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In response to ramp-and-hold indentation, the slowly-adapting type I (SAI) afferent exhibits an exponential decrease in its firing frequency during the hold phase. Such adaptation may be tied to skin relaxation but is neither well understood nor has it been quantitatively modeled. The specific hypothesis of this work is that skin relaxation is a primary contributor to observed changes in firing rate. Double exponential functions were fit to 21 responses from a mouse SAI afferent for both instantaneous firing rate and indenter tip force over time. The model was then generalized by using a linear transformation between fit parameters for force and firing rate data, allowing prediction of firing rates from force. The results show that the generalized model matches the recorded firing rate (R2 = 0.65) equally well as fitting a double-exponential function directly to firing rate (R2 = 0.67) for a second dataset. When the procedure was repeated with two D-hair fibers, the generalized model matched the recorded firing rate (R2 = 0.47) much more poorly compared to the fitted double-exponential function (R2 = 0.89). Thus, firing rate adaptation in SAI responses can be predicted by skin relaxation, whereas this factor alone did not adequately describe adaptation in the D-hair.

Background A strong calculus foundation is essential to undergraduate engineering success. However, some students may be self‐selecting to begin their mathematics sequence in a lower‐level calculus course than their prior achievement and aptitude would suggest is appropriate (i.e., undermatch). Purpose This study examined (a) the relationship between engineering students' academic outcomes and first‐year calculus course taken, (b) the extent to which first‐year engineering students select calculus courses appropriate for their prior mathematics achievement and background, and (c) students' rationales for calculus course selection. Design/Method The study used a mixed‐methods approach consisting of quantitative t‐test, multiple regression, and classification decision tree model analyses of student records of (a) first‐year engineering students from 2009 to 2016 (n = 2689) at a highly selective public research university and (b) qualitative focus groups of 95 undergraduate engineering students in 2017–2018. Results Students who begin their math sequence in Calculus I had lower graduating grade point averages, longer time‐to‐degree, and were less likely to major in popular engineering fields than those who started in Calculus II. Of first‐year undergraduates, 18.4% undermatched their choice of calculus course. Students' rationales for choosing a particular calculus course included (a) prior achievement, (b) recommendations from others, and (c) self‐confidence. Conclusions Results suggest that undermatching the choice of first calculus course may lead to negative consequences for students' STEM pathways even at a highly selective engineering school. These results hold implications for practice, especially in terms of advising at the high school and college levels.

When afferents reinnervate the muscle tissue nearby a stimulating electrode, it is hard to control how well the single stimulating site of the electrode aligns physically with the location of the nerve fiber. To account for such issues in positioning, a multi-site electrode might aid by delivering electrical stimulation in a distributed fashion. In particular, by sourcing a smaller magnitude of charge per electrode, it may be possible to reduce the likelihood of tissue damage, even while increasing the extent of tissue above the depolarization threshold. Therefore, the work herein develops a finite-element (FE) model of the electrode-muscle interface to determine the distribution of charge density delivered to muscle as a function of two independent variables and their interaction: 1) interelectrode distance and 2) stimulation amplitude. The results indicate that multi-site electrodes can stimulate more muscle volume at lower input amplitude than a single-site electrode, over a range of tissue properties. Importantly, multisite stimulation may reduce tissue damage and even yet increase the likelihood of stimulating a fiber. Further work is yet needed to tie the modeling results with experimental validation in real tissue.

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