<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD with MathML3 v1.3 20210610//EN"  "JATS-archivearticle1-3-mathml3.dtd"><article xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.3"><front><journal-meta><journal-id journal-id-type="nlm-ta">elife</journal-id><journal-id journal-id-type="publisher-id">eLife</journal-id><journal-title-group><journal-title>eLife</journal-title></journal-title-group><issn publication-format="electronic" pub-type="epub">2050-084X</issn><publisher><publisher-name>eLife Sciences Publications, Ltd</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">105946</article-id><article-id pub-id-type="doi">10.7554/eLife.105946</article-id><article-id pub-id-type="doi" specific-use="version">10.7554/eLife.105946.4</article-id><article-version article-version-type="publication-state">version of record</article-version><article-categories><subj-group subj-group-type="display-channel"><subject>Research Article</subject></subj-group><subj-group subj-group-type="heading"><subject>Neuroscience</subject></subj-group></article-categories><title-group><article-title>Tactile localization of the breast, areola, and nipple</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Long</surname><given-names>Katie H</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="fn" rid="con1"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author"><name><surname>Fitzgerald</surname><given-names>Emily E</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="con2"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author"><name><surname>Berger-Wolf</surname><given-names>Ev I</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="fn" rid="con3"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author"><name><surname>Fawaz</surname><given-names>Amani</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="con4"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author"><name><surname>Lindau</surname><given-names>Stacy T</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0002-9054-6538</contrib-id><xref ref-type="aff" rid="aff4">4</xref><xref ref-type="aff" rid="aff5">5</xref><xref ref-type="aff" rid="aff6">6</xref><xref ref-type="other" rid="fund1"/><xref ref-type="other" rid="fund2"/><xref ref-type="fn" rid="con5"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author" equal-contrib="yes"><name><surname>Bensmaia</surname><given-names>Sliman J</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0003-4039-9135</contrib-id><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff7">7</xref><xref ref-type="fn" rid="equal-contrib1">†</xref><xref ref-type="fn" rid="con6"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author" corresp="yes" equal-contrib="yes"><name><surname>Greenspon</surname><given-names>Charles M</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0002-6806-3302</contrib-id><email>cmgreenspon@uchicago.edu</email><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="equal-contrib1">†</xref><xref ref-type="fn" rid="con7"/><xref ref-type="fn" rid="conf2"/></contrib><aff id="aff1"><label>1</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/024mw5h28</institution-id><institution>Committee on Computational Neuroscience, University of Chicago</institution></institution-wrap><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff><aff id="aff2"><label>2</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/024mw5h28</institution-id><institution>Department of Organismal Biology and Anatomy, University of Chicago</institution></institution-wrap><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff><aff id="aff3"><label>3</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/0217hb928</institution-id><institution>Department of Neuroscience, Middlebury College</institution></institution-wrap><addr-line><named-content content-type="city">Middlebury</named-content></addr-line><country>United States</country></aff><aff id="aff4"><label>4</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/024mw5h28</institution-id><institution>Department of Obstetrics and Gynecology, University of Chicago</institution></institution-wrap><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff><aff id="aff5"><label>5</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/024mw5h28</institution-id><institution>Department of Medicine-Geriatrics and Palliative Medicine, University of Chicago</institution></institution-wrap><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff><aff id="aff6"><label>6</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/024mw5h28</institution-id><institution>Comprehensive Cancer Center, University of Chicago</institution></institution-wrap><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff><aff id="aff7"><label>7</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/024mw5h28</institution-id><institution>Neuroscience Institute, University of Chicago</institution></institution-wrap><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff></contrib-group><contrib-group content-type="section"><contrib contrib-type="editor"><name><surname>Makin</surname><given-names>Tamar R</given-names></name><role>Reviewing Editor</role><aff><institution-wrap><institution-id institution-id-type="ror">https://ror.org/013meh722</institution-id><institution>University of Cambridge</institution></institution-wrap><country>United Kingdom</country></aff></contrib><contrib contrib-type="senior_editor"><name><surname>Makin</surname><given-names>Tamar R</given-names></name><role>Senior Editor</role><aff><institution-wrap><institution-id institution-id-type="ror">https://ror.org/013meh722</institution-id><institution>University of Cambridge</institution></institution-wrap><country>United Kingdom</country></aff></contrib></contrib-group><author-notes><fn fn-type="con" id="equal-contrib1"><label>†</label><p>These authors contributed equally to this work</p></fn></author-notes><pub-date publication-format="electronic" date-type="publication"><day>11</day><month>06</month><year>2026</year></pub-date><volume>14</volume><elocation-id>RP105946</elocation-id><history><date date-type="sent-for-review" iso-8601-date="2025-01-19"><day>19</day><month>01</month><year>2025</year></date></history><pub-history><event><event-desc>This manuscript was published as a preprint.</event-desc><date date-type="preprint" iso-8601-date="2025-02-02"><day>02</day><month>02</month><year>2025</year></date><self-uri content-type="preprint" xlink:href="https://doi.org/10.1101/2022.09.14.507974"/></event><event><event-desc>This manuscript was published as a reviewed preprint.</event-desc><date date-type="reviewed-preprint" iso-8601-date="2025-04-08"><day>08</day><month>04</month><year>2025</year></date><self-uri content-type="reviewed-preprint" xlink:href="https://doi.org/10.7554/eLife.105946.1"/></event><event><event-desc>The reviewed preprint was revised.</event-desc><date date-type="reviewed-preprint" iso-8601-date="2025-11-13"><day>13</day><month>11</month><year>2025</year></date><self-uri content-type="reviewed-preprint" xlink:href="https://doi.org/10.7554/eLife.105946.2"/></event><event><event-desc>The reviewed preprint was revised.</event-desc><date date-type="reviewed-preprint" iso-8601-date="2026-05-15"><day>15</day><month>05</month><year>2026</year></date><self-uri content-type="reviewed-preprint" xlink:href="https://doi.org/10.7554/eLife.105946.3"/></event></pub-history><permissions><copyright-statement>© 2025, Long et al</copyright-statement><copyright-year>2025</copyright-year><copyright-holder>Long et al</copyright-holder><ali:free_to_read/><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><ali:license_ref>http://creativecommons.org/licenses/by/4.0/</ali:license_ref><license-p>This article is distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use and redistribution provided that the original author and source are credited.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="elife-105946-v1.pdf"/><self-uri content-type="figures-pdf" xlink:href="elife-105946-figures-v1.pdf"/><abstract><p>Touch plays a key role in our perception of our body and shapes our interactions with the world, from the objects we manipulate to the people we touch. While the tactile sensibility of the hand has been extensively characterized, much less is known about touch on other parts of the body. Despite the important role of the breast in lactation, as well as in affective and sexual touch, relatively little is known about its sensory properties. To fill this gap, we investigated the ability of women to locate touches on the breast and compared it to that of the hand and back, body regions that span the range of tactile discriminative capabilities. First, we found that the tactile precision of the breast was even lower than that of the back, heretofore the paragon of poor precision. Second, precision was lower for breasts that had undergone greater expansion, consistent with the hypothesis that innervation capacity does not scale with body size. Third, touches to different regions of the nipple were largely indistinguishable, suggesting sparse innervation density. Fourth, localization errors were systematically biased toward the nipple.</p></abstract><kwd-group kwd-group-type="author-keywords"><kwd>breast</kwd><kwd>touch</kwd><kwd>affective</kwd></kwd-group><kwd-group kwd-group-type="research-organism"><title>Research organism</title><kwd>Human</kwd></kwd-group><funding-group><award-group id="fund1"><funding-source><institution-wrap><institution-id institution-id-type="ror">https://ror.org/02t771148</institution-id><institution>National Cancer Institute</institution></institution-wrap></funding-source><award-id>R21CA226726</award-id><principal-award-recipient><name><surname>Lindau</surname><given-names>Stacy T</given-names></name></principal-award-recipient></award-group><award-group id="fund2"><funding-source><institution-wrap><institution-id institution-id-type="ror">https://ror.org/02t771148</institution-id><institution>National Cancer Institute</institution></institution-wrap></funding-source><award-id>R01CA281301</award-id><principal-award-recipient><name><surname>Lindau</surname><given-names>Stacy T</given-names></name></principal-award-recipient></award-group><award-group id="fund3"><funding-source><institution-wrap><institution-id institution-id-type="ror">https://ror.org/01s5ya894</institution-id><institution>National Institute of Neurological Disorders and Stroke</institution></institution-wrap></funding-source><award-id>NS122333</award-id><principal-award-recipient><name><surname>Bensmaia</surname><given-names>Sliman J</given-names></name></principal-award-recipient></award-group><award-group id="fund4"><funding-source><institution-wrap><institution>University of Chicago Women's Board</institution></institution-wrap></funding-source><principal-award-recipient><name><surname>Lindau</surname><given-names>Stacy T</given-names></name></principal-award-recipient></award-group><funding-statement>The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.</funding-statement></funding-group><custom-meta-group><custom-meta specific-use="meta-only"><meta-name>Author impact statement</meta-name><meta-value>The breast, despite its importance in sexual and affective touch, exhibits poor tactile localization and demonstrates a relationship between size and innervation density.</meta-value></custom-meta><custom-meta specific-use="meta-only"><meta-name>publishing-route</meta-name><meta-value>prc</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>The sense of touch fulfills a variety of different functions in everyday life, from guiding our interactions within the environment to supporting affective communication and sexual function (<xref ref-type="bibr" rid="bib23">McGlone et al., 2014</xref>). One of the key properties of touch sensations is that they are localized to a specific part of the body: contact on the shoulder produces a sensation experienced on the shoulder, for example. The precision with which we can localize events on the skin has been shown to be determined by the innervation density at that location (<xref ref-type="bibr" rid="bib3">Corniani and Saal, 2020</xref>; <xref ref-type="bibr" rid="bib6">Craig and Lyle, 2001</xref>). Because the skin of the fingertips and lips is the most densely innervated, the precision of these body regions is highest, conferring to us an enhanced ability to distinguish touches on the fingers even when they are close to each other. Innervation density and function are intrinsically related: the fingertips are thought to be densely innervated because they account for the vast majority of contacts with objects, and precise information about object interactions is critical to dexterous manipulation (<xref ref-type="bibr" rid="bib17">Johansson and Vallbo, 1979</xref>; <xref ref-type="bibr" rid="bib7">Edmondson et al., 2022</xref>). In contrast, the precision on the back is low because precise localization of a touch on the back is of limited value. Skin surface area also plays a role in innervation density; for example, people with large hands exhibit lower precision than those with small ones (<xref ref-type="bibr" rid="bib25">Peters et al., 2009</xref>; <xref ref-type="bibr" rid="bib30">Wong et al., 2013</xref>). This phenomenon is hypothesized to reflect the fact that the number of nerve fibers does not scale with body size: a large body will be more sparsely innervated than a small one given a fixed number of nerve fibers.</p><p>While tactile precision has been extensively studied on the limbs and face, precision on the torso has received far less experimental attention (<xref ref-type="bibr" rid="bib22">Mancini et al., 2014</xref>; <xref ref-type="bibr" rid="bib29">Weinstein, 1968</xref>), with the breast being largely ignored beyond its anatomy (<xref ref-type="bibr" rid="bib19">Longo et al., 2014</xref>; <xref ref-type="bibr" rid="bib26">Tairych et al., 1998</xref>). To fill this gap, we sought to characterize the spatial precision of the female breast, which has roles in lactation, affective touch, and sex. These functions set it apart from other regions of the body. In previous studies, the tactile precision of the breast was found to be comparably low to that of the back and calf (<xref ref-type="bibr" rid="bib29">Weinstein, 1968</xref>). However, the experimental approaches have received scrutiny to their susceptibility to inaccuracies (<xref ref-type="bibr" rid="bib5">Craig and Johnson, 2000</xref>); only the outer breast was tested (excluding the nipple-areolar complex [NAC]), and the relationship with breast size was not assessed, or only examined the NAC but not the outer breast (<xref ref-type="bibr" rid="bib19">Longo et al., 2014</xref>). Given that the timeline for breast development extends well past that of nervous system development (<xref ref-type="bibr" rid="bib16">Javed and Lteif, 2013</xref>), the female breast offers a powerful test of the fixed innervation hypothesis, which would predict that people with larger breasts would have poorer spatial precision than people with smaller ones.</p><p>In the present study, we first measured the tactile precision of two regions of the breast in women – the outer (lateral) breast and medial breast, which includes the NAC – and compared these to the hand and back. Second, we examined the relationship between the precision of the outer breast and breast size. Third, we examined women’s ability to judge the absolute location of touches to their breast. We first found that the spatial precision of the breast is very low, with similar sensitivity to the back. Second, spatial precision is inversely correlated with breast size, as predicted from the fixed innervation hypothesis. Third, touches to different parts of the nipple are indistinguishable, suggesting sparse tactile innervation. Fourth, touches on the outer breast are systematically mislocalized as being closer to the nipple than they actually are.</p></sec><sec id="s2" sec-type="results"><title>Results</title><sec id="s2-1"><title>The breast has low spatial precision</title><p>We first measured each participant’s ability to judge the relative position of two touches applied in succession at two nearby locations on the skin of the hand, back, and breast using a punctate probe. The first of the two touches (the reference) was at the same position on each trial, and the second touch (the comparison) was either above or below the first at a pre-specified distance. For the hand, distances ranged from 1 to 10 mm; for the other body regions, distances ranged from 2.5 to 40 mm, anticipating lower precision based on preliminary testing (<xref ref-type="fig" rid="fig1">Figure 1</xref>). The participant’s task was to report whether the test stimulus was located above or below the reference stimulus. We then assessed the participant’s performance as a function of the distance between the test and reference and characterized the distance from the reference required to reliably locate the test stimulus – the just noticeable difference (JND) – for each participant and region.</p><fig-group><fig id="fig1" position="float"><label>Figure 1.</label><caption><title>Location discrimination.</title><p>(<bold>A</bold>) Example psychometric functions for one subject on the location discrimination task for the hand, back, outer breast, and medial breast (including NAC). Negative values denote test points ‘below’ the reference and the JND indicates the distance at which the subject could reliably (75% trials) locate the stimulus. (<bold>B</bold>) Distribution of JNDs for each subject at each region. (<bold>C</bold>) Relationship between the difference in size between the bust and underbust (Δ Bust) and the JND of the lateral breast and (<bold>D</bold>) medial breast, respectively.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-105946-fig1-v1.tif"/></fig><fig id="fig1s1" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 1.</label><caption><title>Spatial precision across regions.</title><p>Relationship between the delta bust (bust – underbust) and the spatial precision (JND) for the (<bold>A</bold>) hand and (<bold>B</bold>) back.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-105946-fig1-figsupp1-v1.tif"/></fig></fig-group><p>As expected, the hand demonstrated significantly greater spatial precision (median [25th, 75th] percentiles: 2.16 [1.73, 2.93] mm) than either the back (5.72 [4.36, 8.16] mm) or either breast region (6.63 [5.41, 7.73] mm and 8.00 [5.72, 10.80] mm, for the lateral and medial breast, respectively) as indicated by the lower JNDs (<xref ref-type="fig" rid="fig1">Figure 1A, B</xref> and 1-way ANOVA: F<sub>[3,126]</sub>=22.7, p&lt;0.01; Tukey’s HSD post-hoc t-test: p&lt;0.01). Interestingly, the medial breast yielded even shallower functions and lower spatial precision than did the back (<xref ref-type="fig" rid="fig1">Figure 1A, B</xref> and one-way ANOVA with Tukey’s HSD post-hoc t-test: p=0.0284), although no statistical differences were observed between the lateral breast and either the back or medial breast (p=0.3974 and 0.7377, respectively). In other words, touches needed to be between three and four times as far apart on the breast than on the hand to yield equivalent location discrimination performance.</p></sec><sec id="s2-2"><title>Tactile precision is worse for women with larger breasts</title><p>The spatial precision of the hand has been shown to depend on the size of the hand, with smaller hands yielding better precision (<xref ref-type="bibr" rid="bib25">Peters et al., 2009</xref>). With this observation in mind, we investigated whether the inter-participant differences in breast precision might be driven in part by differences in breast size. To determine the relative expansion (increase in surface area) of each participant’s breast, we computed the difference between their bust (circumference of the torso at the nipple line) and underbust (circumference of the torso at the inframammary fold). Comparing this value with their spatial precision, we found that the precision of the lateral breast decreased (JNDs increased) as breast size increased (<xref ref-type="fig" rid="fig1">Figure 1C</xref>, Pearson’s correlation with Bonferroni PHC (n=4): <italic>r</italic>=0.734, p&lt;0.01), a phenomenon that did not extend to the medial breast (<xref ref-type="fig" rid="fig1">Figure 1C</xref>), hand, or back (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1</xref>, p&gt;0.05 for all), implying that any expansion is preferentially limited to the skin of the lateral breast and that the observed relationship between breast size and precision was not spurious.</p></sec><sec id="s2-3"><title>Tactile events are poorly discriminated on the nipple</title><p>While the result that the medial breast has the lowest spatial resolution is not necessarily surprising given the lack of mechanoreceptors near the surface of the skin (<xref ref-type="bibr" rid="bib14">Gutiérrez-Villanueva et al., 2020</xref>), the magnitude of the correlation was unexpected. Indeed, we observed that the JNDs for each participant were, on average, only marginally smaller than the measured diameter of the nipple (80% ± 52%). This would imply that two points on opposite halves of the nipple (80% diameter apart) might be confused as the same point. Given that the NAC is inherently a heterogeneous structure as it is composed of three anatomically distinct regions of the breast (the nipple, the areola, and the nearby outer breast), we reasoned that this approach may be biased and thus not reflect the functional ability to locate sensations on the breast.</p><p>To assess if participants could reliably perceive tactile events at the level of either the areola or nipple, we delivered punctate touches to each quadrant on the nipple or areola and the participant reported the quadrant in which the touch had been delivered (<xref ref-type="fig" rid="fig2">Figure 2A</xref>). Specifically, we marked the edge of the nipple or the 50% point between the center of the nipple and the edge of the areola in each of the cardinal directions such that the proportional distance was constant across participants. When touching different quadrants of the areola, participants were able to reliably locate stimuli (<xref ref-type="fig" rid="fig2">Figure 2B</xref>, mean ± standard deviation: 55% ± 21% where chance is 25%, one-sided Monte-Carlo test, Z=15, p&lt;0.01), with 8 of the 10 participants performing significantly above chance (p&lt;0.05 after Bonferroni PHC where n=10). Of the remaining participants, one performed marginally above chance (40%, p=0.25 after Bonferroni PHC), whereas the other systematically misperceived the location and performed well below chance (7.5%, p=1 after Bonferroni PHC). On the nipple, however, participants were consistently worse at locating stimuli than the areola (Wilcoxon signed-rank test, p=0.0137) where only three of the ten participants outperformed chance, although the group as a whole outperformed chance (<xref ref-type="fig" rid="fig2">Figure 2B</xref>, 36% ± 13%; Z=5.5, p&lt;0.01). This finding suggests that the ability to locate tactile events is significantly worse at the nipple than at the areola, consistent with equivalent innervation and the smaller size of the nipple, and reaffirms our earlier finding that spatial precision at the medial breast is poor. Finally, to determine if this task was also influenced by spatial expansion, we sought to compare the breast size with performance on the quadrant task. Unfortunately, only four of the ten participants returned for measurement and while negative trends were observed, the sample size is insufficient for formal analysis.</p><fig id="fig2" position="float"><label>Figure 2.</label><caption><title>Spatial discrimination at the nipple and areola.</title><p>(<bold>A</bold>) Test locations for the quadrant discrimination task. The outer ring represents the areola and the inner ring the nipple. The subject reported location using a number from 1 to 4 progressing clockwise from ‘above’. (<bold>B</bold>) Proportion correct for participant at each test location. Solid markers indicate participants whose performance was significantly above chance (N=10).</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-105946-fig2-v1.tif"/></fig></sec><sec id="s2-4"><title>Localization of tactile events on the breast is biased towards the nipple</title><p>In the experiments described above, we investigated the participants’ ability to distinguish the relative locations of two touches to the breast. Next, we examined their ability to identify the absolute location of a tactile stimulus on their torso. To this end, we presented a single touch to the breast or the back with a punctate probe at one of 25 locations after which each participant marked the location of the touch on a three-dimensional digital image of the participant’s own breast or back (<xref ref-type="fig" rid="fig3">Figure 3A and B</xref>).</p><fig-group><fig id="fig3" position="float"><label>Figure 3.</label><caption><title>Absolute localization of contact events on the breast and back.</title><p>(<bold>A</bold>) Example localization task data for the breast or (<bold>B</bold>) back of one participant. Gray surface represents scanned torso. Black crosses indicate the true location of each stimulus, purple lines indicate the vector between the stimulus location and reported location, and blue lines indicate the vector between the stimulus location and average reported location across blocks. (<bold>C</bold>) Reporting error (3D Euclidean distance) as a function of distance across participants for the breast and (<bold>D</bold>) back. Error indicates mean error for each trial (mean of purple vector length in <bold>A, B</bold>), bias indicates the error of the average response (blue vectors in <bold>A, B</bold>), and imprecision is the mean pairwise error between individual responses for each point (distance between the end of purple vectors in <bold>A, B</bold>). (<bold>E</bold>) The distribution of angles (2D, no depth axis) between the stimulus location and the reported location (gray) or the difference between said angle and the angle towards the relevant landmark (red) for the breast (nipple) and (<bold>F</bold>) back (scapula).</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-105946-fig3-v1.tif"/></fig><fig id="fig3s1" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 1.</label><caption><title>Tactile localization performance of individual participants.</title><p>(<bold>A</bold>) Mean error for each participant across distances for the back and breast. Dashed line indicates unity. (<bold>B</bold>) Example 2D responses to localization task for the breast of one participant and the (<bold>C</bold>) back of another. Black crosses indicate the true location of each stimulus, purple lines indicate the vector between the stimulus location and reported location, and blue lines indicate the vector between the stimulus location and average reported location across blocks. (<bold>D</bold>) Cartesian coordinate plot of <xref ref-type="fig" rid="fig3">Figure 3E</xref> (breast) where individual participants are represented by lighter colors. (<bold>E</bold>) Same as (<bold>D</bold>) but for <xref ref-type="fig" rid="fig3">Figure 3F</xref> (back). (<bold>F</bold>) Unimodal vector strength of individual participants' biases for breast and back. Dashed line indicates unity, dotted line indicates 95th percentile of vector strength from a simulated uniform distribution matched for the number of angles over which vector strength was computed after discretization (N=11).</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-105946-fig3-figsupp1-v1.tif"/></fig></fig-group><p>To estimate the degree to which participants could accurately localize touch events, we computed the error for each body part across participants and found that, contrary to the precision task, participants had lower errors on their breasts in comparison to their back (<xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1A</xref>; paired t-test, t[9]=7.4, p&lt;0.001). Next, we computed this error as a function of the distance from the center landmark for each region (nipple or the inferior angle of the scapula, i.e. the bottom corner, <xref ref-type="fig" rid="fig3">Figure 3C and D</xref>) and found that in the case of the breast, the errors increased systematically as the distance from the nipple increased consistent with the quadrant localization task (Linear Mixed Model [LMM]: distance: n=248, B=0.234, t=9.194, p&lt;0.001, <xref ref-type="table" rid="table1">Table 1</xref>). This association was not found for the back (distance: n=248, B=0.093, t=1.714, p=0.087, <xref ref-type="table" rid="table2">Table 2</xref>). Then, using an LMM to compare the groups, we found both a significant interaction between the effect of distance and the location (location x distance: n=496, B=–0.139, t=–2.723, p=0.006, <xref ref-type="table" rid="table3">Table 3</xref>). Given that any errors are likely a result of two sources of noise: bias and response variability (imprecision), we next sought to quantify the relative contribution of the two sources. We estimated the bias for each point by computing the centroid of all reports for a given stimulus across trials and measured the error between the centroid and the stimulus location. To measure the imprecision, we computed the mean pairwise distance between each of the reported locations for a given stimulus location and the mean of those reported locations (<xref ref-type="fig" rid="fig3">Figure 3C and D</xref>). We found that, in both the breast and back, the error that originated from systematic bias significantly outweighed that of the imprecision (location x error type: n=995, B=–23.05, t=12.728, p&lt;0.001).</p><table-wrap id="table1" position="float"><label>Table 1.</label><caption><title>Linear mixed model for the relationship between distance and error for tactile localizations on the breast.</title><p><italic>error=distance + (distance | participant</italic>).</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" valign="bottom" colspan="2">Parameter</th><th align="left" valign="bottom">Estimate</th><th align="left" valign="bottom">95% CL</th><th align="left" valign="bottom">DF</th><th align="left" valign="bottom">t-Statistic</th><th align="left" valign="bottom">p-Value</th></tr></thead><tbody><tr><td align="left" valign="bottom"><bold>Fixed</bold></td><td align="left" valign="bottom"/><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Intercept</td><td align="left" valign="bottom">14.656</td><td align="left" valign="bottom">10.547, 18.765</td><td align="left" valign="bottom">248</td><td align="left" valign="bottom">7.0258</td><td align="left" valign="bottom">2.044E-11</td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Distance</td><td align="left" valign="bottom">0.23401</td><td align="left" valign="bottom">0.18388, 0.28414</td><td align="left" valign="bottom">248</td><td align="left" valign="bottom">9.1937</td><td align="left" valign="bottom">1.595E-17</td></tr><tr><td align="left" valign="bottom"><bold>Random</bold></td><td align="left" valign="bottom"/><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Intercept | Participant</td><td align="left" valign="bottom">5.261</td><td align="left" valign="bottom">2.6706, 10.364</td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Distance | Participant</td><td align="left" valign="bottom">0.027219</td><td align="left" valign="bottom">0.0036549, 0.20271</td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr></tbody></table></table-wrap><table-wrap id="table2" position="float"><label>Table 2.</label><caption><title>Linear mixed model for the relationship between distance and error for tactile localizations on the back.</title><p><italic>error=distance + (distance | participant</italic>).</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" valign="bottom" colspan="2">Parameter</th><th align="left" valign="bottom">Estimate</th><th align="left" valign="bottom">95% CL</th><th align="left" valign="bottom">DF</th><th align="left" valign="bottom">t-Statistic</th><th align="left" valign="bottom">p-Value</th></tr></thead><tbody><tr><td align="left" valign="bottom"><bold>Fixed</bold></td><td align="left" valign="bottom"/><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Intercept</td><td align="left" valign="bottom">49.668</td><td align="left" valign="bottom">41.571, 57.764</td><td align="left" valign="bottom">248</td><td align="left" valign="bottom">12.083</td><td align="left" valign="bottom">9.7547e-27</td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Distance</td><td align="left" valign="bottom">0.093385</td><td align="left" valign="bottom">–0.013932, 0.2007</td><td align="left" valign="bottom">248</td><td align="left" valign="bottom">1.7139</td><td align="left" valign="bottom">0.087801</td></tr><tr><td align="left" valign="bottom"><bold>Random</bold></td><td align="left" valign="bottom"/><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Intercept | Participant</td><td align="left" valign="bottom">10.934</td><td align="left" valign="bottom">5.9341, 20.145</td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Distance | Participant</td><td align="left" valign="bottom">0.11002</td><td align="left" valign="bottom">0.036619, 0.33057</td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr></tbody></table></table-wrap><table-wrap id="table3" position="float"><label>Table 3.</label><caption><title>Linear mixed model for the relationship between distance and error for tactile localizations on the breast and back.</title><p><italic>error=distance + location + (distance x location) + (distance | participant</italic>).</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" valign="bottom">Parameter</th><th align="left" valign="bottom"/><th align="left" valign="bottom">Estimate</th><th align="left" valign="bottom">95% CL</th><th align="left" valign="bottom">DF</th><th align="left" valign="bottom">t-Statistic</th><th align="left" valign="bottom">p-Value</th></tr></thead><tbody><tr><td align="left" valign="bottom"><bold>Fixed</bold></td><td align="left" valign="bottom"/><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Intercept</td><td align="left" valign="bottom">14.601</td><td align="left" valign="bottom">8.3922, 20.809</td><td align="left" valign="bottom">496</td><td align="left" valign="bottom">4.6206</td><td align="left" valign="bottom">4.8848e-06</td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Distance</td><td align="left" valign="bottom">0.23491</td><td align="left" valign="bottom">0.13881, 0.33101</td><td align="left" valign="bottom">496</td><td align="left" valign="bottom">4.8027</td><td align="left" valign="bottom">2.0762e-06</td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Location</td><td align="left" valign="bottom">34.927</td><td align="left" valign="bottom">29.63, 40.225</td><td align="left" valign="bottom">496</td><td align="left" valign="bottom">12.954</td><td align="left" valign="bottom">2.8993e-33</td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Distance x Location</td><td align="left" valign="bottom">–0.13876</td><td align="left" valign="bottom">−0.23889,–0.038634</td><td align="left" valign="bottom">496</td><td align="left" valign="bottom">–2.7229</td><td align="left" valign="bottom">0.0066996</td></tr><tr><td align="left" valign="bottom"><bold>Random</bold></td><td align="left" valign="bottom"/><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Intercept | Participant</td><td align="left" valign="bottom">7.9445</td><td align="left" valign="bottom">4.5113, 13.99</td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Distance | Participant</td><td align="left" valign="bottom">0.10285</td><td align="left" valign="bottom">0.049394, 0.21416</td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr></tbody></table></table-wrap><p>As bias was prevalent in the localization task, we next sought to determine if the bias was systematic across stimulus locations. Consequently, we assessed the tendency for the error vector to be uniformly distributed in two dimensions (<xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1B, C</xref>). Importantly, because the back is a relatively flat surface in comparison to the breast, error vectors were only computed in the horizontal plane and depth was excluded when computing the angular error. When computing the absolute angle between stimulus location and the average reported location (blue vectors in <xref ref-type="fig" rid="fig3">Figure 3A and B</xref>) and computed the distribution across participants (<xref ref-type="fig" rid="fig3">Figure 3E and F</xref>). Across participants, the distribution of biases did not significantly deviate from uniformity (permutation test for uniformity: <italic>R</italic>=0.1314, p=0.9331 and <italic>R</italic>=0.1856, p=0.7171, respectively). Next, when we assessed if the bias with respect to the center point (nipple or scapula) was consistent, we found that both the breast and back tended to exhibit biases (<italic>R</italic>=0.3140, p=0.0100 and <italic>R</italic>=0.6164, p&lt;0.0001, respectively), with the effect roughly doubled for the breast.</p><p>To further quantify this observation, we computed the vector strength – a measure of circular uniformity – of the biases for individual participants. For the breast we did not detect significant non-uniform distributions across participants, although some participants demonstrated biases (e.g. towards the top of the shoulder, <xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1D–F</xref>; vector strength Monte-Carlo test: p&lt;0.05 for 4/10 participants). Examining the back, significant non-uniform distributions were observed for all but one participant; however, the direction was inconsistent across participants, implying that reports were not biased towards any single landmark. Next, we computed the distribution of relative angles between the bias vector and the center point of our task and found that seven of ten participants were biased towards the nipple (vector strength Monte-Carlo: p&lt;0.05), and two were biased towards the scapula, suggesting that while individual biases are present, they vary substantially across the population.</p><p>Given these findings, we conclude that the breast has lower tactile precision than the hand and is instead comparable to the back. Moreover, localization of tactile events to both the back and breast are inaccurate, but localizations to the breast are consistently biased towards the nipple.</p></sec></sec><sec id="s3" sec-type="discussion"><title>Discussion</title><p>First, we found that the spatial precision of the lateral breast – excluding the nipple and areola – is almost four times lower than that of the hand, and even lower than that of the back, previously considered the epitome of poor precision. Second, the nipple has such low tactile precision that touches to different aspects of the nipple are nearly indistinguishable from one another. Third, the precision of the breast tends to be poorer for women with large breasts, consistent with the theory that innervation capacity is fixed. Together, the data indicates that the nipple constitutes a landmark on the breast, as evidenced by the fact that absolute localization judgments are less accurate and more biased for touches that are far from the nipple, and the perceived location is pulled systematically toward the nipple.</p><sec id="s3-1"><title>The poor spatial precision of the breast</title><p>The poor spatial precision of the breast – about four times lower than that of the hand and slightly worse than the back – replicates previous findings (<xref ref-type="bibr" rid="bib29">Weinstein, 1968</xref>) achieved using less reliable methods (two-point threshold and a ‘same-different’ paradigm). Tactile spatial precision is determined by density of innervation: more neural tissue is devoted to more highly innervated body regions, and this increased central representation is a key contributor to the increased precision. The low spatial precision of the nipple and areola is consistent with a histological study revealing these regions to be sparsely innervated (<xref ref-type="bibr" rid="bib14">Gutiérrez-Villanueva et al., 2020</xref>).</p></sec><sec id="s3-2"><title>Larger breasts confer lower precision</title><p>We found a significant relationship between breast size and spatial precision: women with larger breasts tended to exhibit lower spatial precision on their breasts, consistent with previous findings that tactile precision scales with body size. Indeed, the spatial precision of the hand has been shown to depend on the size of the hand, with smaller hands exhibiting better precision (<xref ref-type="bibr" rid="bib25">Peters et al., 2009</xref>; <xref ref-type="bibr" rid="bib30">Wong et al., 2013</xref>). These results are consistent with the hypothesis that the number of tactile nerve fibers does not scale with body size, so fibers are more sparsely distributed on bigger bodies, leading to lower precision. Consequently, the precision of the breast is likely determined initially by torso precision and then as a result of subsequent expansion.</p></sec><sec id="s3-3"><title>Reports are biased towards the nipple</title><p>The mental representation of the body is not uniform and veridical (<xref ref-type="bibr" rid="bib20">Longo, 2022</xref>). Localization tends to be more precise when stimuli are applied near anatomical points of reference that form perceptual anchor points (<xref ref-type="bibr" rid="bib28">Weber, 1834</xref>). For example, the navel and spine act as anchor points along the abdomen (<xref ref-type="bibr" rid="bib2">Cholewiak et al., 2004</xref>; <xref ref-type="bibr" rid="bib27">Van Erp, 2005</xref>): touches to the navel or spine are never mistaken for touches anywhere else on the abdomen. Furthermore, touches to locations near these two anchor points are mislocalized following a bias toward these areas: touches near the navel are pulled toward the navel, and touches near the spine are pulled toward the spine. Similar biases are observed on the back of the hand, where touches are mislocalized to be closer to the fingers than they actually are (<xref ref-type="bibr" rid="bib21">Mancini et al., 2011</xref>), and on the forearm, where they are pulled toward the wrist (<xref ref-type="bibr" rid="bib8">Fuchs et al., 2020</xref>). Analogously, we found that precision is highest near the nipple, and perceived locations are pulled toward the nipple, suggesting that the nipple plays a pivotal role in the mental representation of the breast. It must be noted, however, that these same biases may be inadvertently influenced by our study design. As participants were annotating 3D meshes of their breasts, the cognitive importance of the nipple may have also caused them to report sensations as closer to the nipple regardless of the actual percepts. This observation motivates standard reporting methodologies for morphologically diverse body parts such as the (<xref ref-type="bibr" rid="bib24">Nielsen et al., 2026</xref>).</p></sec><sec id="s3-4"><title>Implications for breast prostheses</title><p>Understanding the spatial precision of the breast is particularly important given a recent proliferation of efforts – including using autologous tissue, synthetic grafts, and neuroprosthetic or bionic approaches – to restore sensation to the breast following mastectomy (<xref ref-type="bibr" rid="bib18">Lindau and Bensmaia, 2020</xref>; <xref ref-type="bibr" rid="bib4">Courtiss and Goldwyn, 1976</xref>). In particular, this work shows that the spatial resolution of an implantable sensor sheet should depend on the distance from the nipple. Individual sensors should be placed in each quadrant of the NAC, while subsequent sensors should be placed radially with increasing separation (0.5–2 cm inter-sensor spacing) up to a 5 cm radius, at which point resolution would remain constant at approximately 2 cm. These values, however, depend on the spatial resolution of the stimulation technology, which can vary significantly for both peripheral nerve stimulation (<xref ref-type="bibr" rid="bib1">Charkhkar et al., 2018</xref>) and intracortical microstimulation (<xref ref-type="bibr" rid="bib12">Greenspon et al., 2025b</xref>). Moreover, little is understood about the tactile coding of the primary afferents of the breast, and further research will be needed to both inform stimulus patterning and inform safe stimulation parameters (<xref ref-type="bibr" rid="bib10">Graczyk et al., 2016</xref>; <xref ref-type="bibr" rid="bib15">Hobbs et al., 2025</xref>; <xref ref-type="bibr" rid="bib11">Greenspon et al., 2025a</xref>).</p></sec><sec id="s3-5"><title>Conclusion</title><p>The breast has unique sensory properties because (<xref ref-type="bibr" rid="bib23">McGlone et al., 2014</xref>) it mediates lactation and nursing, (<xref ref-type="bibr" rid="bib3">Corniani and Saal, 2020</xref>) it comprises distinct regions – the nipple, areola, and outer breast – which differ in the type of skin and patterns of sensory innervation, (<xref ref-type="bibr" rid="bib6">Craig and Lyle, 2001</xref>) it has erectile function and gives rise to erogenous sensations, and (<xref ref-type="bibr" rid="bib17">Johansson and Vallbo, 1979</xref>) it undergoes variable expansion across individuals during puberty. First, we find that spatial precision on the breast is lower than that of the back, previously regarded as the body region with lowest tactile precision. Second, spatial precision is lower in larger breasts, presumably due to sensory innervation being fixed prior to expansion during puberty. Third, the nipple itself has poor precision and yet plays a major role in how participants perceive tactile events on their breast.</p></sec></sec><sec id="s4" sec-type="methods"><title>Methods</title><sec id="s4-1"><title>Participants</title><p>A total of 48 healthy adult women (24.2±3.1, 19–32 years) participated in this study: Thirty-four in the location discrimination task (mean ± SD, age range; 22.6±2.7, 19–28 years), ten in the medial breast quadrant localization task (25.3±3.8, 19–32 years), and ten in the absolute localization task (24.7±2.9, 20–28 years). Some participants performed multiple tasks. Experimental procedures were performed in accordance with the relevant guidelines and regulations and were approved by the Institutional Review Board of the University of Chicago (IRB 18–0135). The informed consent process included documentation of written consent from each participant, and the participants were compensated for their participation. We excluded any women who, by self-report, were currently pregnant or breastfeeding, had a history of breast surgery, or any diagnosis of neurological illness.</p></sec><sec id="s4-2"><title>Breast measurements</title><p>In addition to self-reported bra size, we collected standardized, objective measurements from each participant. Specifically, we measured the bust – that is the circumference of the chest at the level of the nipple – and subtracted from it the under-bust, the circumference at the level of the inframammary fold (mean ± SD, range; 12.4±4.6, 7.6–25.4 cm). We also measured the diameter of the areola and nipple (areola: 37.4±11.9, 21–80 mm; nipple: 12.7±2.7, 7–20 mm).</p></sec><sec id="s4-3"><title>Tactile stimuli</title><p>Touches were delivered manually with a 1 mm tipped XP-Pen (XP-Pen USA, CA, USA), which allowed the experimenter to lightly press the stimulus against the skin and ensure that the skin was indented uniformly across touches. The XP-Pen was selected instead of monofilaments because, in pilot experiments, several participants reported discomfort with the sharp edges of the monofilaments on their breasts while also allowing for the application of a constant force. The participants were asked to report any discomfort with the application of the stimulus or the inability to feel the application of the stimulus reliably. Note that spatial precision is consistent across stimulus amplitudes as long as the touch is sufficiently above threshold (<xref ref-type="bibr" rid="bib9">Gibson and Craig, 2002</xref>), which was the case here.</p></sec><sec id="s4-4"><title>Psychophysical tasks</title><sec id="s4-4-1"><title>Location discrimination</title><p>Precision was tested at each of four body regions: the lateral breast, the medial breast (which includes the NAC), the thenar eminence of the hand, and the upper back. The participant – wearing a gown that exposed only the location to be tested – lay supine on a massage table for testing on the lateral breast, medial breast, and thenar eminence, and prone for the testing on the back. Unless the participant expressed a preference, the side of the body to be tested (left/right) was chosen randomly (through a random number generator), but each participant was tested on the same side for all regions. The order in which the different regions were tested was randomized to eliminate any effects of fatigue or learning.</p><p>On each trial, two touches were applied to nearby locations and the participant’s task was to indicate whether the second touch was above or below the first by pressing one of two buttons on a keypad. The location of one of the two touches (the reference) was consistent across each experimental block and the location of the second (the comparison) varied from trial to trial (each at a pre-specified distance). Fifteen comparison locations, aligned along an axis parallel to the body’s axis, were tested on the back, lateral breast, and medial breast. Touch locations were drawn on the body to ensure repeatable presentation and comparisons were placed at locations 0, 2.5, 5, 7.5, 10, 15, 20, or 40 mm above or below the reference (<xref ref-type="fig" rid="fig1">Figure 1A</xref>). Each comparison was repeated five times per block over three blocks (for a total of 15 repeats per comparison, with 225 total trials per body region) in a randomized order. Thirteen comparison locations were tested on the hand, 0, 1, 3, 6, 7.5, and 10 mm away from the reference in both directions along an axis in line with the thumb. For the hand, a judgment of ‘above’ indicated that the comparison was displaced toward the thumb relative to the reference. Each location was repeated five times across three experimental blocks (for a total of 15 repeats per comparison, with 195 total trials).</p><p>Performance was gauged by the proportion of times the participant judged a comparison as above the reference as a function of distance from the reference, where negative distances indicate comparison locations below the reference. Psychometric functions were fit to the data and used to compute the JND.</p></sec><sec id="s4-4-2"><title>Quadrant discrimination</title><p>The objective of this experiment was to assess the degree to which women can distinguish touches to different parts of their NAC. On each trial, the participant was touched at one of four locations on the nipple or areola (organized in a quadrant) and verbally identified the touch location using a number from 1 to 4. Each location was touched ten times per block (40 trials per block, with 80 total trials per breast region). For the areola, each touch was located halfway between the edge of the areola and the nipple. For the nipple, each touch was delivered at the edge of the nipple, in line with each point on the areola (<xref ref-type="fig" rid="fig2">Figure 2A</xref>). The testing side was chosen randomly for each participant (6 left/4 right).</p></sec><sec id="s4-4-3"><title>Absolute localization</title><p>The objective of this experiment was to gauge the accuracy with which women could report where on their breast or back a touch was delivered. On the breast, touches were arranged such that the nipple was the central point and other touches radiated outwards from it (<xref ref-type="fig" rid="fig3">Figure 3A</xref>). Importantly, the two center-most touches occurred on the nipple itself. On the back, touches were arranged the same way around a central point located on the shoulder blade (<xref ref-type="fig" rid="fig3">Figure 3B</xref>). First, the participant’s skin was marked, then a three-dimensional scan of the breast or back was obtained using the EM3D application (Brawny Lads Software, LLC.) and .obj files were uploaded to Blender. The surface of the breast was then masked with a uniform layer of gray to obscure the markings. A laptop (13&quot; screen) was positioned such that the participant could use the trackpad to interact with the 3D image (zoom, rotate, drag object) to report where the touch was experienced on the 3D rendering of their breast. Notably, in both cases, landmarks were observable on the 3D models (e.g. nipple, shoulder, scapula, vertebral line). Each of the 25 stimulus locations was presented in a pseudorandomized order while the participants closed their eyes. After the touch, the participant opened their eyes and marked the perceived location of the touch on the 3D rendering of their breast or back. The participant was encouraged to manipulate the 3D model freely to obtain the best view of their breast or back on each trial. The participant moved the cursor and clicked to indicate where they perceived the touch. Reported locations accumulated on the 3D model throughout the block (during which each location was touched once) to encourage placement of markers in accurate relative positions but were removed at the start of each of three blocks (yielding a total of 3 repeats for each of the 25 locations).</p></sec></sec><sec id="s4-5"><title>Data analysis</title><sec id="s4-5-1"><title>Spatial precision</title><p>To quantify the spatial precision at each test location, we fit a psychometric function (see <xref ref-type="disp-formula" rid="equ1">Equation 1</xref>) to the probability of judging the second touch as above the first versus the relative location of the two stimuli. From these functions, we estimated the distance from the reference point required to reliably discriminate the sensation (75% performance, see <xref ref-type="disp-formula" rid="equ2">Equation 2</xref>).<disp-formula id="equ1"><label>(1)</label><alternatives><mml:math id="m1"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mrow><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mi>p</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>a</mml:mi><mml:mi>b</mml:mi><mml:mi>o</mml:mi><mml:mi>v</mml:mi><mml:mi>e</mml:mi></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:msup><mml:mi>e</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mi>k</mml:mi><mml:mo>∗</mml:mo><mml:mi>x</mml:mi></mml:mrow></mml:msup></mml:mrow></mml:mfrac></mml:mstyle></mml:mrow></mml:mstyle></mml:math><tex-math id="t1">\begin{document}$$\displaystyle p\left (above\right)=\frac{1}{1+e^{- k\ast x}}$$\end{document}</tex-math></alternatives></disp-formula></p><p>where <italic>k</italic> is the growth term of the exponential function and <italic>x</italic> is the distance between the comparison point and the reference point.<disp-formula id="equ2"><label>(2)</label><alternatives><mml:math id="m2"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mrow><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mi>j</mml:mi><mml:mi>n</mml:mi><mml:mi>d</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mi>log</mml:mi><mml:mo>⁡</mml:mo><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mfrac><mml:mn>1</mml:mn><mml:mn>.75</mml:mn></mml:mfrac><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow><mml:mrow><mml:mo>−</mml:mo><mml:mi>k</mml:mi></mml:mrow></mml:mfrac></mml:mstyle></mml:mrow></mml:mstyle></mml:math><tex-math id="t2">\begin{document}$$\displaystyle jnd=\frac{\log \left (\frac{1}{.75}- 1\right)}{- k}$$\end{document}</tex-math></alternatives></disp-formula></p><p>where <italic>k</italic> is the growth term computed in <xref ref-type="disp-formula" rid="equ1">Equation 1</xref>.</p><p>JNDs were then compared between regions using a one-way ANOVA followed by a Tukey's honest significant difference post-hoc test.</p></sec><sec id="s4-5-2"><title>Quadrant localization</title><p>To determine if each participant individually performed the task at greater than chance levels as well as the group as a whole, a Monte-Carlo simulation was used. Across 10,000 simulations, the appropriate number of trials were simulated in which each participant randomly guessed the location and the percent correct was computed across trials for each simulation. Significance was then computed within participant by comparing the observed performance against the simulated distribution and then applying Bonferroni correction. To then determine if the whole group outperformed chance, across each of the 10,000 simulations, the cross-participant average percent correct was computed and the observed percentage compared against the resultant value. The effect size was computed by comparing the observed average percent correct with the mean of the simulation divided by the standard deviation of the simulation.</p></sec><sec id="s4-5-3"><title>Absolute localization task error and bias</title><p>To compute the error for the task, we considered the 3D position of both the stimuli and response. First, to compute the total error, we computed the 3D Euclidean distance between the stimulus location and the participants' response on each trial and then averaged these values together. While the skin is not flat, over the relatively short distances between stimulus and response (typically &lt;5 cm), Euclidean distance was sufficient as minimal curvature occurred over this range. To measure the bias for each point, the 3D position for all responses for a given point across blocks was averaged together and the Euclidean distance between the resultant point and the stimulus location was averaged (centroid). If responses were randomly distributed around the stimulus location, then the error of the average response would be minimal. If there was a consistent offset, then the bias error would be similar to the total error. Finally, to compute imprecision, we computed the mean Euclidean error between the centroid and individual responses.</p><p>Linear mixed models were used to assess significant effects using Matlab’s <italic>fitlme</italic> function. The formula used for each test can be found in <xref ref-type="table" rid="table1 table2 table3 table4">Tables 1–4</xref>. While the fixed effects varied, participants were treated as random effects and the intercept and slope were allowed to vary for each.</p><table-wrap id="table4" position="float"><label>Table 4.</label><caption><title>Linear mixed model for the relationship between distance and error for tactile localizations on the breast and back with respect to error type (bias or imprecision).</title><p>error=distance + location +error type + (error type x location) + (distance | participant).</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" valign="bottom">Parameter</th><th align="left" valign="bottom"/><th align="left" valign="bottom">Estimate</th><th align="left" valign="bottom">95% CL</th><th align="left" valign="bottom">DF</th><th align="left" valign="bottom">t-Statistic</th><th align="left" valign="bottom">p-Value</th></tr></thead><tbody><tr><td align="left" valign="bottom"><bold>Fixed</bold></td><td align="left" valign="bottom"/><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Intercept</td><td align="left" valign="bottom">15.291</td><td align="left" valign="bottom">11.301, 19.281</td><td align="left" valign="bottom">995</td><td align="left" valign="bottom">7.5203</td><td align="left" valign="bottom">1.2187e-13</td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Distance</td><td align="left" valign="bottom">0.10133</td><td align="left" valign="bottom">0.046744, 0.15592</td><td align="left" valign="bottom">995</td><td align="left" valign="bottom">3.6427</td><td align="left" valign="bottom">0.00028369</td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Location</td><td align="left" valign="bottom">29.034</td><td align="left" valign="bottom">26.52, 31.548</td><td align="left" valign="bottom">995</td><td align="left" valign="bottom">22.663</td><td align="left" valign="bottom">5.1594e-92</td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Error Type</td><td align="left" valign="bottom">–4.0629</td><td align="left" valign="bottom">−6.5756,–1.5503</td><td align="left" valign="bottom">995</td><td align="left" valign="bottom">–3.1731</td><td align="left" valign="bottom">0.0015544</td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Location x Error Type</td><td align="left" valign="bottom">–23.048</td><td align="left" valign="bottom">−26.601,–19.495</td><td align="left" valign="bottom">995</td><td align="left" valign="bottom">–12.728</td><td align="left" valign="bottom">1.7171e-34</td></tr><tr><td align="left" valign="bottom"><bold>Random</bold></td><td align="left" valign="bottom"/><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Intercept | Participant</td><td align="left" valign="bottom">5.2017</td><td align="left" valign="bottom">2.942, 9.1969</td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr><tr><td align="left" valign="bottom"/><td align="left" valign="bottom">Distance | Participant</td><td align="left" valign="bottom">0.069106</td><td align="left" valign="bottom">0.033314, 0.14335</td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td><td align="left" valign="bottom"> </td></tr></tbody></table></table-wrap></sec><sec id="s4-5-4"><title>Absolute localization task angular error</title><p>To compute the angle of the errors for each response, we measured the four-quadrant inverse tangent (<xref ref-type="disp-formula" rid="equ3">Equation 3</xref>) between each point and response. Importantly, this was only considered in two dimensions as the variance of angles in the third dimension (depth) was drastically dependent on breast size and the location of the point on the breast. Thus, the angle between the stimulus location and each response (as well as the centroid across responses) was computed. Then, for each stimulus, the angle between the stimulus location and the reference point was computed (center angle). The difference in angle between said angle and the centroid angle was measured.<disp-formula id="equ3"><label>(3)</label><alternatives><mml:math id="m3"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mrow><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mi>θ</mml:mi><mml:mo>=</mml:mo><mml:mi>t</mml:mi><mml:mi>a</mml:mi><mml:msup><mml:mi>n</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup><mml:mrow><mml:mo>(</mml:mo><mml:mfrac><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>y</mml:mi></mml:mrow><mml:mrow><mml:mi mathvariant="normal">Δ</mml:mi><mml:mi>x</mml:mi></mml:mrow></mml:mfrac><mml:mo>)</mml:mo></mml:mrow></mml:mstyle></mml:mrow></mml:mstyle></mml:math><tex-math id="t3">\begin{document}$$\displaystyle \theta =tan^{- 1}\left (\frac{\Delta y}{\Delta x}\right)$$\end{document}</tex-math></alternatives></disp-formula></p></sec><sec id="s4-5-5"><title>Absolute localization task uniformity test</title><p>To test if the cross-participant biases were uniform or not, we measured the range-normalized mean squared error (rnMSE, <xref ref-type="disp-formula" rid="equ4">Equation 4</xref>) between the average distribution of error angles across participants and the mean of the distribution, similar to measurements of residual variance. Then, to determine if the observed rnMSE was significant, we used a permutation test in which for each permutation (n=1e5), we shuffled the angles for each participant before averaging across participants and computing the rnMSE to produce a null distribution of rnMSEs that might be expected if the participants' responses were not systematic. Finally, we computed the proportion of simulations that had greater rnMSEs than the observed rnMSE to produce the p value which was considered significant if it was less than 0.05.<disp-formula id="equ4"><label>(4)</label><alternatives><mml:math id="m4"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mrow><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mi>r</mml:mi><mml:mi>n</mml:mi><mml:mi>M</mml:mi><mml:mi>S</mml:mi><mml:mi>E</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mo>∑</mml:mo><mml:mroot><mml:msup><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>x</mml:mi><mml:mo>−</mml:mo><mml:mrow><mml:mover><mml:mi>x</mml:mi><mml:mo stretchy="false">¯</mml:mo></mml:mover></mml:mrow></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup><mml:mn>2</mml:mn></mml:mroot></mml:mrow><mml:mrow><mml:mo movablelimits="true" form="prefix">max</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mi>x</mml:mi><mml:mo>}</mml:mo></mml:mrow><mml:mo>−</mml:mo><mml:mo movablelimits="true" form="prefix">min</mml:mo><mml:mrow><mml:mo>{</mml:mo><mml:mi>x</mml:mi><mml:mo>}</mml:mo></mml:mrow></mml:mrow></mml:mfrac></mml:mstyle></mml:mstyle></mml:mrow></mml:mstyle></mml:math><tex-math id="t4">\begin{document}$$\displaystyle  rnMSE=\frac{\sum \sqrt[2]{\left (x- \bar{x}\right)^{2}}}{\max\left \{x\right \}- \min\left \{x\right \}}$$\end{document}</tex-math></alternatives></disp-formula></p></sec><sec id="s4-5-6"><title>Absolute localization task vector strength</title><p>The vector strength for individual participants was computed using <xref ref-type="disp-formula" rid="equ5">Equation 5</xref>. Importantly, given the observed heteroskedasticity between distance and error, we did not incorporate the length of the vectors in the computation as this would have biased the computation towards points distal to the nipple for the breast but would not have influenced the back measurements. As the angular errors were distributed between -π and π, to test if the observed vector strength was significant, we used a Monte-Carlo simulation in which for each simulation (n=1e5) we sampled angles from the range [-π, π] from a uniform distribution (n=11) and computed the vector strength from each simulation. We then compared the observed vector strengths for each participant and location against the null distribution and considered it significant if the value exceeded the 95th percentile of the null distribution.<disp-formula id="equ5"><label>(5)</label><alternatives><mml:math id="m5"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mrow><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mstyle displaystyle="true" scriptlevel="0"><mml:mi>v</mml:mi><mml:mi>s</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mroot><mml:mrow><mml:mo>∑</mml:mo><mml:mi>sin</mml:mi><mml:mo>⁡</mml:mo><mml:msup><mml:mrow><mml:mo>(</mml:mo><mml:mi>x</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup><mml:mo>+</mml:mo><mml:mo>∑</mml:mo><mml:mi>cos</mml:mi><mml:mo>⁡</mml:mo><mml:msup><mml:mrow><mml:mo>(</mml:mo><mml:mi>x</mml:mi><mml:mo>)</mml:mo></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msup></mml:mrow><mml:mn>2</mml:mn></mml:mroot><mml:mrow><mml:mi>n</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mi>x</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:mfrac></mml:mstyle></mml:mstyle></mml:mrow></mml:mstyle></mml:math><tex-math id="t5">\begin{document}$$\displaystyle  vs=\frac{\sqrt[2]{\sum \sin\left (x\right)^{2}+\sum \cos\left (x\right)^{2}}}{n\left (x\right)}$$\end{document}</tex-math></alternatives></disp-formula></p></sec></sec></sec></body><back><sec sec-type="additional-information" id="s5"><title>Additional information</title><fn-group content-type="competing-interest"><title>Competing interests</title><fn fn-type="COI-statement" id="conf1"><p>Patents pending (EP3917611 and 12521551) related to sensorized prosthetic breasts based on the spatial precision of the breast described in this paper</p></fn><fn fn-type="COI-statement" id="conf2"><p>No competing interests declared</p></fn></fn-group><fn-group content-type="author-contribution"><title>Author contributions</title><fn fn-type="con" id="con1"><p>Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review and editing</p></fn><fn fn-type="con" id="con2"><p>Conceptualization, Formal analysis, Investigation, Writing – review and editing</p></fn><fn fn-type="con" id="con3"><p>Formal analysis, Methodology, Writing – review and editing</p></fn><fn fn-type="con" id="con4"><p>Investigation, Writing – review and editing</p></fn><fn fn-type="con" id="con5"><p>Conceptualization, Funding acquisition, Writing – original draft, Project administration, Writing – review and editing</p></fn><fn fn-type="con" id="con6"><p>Conceptualization, Supervision, Funding acquisition, Methodology, Writing – original draft, Writing – review and editing</p></fn><fn fn-type="con" id="con7"><p>Conceptualization, Data curation, Formal analysis, Supervision, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing</p></fn></fn-group><fn-group content-type="ethics-information"><title>Ethics</title><fn fn-type="other"><p>Experimental procedures were performed in accordance with the relevant guidelines and regulations and were approved by the Institutional Review Board of the University of Chicago (IRB 18-0135). The informed consent process included documentation of written consent from each participant, and the participants were compensated for their participation.</p></fn></fn-group></sec><sec sec-type="supplementary-material" id="s6"><title>Additional files</title><supplementary-material id="mdar"><label>MDAR checklist</label><media xlink:href="elife-105946-mdarchecklist1-v1.docx" mimetype="application" mime-subtype="docx"/></supplementary-material></sec><sec sec-type="data-availability" id="s7"><title>Data availability</title><p>Data for this study can be found online at <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.27939606">FigShare</ext-link>, while code is available on <ext-link ext-link-type="uri" xlink:href="https://github.com/sensorimotor-bionics/BreastAcuity">GitHub</ext-link> (copy archived at <xref ref-type="bibr" rid="bib13">Greenspon, 2026</xref>). Participant meshes are not available due to the sensitive nature of the data except for one participant who explicitly consented to a cropped version of their model being used for figures.</p><p>The following dataset was generated:</p><p><element-citation publication-type="data" specific-use="isSupplementedBy" id="dataset1"><person-group person-group-type="author"><name><surname>Greenspon</surname><given-names>C</given-names></name></person-group><year iso-8601-date="2025">2025</year><data-title>The coarse mental map of the breast is anchored on the nipple</data-title><source>figshare</source><pub-id pub-id-type="doi">10.6084/m9.figshare.27939606</pub-id></element-citation></p></sec><ack id="ack"><title>Acknowledgements</title><p>Research supported in this publication was supported in part by National Cancer Institute grants R21CA226726 and R01CA281301, National Institute of Neurological Diseases and Stroke grant NS122333, and funding from the University of Chicago Women’s Board. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We would like to thank Katrina Schmitt and Elizabeth Pinkerton for their help on this project. 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The study provides two <bold>important</bold> contributions, by <bold>convincingly</bold> showing that tactile acuity on the breast is poor in comparison to other body parts, and that acuity is worst in larger breasts, indicating that the number of tactile sensors is fixed. This study will be of interest to the broader community of touch, as well as those interested in breast reconstruction and sexual function.</p></body></sub-article><sub-article article-type="referee-report" id="sa1"><front-stub><article-id pub-id-type="doi">10.7554/eLife.105946.4.sa1</article-id><title-group><article-title>Reviewer #1 (Public review):</article-title></title-group><contrib-group><contrib contrib-type="author"><anonymous/><role specific-use="referee">Reviewer</role></contrib></contrib-group></front-stub><body><p>[Editors' note: this version has been assessed by the Senior Editor without further input from the original reviewers. The authors have moderated their claims and discussed the limitations of their experimental design more transparently. The previous reviews are included for reference.]</p><p>Comments on previous version:</p><p>The authors investigated tactile spatial perception on the breast using discrimination, categorization, and direct localization tasks. They reach four main conclusions:</p><p>(1) The breast has poor tactile spatial resolution.</p><p>This conclusion is based on comparing just noticeable differences, a marker of tactile spatial resolution, across four body regions, two on the breast. The data compellingly support the conclusion; the study outshines other studies on tactile spatial resolution that tend to use problematic measures of tactile resolution, such as two-point-discrimination thresholds. The result will interest researchers in the field and possibly in other fields due to the intriguing tension between the finding and the sexually arousing function of touching the breast.</p><p>The manuscript incorrectly describes the result as poor spatial acuity. Acuity measures the average absolute error, and acuity is good when response biases are absent. Precision relates to the error variance. It is common to see high precision with low acuity or vice versa. Just noticeable differences assess precision or spatial resolution, while points of subjective equality evaluate acuity or bias. Similar confusions between these terms appear throughout the manuscript.</p><p>A paragraph within the next section seems to follow up on this insight by examining the across-participant consistency of the differences in tactile spatial resolution between body parts. To this aim, pairwise rank correlations between body sites are conducted. This analysis raises red flags from a statistical point of view. (1) An ANOVA and its follow-up tests assume no variation in the size of the tested effect but varying base values across participants. Thus, if significant differences between conditions are confirmed by the original statistical analysis, most participants will have better spatial resolution in one condition than the other condition, and the difference between body sites will be similar across participants. (2) Correlations are power-hungry, and non-parametric tests are power-hungry. Thus, the number of participants needed for a reliable rank correlation analysis far exceeds that of the study. In sum, a correlation should emerge between body sites associated with significantly different tactile JNDs; however, these correlations might only be significant for body sites with pronounced differences due to the sample size.</p><p>(2) Larger breasts are associated with lower tactile spatial resolution</p><p>This conclusion is based on a strong correlation between participants' JNDs and the size of their breasts. The depicted correlation convincingly supports the conclusion. The sample size is below that recommended for correlations based on power analyses, but simulations show that spurious correlations of the reported size are extremely unlikely at N=18. Moreover, visual inspection rules out that outliers drive these correlations. Thus, they are convincing. This result is of interest to the field, as it aligns with the hypothesis that nerve fibers are more sparsely distributed across larger body parts.</p><p>(3) The nipple is a unit</p><p>The data do not support this conclusion. The conclusion that the nipple is perceived as a unit is based on poor tactile localization performance for touches on the nipple compared to the areola. The problem is that the localization task is a quadrant identification task with the center being at the nipple. Quadrants for the areola could be significantly larger due to the relative size of the areola and the nipple; the results section seems to suggest this was accounted for when placing the tactile stimuli within the quadrants, but the methods section suggests otherwise. Additionally, the areola has an advantage because of its distance from the nipple, which leads to larger Euclidean distances between the centers of the quadrants than for the nipple. Thus, participants should do better for the areola than for the nipple even if both sites have the same tactile resolution.</p><p>To justify the conclusion that the nipple is a unit, additional data would be required. (1) One could compare psychometric curves with the nipple as the center and psychometric curves with a nearby point on the areola as the center. (2) Performance in the quadrant task could be compared for the nipple and an equally sized portion of the areola and tactile locations that have the same distance to the border between quadrants in skin coordinates. (3) Tactile resolution could be directly measured for both body sites using a tactile orientation task with either a two-dot probe or a haptic grating.</p><p>Categorization accuracy in each area was tested against chance using a Monte Carlo test, which is fine, though the calculation of the test statistic, Z, should be reported in the Methods section, as there are several options. Localization accuracies are then compared between areas using a paired t-test. It is a bit confusing that once a distribution-approximating test is used, and once a test that assumes Gaussian distributions when the data is Bernoulli/Binomial distributed. Sampling-based and t-tests are very robust, so these surprising choices should have hardly any effect on the results.</p><p>A correlation based on N=4 participants is dangerously underpowered. A quick simulation shows that correlation coefficients of randomly sampled numbers are uniformly distributed at such a low sample size. This likely spurious correlation is not analyzed, but quite prominently featured in a figure and discussed in the text, which is worrisome.</p><p>(4) Localization of tactile events on the breast is biased towards the nipple</p><p>The conclusion that tactile percepts are drawn toward the nipple is based on localization biases for tactile stimuli on the breast compared to the back. Unfortunately, the way participants reported the tactile locations introduces a major confound. Participants indicated the perceived locations of the tactile stimulus on 3D models of these body parts. The nipple is a highly distinctive and cognitively represented landmark, far more so than the scapula, making it very likely that responses were biased toward the nipple regardless of the actual percepts. One imperfect but better alternative would have been to ask participants to identify locations on a neutral grey patch and help them relate this patch to their skin by repeatedly tracing its outline on the skin.</p><p>Participants also saw their localization responses for the previously touched locations. This is unlikely to induce bias towards the nipple, but it renders any estimate of the size and variance of the errors unreliable. Participants will always make sure that the marked locations are sufficiently distant from each other.</p><p>The statistical analysis is again a homebrew solution and hard to follow. It remains unclear why standard and straightforward measures of bias, such as regressing reported against actual locations, were not used.</p><p>Null-hypothesis significance testing only lets scientists either reject the null hypothesis or not. The latter does NOT mean the Null hypothesis is true, i.e., it can never be concluded that there is no effect. This rule applies to every NHST test. However, it raises particular concerns with distribution tests. The only conclusion possible is that the data are unlikely from a population with the tested distribution; these tests do not provide insight into the actual distribution of the data, regardless of whether the result is significant or not.</p></body></sub-article><sub-article article-type="referee-report" id="sa2"><front-stub><article-id pub-id-type="doi">10.7554/eLife.105946.4.sa2</article-id><title-group><article-title>Reviewer #2 (Public review):</article-title></title-group><contrib-group><contrib contrib-type="author"><anonymous/><role specific-use="referee">Reviewer</role></contrib></contrib-group></front-stub><body><p>Summary:</p><p>The authors tested tactile acuity on the breast of females using several tasks.</p><p>Results:</p><p>Tactile acuity, assessed by just-noticeable differences in judging whether a touch was above or below a comparison stimulus, was lower on both the lateral and medial breast than on the hand and back. Acuity also scaled inversely with breast size, echoing earlier findings that larger hands exhibit lower acuity, presumably because a similar number of tactile receptors must be distributed over larger or smaller body surfaces. Observing this principle in the breast as on the hand strengthens the view that fixed innervation is a general organizing principle of the tactile system. Both methodology and analysis appear sound.</p><p>Most participants were unable to localize touch to a specific quadrant of the nipple, suggesting it is perceived as a single tactile unit. However, the study does not address whether touches to the nipple and areola are confused; conceptualizing the nipple as a perceptual (landmark) unit would suggest that such confusion should not take place. Aside from this limitation, the methodology and analysis appear sound.</p><p>Absolute touch localization, assessed by asking participants to indicate locations on a 3D rendering of their own torso, revealed a bias toward the nipple. The authors interpret this as evidence that the nipple serves as a landmark attracting perceived touch. However, as reviewers noted during review, alternative explanations cannot be fully ruled out: because the stimulus array was centered on the nipple, the observed bias may stem from stimulus distribution rather than landmark status. Aside from this caveat, the methodology and analysis appear sound.</p><p>Overall assessment:</p><p>The study offers a welcome exception to the prevailing bias in tactile research that limits investigation to the hand and arm. Its support for the fixed innervation hypothesis and its suggestion that the nipple may serve as a potential landmark-though requiring further scrutiny-illustrate the value of extending research to other body regions. By employing multiple tasks, the authors address several key aspects of tactile perception and create links to earlier findings.</p></body></sub-article><sub-article article-type="author-comment" id="sa3"><front-stub><article-id pub-id-type="doi">10.7554/eLife.105946.4.sa3</article-id><title-group><article-title>Author response</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Long</surname><given-names>Katie H</given-names></name><role specific-use="author">Author</role><aff><institution>University of Chicago</institution><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Fitzgerald</surname><given-names>Emily E</given-names></name><role specific-use="author">Author</role><aff><institution>University of Chicago</institution><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Berger-Wolf</surname><given-names>Ev I</given-names></name><role specific-use="author">Author</role><aff><institution>University of Chicago</institution><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Fawaz</surname><given-names>Amani</given-names></name><role specific-use="author">Author</role><aff><institution>University of Chicago</institution><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Lindau</surname><given-names>Stacy T</given-names></name><role specific-use="author">Author</role><aff><institution>University of Chicago</institution><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Bensmaia</surname><given-names>Sliman J</given-names></name><role specific-use="author">Author</role><aff><institution>University of Chicago</institution><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Greenspon</surname><given-names>Charles M</given-names></name><role specific-use="author">Author</role><aff><institution>University of Chicago</institution><addr-line><named-content content-type="city">Chicago</named-content></addr-line><country>United States</country></aff></contrib></contrib-group></front-stub><body><p>The following is the authors’ response to the previous reviews</p><disp-quote content-type="editor-comment"><p><bold>Public Reviews:</bold></p><p><bold>Reviewer #1 (Public review):</bold></p><p>The manuscript incorrectly describes the result as poor spatial acuity. Acuity measures the average absolute error, and acuity is good when response biases are absent. Precision relates to the error variance. It is common to see high precision with low acuity or vice versa. Just noticeable differences assess precision or spatial resolution, while points of subjective equality evaluate acuity or bias. Similar confusions between these terms appear throughout the manuscript.</p></disp-quote><p>While I do not agree with the reviewer's usage of the word “acuity” and a cursory Google search does not agree with the provided definition, I have replaced acuity with precision as appropriate to improve clarity.</p><disp-quote content-type="editor-comment"><p>A paragraph within the next section seems to follow up on this insight by examining the across-participant consistency of the differences in tactile spatial resolution between body parts. To this aim, pairwise rank correlations between body sites are conducted. This analysis raises red flags from a statistical point of view. (1) An ANOVA and its follow-up tests assume no variation in the size of the tested effect but varying base values across participants. Thus, if significant differences between conditions are confirmed by the original statistical analysis, most participants will have better spatial resolution in one condition than the other condition, and the difference between body sites will be similar across participants. (2) Correlations are power-hungry, and non-parametric tests are power-hungry. Thus, the number of participants needed for a reliable rank correlation analysis far exceeds that of the study. In sum, a correlation should emerge between body sites associated with significantly different tactile JNDs; however, these correlations might only be significant for body sites with pronounced differences due to the sample size.</p></disp-quote><p>We have entirely removed this result from both the text and supplement.</p><disp-quote content-type="editor-comment"><p>The data do not support this conclusion. The conclusion that the nipple is perceived as a unit is based on poor tactile localization performance for touches on the nipple compared to the areola. The problem is that the localization task is a quadrant identification task with the center being at the nipple. Quadrants for the areola could be significantly larger due to the relative size of the areola and the nipple; the results section seems to suggest this was accounted for when placing the tactile stimuli within the quadrants, but the methods section suggests otherwise. Additionally, the areola has an advantage because of its distance from the nipple, which leads to larger Euclidean distances between the centers of the quadrants than for the nipple. Thus, participants should do better for the areola than for the nipple even if both sites have the same tactile resolution.</p></disp-quote><p>We agree with this interpretation and have updated the language throughout.</p><disp-quote content-type="editor-comment"><p>Categorization accuracy in each area was tested against chance using a Monte Carlo test, which is fine, though the calculation of the test statistic, Z, should be reported in the Methods section, as there are several options. Localization accuracies are then compared between areas using a paired t-test. It is a bit confusing that once a distribution-approximating test is used, and once a test that assumes Gaussian distributions when the data is Bernoulli/Binomial distributed. Sampling-based and t-tests are very robust, so these surprising choices should have hardly any effect on the results.</p></disp-quote><p>Excellent point. We have replaced the paired t-test with a signed rank test and added text to the methods to expand upon this.</p><disp-quote content-type="editor-comment"><p>A correlation based on N=4 participants is dangerously underpowered. A quick simulation shows that correlation coefficients of randomly sampled numbers are uniformly distributed at such a low sample size. This likely spurious correlation is not analyzed, but quite prominently featured in a figure and discussed in the text, which is worrisome.</p></disp-quote><p>We have removed this panel to reduce this concern.</p><disp-quote content-type="editor-comment"><p>The conclusion that tactile percepts are drawn toward the nipple is based on localization biases for tactile stimuli on the breast compared to the back. Unfortunately, the way participants reported the tactile locations introduces a major confound. Participants indicated the perceived locations of the tactile stimulus on 3D models of these body parts. The nipple is a highly distinctive and cognitively represented landmark, far more so than the scapula, making it very likely that responses were biased toward the nipple regardless of the actual percepts. One imperfect but better alternative would have been to ask participants to identify locations on a neutral grey patch and help them relate this patch to their skin by repeatedly tracing its outline on the skin.</p></disp-quote><p>While I wholeheartedly agree with the sentiments of the reviewer, in our experience performing these tests across many women we have found that the variability of the morphology of the breast makes it incredibly hard for women to perform this task in the way the reviewer is describing. Consequently, there is likely no perfect version of the task. That said, we have endeavored to acknowledge the limitations of the approach in the discussion.</p><disp-quote content-type="editor-comment"><p>Participants also saw their localization responses for the previously touched locations. This is unlikely to induce bias towards the nipple, but it renders any estimate of the size and variance of the errors unreliable. Participants will always make sure that the marked locations are sufficiently distant from each other.</p></disp-quote><p>I again respectfully disagree with this interpretation. If the participants were to always make sure marked locations were sufficiently distant from each other then the degree of error and bias would be similar between regions given that the visual pattern would be almost identical. As this is not true in the data, I disagree with the premise, though we hope the changes to the discussion acknowledge limitations with the data collection method.</p><disp-quote content-type="editor-comment"><p>Null-hypothesis significance testing only lets scientists either reject the null hypothesis or not. The latter does NOT mean the Null hypothesis is true, i.e., it can never be concluded that there is no effect. This rule applies to every NHST test. However, it raises particular concerns with distribution tests. The only conclusion possible is that the data are unlikely from a population with the tested distribution; these tests do not provide insight into the actual distribution of the data, regardless of whether the result is significant or not.</p></disp-quote><p>Thank you for this comment. We have updated the language to make it explicit that we do not mean to imply failing to deviate from the Null distribution does not mean that they are in fact Null in nature.</p><disp-quote content-type="editor-comment"><p><bold>Recommendations for the authors:</bold></p><p><bold>Reviewer #2 (Recommendations for the authors):</bold></p><p>I am wondering whether the interpretation of &quot;the nipple as a sensory unit&quot; is also supported by localization performance as reported in the analysis around Fig. 3 and supplementary Fig. 2. I cannot really see the error lines in that figure, and cannot tell whether any of the touches were on the nipple proper. Specifically I am wondering whether touch to the nipple is reliably attributed to the nipple, and touch to the areola to the areola, or whether confusion exists between the two. The description of the nipple as a sensory unit implies reliable attribution of touch to the respective area. Also the discussion (lines 309ff) is ambiguous about this.</p></disp-quote><p>Thank you for this comment. We have removed language about the nipple being a unit and reframed the text in the discussion. We have also clarified that touches were indeed on the nipple.</p><disp-quote content-type="editor-comment"><p>typos etc.</p><p>lines 68-71 - implied causality is not backed up by evidence and could be the other way around than stated here</p><p>line 82 grammar is inconsistent</p><p>lines 199-200, &quot;on the nipple&quot; occurs twice</p></disp-quote><p>Thank you for catching these. We have addressed the typos and grammar. We have also added a citation to the sentence where this exact hypothesis is stated. We have also relaxed the language to imply it is indeed a hypothesis.</p></body></sub-article></article>