Mitra J. Z. Hartmann

Animal nervous systems must coordinate the sequence and timing of numerous muscles—a challenging control problem. The challenge is particularly acute for highly mobile sensing structures with many degrees of freedom, such as eyes, pinnae, hands, forepaws, and whiskers, because these low-mass, distal sensors require complex muscle coordination. This work examines how the geometry of the rat whisker array simplifies the coordination required for "whisking" behavior. 1 , 2 , 3 During whisking, 33 intrinsic ("sling") muscles are the primary drivers 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 of the rapid, rhythmic protractions of the large mystacial vibrissae (whiskers), which vary more than 6-fold in length and 3-fold in base diameter. 13 , 14 , 15 , 16 Although whisking is a rhythmic, centrally patterned behavior, 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 rodents can change the position, shape, and size of the whisker array, indicating considerable voluntary control. 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 To begin quantifying how the array's biomechanics contribute to whisking movements, we used three-dimensional anatomical reconstructions of follicle and sling-muscle geometry to simulate the movement resulting from uniform contraction of sling muscles across the array. This simulation provides a geometric baseline for whisker protraction when driven purely by intrinsic sling muscles. It does not isolate neural from biomechanical contributions but helps identify deviations that suggest active control. Simulations reveal that all follicles rotate through approximately equal angles, regardless of size. The maximum distance between whisker tips occurs at approximately 90% of resting muscle length, after which whisker tips converge and sensing resolution increases monotonically during protraction.

1. Summary Animal nervous systems must coordinate the sequence and timing of numerous muscles − a challenging control problem. The challenge is particularly acute for highly mobile sensing structures with many degrees of freedom, such as eyes, pinnae, hands, forepaws, and whiskers, because these low-mass, distal sensors require complex muscle coordination. This work examines how the geometry of the rat whisker array simplifies coordination required for “whisking” behavior 1-3 . During whisking, 33 intrinsic (“sling”) muscles are the primary drivers 4-12 of the rapid, rhythmic protractions of the large mystacial vibrissae (whiskers), which vary more than sixfold in length and threefold in base diameter 13-16 . Although whisking is a rhythmic, centrally-patterned behavior 17-24 , rodents can change the position, shape, and size of the whisker array, indicating considerable voluntary control 25-34 . To begin quantifying how the array’s biomechanics contribute to whisking movements, we used three-dimensional anatomical reconstructions of follicle and sling muscle geometry to simulate the movement resulting from a “uniform motor command,” defined as equal firing rates across all sling muscle motor neurons. This simulation provides a baseline profile of protraction under anatomically realistic but uniformly driven conditions. It does not isolate neural from biomechanical contributions but helps identify deviations that suggest active control. Simulations reveal that all follicles rotate through approximately equal angles, regardless of size. The angular fanning of the whiskers at their bases increases monotonically throughout protraction, while maximum distance between whisker tips occurs at approximately 90% of resting muscle length, after which whisker tips converge and sensing resolution increases monotonically.

Whiskers (vibrissae) are important tactile sensors for most mammals. We introduce a novel approach to quantitatively compare 3D geometry of whisker arrays across species with different whisker numbers and arrangements, focusing on harbor seals (Phoca vitulina), house mice (Mus musculus) and Norway rats (Rattus norvegicus). Whiskers of all three species decrease in arclength and increase in curvature from caudal to rostral. They emerge from the face with elevation angles that vary linearly with dorsoventral position, and with curvature orientations that vary diagonally as linear combinations of dorsoventral and rostrocaudal positions. In seals, this diagonal varies linearly with horizontal emergence angles, and is orthogonal to the diagonal for rats and mice. This work provides the first evidence for common elements of whisker arrangements across species in different mammalian orders. Placing the whisker array model on a CAD model of a seal head enables future mechanical studies of whisker-based sensing, including wake tracking.

[This corrects the article DOI: 10.1371/journal.pone.0194981.].

Abstract Whiskers (vibrissae) are important tactile sensors for most mammals. We introduce a novel approach to quantitatively compare 3D geometry of whisker arrays across species with different whisker numbers and arrangements, focusing on harbor seals ( Phoca vitulina ), house mice ( Mus musculus ) and Norway rats ( Rattus norvegicus ). Whiskers of all three species decrease in arclength and increase in curvature from caudal to rostral. They emerge from the face with elevation angles that vary linearly with dorsoventral position, and with curvature orientations that vary diagonally as linear combinations of dorsoventral and rostrocaudal positions. In seals, this diagonal varies linearly with horizontal emergence angles, and is orthogonal to the diagonal for rats and mice. This work provides the first evidence for common elements of whisker arrangements across species in different mammalian orders. Placing the equation-based whisker array on a CAD model of a seal head enables future mechanical studies of whisker-based sensing, including wake-tracking. SUMMARY STATEMENT We quantify the three-dimensional positions and orientations of the whiskers across the face of the harbor seal, and compare this geometry with the whisker arrays of rats and mice.

Understanding neural function requires quantification of the sensory signals that an animal's brain evolved to interpret. These signals in turn depend on the morphology and mechanics of the animal's sensory structures. Although the house mouse (Mus musculus) is one of the most common model species used in neuroscience, the spatial arrangement of its facial sensors has not yet been quantified. To address this gap, the present study quantifies the facial morphology of the mouse, with a particular focus on the geometry of its vibrissae (whiskers). The study develops equations that establish relationships between the three-dimensional (3D) locations of whisker basepoints, whisker geometry (arclength, curvature) and the 3D angles at which the whiskers emerge from the face. Additionally, the positions of facial sensory organs are quantified relative to bregma-lambda. Comparisons with the Norway rat (Rattus norvegicus) indicate that when normalized for head size, the whiskers of these two species have similar spacing density. The rostral-caudal distances between facial landmarks of the rat are a factor of ∼2.0 greater than the mouse, while the scale of bilateral distances is larger and more variable. We interpret these data to suggest that the larger size of rats compared with mice is a derived (apomorphic) trait. As rodents are increasingly important models in behavioral neuroscience, the morphological model developed here will help researchers generate naturalistic, multimodal patterns of stimulation for neurophysiological experiments and allow the generation of synthetic datasets and simulations to close the loop between brain, body and environment.

Whisker-based tactile sensors have the potential to perform fast and accurate 3D mappings of the environment, complementing vision-based methods under conditions of glare, reflection, proximity, and occlusion. However, current algorithms for mapping with whiskers make assumptions about the conditions of contact, and these assumptions are not always valid and can cause significant sensing errors. Here we introduce a new whisker sensing system with a tapered, flexible whisker. The system provides inputs to two separate algorithms for estimating radial contact distance on a whisker. Using a Gradient-Moment (GM) algorithm, we correctly detect contact distance in most cases (within 4% of the whisker length). We introduce the Z-Dissimilarity score as a new metric that quantifies uncertainty in the radial contact distance estimate using both the GM algorithm and a Moment-Force (MF) algorithm that exploits the tapered whisker design. Combining the two algorithms ultimately results in contact distance estimates more robust than either algorithm alone.

Facial vibrissae (whiskers) are thin, tapered, flexible, hair-like structures that are an important source of tactile sensory information for many species of mammals. In contrast to insect antennae, whiskers have no sensors along their lengths. Instead, when a whisker touches an object, the resulting deformation is transmitted to mechanoreceptors in a follicle at the whisker base. Previous work has shown that the mechanical signals transmitted along the whisker will depend strongly on the whisker's geometric parameters, specifically on its taper (how diameter varies with arc length) and on the way in which the whisker curves, often called "intrinsic curvature." Although previous studies have largely agreed on how to define taper, multiple methods have been used to quantify intrinsic curvature. The present work compares and contrasts different mathematical approaches towards quantifying this important parameter. We begin by reviewing and clarifying the definition of "intrinsic curvature," and then show results of fitting whisker shapes with several different functions, including polynomial, fractional exponent, elliptical, and Cesàro. Comparisons are performed across ten species of whiskered animals, ranging from rodents to pinnipeds. We conclude with a discussion of the advantages and disadvantages of using the various models for different modeling situations. The fractional exponent model offers an approach towards developing a species-specific parameter to characterize whisker shapes within a species. Constructing models of how the whisker curves is important for the creation of mechanical models of tactile sensory acquisition behaviors, for studies of comparative evolution, morphology, and anatomy, and for designing artificial systems that can begin to emulate the whisker-based tactile sensing of animals.