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Articles in PresS. J Neurophysiol (November 12, 2014). doi:10.1152/jn.00670.2014
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The Vision of Hsiao on Somatosensation
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Martha Flanders and John F. Soechting
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Laboratory of Neurophysiology, University of Minnesota, Minneapolis, MN 55455
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Running title: Research contributions of S.S. Hsiao
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Keywords: somatosensory, haptics, touch, Pacinian corpuscle, neuroprosthetics
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Corresponding author:
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Martha Flanders
6-145 Jackson Hall
321 Church St SE
Minneapolis, MN 55455
Phone (612) 624-6601
Fax (612) 626-5009
[email protected]
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Copyright © 2014 by the American Physiological Society.
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ABSTRACT
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The goal of this review is to start to consolidate and distill the substantial body of
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research that comprises the published work of the late Professor Steven S. Hsiao. The
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studies of Hsiao began by demonstrating the receptive field properties of somatosensory
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neurons, progressed to describing cortical feature selectivity, and then eventually elevated
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the field to hopes of tapping into natural neural codes with artificial somatosensory
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feedback. With ongoing analogies to contemporaneous studies in visual neuroscience,
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the research results and writings of Hsiao have provided the fields of haptics and
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somatosensory neurophysiology with the conceptual tools needed to allow profound
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progress. Specifically, Hsiao suggested that slowly-adapting tactile form perception
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could be restored with cortical microstimulation, rapidly-adapting slip reflexes should be
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relegated to low-level, hard-wired prosthetic components, and Pacinian-corpuscle
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spatiotemporal population responses could potentially be decoded/encoded to provide
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information about interactions of hands and hand-held instruments with external objects.
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Future studies will be guided by these insightful reports from Hsiao.
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BEGINNINGS
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Twenty-two years ago, we (Soechting and Flanders 1992) were neighbors with Steve
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Hsiao and his mentor in a volume of the Annual Review of Neuroscience (Johnson and
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Hsiao 1992). In their review, our contemporaries put forward the most lucid description
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of tactile receptor sensitivities that we have encountered to date, outlining the
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complementary nature of slowly-adapting type one (SAI) afferents (from Merkel
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complexes), rapidly-adapting type one (RAI) afferents (from Meissner corpuscles), and
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the rapidly-adapting signals from Pacinian corpuscles (PC). They explained the
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preference of SAIs for isolated curves of skin indentation (LaMotte and Srinivasan 1987;
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Phillips and Johnson 1981) as a mechanical surround-suppression effect (implicitly
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analogous to the center-surround organization in the visual system), and went on to
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speculate that the SAI receptor density may be matched to the skin’s low-pass filtering to
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achieve the best possible spatial resolution. Whereas SAIs specialize in spatial
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resolution, encapsulated receptor structures make RAIs and PCs selective for higher
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frequency vibrations, and these latter two groups are complementary to each other in their
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superficial location/small receptive field size (RA) compared to deep location/large
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receptive field size (PC). With the example of tool use, Johnson and Hsiao (1992)
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concisely summarized that SAIs would give a maintained representation of the detailed
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form of the tool while RAs would, with high spatiotemporal fidelity, signal any slippage
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of the instrument within the hand. The authors envisioned that the population of PCs
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would transduce spatiotemporal patterns of transmitted vibrations to represent “transient
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mechanical events that occur at the working surfaces of the instrument” (p. 246).
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Regardless of whether these words were written by Hsiao or his mentor, this is the vision
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of somatosensation with which Steven S. Hsiao began his career.
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Hsiao’s first publication was momentous (Phillips et al. 1988). In it, the authors used
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their new technique of characterizing the response of an individual neuron (peripheral or
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cortical) by generating a spatial event plot (SEP). Figure 1 expands on Fig. 1 from
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Phillips et al. (1988) in order to explain the approach. Immobilized monkeys were
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anesthetized for peripheral recordings but alert for cortical recordings. As shown
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schematically in Fig 1A, a raised letter was moved across a stationary finger pad. The
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letters were raised above the background by 500 m, moved across the skin at 50 mm/s,
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and applied with a servo-controlled normal force of 60 g. After each proximal to distal
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movement, the letter stimulus was shifted 0.2 mm along its long axis (i.e., perpendicular
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to the direction of the scanning movement) so that the neuron’s receptive field (dashed
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circle) now scanned across the letter on a different row. The SEP in Fig. 1B is
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constructed so that within each row, recorded action potentials can be positioned
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according to the location of the receptive field relative to a raised letter stimulus at the
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time when they occurred. In this study, there were 64 sweeps across the letter by the
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receptive field of a somatosensory neuron, resulting in 64 rows of action potentials in the
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SEP.
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Figure 1 of Phillips et al. (1988) exhibited the action potentials of a cortical area 3b SA
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neuron that always fired when the leading edge of the letter “K” was in its receptive field,
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and fired with high fidelity whenever a raised portion occupied its receptive field. Figure
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2 of Phillips et al. (1988) then revealed that a similarly high spatial resolution was
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observed in recordings from SAI afferents. We exhibit this phenomenon in Fig. 2 (row
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2), which is reprinted from a subsequent study where raised dot patterns (350 m) were
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slowly scanned (20 mm/s) and applied with a servo-controlled normal force of 30 g
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(Connor et al. 1990). As first shown by Phillips et al. (1988), Fig. 2 (row 3) demonstrates
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that RA afferents also had sufficiently small receptive fields to provide an isomorphic
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representation of the stimulus pattern. In contrast, PC afferents (Fig. 2, bottom row)
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failed to do so because of their large receptive fields and preferred vibration rates (100-
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300 Hz) above the speed of the scanned stimuli.
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Hsiao and colleagues (Phillips et al. 1988) explained that these SEPs truly represented the
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response of a single neuron to a stimulus moved across the skin, but also, especially in
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the case of dense and uniform SA1 and RA afferent populations, they could be
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interpreted as representing the population response, or the “neural image” of the stimulus.
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They went on to discuss the sensitivities of various somatosensory cortical neurons as a
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progression from an isomorphic to an abstracted touch representation.
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As a sign of the times, this 1988 paper was entitled “Spatial pattern representation and
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transformation…,” similar to our own titles involving sensorimotor transformations (e.g.,
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Soechting and Flanders 1989a,b), where we conceptualized neural processing as
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occurring in successive stages with information being serially transformed from one stage
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to the next. The framework laid by Phillips et al. (1988) also broke transformations into
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sequential stages. They hypothesized that cortical area 3b RA neurons and area 1
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neurons may exhibit intermediate representations – much like the hidden units in Zipser
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and Anderson’s (1988) model of transformation in parietal visual cortex.
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FEATURES OF SENSORY RESPONSES
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In the 1990’s and beyond, Hsiao and colleagues continued to develop sophisticated
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methods for precise stimulation (e.g., Lane et al. 2010) and analysis of receptive fields,
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while their conceptual framework evolved toward feature selectivity and perceptual
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constancy. The early work on SAI and RA afferents was extended and elaborated by
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showing the precise features of the stimuli encoded by the afferents, and by deducing that
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roughness can be encoded by the spatial variations in the firing rate of a population of
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SAIs (Connor et al. 1990; Blake et al. 1997, see Fig 2). More recently, Hsiao’s former
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coworker, Bensmaia, further extended this interpretation by showing that the finer
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features of texture stimuli are represented by spike timing in RA and PC afferents, and
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has emphasized the central convergence of these different types of peripheral afferent
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inputs (Weber et al. 2013; Saal and Bensmaia 2014).
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Just as visual cortical neurons are tuned to the orientations of bars, neurons in primary
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(S1) and secondary (S2) somatosensory cortex are tuned to the orientation of edges
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impressed on the hand, a feature extracted from the response of populations of SAI
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afferents (Hsiao et al. 2002). S2 neurons have receptive fields extending over multiple
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digits, with markedly similar tuning properties for each finger (Fitzgerald et al. 2004,
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2006), facilitating the haptic discrimination of the shapes of large objects. Hsiao and
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colleagues noted the similarities in orientation selectivity in primary visual and
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somatosensory cortical areas and suggested that these similarities arose from analogous
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neural mechanisms in these areas (Bensmaia et al. 2008).
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In the visual system, it is well known that the representation of motion is transformed
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from a representation of the components of a pattern (e.g., the stripes of a plaid) to one of
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the motion of the entire pattern (the plaid) as one ascends the hierarchy of visual cortical
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areas (Movshon et al. 1985). Furthermore, this “dorsal stream” transformation evolves
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gradually over time (Masson and Stone 2002). Hsiao and colleagues discovered an
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analogous phenomenon in the tactile perception of motion (Pei et al. 2008) and
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subsequently demonstrated a similar hierarchy in the somatosensory cortical areas (Pei et
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al. 2011). Neurons in S1 area 3b responded to local (component) motion (analogous to
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neurons in V1 area 17). However in S1 area 1, some neurons encoded the pattern motion
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while others were tuned to component motion or exhibited intermediate characteristics
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(analogous to the medial temporal visual area MT).
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Ascending the hierarchy of “ventral stream” areas, cortical neurons are tuned to
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progressively more complex features of contours and objects (cf., Brincat and Connor
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2004). In a collaboration of the Hsiao and Connor laboratories, Yau et al. (2009)
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explicitly tested the idea that there are analogous coding schemes in visual and
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somatosensory areas. They recorded activity from intermediate visual area (V4) for
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visual stimuli, and somatosensory area (S2) for tactile stimuli. In each case, monkeys
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were presented with contours whose directions of curvature were systematically varied.
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Indeed, they found neurons in both areas that responded briskly to such stimuli, and
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found very similar patterns of tuning in both areas. Thus the concept of hierarchies of
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feature representation holds well for both vision and somatosensation.
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GOALS FOR THE FUTURE
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In a recent paper on neuroprosthetics, Hsiao et al. (2011) gave their forecast and
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recommendations on the prospect of providing artificial somatosensory feedback.
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Building on decades of his work on feature selectivity, Hsiao predicted that it will
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eventually be possible, using electrical or optical stimulation in cortex, to find the
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“natural neural codes” (p. 76) to provide SA-type perception of form. Regarding the
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restoration of RA-type input, Hsiao et al. (2011) recommended hard-wiring slip reflexes
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into the mechanical hand itself. The authors reasoned that the user need not be
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consciously aware of slippage, as long as it is automatically corrected. They compared
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this to the case of Dr. Strangelove, where the movie character’s funny right hand had a
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mind of its own. The authors also saw promise in the prospect of tapping into the PC
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channel, if we can “mimic the temporal pattern of what a PC afferent would have
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experienced under the same circumstances” (p. 73). The idea is to use the spatiotemporal
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patterns that naturally arise when a person uses a tool to interact with external objects. In
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this case the authors mentioned examples of a blind person using a cane and, more
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dramatically, Luke Skywalker using his prosthetic hand to wield his lightsaber weapon!
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Another current topic that will extend beyond the work of Hsiao is research on spinal
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circuits, where we are beginning to gain an appreciation for the processing of tactile
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feedback in the dorsal horn. At the end of their detailed review of peripheral and spinal
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“touch” representations, Abraira and Ginty (2013) thanked their close colleague Steven
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Hsiao for his helpful comments on the manuscript. Remarkably, these authors analogized
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the spinal dorsal horn to the retina, for its complexity and importance in early sensory
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processing. Indeed, individual peripheral afferent neurons may serve as the first stage of
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directional feature selectivity (Pruszynski and Johansson 2014). Furthermore, this dorsal-
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horn spinal circuit may be essential for comparing cortical motor commands with
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somatosensory feedback during tool use and tactile exploration (Flanders 2011; Weiss
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and Flanders 2011).
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Whereas the pioneering approach of the spatial event plot (Johnson and Hsiao 1992;
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Phillips et al. 1988) was necessarily done with the hand immobilized, a challenge for
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future experimentation is to put tools in the hands and let them move freely along
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surfaces. This future research will be guided by the vision of Hsiao.
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Acknowledgements
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The authors were supported by a grant for the National Institute of Neurological
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Disorders and Stroke NS027484. We thank the three reviewers for their very helpful
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suggestions.
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Figure Captions
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FIG. 1.
Panel A shows how moving a raised letter (K) toward the distal
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end of a finger pad, from right to left in this figure, advances the stationary skin receptive
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field (dashed circle) from left to right across the letter. The receptive field was advanced
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by 1 mm every 20 ms (50 mm/s). Panel B shows the conventions of a spatial event plot
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(SEP) for the action potentials recorded at each location.
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FIG. 2.
Example spatial event plots (SEPs) gathered while grids of 0.5 mm
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diameter raised dots were scanned across the distal finger pad of an anesthetized macaque
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monkey. The top row shows the dot spacing (1.3 – 6.2 mm) of the stimuli. The middle
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two rows show that SAI and RA peripheral afferents can provide nearly isomorphic
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neural images of the pattern; the bottom row suggests that PC afferents cannot.
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Reproduced with permission from Connor et al., J Neurosci 10:3826 (Fig. 4), 1990.
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A. Schematic of receptive field
B. Spatial event plot to mark
scanning across a raised letter
action potentials at place of
occurrence on letter stimulus
K
8 mm
high
receptive field swept across
64 rows
raised 500 µm
upper
corner of
embossed
letter “K”
2 mm wide
1 mm/tick (20 ms/tick at 50 mm/s)
ce.
eter and dot spacinghad statistically significant
essestimates(ANOVA p < 0.000 1). Perceived
asedsomewhat with increasingdot size, espeerdot spacings.Dot spacinghad a much larger
t diameter, roughnessincreasedwith increasing
o 3.2 mm, then declined. Thus, the roughness
ectionsfor typical SA,
s.The corresponding
stimuluspattern are
w (dot diameter,0.5
omprises
a setof rasm repetitive parallel
ulusacrossthe recepstimulusshiftedverbetweeneachscan.
. . a.-.
. . .......
..........
...........
.*-,
:.-
.
Figure 3B shows, for example, that dot spacingsof approximately 2 and 5 mm produce the sameroughnessmagnitude
even though they evoke very different neural responses,as described in the next section. The remainder of the paper is concerned with discovering the coding mechanismthat extracts a
constant factor in different neural responses
that evoke the same
subjective senseof roughness.
.
..........
......
.....
.
......
......
‘.-.-.-.-*-,
......... .
......... Z.’
. . l :
.’
PC
Dot spacing (mm)