Whisker-based pre-neuronal and peripheral encoding of surface stickiness

Reviewer #1 (Public review):

Summary:

This study offers a careful and technically strong look at how surface stickiness changes whisker-surface interactions and how that information reaches peripheral sensory neurons. The authors use 3D whisker tracking to capture bending, twisting, rolling, and tip motion during contact with surfaces that differ in stickiness, coarseness, and position. They show that sticky surfaces, especially silicone, broaden the range of whisker deformation, produce stronger but less frequent stick-slip events, and change firing rates in some trigeminal ganglion neurons. Overall, the study is valuable because it goes beyond standard 2D tracking and shows that out-of-plane motion and roll are important for understanding how whiskers encode texture.

Strengths:

The study is technically strong and well motivated. Its main strength is the use of 3D whisker tracking to show that surface stickiness affects whisker deformation in ways that standard 2D tracking would miss, including torsion, roll, out-of-plane motion, and stick-slip dynamics. The authors also connect these mechanical effects to TG activity, providing evidence that stickiness information is available in peripheral sensory responses. Overall, the work expands the study of whisker-based texture sensing beyond coarseness and provides a richer biomechanical framework for understanding tactile encoding.

Weaknesses:

The main weakness is that stickiness is not formally defined early in the manuscript, even though it is the central experimental variable. Several methodological choices also need clearer justification or validation, including the use of 2D measures as comparators for torsion and roll, the thresholds used for stick-slip detection, the degree-5 polynomial fit, the reference ROI, and aspects of the 3D surface reconstruction. The neural evidence should also be interpreted cautiously because the TG sample is small, only a subset of units discriminated silicone, and the correlation between strain sensitivity and silicone discrimination is suggestive rather than definitive.

Reviewer #2 (Public review):

The authors explore the sensation of stickiness from the point of view of whisker exploration and encoding in the trigeminal ganglion. In doing so, they develop methods for 3D whisker tracking to describe stick-specific parameters such as stick-slip rates and strain. Overall, the methods are strong, and the authors present the results appropriately. Overall, I think exploration of the sensation of stickiness is a great question.

My main criticism is in relation to the chosen stimuli, and I wonder whether the authors may have room to explore more naturally sticky materials and what this may mean for the animal.

(1) Chosen stimuli for stickiness:

Four different materials are used, with the aim of presenting animals with graded measures of stickiness. The results show that silicone stands out against the others; it's less clear whether the intermediate textures (Delrin and resin) may be truly intermediate in stickiness.

I wonder if the stimuli chosen were truly representative of the aim of providing a gradient of stickiness. Did the materials differ in other features, such as surface temperature, texture, etc., which could explain some results? The authors discuss this in terms of coefficients of friction and how these estimates are not quantified in relation to whiskers themselves.

Measures of stick-slip and strain with silicone vs other materials make intuitive sense. Could the authors add additional naturally sticky stimuli to exemplify the results? For example, adhesive, glue, or a sugary substance.

(2) Tracking methods and quantification:

The 3D tracking methods, which incorporate whisker twists, strain, and other fine features of whisker exploration, present an advance in terms of analysis of how whiskers may explore more complex, natural features of environments. The analyses and quantifications are all solid and robust. The technical approaches are well-prepared to take the work a step further in terms of stimulus choice.

(3) Peripheral coding of stickiness:

The authors report that some units respond preferentially to whisking on silicone and that this has to do with strain on the whisker. Is there a possibility to understand the nature or anatomy of these units and why they might be preferential for the sticky sensation? Can the location in the follicle be assigned? And/or would the methodology allow for assignment of where the specifically sticky-tuned units project centrally?

(4) Relationship to natural stimuli:

A piece missing from the paper is more discussion and exploration of why stickiness may be important for sensory coding, as well as potentially more naturally sticky stimuli. One could imagine that a mouse navigating the world could find stickiness attractive, if it were a source of sweet food, for example, or it could potentially be a sensation the animal prefers to avoid. Stickiness could also indicate contamination or a sticky trap, to be avoided. If the authors are able to add naturally sticky stimuli, the whisker exploration and encoding could potentially provide further cues towards the valence of stickiness for mice.

Reviewer #3 (Public review):

This paper tackles an underexplored dimension of whisker-based texture sensing: while surface coarseness encoding has been extensively characterized in rodents, the mechanical and neural basis for stickiness sensing has not previously been examined. The authors make two intertwined contributions that together represent a substantial advance: a methodological one - a 3D whisker tracking pipeline operating at 4000 fps, capable of capturing torsion, roll, and out-of-plane whisker motion - and a scientific one - a first characterization of how whisker mechanics and primary trigeminal afferent responses differ between surfaces of high and low stickiness. The work is technically solid, the dataset is large, and the question is well motivated both by the multidimensional nature of tactile texture perception and by the practical advantages of the whisker system for studying touch mechanics.

Strengths.:

The 3D tracking system is a timely advance over existing tools, particularly in its handling of non-planar whisker shapes and the full automation required for the sub-millisecond resolution needed to detect stick-slip events. The mechanical dataset is extensive. The finding that whisking against silicone expands the sampled whisker strain space and produces stronger but less frequent stick-slip events is clearly demonstrated and internally consistent with the proposed mechanism of greater strain accumulation before frictional release - a physically intuitive result. The open release of the tracking code considerably increases the value of this work to the broader community.

Weaknesses:

A few aspects of the paper, if sharpened, would considerably strengthen the evidence and the clarity of the conclusions.

The central claim - that "stickiness information is available to the whisker system" - does not capture the precision of what the paper demonstrates. As stated, the finding is close to guaranteed: any variation in surface friction will produce some change in whisker mechanics, so the presence of mechanical differences between materials is expected rather than surprising. The more valuable question the paper is well positioned to answer is which specific dimensions of the whisker mechanical response are most informative about surface stickiness. The paper reports effects on strain distribution breadth, stick-slip amplitude, and stick-slip rate, but does not synthesize which of these - or which sub-dimensions (bending, twisting, or rolling) - carry the most discriminating information. Identifying the salient dimensions of the mechanical response and relating them to the proposed frictional mechanism would sharpen the paper's conclusions substantially.

A related but distinct limitation is the absence of direct force measurements during whisker-surface contact. The authors acknowledge this openly, and I recognize it is not easily remedied within the current experimental setup. It does, however, constrain interpretation: without knowing the actual forces generated at the whisker-surface interface, the assumed stickiness ordering of the tested materials cannot be validated, and - importantly - the relative contribution of surface friction and material compliance to the observed mechanical differences cannot be determined. This is an important direction for future work in this area.

The paper argues carefully that 2D tracking is insufficient for capturing the full mechanical picture of whisker-surface interactions, and the figure currently in the supplementary material (Figure S2) makes this case convincingly through multiple analyses. This argument is the core justification for the paper's methodological contribution and deserves a place in the main manuscript. Furthermore, while the mechanical case for 3D over 2D tracking is well made, it has not yet been tested at the neural level: the regression model used to predict neural firing incorporates 3D variables, but its performance is not compared against an equivalent model restricted to 2D variables. Such a comparison would directly demonstrate whether torsion and roll - the signals inaccessible to 2D tracking - carry neural predictive value, and would elegantly unite the paper's methodological and scientific contributions.

Finally, the three-dimensional plots in Figure 3 are the paper's primary representation of its main mechanical result, and there is a real opportunity to make them considerably more informative. The whisker deformation probability distributions (panel B) are rendered in 3D from a single viewing angle, making it difficult to assess the shape or anisotropy of the distributions - and in particular to see which dimensions expand most for silicone relative to the other materials. This is precisely the information needed to identify the most salient dimensions of the stickiness signal, and two-dimensional representations would make it directly readable.