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Aging and Curvature Discrimination from Static and Dynamic Touch

Identifieur interne : 002284 ( Pmc/Curation ); précédent : 002283; suivant : 002285

Aging and Curvature Discrimination from Static and Dynamic Touch

Auteurs : J. Farley Norman [États-Unis] ; Astrid M. L. Kappers [Pays-Bas] ; Jacob R. Cheeseman [États-Unis] ; Cecilia Ronning [États-Unis] ; Kelsey E. Thomason [États-Unis] ; Michael W. Baxter [États-Unis] ; Autum B. Calloway [États-Unis] ; Davora N. Lamirande [États-Unis]

Source :

RBID : PMC:3699499

Abstract

Two experiments evaluated the ability of 30 older and younger adults to discriminate the curvature of simple object surfaces from static and dynamic touch. The ages of the older adults ranged from 66 to 85 years, while those of the younger adults ranged from 20 to 29 years. For each participant in both experiments, the minimum curvature magnitude needed to reliably discriminate between convex and concave surfaces was determined. In Experiment 1, participants used static touch to make their judgments of curvature, while dynamic touch was used in Experiment 2. When static touch was used to discriminate curvature, a large effect of age occurred (the thresholds were 0.67 & 1.11/m for the younger and older participants, respectively). However, when participants used dynamic touch, there was no significant difference between the ability of younger and older participants to discriminate curvature (the thresholds were 0.58 & 0.59/m for the younger and older participants, respectively). The results of the current study demonstrate that while older adults can accurately discriminate surface curvature from dynamic touch, they possess significant impairments for static touch.


Url:
DOI: 10.1371/journal.pone.0068577
PubMed: 23844224
PubMed Central: 3699499

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PMC:3699499

Le document en format XML

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<p>Two experiments evaluated the ability of 30 older and younger adults to discriminate the curvature of simple object surfaces from static and dynamic touch. The ages of the older adults ranged from 66 to 85 years, while those of the younger adults ranged from 20 to 29 years. For each participant in both experiments, the minimum curvature magnitude needed to reliably discriminate between convex and concave surfaces was determined. In Experiment 1, participants used static touch to make their judgments of curvature, while dynamic touch was used in Experiment 2. When static touch was used to discriminate curvature, a large effect of age occurred (the thresholds were 0.67 & 1.11/m for the younger and older participants, respectively). However, when participants used dynamic touch, there was no significant difference between the ability of younger and older participants to discriminate curvature (the thresholds were 0.58 & 0.59/m for the younger and older participants, respectively). The results of the current study demonstrate that while older adults can accurately discriminate surface curvature from dynamic touch, they possess significant impairments for static touch.</p>
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<journal-id journal-id-type="nlm-ta">PLoS One</journal-id>
<journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id>
<journal-id journal-id-type="publisher-id">plos</journal-id>
<journal-id journal-id-type="pmc">plosone</journal-id>
<journal-title-group>
<journal-title>PLoS ONE</journal-title>
</journal-title-group>
<issn pub-type="epub">1932-6203</issn>
<publisher>
<publisher-name>Public Library of Science</publisher-name>
<publisher-loc>San Francisco, USA</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="pmid">23844224</article-id>
<article-id pub-id-type="pmc">3699499</article-id>
<article-id pub-id-type="publisher-id">PONE-D-13-16262</article-id>
<article-id pub-id-type="doi">10.1371/journal.pone.0068577</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline-v2">
<subject>Biology</subject>
<subj-group>
<subject>Neuroscience</subject>
<subj-group>
<subject>Sensory Perception</subject>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v2">
<subject>Medicine</subject>
<subj-group>
<subject>Anatomy and Physiology</subject>
<subj-group>
<subject>Physiological Processes</subject>
<subj-group>
<subject>Aging</subject>
</subj-group>
</subj-group>
</subj-group>
<subj-group>
<subject>Mental Health</subject>
<subj-group>
<subject>Psychology</subject>
<subj-group>
<subject>Behavior</subject>
<subj-group>
<subject>Human Performance</subject>
</subj-group>
</subj-group>
<subj-group>
<subject>Sensory Perception</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v2">
<subject>Social and Behavioral Sciences</subject>
<subj-group>
<subject>Psychology</subject>
<subj-group>
<subject>Behavior</subject>
<subj-group>
<subject>Human Performance</subject>
</subj-group>
</subj-group>
<subj-group>
<subject>Sensory Perception</subject>
</subj-group>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Aging and Curvature Discrimination from Static and Dynamic Touch</article-title>
<alt-title alt-title-type="running-head">Aging and Tactile Curvature Discrimination</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Norman</surname>
<given-names>J. Farley</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="corresp" rid="cor1">
<sup>*</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Kappers</surname>
<given-names>Astrid M. L.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cheeseman</surname>
<given-names>Jacob R.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ronning</surname>
<given-names>Cecilia</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Thomason</surname>
<given-names>Kelsey E.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Baxter</surname>
<given-names>Michael W.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Calloway</surname>
<given-names>Autum B.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lamirande</surname>
<given-names>Davora N.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<label>1</label>
<addr-line>Department of Psychology, Western Kentucky University, Bowling Green, Kentucky, United States of America</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Center for the Study of Lifespan Development, Western Kentucky University, Bowling Green, Kentucky, United States of America</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Faculty of Human Movement Sciences, Vrije Universiteit, Amsterdam, The Netherlands</addr-line>
</aff>
<contrib-group>
<contrib contrib-type="editor">
<name>
<surname>Sathian</surname>
<given-names>Krish</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"></xref>
</contrib>
</contrib-group>
<aff id="edit1">
<addr-line>Emory University, United States of America</addr-line>
</aff>
<author-notes>
<corresp id="cor1">* E-mail:
<email>Farley.Norman@wku.edu</email>
</corresp>
<fn fn-type="conflict">
<p>
<bold>Competing Interests: </bold>
The authors have declared that no competing interests exist.</p>
</fn>
<fn fn-type="con">
<p>Conceived and designed the experiments: JFN AMLK. Performed the experiments: JFN JRC CR KET MWB ABC DNL. Analyzed the data: JFN. Contributed reagents/materials/analysis tools: JFN AMLK. Wrote the paper: JFN JRC MWB.</p>
</fn>
</author-notes>
<pub-date pub-type="collection">
<year>2013</year>
</pub-date>
<pub-date pub-type="epub">
<day>2</day>
<month>7</month>
<year>2013</year>
</pub-date>
<volume>8</volume>
<issue>7</issue>
<elocation-id>e68577</elocation-id>
<history>
<date date-type="received">
<day>21</day>
<month>4</month>
<year>2013</year>
</date>
<date date-type="accepted">
<day>29</day>
<month>5</month>
<year>2013</year>
</date>
</history>
<permissions>
<copyright-year>2013</copyright-year>
<copyright-holder>Norman et al</copyright-holder>
<license>
<license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<abstract>
<p>Two experiments evaluated the ability of 30 older and younger adults to discriminate the curvature of simple object surfaces from static and dynamic touch. The ages of the older adults ranged from 66 to 85 years, while those of the younger adults ranged from 20 to 29 years. For each participant in both experiments, the minimum curvature magnitude needed to reliably discriminate between convex and concave surfaces was determined. In Experiment 1, participants used static touch to make their judgments of curvature, while dynamic touch was used in Experiment 2. When static touch was used to discriminate curvature, a large effect of age occurred (the thresholds were 0.67 & 1.11/m for the younger and older participants, respectively). However, when participants used dynamic touch, there was no significant difference between the ability of younger and older participants to discriminate curvature (the thresholds were 0.58 & 0.59/m for the younger and older participants, respectively). The results of the current study demonstrate that while older adults can accurately discriminate surface curvature from dynamic touch, they possess significant impairments for static touch.</p>
</abstract>
<funding-group>
<funding-statement>No current external funding sources for this study.</funding-statement>
</funding-group>
<counts>
<page-count count="6"></page-count>
</counts>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>It has been known for more than 20 years that aging has detrimental effects on performance for simple tactile tasks. For example, tactile acuity deteriorates markedly with increases in age
<xref ref-type="bibr" rid="pone.0068577-Norman1">[1]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-Woodward1">[5]</xref>
; older adults, when performing a tactile grating orientation task, possess thresholds that are more than double (2.4 times higher than) those of younger adults in their twenties
<xref ref-type="bibr" rid="pone.0068577-Norman2">[2]</xref>
. In addition, significant age-related differences in performance have been observed in a tactile letter identification task
<xref ref-type="bibr" rid="pone.0068577-VegaBermudez2">[6]</xref>
. Given that these age-related differences in tactile acuity do exist, it is an interesting fact that older adults can perform as well as younger adults when they are asked to haptically discriminate
<xref ref-type="bibr" rid="pone.0068577-Norman1">[1]</xref>
or estimate
<xref ref-type="bibr" rid="pone.0068577-Norman2">[2]</xref>
solid object shape. In Experiment 1 of Norman et al.
<xref ref-type="bibr" rid="pone.0068577-Norman1">[1]</xref>
, younger and older adults haptically explored two solid objects on any given trial (bell peppers, Capsicum annuum) and were required to discriminate whether their shapes were the same or different. Their older participants performed as well as the younger participants despite the fact that they were more than 50 years older (on average). In Experiments 1 and 2 of Norman et al.
<xref ref-type="bibr" rid="pone.0068577-Norman2">[2]</xref>
, younger and older adults were asked to estimate the shape of quadric surfaces using either their entire hand or just the tip of their index finger. In both cases (hand and fingertip), the older participants’ judgments of 3-D surface shape were as accurate and reliable as those of the younger participants.</p>
<p>In a series of investigations in the late 1990’s
<xref ref-type="bibr" rid="pone.0068577-Pont1">[7]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-Pont2">[8]</xref>
, Pont, Kappers, and Koenderink evaluated static tactile and active haptic curvature discrimination. They used a set of blocks whose top surfaces were curved in either a convex or concave manner – the curvature magnitudes of the convex and concave circular arcs varied from 0.2 to 1.8/m. Pont et al. found that their participants’ curvature discrimination thresholds depended upon which part of the hand or fingers was used to feel the curved stimuli. The thresholds also varied as a function of the spatial extent over which the stimuli were touched. Pont et al. concluded that their participants’ static and dynamic perceptions of curvature were derived from differences in surface attitude/orientation (i.e., surfaces with higher curvature have greater changes in surface attitude/orientation and surfaces with lower curvature have smaller changes in surface attitude/orientation).</p>
<p>In everyday interactions with objects, we often perceive important properties about them (e.g., their shape, curvature, size, etc.) from immediate contact, when our hands and fingers come into actual physical contact with object surfaces
<xref ref-type="bibr" rid="pone.0068577-Goodwin1">[9]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-VanDoorn1">[11]</xref>
. This physical contact stimulates slowly- and rapidly-adapting sensory mechanoreceptors within the skin
<xref ref-type="bibr" rid="pone.0068577-Srinivasan1">[12]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-LaMotte2">[14]</xref>
; the resulting patterns of cutaneous activity eventually produce activation in a variety of areas within the cerebral cortex
<xref ref-type="bibr" rid="pone.0068577-Bodegrd1">[15]</xref>
, leading to conscious awareness and perception. It is very important to note, however, that cutaneous activity resulting from simple contact is not the only source of information available to support the tactile perception of object shape. When we actively manipulate objects using a variety of exploratory procedures
<xref ref-type="bibr" rid="pone.0068577-Klatzky1">[16]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-Lederman1">[17]</xref>
, this leads to activation of not only cutaneous receptors within the skin, but also results in the stimulation of muscle and joint receptors. The additional sensory and proprioceptive information made possible by active touch has been shown to enhance shape perception
<xref ref-type="bibr" rid="pone.0068577-Gibson1">[18]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-Kappers1">[22]</xref>
. It has also been demonstrated that kinesthetic information alone
<xref ref-type="bibr" rid="pone.0068577-Loomis1">[23]</xref>
, without any cutaneous activity at all, can be sufficient to permit the perception of shape
<xref ref-type="bibr" rid="pone.0068577-Clark1">[24]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-Magee1">[27]</xref>
. For example, experimenters in the study by Magee and Kennedy
<xref ref-type="bibr" rid="pone.0068577-Magee1">[27]</xref>
guided blindfolded participants’ fingers along the outlines of drawings of familiar objects; even though there was no cutaneous information at all (the participants’ fingers were not allowed to touch the drawings), the participants were able to successfully identify the depicted objects.</p>
<p>From the previous review of the literature, it is clear that shape perception can occur from static touch
<xref ref-type="bibr" rid="pone.0068577-Pont1">[7]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-Goodwin1">[9]</xref>
. It is also clear that active object manipulation
<xref ref-type="bibr" rid="pone.0068577-Lederman1">[17]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-Kappers1">[22]</xref>
can facilitate shape perception. The kinesthetic information that accompanies active manipulation is an important source of information in its own right, apart from the shape-related information detected and transmitted by cutaneous receptors in the skin. Tactile acuity is conventionally measured in a static, passive manner (e.g., by the application of a tactile grating to an immobilized participant’s fingertip). Because aging has been shown to lead to significant deteriorations in tactile acuity, it is likely that older adults will also exhibit a reduced ability to discriminate curvature from static touch in the current experiments (because both static shape and tactile acuity tasks, such as tactile grating orientation discrimination, depend upon cutaneous input). If an age-related deficit in discriminating curvature from static touch is observed in the current experiments, it will not necessarily occur for dynamic touch (because older adults may be able to compensate by relying on the kinesthetic information that accompanies their own exploratory movements). The purpose of the current set of experiments was to explore this issue and compare younger and older adults’ abilities to discriminate surface curvature when they employ static and dynamic touch.</p>
</sec>
<sec id="s2">
<title>Experiment 1</title>
<sec id="s2a">
<title>Methods</title>
<sec id="s2a1">
<title>Participants and ethics</title>
<p>Eight older adults (mean age was 75.6 years, SD = 4.5; their ages ranged from 71 to 85 years) and 8 younger adults (mean age was 22.1 years, SD = 3.0; their ages ranged from 20 to 29 years) participated in the experiment. The participants were either students at Western Kentucky University or were recruited from the local community (Warren County, Kentucky); three of the younger participants were coauthors (ABC, DNL, KET). All participants gave written consent prior to participation in the experiment. All of the participants (except the three coauthors) were naïve and unaware of the purposes of the experiment. The experiment was approved by the Western Kentucky University Human Subjects Review Board.</p>
</sec>
<sec id="s2a2">
<title>Apparatus</title>
<p>The order of presentation of the experimental stimuli was randomly determined for each participant by an Apple MacBook computer. The participants’ responses were entered into the computer for later analysis.</p>
</sec>
<sec id="s2a3">
<title>Experimental stimuli</title>
<p>The stimulus objects were the same as those used by Pont et al.
<xref ref-type="bibr" rid="pone.0068577-Pont1">[7]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-Pont2">[8]</xref>
; the curved blocks were 20 cm long, 2 cm wide, and approximately 5 cm tall. Their top surfaces were curved either in a convex or concave circular arc (see
<xref ref-type="fig" rid="pone-0068577-g001">Figure 1</xref>
); the curvature magnitudes ranged from 0.2 to 2.2/m. The curved blocks were made from PVC (polyvinyl chloride) using a computer-controlled milling machine. In addition to the surface curvature task, we evaluated the participants’ tactile acuity using tactile gratings (JVP Domes, Stoelting, Inc.;
<xref ref-type="bibr" rid="pone.0068577-VanBoven1">[28]</xref>
). In particular, we used a set of tactile gratings where the groove widths ranged from 6 to 0.5 mm (6, 5, 4, 3, 2, 1.5, 1.2, 1.0, 0.75, & 0.5 mm).</p>
<fig id="pone-0068577-g001" orientation="portrait" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0068577.g001</object-id>
<label>Figure 1</label>
<caption>
<title>Photographs of ten of the stimulus objects.</title>
<p>The objects with concave upper surfaces are shown on the left, while those with convex upper surfaces are presented on the right. The surface curvatures increase from 0.2 m
<sup>−1</sup>
(located at the bottom) to 1.8 m
<sup>−1</sup>
(located at the top).</p>
</caption>
<graphic xlink:href="pone.0068577.g001"></graphic>
</fig>
</sec>
<sec id="s2a4">
<title>Procedure</title>
<p>The procedures for the curvature discrimination task were similar to those of Pont et al.
<xref ref-type="bibr" rid="pone.0068577-Pont1">[7]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-Pont2">[8]</xref>
. The participants reached through an occluding curtain to feel the upper surface of the experimental stimuli. They used their three middle fingers to touch the upper surface of the curved blocks (see
<xref ref-type="fig" rid="pone-0068577-g002">Figure 2</xref>
); once contact was made with the block, the participants were not allowed to move their fingers (i.e., they used static touch). This was analogous to condition “6 normal” of Pont et al.
<xref ref-type="bibr" rid="pone.0068577-Pont1">[7]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-Pont2">[8]</xref>
. Goodwin et al.
<xref ref-type="bibr" rid="pone.0068577-Goodwin1">[9]</xref>
found that the least amount of curvature that could be detected with a single stationary fingertip was 5.15/m (4.9/m for convex curvatures & 5.4/m for concave curvatures). In order to obtain the best performance (i.e., the lowest thresholds) for discriminations of static curvature, our participants therefore needed to use multiple fingertips simultaneously to sample the curvature of the blocks. The participants’ task on each trial was to judge whether any given stimulus block was convex or concave. The participants were given an unlimited amount of time to touch the experimental stimuli; most judgments, however, were made within two to three seconds (it is not surprising that the participants made their judgments rapidly; Srinivasan & LaMotte
<xref ref-type="bibr" rid="pone.0068577-Srinivasan1">[12]</xref>
demonstrated that there is considerable adaptation in the responses of cutaneous sensory receptors within one second of the application of a touch stimulus, see their
<xref ref-type="fig" rid="pone-0068577-g003">Figure 3</xref>
).</p>
<fig id="pone-0068577-g002" orientation="portrait" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0068577.g002</object-id>
<label>Figure 2</label>
<caption>
<title>A photograph demonstrating how the participants used static touch when making a judgment in Experiment 1.</title>
</caption>
<graphic xlink:href="pone.0068577.g002"></graphic>
</fig>
<fig id="pone-0068577-g003" orientation="portrait" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0068577.g003</object-id>
<label>Figure 3</label>
<caption>
<title>Experimental results for static curvature discrimination.</title>
<p>A: The participants' overall curvature discrimination thresholds are plotted separately for each age group. The error bars indicate ± one SE. B: The individual younger and older participants' curvature discrimination thresholds are plotted as a function of age. The younger coauthors’ thresholds are depicted with open triangles, while thresholds for the younger non-authors are presented using open circles. The older participants’ thresholds are indicated by the filled circles.</p>
</caption>
<graphic xlink:href="pone.0068577.g003"></graphic>
</fig>
<p>An experimental session began with participants judging a block of 40 trials (20 trials with convex blocks & 20 trials with concave blocks, all presented in a random order) at the highest curvature (which was either 2.2 or 1.8/m). Pilot testing revealed that older adults were less sensitive to curvature; because of this, their testing began with blocks that possessed a curvature of 2.2/m. Succeeding blocks of 40 trials with lower curvatures (e.g., 1.4, 1.0, 0.6, & 0.2/m) were run, until the participants’ curvature discrimination performance dropped below a d’ value of 1.35. Once we had found curvature values that produced performance above and below each participant’s discrimination threshold (i.e., those curvatures that produced d’ values above and below 1.35), linear interpolation was used to calculate the final threshold estimate.</p>
<p>Similar procedures were used to measure the participants’ tactile acuity. Tactile gratings were briefly (approximately 1.0 seconds) applied manually
<xref ref-type="bibr" rid="pone.0068577-Norman2">[2]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-VanBoven1">[28]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-Norman4">[30]</xref>
to the distal fingerpad of the index finger; the grooves of the gratings were oriented either parallel or perpendicular to the long axis of the finger. The participants’ task was to judge (without vision) whether the grating’s orientation was parallel or perpendicular. Successive blocks of 40 trials (20 parallel trials & 20 perpendicular trials, all in a random order) with decreasing groove width were run, until each participant’s grating orientation discrimination performance dropped below a d’ value of 1.35. The threshold estimate was then calculated in an identical manner to that obtained for the surface curvature discrimination task. The initial groove width used for the younger participants was 3 mm. Larger initial groove widths (4 to 6 mm) were needed to determine thresholds for the older participants, because of the well known age-related deterioration in tactile acuity
<xref ref-type="bibr" rid="pone.0068577-Norman1">[1]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-Woodward1">[5]</xref>
.</p>
</sec>
</sec>
<sec id="s2b">
<title>Results and Discussion</title>
<p>The older and younger participants’ results are shown in
<xref ref-type="fig" rid="pone-0068577-g003">Figures 3</xref>
and
<xref ref-type="fig" rid="pone-0068577-g004">4</xref>
for the curvature and grating orientation discrimination tasks, respectively. As is readily evident, there were significant effects of age for both tasks (curvature discrimination: t(14) = 3.3, p<.006, 2-tailed; grating orientation discrimination: t(14) = 4.8, p<.001, 2-tailed). On average, the older participants’ thresholds were 66.4 percent higher than those of the younger participants for the surface curvature discrimination task, and were more than three times (3.23 times) higher than those of the younger participants for the grating orientation task. The thresholds for the younger participants who were coauthors (ABC, DNL, KET) were not significantly different from the non-author younger participants for both tasks (curvature discrimination: t(6) = 0.2, p = .87; grating orientation discrimination: t(6) = 1.9, p>.1). As can be seen in
<xref ref-type="fig" rid="pone-0068577-g003">Figures 3</xref>
and
<xref ref-type="fig" rid="pone-0068577-g004">4</xref>
, the effect sizes were large (Cohen’s d was 1.66 & 2.98 for the curvature and grating orientation discrimination tasks, respectively). Given the effect sizes and the number of participants in each age group, the resulting power (for a 2-tailed test, α = .05) was 0.91 and 0.99 for the curvature and grating orientation discrimination tasks, respectively. This means, for example, that given the size of the obtained effects and the magnitude of the inter-participant variability, that we had a 91 to 99 percent chance of detecting the effects with our chosen sample size.</p>
<fig id="pone-0068577-g004" orientation="portrait" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0068577.g004</object-id>
<label>Figure 4</label>
<caption>
<title>Experimental results (Tactile Acuity).</title>
<p>The participants' grating orientation thresholds are plotted separately for each age group. The error bars indicate ± one SE.</p>
</caption>
<graphic xlink:href="pone.0068577.g004"></graphic>
</fig>
<p>Given that all of the participants performed both tactile judgments (curvature discrimination & grating orientation discrimination), we decided to evaluate whether there is any relationship between the performances obtained for these two tasks. We found that there was no significant correlation (Older participants: Pearson r = −0.2, r
<sup>2</sup>
 = 0.04, p = .62; Younger participants: Pearson r = 0.004, r
<sup>2</sup>
<.001, p = .99). Thus, if any given participant performs well for curvature discrimination, it tells us nothing about their tactile acuity; conversely, high tactile acuity does not reveal anything about a participant’s ability to discriminate surface curvature.</p>
</sec>
</sec>
<sec id="s3">
<title>Experiment 2</title>
<p>The results of Experiment 1 demonstrate that older adults can reliably discriminate surface curvature. However, their ability to detect differences in static curvature is impaired relative to the abilities of younger adults (see
<xref ref-type="fig" rid="pone-0068577-g003">Figure 3</xref>
). It is important to keep in mind that this age-related impairment for static touch might not necessarily occur for dynamic touch. This is because during active touch kinesthetic and proprioceptive information is available in addition to cutaneous information from the hand and fingers
<xref ref-type="bibr" rid="pone.0068577-Gibson1">[18]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-Clark1">[24]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-Shimansky1">[26]</xref>
. It is conceivable that older adults could compensate for the reduction in cutaneous information about static curvature by taking best advantage of the proprioceptive information that occurs during active haptic manipulation. The purpose of Experiment 2 was to examine this possibility by allowing our participants to actively feel the experimental stimuli while discriminating surface curvature.</p>
</sec>
<sec id="s4">
<title></title>
<sec sec-type="methods" disp-level="2" id="s4a">
<title>Methods</title>
<sec id="s4a1">
<title>Participants and ethics</title>
<p>The participants were 14 naïve adults, none of whom had participated in Experiment 1. Seven of the participants were 66 years of age or older (mean age was 71.9 years, SD = 3.4; ages ranged from 66 to 77 years), while the remaining seven participants were 25 years of age or younger (mean age was 22.0 years, SD = 1.4; ages ranged from 21 to 25 years). The participants were either students at Western Kentucky University or were recruited from the local community (Warren County, Kentucky). All participants gave written consent prior to participation in the experiment. The experiment was approved by the Western Kentucky University Human Subjects Review Board.</p>
</sec>
<sec id="s4a2">
<title>Apparatus</title>
<p>The apparatus was the same as that used in Experiment 1.</p>
</sec>
<sec id="s4a3">
<title>Experimental stimuli</title>
<p>The stimulus objects were the same as those used in Experiment 1.</p>
</sec>
<sec id="s4a4">
<title>Procedure</title>
<p>The basic procedure and task was identical to that used in Experiment 1. The participants would reach through an occluding curtain and feel a single stimulus block on any given trial. In this experiment, however, the participants would actively feel the middle 10-cm section of each curved block’s upper surface with a single index finger. As in Experiment 3 of Pont et al.
<xref ref-type="bibr" rid="pone.0068577-Pont2">[8]</xref>
, the participants’ finger movements were limited (i.e., restricted to 10 cm) by an aperture. Once again, the participants had an unlimited amount of time to feel each curved surface and determine whether it was convex or concave; most of the judgments were made within two to three seconds.</p>
<p>The remainder of the procedures for the curvature discrimination and tactile acuity tasks were identical to those used in Experiment 1. Successive blocks of 40 trials were once again run for both tasks, with decreasing curvature and groove width, until performance dropped below a d’ value of 1.35. The final threshold estimates were calculated in the same manner as was done in Experiment 1.</p>
</sec>
</sec>
<sec disp-level="2" id="s4b">
<title>Results and discussion</title>
<p>The results of the dynamic curvature discrimination task are shown in
<xref ref-type="fig" rid="pone-0068577-g005">Figure 5</xref>
, while the results for the tactile grating orientation task are shown in
<xref ref-type="fig" rid="pone-0068577-g006">Figure 6</xref>
. Once again, there was a significant effect of age upon tactile acuity (t(12) = 3.7, p = .003, 2-tailed): the older participants’ grating orientation thresholds were more than double those of the younger participants (see
<xref ref-type="fig" rid="pone-0068577-g006">Figure 6</xref>
). However, the pattern of results obtained for the curvature discrimination task was unlike that observed in Experiment 1. In this experiment, there was no effect of age (see
<xref ref-type="fig" rid="pone-0068577-g005">Figure 5</xref>
) upon the participants’ curvature discrimination thresholds (t(12) = 0.07, p = .94, 2-tailed). The individual participants’ curvature discrimination thresholds are shown in the right panel of
<xref ref-type="fig" rid="pone-0068577-g005">Figure 5</xref>
. One can see from this figure that the distributions for the younger and older participants overlap completely, and that within the group of older participants themselves, increases in age did not make any difference – i.e., performance for the 77 year-old participant was just as good as (actually better than) that exhibited by the 66 year-old participant. The difference between the average curvature discrimination thresholds of the younger and older participants (left panel of
<xref ref-type="fig" rid="pone-0068577-g005">Figure 5</xref>
) was 0.01/m; a power analysis revealed that a total of 25,002 participants (12,501 older participants and 12,501 younger participants) would be needed to have a 90 percent chance of detecting a difference this small. It is readily apparent that even if this difference (curvature discrimination thresholds of 0.587 vs. 0.577/m) did exist in the general population, it is of no practical or meaningful importance.</p>
<fig id="pone-0068577-g005" orientation="portrait" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0068577.g005</object-id>
<label>Figure 5</label>
<caption>
<title>Experimental results for dynamic curvature discrimination.</title>
<p>A: The participants' overall curvature discrimination thresholds are plotted separately for each age group. The error bars indicate ± one SE. B: The individual younger (open circles) and older participants' (filled circles) curvature discrimination thresholds are plotted as a function of age.</p>
</caption>
<graphic xlink:href="pone.0068577.g005"></graphic>
</fig>
<fig id="pone-0068577-g006" orientation="portrait" position="float">
<object-id pub-id-type="doi">10.1371/journal.pone.0068577.g006</object-id>
<label>Figure 6</label>
<caption>
<title>Experimental results (Tactile Acuity).</title>
<p>The participants' grating orientation thresholds are plotted separately for each age group. The error bars indicate ± one SE.</p>
</caption>
<graphic xlink:href="pone.0068577.g006"></graphic>
</fig>
<p>A 2-way between-subjects analysis of variance (ANOVA) was conducted to compare the results obtained for static (Experiment 1) and dynamic (Experiment 2) touch. The results of the ANOVA revealed that there were main effects of both touch type (static vs. dynamic, F(1, 26) = 10.3, p = .003, partial
<inline-formula>
<inline-graphic xlink:href="pone.0068577.e001.jpg"></inline-graphic>
</inline-formula>
 = .29) and age (F(1, 26) = 5.6, p<.03, partial
<inline-formula>
<inline-graphic xlink:href="pone.0068577.e002.jpg"></inline-graphic>
</inline-formula>
 = .18). However, it is readily evident from a comparison of
<xref ref-type="fig" rid="pone-0068577-g003">Figures 3</xref>
and
<xref ref-type="fig" rid="pone-0068577-g005">5</xref>
that the large effect of age obtained for static touch disappeared when the participants dynamically explored the curvature of the experimental stimuli (i.e., there was a significant interaction: F(1, 26) = 5.1, p = .03, partial
<inline-formula>
<inline-graphic xlink:href="pone.0068577.e003.jpg"></inline-graphic>
</inline-formula>
 = .17).</p>
</sec>
</sec>
<sec id="s5">
<title>General Discussion</title>
<p>The results of Experiment 1 clearly indicate that aging has significant and large effects upon the ability to discriminate surface curvature by static touch (
<xref ref-type="fig" rid="pone-0068577-g003">Figure 3</xref>
); this large effect of age resembles the well-known deterioration that occurs in tactile acuity
<xref ref-type="bibr" rid="pone.0068577-Norman1">[1]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-VegaBermudez2">[6]</xref>
(also see
<xref ref-type="fig" rid="pone-0068577-g004">Figure 4</xref>
). Apparently, aging negatively affects performance for multiple static tactile tasks. However, it is interesting in this context to note that performance for the current two static tasks (the grating orientation task used to evaluate tactile acuity and static surface curvature discrimination) do not correlate to any appreciable degree, either for older or younger adults.</p>
<p>In comparison to Experiment 1, the participants’ performance improved (thresholds were lower, compare
<xref ref-type="fig" rid="pone-0068577-g003">Figures 3</xref>
and
<xref ref-type="fig" rid="pone-0068577-g005">5</xref>
) when information obtained by dynamic touch was available – this was especially true for the older participants. Many studies have similarly shown that active touch leads to better shape perception than passive touch
<xref ref-type="bibr" rid="pone.0068577-Lederman1">[17]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-Kappers1">[22]</xref>
. It is also clear from the results of Experiment 2 that there was no significant effect of age upon the ability to discriminate surface curvature from dynamic touch (
<xref ref-type="fig" rid="pone-0068577-g005">Figure 5</xref>
). One possibility for the equal ability of older adults to dynamically perceive and discriminate surface curvature (despite the fact that older adults’ static curvature discrimination is impaired) is the availability of kinesthetic information during active/dynamic exploration
<xref ref-type="bibr" rid="pone.0068577-Loomis1">[23]</xref>
. It is well known that the kinesthetic and proprioceptive information that accompanies hand and arm movements permits the perception of object shape all on its own, apart from the information about shape provided by cutaneous receptors in the skin
<xref ref-type="bibr" rid="pone.0068577-Gibson1">[18]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-Clark1">[24]</xref>
–
<xref ref-type="bibr" rid="pone.0068577-Magee1">[27]</xref>
. While previous studies have found that kinesthetic and cutaneous inputs provide similar information enabling the recognition of raised-line drawings
<xref ref-type="bibr" rid="pone.0068577-Voisin1">[31]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-Symmons1">[32]</xref>
, other studies have found kinesthetic information to predominate
<xref ref-type="bibr" rid="pone.0068577-Loo1">[25]</xref>
,
<xref ref-type="bibr" rid="pone.0068577-Magee1">[27]</xref>
. For example, in one condition of a study by Magee and Kennedy
<xref ref-type="bibr" rid="pone.0068577-Magee1">[27]</xref>
, the experimenters guided participants’ hands along the outer contours of drawings of familiar objects (no cutaneous input). In another condition, the experimenters moved the contours of raised-line drawings underneath participants’ stationary fingertips (no kinesthetic input). The participants in this study who had access to kinesthetic information (but not cutaneous information) recognized many more depicted objects than those participants who only had access to cutaneous (but not kinesthetic) information. In the current study, the curvature discrimination performance of both older and younger participants improved in Experiment 2 when kinesthetic information (resulting from dynamic touch) was available. The magnitude of the improvement was larger, however, for the older participants; this larger improvement for the older participants allowed them to perform just as well as the younger participants (see
<xref ref-type="fig" rid="pone-0068577-g005">Figure 5</xref>
). If it was the kinesthetic information available in Experiment 2 that permitted the older participants to perform as well as the younger participants, it seems likely that we would probably also have obtained similar results (i.e., no effect of age for dynamic curvature discrimination) if we had removed cutaneous information altogether and required our participants to judge curvatures solely from kinesthetic input.</p>
<p>Given our current findings that the negative effects of increased age only exist for static touch (
<xref ref-type="fig" rid="pone-0068577-g003">Figure 3</xref>
) and do not occur for situations involving active touch (
<xref ref-type="fig" rid="pone-0068577-g005">Figure 5</xref>
), it is unlikely that the deficits found in the current study significantly impair many of the everyday activities of older adults.</p>
</sec>
<sec sec-type="conclusions" id="s6">
<title>Conclusions</title>
<p>Aging is accompanied by substantive deficits in static, but not dynamic, surface curvature discrimination.</p>
</sec>
</body>
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