RESUMEN
The control of shape in active structures is a key problem for the realization of smart sensors and actuators, which often draw inspiration from natural systems. In this context, slender structures, such as thin plates, have been studied as a relevant example of shape morphing systems where curvature is generated by in-plane incompatibilities. In particular, in hydrogel plates these incompatibilities can be programmed at fabrication time, such that a target configuration is attained at equilibrium upon swelling or shrinking. While these aspects have been examined in detail, understanding the transient morphing of such active structures deserves further investigation. In this study, we develop a geometrical model for the transient shaping of thin hydrogel plates by extending the theory of non-Euclidean plates. We validate the proposed model using experiments on gel samples that are programmed to reach axisymmetric equilibrium shapes. Interestingly, our experiments show the emergence of non-axisymmetric shapes for early times, as a consequence of boundary layer effects induced by solvent transport. We rationalize these observations using numerical simulations based on a detailed poroelastic model. Overall, this work highlights the limitations of purely geometrical models and the importance of transient, reduced theories for morphing plates that account for the coupled physics driving the evolution of shape. Computational approaches employing these theories will allow to achieve accurate control on the morphing dynamics and ultimately advance 4D printing technologies.
RESUMEN
Visualization and tracking of the facial whiskers is critical to many studies of rodent behavior. High-speed videography is the most robust methodology for characterizing whisker kinematics, but whisker visualization is challenging due to the low contrast of the whisker against its background. Recently, we showed that fluorescent dye(s) can be applied to enhance visualization and tracking of whisker(s) ( Rigosa et al., 2017 ), and this protocol provides additional details on the technique.
RESUMEN
Visualization and tracking of the facial whiskers is required in an increasing number of rodent studies. Although many approaches have been employed, only high-speed videography has proven adequate for measuring whisker motion and deformation during interaction with an object. However, whisker visualization and tracking is challenging for multiple reasons, primary among them the low contrast of the whisker against its background. Here, we demonstrate a fluorescent dye method suitable for visualization of one or more rat whiskers. The process makes the dyed whisker(s) easily visible against a dark background. The coloring does not influence the behavioral performance of rats trained on a vibrissal vibrotactile discrimination task, nor does it affect the whiskers' mechanical properties.
Asunto(s)
Colorantes Fluorescentes/metabolismo , Imagen Óptica/métodos , Coloración y Etiquetado/métodos , Vibrisas/fisiología , Animales , Conducta Animal , RatasRESUMEN
A major challenge of sensory systems neuroscience is to quantify the brain activity underlying perceptual experiences and to explain this activity as the outcome of elemental neuronal response properties. One strategy is to measure variations in neuronal response in relation to controlled variations in an artificial stimulus. The limitation is that the stimuli scarcely resemble those which the sensory system has evolved to process-natural, behaviourally relevant stimuli. A more recent strategy is to measure neuronal responses during presentation of natural stimuli, but such experiments have failed to predict the observed responses according to the fundamental properties of neurons. In the work described here, we focus on tactile sensation in rats, and try to bridge the gap between neurons' responses to natural stimuli and their responses to controlled, artificial stimuli. We focus on texture, a submodality in which the rat whisker sensory system excels. Because the physical characteristics of texture stimuli have not yet been studied, the first set of experiments measures textures from the whiskers' point of view. The second set of experiments describes neurons' responses to textures. The third set of experiments computes kernels (estimates of the extracted stimulus features) of sensory neurons using white noise and then tries to account for natural texture responses according to these kernels. These investigations suggest ways of using natural stimuli to assemble a more complete picture of the neuronal basis of tactile sensation.
Asunto(s)
Neuronas Aferentes/metabolismo , Tacto/fisiología , Vibrisas/fisiología , Vías Aferentes/anatomía & histología , Vías Aferentes/fisiología , Animales , Conducta Animal/fisiología , Estimulación Física , Ratas , Propiedades de Superficie , Vibrisas/anatomía & histologíaRESUMEN
Rodents excel in making texture judgments by sweeping their whiskers across a surface. Here we aimed to identify the signals present in whisker vibrations that give rise to such fine sensory discriminations. First, we used sensors to capture vibration signals in metal whiskers during active whisking of an artificial system and in natural whiskers during whisking of rats in vivo. Then we developed a classification algorithm that successfully matched the vibration frequency spectra of single trials to the texture that induced it. For artificial whiskers, the algorithm correctly identified one texture of eight alternatives on 40% of trials; for in vivo natural whiskers, the algorithm correctly identified one texture of five alternatives on 80% of trials. Finally, we asked which were the key discriminative features of the vibration spectra. Under both artificial and natural conditions, the combination of two features accounted for most of the information: The modulation power-the power of the part of the whisker movement representing the modulation due to the texture surface-increased with the coarseness of the texture; the modulation centroid-a measure related to the center of gravity within the power spectrum-decreased with the coarseness of the texture. Indeed, restricting the signal to these two parameters led to performance three-fourths as high as the full spectra. Because earlier work showed that modulation power and centroid are directly related to neuronal responses in the whisker pathway, we conclude that the biological system optimally extracts vibration features to permit texture classification.
Asunto(s)
Potenciales de Acción/fisiología , Biomimética/métodos , Aprendizaje Discriminativo/fisiología , Mecanorreceptores/fisiología , Modelos Neurológicos , Tacto/fisiología , Vibrisas/fisiología , Vías Aferentes/fisiología , Animales , Biomimética/instrumentación , Simulación por Computador , Masculino , Movimiento/fisiología , Estimulación Física/instrumentación , Estimulación Física/métodos , Ratas , Ratas Wistar , Umbral Sensorial/fisiología , Percepción Espacial/fisiología , Propiedades de Superficie , VibraciónRESUMEN
A major challenge of sensory systems neuroscience is to quantify brain activity underlying perceptual experiences and to explain this activity as the outcome of elemental neuronal response properties. Rats make extremely fine discriminations of texture by "whisking" their vibrissae across an object's surface, yet the neuronal coding underlying texture sensations remains unknown. Measuring whisker vibrations during active whisking across surfaces, we found that each texture results in a unique "kinetic signature" defined by the temporal profile of whisker velocity. We presented these texture-induced vibrations as stimuli while recording responses of first-order sensory neurons and neurons in the whisker area of cerebral cortex. Each texture is encoded by a distinctive, temporally precise firing pattern. To look for the neuronal coding properties that give rise to texture-specific firing patterns, we delivered horizontal and vertical whisker movements that varied randomly in time ("white noise") and found that the response probabilities of first-order neurons and cortical neurons vary systematically according to whisker speed and direction. We applied the velocity-tuned spike probabilities derived from white noise to the sequence of velocity features in the texture to construct a simulated texture response. The close match between the simulated and real responses indicates that texture coding originates in the selectivity of neurons to elemental kinetic events.