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Edge-orientation processing in first-order tactile neurons

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Abstract

A fundamental feature of first-order neurons in the tactile system is that their distal axon branches in the skin and forms many transduction sites, yielding complex receptive fields with many highly sensitive zones. We found that this arrangement constitutes a peripheral neural mechanism that allows individual neurons to signal geometric features of touched objects. Specifically, we observed that two types of first-order tactile neurons that densely innervate the glabrous skin of the human fingertips signaled edge orientation via both the intensity and the temporal structure of their responses. Moreover, we found that the spatial layout of a neuron's highly sensitive zones predicted its sensitivity to particular edge orientations. We submit that peripheral neurons in the touch-processing pathway, as with peripheral neurons in the visual-processing pathway, perform feature extraction computations that are typically attributed to neurons in the cerebral cortex.

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Figure 1: Stimuli and sensitivity maps.
Figure 2: Observed and predicted neural responses.
Figure 3: Orientation discrimination and speed effect.
Figure 4: Timing of action potentials.

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Change history

  • 15 September 2014

    In the version of this supplementary file originally posted online, the raster image in Supplementary Figure 2a was left/right mirror-reversed. The error has been corrected in this file as of 15 September 2014.

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Acknowledgements

We thank B. Edin and D. Wolpert for their helpful comments on previous versions of this manuscript. We thank A. Bäckström, C. Hjältén, E. Jarocka, P. Jenmalm, P. Utsi and G. Westling for their technical and logistical support. This work was funded by the Swedish Research Council Projects 08667 and 22209, as well as by the Strategic Research Program in Neuroscience at the Karolinska Institute. J.A.P. received a long-term fellowship from the Human Frontier Science Program.

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Correspondence to J Andrew Pruszynski.

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Integrated supplementary information

Supplementary Figure 1 Experimental setup and basic methodology.

(a,b) Participants sat with their palm facing upwards and their fingers firmly attached to a table. We recorded action potentials from single first-order tactile neurons innervating the fingertips by inserting an electrode (‘E’ in a) into the median nerve at the level of the upper arm wrist50. The stimulating surface, wrapped around a rotating drum, moved across the neuron’s receptive field (blue mark in b) along the proximal-distal axis of the finger. (c) The stimulating surface consisted of various embossed elements (gray areas) including three small dots, lines with different orientations, and different shapes including triangles, diamonds and squares.

Supplementary Figure 2 Intensity of a neuron’s response signals line orientation.

(a) Top, spatial event plot focusing on the line stimuli and sensitivity maps for an exemplar FA-1 neurons (calibration bar = 1 mm). Color code above the line stimuli indicates complementary edge orientations. Bottom, the black and gray lines represent the neuron’s firing rate profiles for all line orientations. Format as in Fig. 2d. (b) Same format as a for an exemplar SA-1 neuron. (c) Relationship between peak firing rates for line stimuli with complementary orientations for FA-1 (n = 26) and SA-1 (n = 21) neurons, respectively. All dots are above the diagonal because the stronger response is shown along the vertical axis. Greater distances from the diagonal indicate stronger effects of edge orientation on the peak firing rate. Filled dots indicate a significant difference between complementary orientations (P < 0.05, one-sample, two-tailed, t-test corrected for 141 (47 neurons x 3 complementary pairs) comparisons, n = 12 per line orientation; see Methods). The diamonds indicate the exemplar neurons shown in a and b. Inset, mean difference (+1 s.e.m.) in peak firing rate for the complementary orientations for significant differences. (d) ROC curves illustrating the discrimination capacity of the exemplar neurons shown in a (top) and b (bottom) for each of the three complementary pairs. Lines dashed if the area under the ROC curve did not exceed 0.75. (e) ROC curves illustrating discrimination capacity across all FA-1 (n = 26) and SA-1 (n = 21) neurons for all line orientation pairs (color-coded). Lines gray if the area under the ROC curve did not exceed 0.75. (f) ROC area across neurons for each pair of complementary line orientations. The horizontal white line indicates the median value and the extent of the box depicts the interquartile range.

Supplementary Figure 3 Classification details.

Confusion matrices based on peak firing rate (a) or firing rate profile (b) for the matched speed condition (top) and the 30 mm/s drum speed (bottom). Each matrix shows how true edge orientations were classified as a percentage of the total number of samples. Elements with black backgrounds indicate correct classification. Bold numbers show the pairs of true and classified edge orientations that occurred more often than expected by chance. Briefly, we estimated the probability of randomly placing a finite number of samples (speed matched: 14 neurons x 12 repeats = 168 samples; 30 mm/s drum speed: 47 x 12 = 564 samples) into one of seven elements using a bootstrap procedure with 10000 repeats. In the limit, the result is clearly 14.2% (i.e. 1 / 7) but the number of samples determines the confidence interval. In our case, the 99th percentile of assignments was 21% and 18% for the speed matched and 30 mm/s drum speed data, respectively.

Supplementary Figure 4 Spike timing analysis for an exemplar FA-1 neuron.

(a) Top, instantaneous firing rate in response to the indicated line stimuli and the neuron’s sensitivity map. Bottom, raster plots showing responses to the 12 individual passes of the stimulus where each dot represents an action potential. (b) Action potentials were convolved with Gaussian kernels (s.d. = 0.5, 1, 2, 4, 8, 16 and 32 ms) to investigate the importance of precise spike timing for signaling line orientation information. Traces show probability density for the occurrence of action potentials as a function of time for each kernel computed by averaging the 12 responses after convolution. Note that increased kernel-widths gradually abolished the detailed temporal structure of the response. (c) Average correlation coefficients (± 1 s.d.) obtained when correlating each response to the vertical line stimulus (0°) with each response to every other line stimulus as a function of kernel width. For narrow kernels, the highest correlation clearly occurred when vertical line stimuli were compared to other vertical line stimuli. With wider kernels, correlation coefficients between the vertical line stimuli and the other stimuli were more similar. For this particular neuron, the 2 ms filter yielded the best classification results on average (red traces in b,c). (d) Same layout as c but for all line stimuli and the 2 ms kernel. Note that the highest correlations coefficients occurred when a given line orientation was compared to itself (dashed line).

Supplementary Figure 5 Effect of edge orientation and speed on spike timing.

(a) Raster plots and probability density (2 ms kernel) for the occurrence of action potentials shown as a function of drum position for all seven line orientations and four speed conditions for an exemplar SA-1 neuron (#33, see also Fig. 3). Sensitivity map generated at the 30 mm/s drum speed (calibration bar = 2 mm). Note the similarity of the firing probability profiles as a function of speed in contrast to the substantial changes that occur as a function of orientation. Asterisks indicate speed-matched conditions. (b) Same format as a for an exemplar FA-1 neuron (#40).

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Pruszynski, J., Johansson, R. Edge-orientation processing in first-order tactile neurons. Nat Neurosci 17, 1404–1409 (2014). https://doi.org/10.1038/nn.3804

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