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Li H, Yang J, Yu Y, Wang W, Liu Y, Zhou M, Li Q, Yang J, Shao S, Takahashi S, Ejima Y, Wu J. Global surface features contribute to human haptic roughness estimations. Exp Brain Res 2022; 240:773-789. [PMID: 35034179 PMCID: PMC8918205 DOI: 10.1007/s00221-021-06289-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 12/08/2021] [Indexed: 12/03/2022]
Abstract
Previous studies have paid special attention to the relationship between local features (e.g., raised dots) and human roughness perception. However, the relationship between global features (e.g., curved surface) and haptic roughness perception is still unclear. In the present study, a series of roughness estimation experiments was performed to investigate how global features affect human roughness perception. In each experiment, participants were asked to estimate the roughness of a series of haptic stimuli that combined local features (raised dots) and global features (sinusoidal-like curves). Experiments were designed to reveal whether global features changed their haptic roughness estimation. Furthermore, the present study tested whether the exploration method (direct, indirect, and static) changed haptic roughness estimations and examined the contribution of global features to roughness estimations. The results showed that sinusoidal-like curved surfaces with small periods were perceived to be rougher than those with large periods, while the direction of finger movement and indirect exploration did not change this phenomenon. Furthermore, the influence of global features on roughness was modulated by local features, regardless of whether raised-dot surfaces or smooth surfaces were used. Taken together, these findings suggested that an object’s global features contribute to haptic roughness perceptions, while local features change the weight of the contribution that global features make to haptic roughness perceptions.
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Affiliation(s)
- Huazhi Li
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama, 700-8530, Japan
| | - Jiajia Yang
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama, 700-8530, Japan. .,Section On Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA.
| | - Yinghua Yu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama, 700-8530, Japan.,Section On Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA
| | - Wu Wang
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
| | - Yulong Liu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama, 700-8530, Japan
| | - Mengni Zhou
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama, 700-8530, Japan
| | - Qingqing Li
- Department of Teacher Education, Wenzhou University, Wenzhou, China
| | - Jingjing Yang
- School of Computer Science and Technology, Changchun University of Science and Technology, Changchun, China
| | - Shiping Shao
- School of Social Welfare, Yonsei University, Seoul, Korea
| | - Satoshi Takahashi
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama, 700-8530, Japan
| | - Yoshimichi Ejima
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama, 700-8530, Japan
| | - Jinglong Wu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, 3-1-1 Tsushima-Naka, Kita-ku, Okayama, 700-8530, Japan.,School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
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Yang J, Huber L, Yu Y, Bandettini PA. Linking cortical circuit models to human cognition with laminar fMRI. Neurosci Biobehav Rev 2021; 128:467-478. [PMID: 34245758 DOI: 10.1016/j.neubiorev.2021.07.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 06/29/2021] [Accepted: 07/05/2021] [Indexed: 10/20/2022]
Abstract
Laboratory animal research has provided significant knowledge into the function of cortical circuits at the laminar level, which has yet to be fully leveraged towards insights about human brain function on a similar spatiotemporal scale. The use of functional magnetic resonance imaging (fMRI) in conjunction with neural models provides new opportunities to gain important insights from current knowledge. During the last five years, human studies have demonstrated the value of high-resolution fMRI to study laminar-specific activity in the human brain. This is mostly performed at ultra-high-field strengths (≥ 7 T) and is known as laminar fMRI. Advancements in laminar fMRI are beginning to open new possibilities for studying questions in basic cognitive neuroscience. In this paper, we first review recent methodological advances in laminar fMRI and describe recent human laminar fMRI studies. Then, we discuss how the use of laminar fMRI can help bridge the gap between cortical circuit models and human cognition.
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Affiliation(s)
- Jiajia Yang
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan; Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA.
| | - Laurentius Huber
- MR-Methods Group, Faculty of Psychology and Neuroscience, University of Maastricht, Maastricht, the Netherlands
| | - Yinghua Yu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan; Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA
| | - Peter A Bandettini
- Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA; Functional MRI Core Facility, National Institute of Mental Health, Bethesda, MD, USA
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Yang J, Yu Y, Shigemasu H, Kadota H, Nakahara K, Kochiyama T, Ejima Y, Wu J. Functional heterogeneity in the left lateral posterior parietal cortex during visual and haptic crossmodal dot-surface matching. Brain Behav 2021; 11:e02033. [PMID: 33470046 PMCID: PMC7994684 DOI: 10.1002/brb3.2033] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 12/26/2020] [Accepted: 12/31/2020] [Indexed: 01/28/2023] Open
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.
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Affiliation(s)
- Jiajia Yang
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.,Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA
| | - Yinghua Yu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.,Section on Functional Imaging Methods, National Institute of Mental Health, Bethesda, MD, USA.,Center for Information and Neural Networks, National Institute of Information and Communications Technology, Suita, Japan
| | | | | | | | | | - Yoshimichi Ejima
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan
| | - Jinglong Wu
- Graduate School of Interdisciplinary Science and Engineering in Health Systems, Okayama University, Okayama, Japan.,Beijing Institute of Technology, Beijing, China
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