Linear Integration of Tactile and Non-tactile Inputs Mediates Estimation of Fingertip Relative Position

Abstract

While skin, joints and muscles receptors alone provide lower level information about individual variables (e.g., exerted limb force and limb displacement), the distance between limb endpoints (i.e., relative position) has to be extracted from high level integration of somatosensory and motor signals. In particular, estimation of fingertip relative position likely involves more complex sensorimotor transformations than those underlying hand or arm position sense: the brain has to estimate where each fingertip is relative to the hand and where fingertips are relative to each other. It has been demonstrated that during grasping, feedback of digit position drives rapid adjustments of fingers force control. However, it has been shown that estimation of fingertips' relative position can be biased by digit forces. These findings raise the question of how the brain combines concurrent tactile (i.e., cutaneous mechanoreceptors afferents induced by skin pressure and stretch) and non-tactile (i.e., both descending motor command and joint/muscle receptors signals associated to muscle contraction) digit force-related inputs for fingertip distance estimation. Here we addressed this question by quantifying the contribution of tactile and non-tactile force-related inputs for the estimation of fingertip relative position. We asked subjects to match fingertip vertical distance relying only on either tactile or non-tactile inputs from the thumb and index fingertip, and compared their performance with the condition where both types of inputs were combined. We found that (a) the bias in the estimation of fingertip distance persisted when tactile inputs and non-tactile force-related signals were presented in isolation; (b) tactile signals contributed the most to the estimation of fingertip distance; (c) linear summation of the matching errors relying only on either tactile or non-tactile inputs was comparable to the matching error when both inputs were simultaneously available. These findings reveal a greater role of tactile signals for sensing fingertip distance and suggest a linear integration mechanism with non-tactile inputs for the estimation of fingertip relative position.

Keywords: digit forces; digit position sense; haptic bias; perception; tactile inputs.

Figure 1

Experimental set-ups. In each experiment, subjects were required to sense and memorize fingertip vertical distance (d_y, vertical black double arrows) while either exerting (Experiment 1 and 3) or experiencing (Experiment 2) digit forces (“Sense distance”). Subjects was then asked to reproduce the memorized digit position (“Match”). Direction of force related input associated to voluntary digit forces or passive fingertip stimulation are represented by blue arrows. Opaque fingers depict the hypothetical bias exhibited during reproduction. Yellow and red dots represent digit center of pressure (CoP) for Experiment 1 and 2, and point of force application (PFA) for Experiment 3, respectively. Dashed lines in Experiment 1 depict the static sensorized object. Subjects in Experiment 1 were provided by both tactile and non-tactile inputs during sense distance. In Experiment 2, only tactile signals were available to sense and memorize digit distance. Since the finger-pad was not involved in the task, during Experiment 3 subjects relied only on non-tactile signals to estimate digit distance.

Figure 2

Experimental protocols and trial epochs used in each experiment. (A) temporal sequence of the phases characterizing each trial in all experiments. In bold are the main phases. Ramp up and ramp down represent the time spent by the haptic devices in Experiment 2 and 3 to reach the force threshold and to come back to zero force value, respectively. (B) profiles of relative (d_y; green traces) and absolute (CoP or PFA) digit finger positions (red and blue traces) from a representative subject. Data are from “Sense distance” and “Hold” phases of T_UP-I_DNforce combination presented in each experiment. Horizontal dash lines denote the range of d_y subjects experienced during the sense phase. Note the different scale of the vertical axes for d_y during the “Sense distance” and Hold” phases.

Figure 3

Matching error. Median and 95% confidence intervals (CI) of matching errors of Experiment 1 (left), Experiment 2 (center) and Experiment 3 (right) for each digit force combination. Asterisks denote the mean matching error averaged across the 5 repetitions of each subject in each condition. Positive errors denote higher position of thumb relative to index fingertip, and vice versa for negative errors. T_UP-I_UP: both digits' tangential forces directed upward; T_DN-I_DN: both digits' tangential forces directed downward; T_UP-I_DN: thumb and index tangential forces directed upward and downward, respectively; T_DN-I_UP: thumb and index tangential forces directed downward and upward, respectively; Null: no digit forces; and F_n only: only digit normal forces.

Figure 4

Matching errors as function of repetition. Single trial matching error exhibited by each subject during T_UP-I_DN and T_DN-I_UP is plotted against repetitions in Experiment 2 (A) and Experiment 3 (B). Data from all subjects are shown for each condition and experiment, and ordered as a function of repetition, e.g., the first 10 dots depicted in the left plot (Experiment 2A) denote the first repetition of T_UP-I_DN force combination of each one of the 10 subjects. Pearson correlation coefficient (r) and regression statistics (p) is reported in each plot.

Figure 5

Individual and combined bias elicited by tactile and/or non-tactile inputs. Blue bar: median ± 95% CI of the sum of matching errors exhibited in Experiment 2 (tactile inputs only) and 3 (non-tactile inputs only). Red bar: median ± CI matching error observed when both inputs were simultaneously presented (Experiment 1).

Figure 6

Reliability based cue combination analysis. Inverse of the variance (i.e., reliability) of the matching errors exhibited in experiment 1 (r_exp1; dot), 2 (r_exp2; lower dashed horizontal line), and 3 (r_exp3; upper dashed horizontal line) for condition T_UP-I_DNand T_DN-I_UP.Position of r_exp1 within the plot supports (green and yellow areas) or reject (pink area) the hypothesis of linear combination of tactile and non-tactile signals for finger distance estimation.

Figure 7

Strength of bias. Probability to elicit positive or negative consistent d_y matching errors, i.e., thumb higher (positive) or lower (negative) than index fingertip, respectively, when either tactile (dark bars) or non-tactile (light bars) force related signals were available. For each force condition, probabilities were calculated by testing whether the error exhibited in each of the 50 trials was within the inter-quantile range of errors exhibited during baseline condition (null).

Figure 8

Putative sensorimotor network for fingertip distance estimation during manipulation. Direction and magnitude of force-related signals to/from the digits during manipulation are encoded by ensembles of tactile mechanoreceptors (blue arrow Birznieks et al., ; Johansson and Flanagan, , and muscle spindle afferents (solid red arrow; Goodwin et al., ; Burke et al., ; Ribot-Ciscar et al., ; Smith et al., ; Dimitriou and Edin, 2010). Tactile and proprioceptive inputs reach primary somatosensory cortex (areas 3b and 3a, respectively; Thach, ; Jenmalm et al., 2003). Unimodal and multimodal neurons in primary and secondary somatosensory cortex integrate (Kim et al., 2015) and convey sensory information to the anterior lobe of cerebellum and the inferior parietal lobule (Clower et al., 2001). Here, further sensory integration occurs to enable body representation (Longo et al., 2010) and predictions about future body state (Hua and Houk, ; Blakemore and Sirigu, ; Pynn and De Souza, 2013). Motor cortex controlling digit force production (dotted red arrow) contributes to fingertip distance representation through an efference copy (dashed red arrow) sent to the somatosensory cortex (Blakemore et al., 1999) and the cerebellum (Hua and Houk, 1997), both projecting to parietal cortex (Clower et al., 2001). Blue box and blue arrows denote the putative network primarily involved in Experiment 2, whereas red boxes and red arrows denote the network that might have been involved in Experiment 3. White boxes and black arrows represent the neural network more likely to be involved in each of the three experiments when both (or either) tactile and non-tactile signals are available to estimate finger relative position (Kavounoudias et al., 2008).