correlated with perceived slipperiness but not roughness. At the same time perceived roughness was strongly related to vibrations in the force, indicating distinct physical bases for these perceptual dimensions. These results show that humans actively tailor contact mechanics to perceptual goals during active exploration, supporting a sensorimotor account of texture perception. SO_SCPLOWIGNIFICANCEC_SCPLOWO_SCPCAP C_SCPCAPO_SCPLOWSTATEMENTC_SCPLOWTouch is usually studied as if the skin passively receives information, but in everyday life we actively move and press against objects to recognize them and learn what they feel like. This study measured both fingertip motion and contact forces while people freely explored textures and judged hardness, slipperiness, and roughness - the three of the most salient dimensions of tactile experience. The results show that people adjust how they move and press depending on what they want to perceive, and that different physical signals - friction and vibration - support different texture judgments. This work helps explain touch as an active sensorimotor process, with implications for neuroscience, haptics, robotics, and neuroprosthetics.

neuroscience↗

bioRxiv2026

Whole-fingertip 3D Skin Surface Deformation under Tangential Loading

AO_SCPLOWBSTRACTC_SCPLOWDuring tactile interaction, skin deformation drives the widespread activation of tactile afferents distributed across the fingertip. Yet the full spatial extent and evolution of these deformations remain largely unquantified. Using high-resolution 3D imaging, we reconstructed the complete volar surface of the fingertip under progressive tangential loadings typical of object manipulation. We show that much of the deformation occurs in the out-of-contact regions, accounting for approximately 70% of the total deformation energy. This deformation consistently initiates in the peripheral zones and smoothly propagates inward as partial slip develops. Tangential loading also induces pronounced directional asymmetries and local curvature changes, reflecting both surface and bulk tissue deformation. Furthermore, we observe localized strain patterns consistent with skin wrinkling across all participants, with individual variations in intensity and location driven by distinct frictional and biomechanical properties. This dataset provides a strong foundation for developing highly accurate biomechanical models and for linking fingertip mechanics to tactile neural encoding.

neuroscience↗

bioRxiv2026

Collagen Shapes Fingertip Surface Strains during Normal Loading

When making contact, fingertip mechanoreceptors respond to the skin deformation, and provide essential information for tactile perception and object manipulation. Since subsurface measurements remain challenging, strains close to the receptors are commonly estimated using numerical models. Here, we present a biomechanical finite element model simulating fingertip normal loading against a flat plate. Several model variants are designed to isolate the role of tissue heterogeneity and collagen-induced anisotropy. Their predictions are compared to experimental data of fingertip surface strains obtained with 3-D stereo imaging. By varying the stiffness contrast and fiber orientation, we demonstrate that incorporating collagen anisotropy is required to reproduce strain localization at the contact edge while maintaining realistic global shape changes. In particular, fibers aligned parallel to the skin surface induce local skin thickening and a pronounced radial expansion beneath the contact edge, affecting mechanoreceptors. This observation suggests a collagen-mediated contribution to the deep transmission of mechanical stimuli. These results highlight collagen architecture as a key determinant of fingertip mechanics and underscore its importance for accurate modeling of tactile interactions.

bioengineering↗

bioRxiv2025

3-D Reconstruction of Fingertip Deformation during Contact Initiation

Dexterous manipulations rely on tactile feedback from the fingertips, which provides crucial information about contact events, object geometry, interaction forces, friction, and more. Accurately measuring skin deformations during tactile interactions can shed light on the mechanics behind such feedback. To address this, we developed a novel setup using 3-D digital image correlation (DIC) to both reconstruct the bulk deformation and local surface skin deformation of the fingertip under natural loading conditions. Here, we studied the local spatiotemporal evolution of the skin surface during contact initiation. We showed that, as soon as contact occurs, the skin surface deforms very rapidly and exhibits high compliance at low forces (<0.05 N). As loading and thus the contact area increases, a localized deformation front forms just ahead of the moving contact boundary. Consequently, substantial deformation extending beyond the contact interface was observed, with maximal amplitudes ranging from 5% to 10% at 5 N, close to the border of the contact. Furthermore, we found that friction influences the partial slip caused by these deformations during contact initiation, as previously suggested. Our setup provides a powerful tool to get new insights into the mechanics of touch and opens avenues for a deeper understanding of tactile afferent encoding.

neuroscience↗

bioRxiv2023

Sub-surface deformation of individual fingerprint ridges during tactile interactions

The human fingertip can detect small tactile features with a spatial acuity roughly the width of a fingerprint ridge. However, how individual ridges deform under contact to support accurate and high-precision tactile feedback is currently unknown. The complex mechanical structure of the glabrous skin, composed of multiple layers and intricate morphology within which mechanoreceptors are embedded, makes this question challenging. Here, we used optical coherence tomography to image and track sub-surface deformations of hundreds of individual fingerprint ridges across ten participants and four individual contact events at high spatial resolution in vivo. We calculated strain patterns in both the stratum corneum and viable epidermis in response to a variety of passively-applied tactile stimuli, including static indentation, stick-to-slip events, sliding of a flat surface in different directions, and interaction with small tactile features, such as edges and grooves. We found that ridges could stretch, compress, and undergo considerable shearing orthogonal to the skin surface, but there was limited horizontal shear. Therefore, it appears that the primary components of ridge deformation and, potentially, neural responses are deformations of the ridge flanks and their relative movement, rather than overall bending of the ridges themselves. We conclude that the local distribution of mechanoreceptors across the ridges might be ideally suited to extract the resulting strain gradients and that the fingertip skin may possess a higher mechanical spatial resolution than that of a single ridge.

neuroscience↗

bioRxiv2022

Biomechanics of Finger Pad Response under Torsion

Surface skin deformation of the finger pad during partial slippage at finger-object interfaces elicits tactile feedback. During object manipulation, torque is often present, which can cause partial slippage. Until now, studies of surface skin deformation have used stimuli sliding on rectilinear tangential trajectories. Here we studied surface skin dynamics under torsion. A custom robotic platform stimulated the finger pad with a flat transparent surface, controlling the normal forces and rotation speeds applied while monitoring the contact interface using optical imaging. We observed the characteristic pattern by which partial slips develop, starting at the periphery of the contact and propagating towards its centre, and the resulting surface strains. The 20-fold range of normal forces and angular velocities used highlights the effect of those parameters on the resulting torque and skin strains. While normal force increases the contact area, generated torque, strains, and twist angle required to reach full slip, angular velocity increases loss of contact at the periphery and strain rates (although not total strains). We also discuss the surprisingly large inter-individual variability in skin biomechanics, notably observed in the twist angle the stimulus needed to rotate before reaching full slip.

neuroscience↗

bioRxiv2021

Measuring fingerpad deformation during active object manipulation

AO_SCPLOWBSTRACTC_SCPLOWDuring active object manipulation, the finger-object interactions give rise to complex fingertip skin deformations. These deformations are in turn encoded by the local tactile afferents and provide rich and behaviorally relevant information to the central nervous system. Most of the work studying the mechanical response of the finger to dynamic loading has been performed under a passive setup, thereby precisely controlling the kinematics or the dynamics of the loading. However, to identify aspects of the deformations that are relevant to online control during object manipulation, it is desirable to measure the skin response in an active setup. To that end, we developed a device that allows us to monitor finger forces, skin deformations, and kinematics during fine manipulation. We describe the device in detail and test it to precisely describe how the fingertip skin in contact with the object deforms during a simple vertical oscillation task. We show that the level of grip force directly influences the fingerpad skin strains and that the strain rates are substantial during active manipulation (norm up to 100%/s). The developed setup will enable us to causally relate sensory information, i.e. skin deformation, to online control, i.e. grip force adjustment, in future studies.

neuroscience↗

bioRxiv2021

Fast grip force adaptation to friction relies on localized fingerpad strains

AO_SCPLOWBSTRACTC_SCPLOWHumans can quickly adjust their grip force to a change in friction at the object-skin interface during dexterous manipulation in a precision grip. To perform this adjustment, they rely on the feedback of the mechanoreceptive afferents innervating the fingertip skin. Because these tactile afferents encode information related to skin deformation, the nature of the feedback signaling a change in friction must somehow originate from a difference in the way the skin deforms when manipulating objects of different frictions. To better characterize the origin of the underlying sensory events, we asked human participants to perform a grip-lifting task with a manipulandum equipped with an optical imaging system. This system enabled to monitor fingertip skin strains through transparent plates of glass that had different levels of friction. We observed that, following an unexpected change in friction, participants adapted their grip force within 370ms after contact with the surface. By comparing the deformation patterns when unexpectedly switching from a high to a low friction condition, we found a significant increase in skin deformation inside the contact area arising over 100ms before the motor response, during the loading phase, suggesting that local and partial deformation patterns prior to lift-off are used in the nervous system to adjust the grip force as a function of the frictional condition.

neuroscience↗

bioRxiv2018

Rapid Geometric Feature Signaling In The Spiking Activity Of A Complete Population Of Tactile Nerve Fibers

Tactile feature extraction is essential to guide the dexterous manipulation of objects. The longstanding theory is that geometric features at each location of contact between hand and object are extracted from the spatial layout of the response of populations of tactile nerve fibers. However, recent evidence suggests that some features (edge orientation, e.g.) are extracted very rapidly (<200ms), casting doubt that this information relies on a spatial code, which ostensibly requires integrating responses over time. An alternative hypothesis is that orientation is conveyed in precise temporal spiking patterns. Here, we simulate, using a recently developed and validated model, the responses of tactile fibers from the entire human fingertip ([~]800 afferents) to edges indented into the skin. We show that edge orientation can be quickly (<50 ms) and accurately (<3{degrees}) decoded from the spatial pattern of activation across the afferent population, starting with the very first spike. Next, we implement a biomimetic decoder of edge orientation, consisting of a bank of oriented Gabor filters, designed to mimic the documented responses of cortical neurons. We find that the biomimetic approach leads to orientation decoding performance that approaches the limit set by optimal decoders and is actually more robust to changes in other stimulus features. Finally, we show that orientation signals, measured from single units in non-human primate cortex (2 macaque monkeys, 1 female), follow a time course consistent with that of their counterparts in the nerve. We conclude that a spatial code is fast and accurate enough to support object manipulation.

neuroscience↗