start-ver=1.4 cd-journal=joma no-vol=14 cd-vols= no-issue=5 article-no= start-page=414 end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2024 dt-pub=20240424 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Go/No-Go Ratios Modulate Inhibition-Related Brain Activity: An Event-Related Potential Study en-subtitle= kn-subtitle= en-abstract= kn-abstract=(1) Background: Response inhibition refers to the conscious ability to suppress behavioral responses, which is crucial for effective cognitive control. Currently, research on response inhibition remains controversial, and the neurobiological mechanisms associated with response inhibition are still being explored. The Go/No-Go task is a widely used paradigm that can be used to effectively assess response inhibition capability. While many studies have utilized equal numbers of Go and No-Go trials, how different ratios affect response inhibition remains unknown; (2) Methods: This study investigated the impact of different ratios of Go and No-Go conditions on response inhibition using the Go/No-Go task combined with event-related potential (ERP) techniques; (3) Results: The results showed that as the proportion of Go trials decreased, behavioral performance in Go trials significantly improved in terms of response time, while error rates in No-Go trials gradually decreased. Additionally, the NoGo-P3 component at the central average electrodes (Cz, C1, C2, FCz, FC1, FC2, PCz, PC1, and PC2) exhibited reduced amplitude and latency; (4) Conclusions: These findings indicate that different ratios in Go/No-Go tasks influence response inhibition, with the brain adjusting processing capabilities and rates for response inhibition. This effect may be related to the brain's predictive mechanism model. en-copyright= kn-copyright= en-aut-name=ZhangNan en-aut-sei=Zhang en-aut-mei=Nan kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=AnWeichao en-aut-sei=An en-aut-mei=Weichao kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=YuYinghua en-aut-sei=Yu en-aut-mei=Yinghua kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=WuJinglong en-aut-sei=Wu en-aut-mei=Jinglong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=YangJiajia en-aut-sei=Yang en-aut-mei=Jiajia kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= affil-num=1 en-affil=Graduate of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=2 en-affil=Graduate of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=3 en-affil=Graduate of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=4 en-affil=Graduate of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=5 en-affil=Graduate of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= en-keyword=response inhibition kn-keyword=response inhibition en-keyword=ratio kn-keyword=ratio en-keyword=go/no-go task kn-keyword=go/no-go task en-keyword=ERP kn-keyword=ERP en-keyword=NoGo-P3 component kn-keyword=NoGo-P3 component END start-ver=1.4 cd-journal=joma no-vol=248 cd-vols= no-issue= article-no= start-page=118867 end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2022 dt-pub=202203 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Layer-specific activation in human primary somatosensory cortex during tactile temporal prediction error processing en-subtitle= kn-subtitle= en-abstract= kn-abstract=The human brain continuously generates predictions of incoming sensory input and calculates corresponding prediction errors from the perceived inputs to update internal predictions. In human primary somatosensory cortex (area 3b), different cortical layers are involved in receiving the sensory input and generation of error signals. It remains unknown, however, how the layers in the human area 3b contribute to the temporal prediction error processing. To investigate prediction error representation in the area 3b across layers, we acquired layer specific functional magnetic resonance imaging (fMRI) data at 7T from human area 3b during a task of index finger poking with no-delay, short-delay and long-delay touching sequences. We demonstrate that all three tasks increased activity in both superficial and deep layers of area 3b compared to the random sensory input. The fMRI signal was differentially modulated solely in the deep layers rather than the superficial layers of area 3b by the delay time. Compared with the no-delay stimuli, activity was greater in the deep layers of area 3b during the short delay stimuli but lower during the long-delay stimuli. This difference activity features in the superficial and deep layers suggest distinct functional contributions of area 3b layers to tactile temporal prediction error processing. The functional segregation in area 3b across layers may reflect that the excitatory and inhibitory interplay in the sensory cortex contributions to flexible communication between cortical layers or between cortical areas. en-copyright= kn-copyright= en-aut-name=YuYinghua en-aut-sei=Yu en-aut-mei=Yinghua kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=HuberLaurentius en-aut-sei=Huber en-aut-mei=Laurentius kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=YangJiajia en-aut-sei=Yang en-aut-mei=Jiajia kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=FukunagaMasaki en-aut-sei=Fukunaga en-aut-mei=Masaki kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=ChaiYuhui en-aut-sei=Chai en-aut-mei=Yuhui kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=JangrawDavid C. en-aut-sei=Jangraw en-aut-mei=David C. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=ChenGang en-aut-sei=Chen en-aut-mei=Gang kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= en-aut-name=HandwerkerDaniel A. en-aut-sei=Handwerker en-aut-mei=Daniel A. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=8 ORCID= en-aut-name=MolfesePeter J. en-aut-sei=Molfese en-aut-mei=Peter J. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=9 ORCID= en-aut-name=EjimaYoshimichi en-aut-sei=Ejima en-aut-mei=Yoshimichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=10 ORCID= en-aut-name=SadatoNorihiro en-aut-sei=Sadato en-aut-mei=Norihiro kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=11 ORCID= en-aut-name=WuJinglong en-aut-sei=Wu en-aut-mei=Jinglong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=12 ORCID= en-aut-name=BandettiniPeter A. en-aut-sei=Bandettini en-aut-mei=Peter A. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=13 ORCID= affil-num=1 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=2 en-affil=MR-Methods Group, MBIC, Cognitive Neuroscience Department, Faculty of Psychology and Neuroscience, University of Maastricht, Cognitive Neuroscience kn-affil= affil-num=3 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=4 en-affil=Division of Cerebral Research, National Institute for Physiological Sciences kn-affil= affil-num=5 en-affil=Section on Functional Imaging Methods, National Institute of Mental Health kn-affil= affil-num=6 en-affil=Section on Functional Imaging Methods, National Institute of Mental Health kn-affil= affil-num=7 en-affil=Scientific and Statistical Computational Core, National Institute of Mental Health kn-affil= affil-num=8 en-affil=Section on Functional Imaging Methods, National Institute of Mental Health kn-affil= affil-num=9 en-affil=Section on Functional Imaging Methods, National Institute of Mental Health kn-affil= affil-num=10 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=11 en-affil=Division of Cerebral Research, National Institute for Physiological Sciences kn-affil= affil-num=12 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=13 en-affil=Section on Functional Imaging Methods, National Institute of Mental Health kn-affil= en-keyword=Layer-specific fMRI kn-keyword=Layer-specific fMRI en-keyword=Tactile prediction kn-keyword=Tactile prediction en-keyword=Primary somatosensory cortex kn-keyword=Primary somatosensory cortex en-keyword=Temporal prediction error kn-keyword=Temporal prediction error en-keyword=High-resolution CBV-fMRI kn-keyword=High-resolution CBV-fMRI END start-ver=1.4 cd-journal=joma no-vol=11 cd-vols= no-issue=15 article-no= start-page=7049 end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2021 dt-pub=20210730 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=A New Method for Haptic Shape Discriminability Detection en-subtitle= kn-subtitle= en-abstract= kn-abstract=Touch shape discrimination is not only closely related to tactile mechanoreceptors but also higher cognitive function. However, previous shape discrimination methods are difficult to complete in a short time, and the devices are complicated to operate and not user-friendly for nonprofessionals. Here, we propose a new method, the evaluation quantity of which is the angle discrimination threshold. In addition, to make this method easy to use for nonprofessionals, we designed a haptic angle sorting system, including the device and software. To evaluate this method, the angle sorting and two-angle discrimination experiments were compared, and it was found that participants spent significantly less time in the former experiment than in the latter. At the same time, there is a strong correlation between the performance of angle sorting and two-angle discrimination, which shows that the angle threshold obtained by the new method can also be used to evaluate the ability of touch discrimination. Moreover, the angle sorting results of different age groups also further demonstrate the feasibility of the method. The efficiency of this new method and the effectiveness of the system also provide a convenient means for evaluating haptic shape discrimination, which may have potential clinical application value in the early diagnosis of peripheral neuropathy and even in the evaluation of cognitive function. en-copyright= kn-copyright= en-aut-name=LiuYulong en-aut-sei=Liu en-aut-mei=Yulong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=YangJiajia en-aut-sei=Yang en-aut-mei=Jiajia kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=YuYinghua en-aut-sei=Yu en-aut-mei=Yinghua kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=YuYiyang en-aut-sei=Yu en-aut-mei=Yiyang kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=WangWu en-aut-sei=Wang en-aut-mei=Wu kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=LiHuazhi en-aut-sei=Li en-aut-mei=Huazhi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=TakahashiSatoshi en-aut-sei=Takahashi en-aut-mei=Satoshi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= en-aut-name=EjimaYoshimichi en-aut-sei=Ejima en-aut-mei=Yoshimichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=8 ORCID= en-aut-name=WuQiong en-aut-sei=Wu en-aut-mei=Qiong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=9 ORCID= en-aut-name=WuJinglong en-aut-sei=Wu en-aut-mei=Jinglong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=10 ORCID= affil-num=1 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=2 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=3 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=4 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=5 en-affil=The School of Psychological and Cognitive Sciences, Peking University kn-affil= affil-num=6 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=7 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=8 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=9 en-affil=Department of Psychology, Suzhou University of Science and Technology, kn-affil= affil-num=10 en-affil=Research Center for Medical Artificial Intelligence, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences kn-affil= en-keyword=haptic angle discrimination kn-keyword=haptic angle discrimination en-keyword=angle sort kn-keyword=angle sort en-keyword=discrimination threshold kn-keyword=discrimination threshold en-keyword=haptic device kn-keyword=haptic device en-keyword=human haptics kn-keyword=human haptics END start-ver=1.4 cd-journal=joma no-vol=11 cd-vols= no-issue=3 article-no= start-page=e02033 end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2021 dt-pub=20210119 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Functional heterogeneity in the left lateral posterior parietal cortex during visual and haptic crossmodal dot-surface matching en-subtitle= kn-subtitle= en-abstract= kn-abstract=Background
Vision and touch are thought to contribute information to object perception in an independent but complementary manner. The left lateral posterior parietal cortex (LPPC) has long been associated with multisensory information processing, and it plays an important role in visual and haptic crossmodal information retrieval. However, it remains unclear how LPPC subregions are involved in visuo‐haptic crossmodal retrieval processing.
Methods
In the present study, we used an fMRI experiment with a crossmodal delayed match‐to‐sample paradigm to reveal the functional role of LPPC subregions related to unimodal and crossmodal dot‐surface retrieval.
Results
The visual‐to‐haptic condition enhanced the activity of the left inferior parietal lobule relative to the haptic unimodal condition, whereas the inverse condition enhanced the activity of the left superior parietal lobule. By contrast, activation of the left intraparietal sulcus did not differ significantly between the crossmodal and unimodal conditions. Seed‐based resting connectivity analysis revealed that these three left LPPC subregions engaged distinct networks, confirming their different functions in crossmodal retrieval processing.
Conclusion
Taken together, the findings suggest that functional heterogeneity of the left LPPC during visuo‐haptic crossmodal dot‐surface retrieval processing reflects that the left LPPC does not simply contribute to retrieval of past information; rather, each subregion has a specific functional role in resolving different task requirements. en-copyright= kn-copyright= en-aut-name=YangJiajia en-aut-sei=Yang en-aut-mei=Jiajia kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=YuYinghua en-aut-sei=Yu en-aut-mei=Yinghua kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=ShigemasuHiroaki en-aut-sei=Shigemasu en-aut-mei=Hiroaki kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=KadotaHiroshi en-aut-sei=Kadota en-aut-mei=Hiroshi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=NakaharaKiyoshi en-aut-sei=Nakahara en-aut-mei=Kiyoshi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=KochiyamaTakanori en-aut-sei=Kochiyama en-aut-mei=Takanori kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=EjimaYoshimichi en-aut-sei=Ejima en-aut-mei=Yoshimichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= en-aut-name=WuJinglong en-aut-sei=Wu en-aut-mei=Jinglong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=8 ORCID= affil-num=1 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=2 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=3 en-affil=Kochi University of Technology kn-affil= affil-num=4 en-affil=Kochi University of Technology kn-affil= affil-num=5 en-affil=Kochi University of Technology kn-affil= affil-num=6 en-affil=ATR Brain Activity Imaging Center kn-affil= affil-num=7 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=8 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University kn-affil= en-keyword=crossmodal processing kn-keyword=crossmodal processing en-keyword=fMRI kn-keyword=fMRI en-keyword=haptic dot-surface matching kn-keyword=haptic dot-surface matching en-keyword=lateral posterior parietal cortex kn-keyword=lateral posterior parietal cortex en-keyword=memory retrieval kn-keyword=memory retrieval END start-ver=1.4 cd-journal=joma no-vol=5 cd-vols= no-issue=5 article-no= start-page=eaav9053 end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2019 dt-pub=20190501 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Layer-specific activation of sensory input and predictive feedback in the human primary somatosensory cortex en-subtitle= kn-subtitle= en-abstract= kn-abstract=When humans perceive a sensation, their brains integrate inputs from sensory receptors and process them based on their expectations. The mechanisms of this predictive coding in the human somatosensory system are not fully understood. We fill a basic gap in our understanding of the predictive processing of somatosensation by examining the layer-specific activity in sensory input and predictive feedback in the human primary somatosensory cortex (S1). We acquired submillimeter functional magnetic resonance imaging data at 7T (n = 10) during a task of perceived, predictable, and unpredictable touching sequences. We demonstrate that the sensory input from thalamic projects preferentially activates the middle layer, while the superficial and deep layers in S1 are more engaged for cortico-cortical predictive feedback input. These findings are pivotal to understanding the mechanisms of tactile prediction processing in the human somatosensory cortex. en-copyright= kn-copyright= en-aut-name=YuYinghua en-aut-sei=Yu en-aut-mei=Yinghua kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=HuberLaurentius en-aut-sei=Huber en-aut-mei=Laurentius kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=YangJiajia en-aut-sei=Yang en-aut-mei=Jiajia kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=JangrawDavid C. en-aut-sei=Jangraw en-aut-mei=David C. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=HandwerkerDaniel A. en-aut-sei=Handwerker en-aut-mei=Daniel A. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=MolfesePeter J. en-aut-sei=Molfese en-aut-mei=Peter J. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=ChenGang en-aut-sei=Chen en-aut-mei=Gang kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= en-aut-name=EjimaYoshimichi en-aut-sei=Ejima en-aut-mei=Yoshimichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=8 ORCID= en-aut-name=WuJinglong en-aut-sei=Wu en-aut-mei=Jinglong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=9 ORCID= en-aut-name=BandettiniPeter A. en-aut-sei=Bandettini en-aut-mei=Peter A. kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=10 ORCID= affil-num=1 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems,Okayama University kn-affil= affil-num=2 en-affil=Section on Functional Imaging Methods, National Institute of Mental Health kn-affil= affil-num=3 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems,Okayama University kn-affil= affil-num=4 en-affil=Section on Functional Imaging Methods, National Institute of Mental Health kn-affil= affil-num=5 en-affil=Section on Functional Imaging Methods, National Institute of Mental Health kn-affil= affil-num=6 en-affil=Section on Functional Imaging Methods, National Institute of Mental Health kn-affil= affil-num=7 en-affil=Scientific and Statistical Computing Core, National Institute of Mental Health kn-affil= affil-num=8 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems,Okayama University kn-affil= affil-num=9 en-affil=Graduate School of Interdisciplinary Science and Engineering in Health Systems,Okayama University kn-affil= affil-num=10 en-affil=Section on Functional Imaging Methods, National Institute of Mental Health kn-affil= END start-ver=1.4 cd-journal=joma no-vol=5 cd-vols= no-issue=8 article-no= start-page=e02141 end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2019 dt-pub=201908 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Stroking hardness changes the perception of affective touch pleasantness across different skin sites en-subtitle= kn-subtitle= en-abstract= kn-abstract=Human unmyelinated tactile afferents (CT afferents) in hairy skin are thought to be involved in the transmission of affective aspects of touch. How the perception of affective touch differs across human skin has made substantial progress; however, the majority of previous studies have mainly focused on the relationship between stroking velocities and pleasantness ratings. Here, we investigate how stroking hardness affects the perception of affective touch. Affective tactile stimulation was given with four different hardness of brushes a three different forces, which were presented to either palm or forearm. To quantify the physical factors of the stimuli (brush hardness), ten naive, healthy participants assessed brush hardness using a seven-point scale. Based on these ten participants, five more participants were added to rate the hedonic value of brush stroking using a visual analogue scale (VAS). We found that pleasantness ratings over the skin resulted in a preference for light, soft stroking, which was rated as more pleasant when compared to heavy, hard stroking. Our results show that the hairy skin of the forearm is more susceptible to stroking hardness than the glabrous of the palm in terms of the perception of pleasantness. These findings of the current study extend the growing literature related to the effect of stroking characteristics on pleasantness ratings. en-copyright= kn-copyright= en-aut-name=YuJiabin en-aut-sei=Yu en-aut-mei=Jiabin kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=YangJiajia en-aut-sei=Yang en-aut-mei=Jiajia kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=YuYinghua en-aut-sei=Yu en-aut-mei=Yinghua kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=WuQiong en-aut-sei=Wu en-aut-mei=Qiong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=TakahashiSatoshi en-aut-sei=Takahashi en-aut-mei=Satoshi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=EjimaYoshimichi en-aut-sei=Ejima en-aut-mei=Yoshimichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=WuJinglong en-aut-sei=Wu en-aut-mei=Jinglong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= affil-num=1 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Natural Science and Technology, Okayama University kn-affil= affil-num=2 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=3 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=4 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=5 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=6 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=7 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= en-keyword=Neuroscience kn-keyword=Neuroscience en-keyword=Pleasantness ratings kn-keyword=Pleasantness ratings en-keyword=Affective tactile kn-keyword=Affective tactile en-keyword=Physical factors kn-keyword=Physical factors en-keyword=CT afferents kn-keyword=CT afferents en-keyword=Stroking hardness kn-keyword=Stroking hardness END start-ver=1.4 cd-journal=joma no-vol=5 cd-vols= no-issue=8 article-no= start-page=e02141 end-page= dt-received= dt-revised= dt-accepted= dt-pub-year=2019 dt-pub=20190831 dt-online= en-article= kn-article= en-subject= kn-subject= en-title= kn-title=Stroking hardness changes the perception of affective touch pleasantness across different skin sites en-subtitle= kn-subtitle= en-abstract= kn-abstract=Human unmyelinated tactile afferents (CT afferents) in hairy skin are thought to be involved in the transmission of affective aspects of touch. How the perception of affective touch differs across human skin has made substantial progress; however, the majority of previous studies have mainly focused on the relationship between stroking velocities and pleasantness ratings. Here, we investigate how stroking hardness affects the perception of affective touch. Affective tactile stimulation was given with four different hardness of brushes at three different forces, which were presented to either palm or forearm. To quantify the physical factors of the stimuli (brush hardness), ten naïve, healthy participants assessed brush hardness using a seven-point scale. Based on these ten participants, five more participants were added to rate the hedonic value of brush stroking using a visual analogue scale (VAS). We found that pleasantness ratings over the skin resulted in a preference for light, soft stroking, which was rated as more pleasant when compared to heavy, hard stroking. Our results show that the hairy skin of the forearm is more susceptible to stroking hardness than the glabrous of the palm in terms of the perception of pleasantness. These findings of the current study extend the growing literature related to the effect of stroking characteristics on pleasantness ratings. en-copyright= kn-copyright= en-aut-name=YuJiabin en-aut-sei=Yu en-aut-mei=Jiabin kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=1 ORCID= en-aut-name=YangJiajia en-aut-sei=Yang en-aut-mei=Jiajia kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=2 ORCID= en-aut-name=YuYinghua en-aut-sei=Yu en-aut-mei=Yinghua kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=3 ORCID= en-aut-name=WuQiong en-aut-sei=Wu en-aut-mei=Qiong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=4 ORCID= en-aut-name=TakahashiSatoshi en-aut-sei=Takahashi en-aut-mei=Satoshi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=5 ORCID= en-aut-name=EjimaYoshimichi en-aut-sei=Ejima en-aut-mei=Yoshimichi kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=6 ORCID= en-aut-name=WuJinglong en-aut-sei=Wu en-aut-mei=Jinglong kn-aut-name= kn-aut-sei= kn-aut-mei= aut-affil-num=7 ORCID= affil-num=1 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Natural Science and Technology, Okayama University kn-affil= affil-num=2 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=3 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=4 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=5 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=6 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= affil-num=7 en-affil=Cognitive Neuroscience Laboratory, Graduate School of Interdisciplinary, Science and Engineering in Health Systems, Okayama University kn-affil= en-keyword=Affective tactile kn-keyword=Affective tactile en-keyword=CT afferents; Neuroscience kn-keyword=CT afferents; Neuroscience en-keyword=Physical factors kn-keyword=Physical factors en-keyword=Pleasantness ratings kn-keyword=Pleasantness ratings en-keyword=Stroking hardness. kn-keyword=Stroking hardness. END