Vibratory adaptation of cutaneous mechanoreceptive afferents

Abstract

The objective of this study was to investigate the effects of extended suprathreshold vibratory stimulation on the sensitivity of slowly adapting type 1 (SA1), rapidly adapting (RA), and Pacinian (PC) afferents. To that end, an algorithm was developed to track afferent absolute (I0) and entrainment (I1) thresholds as they change over time. We recorded afferent responses to periliminal vibratory test stimuli, which were interleaved with intense vibratory conditioning stimuli during the adaptation period of each experimental run. From these measurements, the algorithm allowed us to infer changes in the afferents' sensitivity. We investigated the stimulus parameters that affect adaptation by assessing the degree to which adaptation depends on the amplitude and frequency of the adapting stimulus. For all three afferent types, I0 and I1 increased with increasing adaptation frequency and amplitude. The degree of adaptation seems to be independent of the firing rate evoked in the afferent by the conditioning stimulus. In the analysis, we distinguished between additive adaptation (in which I0 and I1 shift equally) and multiplicative effects (in which the ratio I1/I0 remains constant). RA threshold shifts are almost perfectly additive. SA1 threshold shifts are close to additive and far from multiplicative (I1 threshold shifts are twice the I0 shifts). PC shifts are more difficult to classify. We used an integrate-and-fire model to study the possible neural mechanisms. A change in transducer gain predicts a multiplicative change in I0 and I1 and is thus ruled out as a mechanism underlying SA1 and RA adaptation. A change in the resting action potential threshold predicts equal, additive change in I0 and I1 and thus accounts well for RA adaptation. A change in the degree of refractoriness during the relative refractory period predicts an additional change in I1 such as that observed for SA1 fibers. We infer that adaptation is caused by an increase in spiking thresholds produced by ion flow through transducer channels in the receptor membrane. In a companion paper, we describe the time-course of vibratory adaptation and recovery for SA1, RA, and PC fibers.

Fig. 1

Impulse rates in slowly adapting 1 (SA1) rapidly adapting (RA) and Pacinian (PC) afferents evoked by vibratory stimuli. Because the relationship between impulse rate and vibratory amplitude is piecewise linear with broad plateaus in all 3 afferent types, the entire function is defined by thresholds for each linear segment. I₀ denotes the absolute threshold (minimum amplitude that evokes a response), I₁ the entrainment threshold (minimum amplitude that evokes a single action potential on each vibratory cycle), I₂ the doubling threshold (minimum amplitude that evokes 2 impulses on some stimulus cycles), and I₃ the double entrainment threshold (minimum amplitude that evokes 2 impulses on every stimulus cycle) (Johnson 1974). The problem with using impulse rate as an index of adaptation is shown by the hypothetical example shown here, in which a 75-μm stimulus amplitude would evoke the same (entrained) impulse rate throughout the adaptation and recovery periods despite the fact that I₀ tripled over that period.

Fig. 2

Time-course of an experimental run. Each run is divided into 3 periods: preadaptation, adaptation, and recovery period. Each trial comprises a 4-s interval consisting of a 3-s interval, which is empty except during the adaptation period followed by a 1-s test stimulus. Adaptation and recovery periods were 1, 2, 4, 8, or 16 min long. The preadaptation period, whose only purpose was to establish the unadapted I₀ and I₁ thresholds, was about 1 min long.

Fig. 3

Absolute and entrainment thresholds. Thresholds obtained from a given afferent are included in the plot only if they were measured at 3 or more frequencies. Dotted lines in the 3rd column denote absolute and entrainment thresholds measured by Freeman and Johnson (1982a).

Fig. 4

Time-course of adaptation and recovery for 1 afferent of each type at 3 adapting amplitudes. Each plot shows the absolute and entrainment threshold amplitudes as they change over time. Data obtained during adaptation and recovery periods are fit with exponential, functions (Leung et al. 2005). Dotted lines, I₀; thick solid lines, I₁; A_a, adapting amplitude; f_a, spike rate evoked in the afferent by the adapting stimulus; F_t, test frequency; F_a, adapting frequency. Stimulus and response parameters that vary from run to run are listed at the top of each plot. Constant stimulus parameters are listed at the right of each row.

Fig. 5

Effects of adapting amplitude on threshold shift for 4 typical SA1 afferents. Circles and dotted line, absolute thresholds; squares and solid line, entrainment thresholds.

Fig. 6

Effects of adapting amplitude on threshold shift for 4 RA afferents. Convention as in Fig. 5.

Fig. 7

Effects of adapting amplitude on threshold shift for 4 PC afferents. Conventions as in Fig. 5.

Fig. 8

Time-course of adaptation and recovery for 1 afferent of each type at 3 adapting frequencies. Conventions as in Fig. 4.

Fig. 9

Effect of adapting frequency on mean threshold shift and on adaptor evoked firing rate. In the top panels, squares and dotted lines denote absolute thresholds; circles and solid lines denote entrainment thresholds. Error bars denote SE (these are inflated as effects of frequency are collapsed across amplitudes). Only cases in which all 3 adapting frequencies were combined with a single adapting amplitude were included. Bottom panels: mean spike rate evoked in afferents at each adapting frequency (error bars denote SE (N_SA1 = 9, N_RA = 11, N_PC = 11).

Fig. 10

Examples in which adapting amplitudes and adaptation varied widely but evoked action potential rates remained constant. Conventions as in Fig. 4.

Fig. 11

Shift in absolute (circles) and entrainment (squares) threshold vs. adaptor-elicited firing rate for 1 SA1 afferent (SA 2). Test and adapting frequencies were 30 Hz, and adapting amplitudes varied from 75 to 300 μm. Six of the 9 adapting stimuli evoked similar spike rates but produced shifts in I₀ and I₁ that span an order of magnitude.

Fig. 12

I₁ vs. I₀ after SA1 adaptation. Dotted lines correspond to the line with unit slope, I₁ = I₀, dashed lines show the relationship expected when I₀ and I₁, change multiplicatively during adaptation (i.e., the ratio I₁ II₀ = constant). Solid line is the regression line through the final, adapted I₀, I₁ pairs corresponding to different adaptation amplitudes. Slope in the bottom right corner of each graph is the regression slope. A regression line with a slope near 1.0 indicates that the shifts in I₀ and I₁ were additive (and nearly identical). Two of the 4 SA1 afferents had substantially larger shifts in I₁ than I₀ but none came close to a multiplicative change in I₀ and I₁ which would require that the regression coincide with the dashed line.

Fig. 13

I₁ vs. I₀ after RA adaptation. Conventions as in Fig. 12. Note that in every fiber the shifts in I₀ and I₁ are additive and identical (or nearly so).

Fig. 14

I₁ vs. I₀ after PC adaptation. Conventions as in Fig. 13.

Fig. 15

Slope of adapted I₁ vs. I₀ and corresponding unadapted I₁/I₀ ratios. Each observation was derived from a single experimental run. Additive hypothesis predicts slope to be 1 regardless of unadapted I₁/I₀ ratio. Multiplicative hypothesis predicts slope to be equal to unadapted I₁/I₀ ratio. For RA afferents, slope is around unity regardless of I₁/I₀. For SA1 and PC afferents, slopes are intermediate between multiplicativity and additivity, although the mode for both types of afferents is near 1. That slopes were independent of I₁/I₀ for all afferents further weakens the multiplicative hypothesis.

Fig. 16

Algorithm performance on simulated data. Simulated thresholds (I₀ and I₁) were programmed to be constant during the preadaptation period, to increase exponentially during the adaptation period, and to decline exponentially to preadaptation levels during recovery period. Time constants and adaptation shifts were derived from an actual RA afferent (RA 17). The tracking algorithm generated test amplitudes, I, and estimated thresholds, I₀ and I₁; based on simulated firing rates. Dashed and solid lines represent hypothetical I₀ and I₁ values as they vary over the course of adaptation and recovery, respectively. Open circles and squares represent the algorithm’s estimates of those I₀ and I₁ values at 4-s intervals, respectively. Dots represent test amplitudes generated by the algorithm at each step.