Dynamic causal modeling of sensorimotor networks elicited by saltatory pneumotactile velocity in the glabrous hand

被引:0
|
作者
Wang, Yingying [1 ,2 ,3 ,4 ]
Oh, Hyuntaek [4 ,5 ]
Barlow, Steven M. [2 ,4 ,5 ]
机构
[1] Univ Nebraska, Neuroimaging Language Literacy & Learning Lab, Dept Special Educ & Commun Disorders, 113 Barkley Mem Ctr, Lincoln, NE 68583 USA
[2] Univ Nebraska, Ctr Brain Biol & Behav, Lincoln, NE 68583 USA
[3] Univ Nebraska, Nebraska Ctr Res Children Youth Families & Sch, Lincoln, NE 68583 USA
[4] Univ Nebraska, Biol Syst Engn, Lincoln, NE 68583 USA
[5] Univ Nebraska, Dept Special Educ & Commun Disorders, Commun Neurosci Lab, Lincoln, NE 68583 USA
关键词
dynamic causal modeling; effective connectivity; fMRI; glabrous hand; saltatory pneumotactile velocity; SECONDARY SOMATOSENSORY CORTEX; UPPER EXTREMITY FUNCTION; TACTILE; MOTOR; STIMULATION; CORTICES; CONNECTIVITY; ADAPTATION; AREAS; CLASSIFICATION;
D O I
10.1111/jon.12968
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background and Purpose The effective connectivity of neuronal networks during passive saltatory pneumotactile velocity stimulation to the glabrous hand with different velocities is still unknown. The present study investigated the effectivity connectivity elicited by saltatory pneumotactile velocity arrays placed on the glabrous hand at three velocities (5, 25, and 65 cm/second). Methods Dynamic causal modeling (DCM) was used on functional MRI data sampled from 20 neurotypical adults. Five brain regions, including the left primary somatosensory (SI) and motor (M1) cortices, bilateral secondary somatosensory (SII) cortices, and right cerebellar lobule VI, were used to build model space. Results Three velocities (5, 25, and 65 cm/second) of saltatory pneumotactile stimuli were processed in both serial and parallel modes within the sensorimotor networks. The medium velocity of 25 cm/second modulated forward interhemispheric connection from the contralateral SII to the ipsilateral SII. Pneumotactile stimulation at the medium velocity of 25 cm/second also influenced contralateral M1 through contralateral SI. Finally, the right cerebellar lobule VI was involved in the sensorimotor networks. Conclusions Our DCM results suggest the coexistence of both serial and parallel processing for saltatory pneumotactile velocity stimulation. Significant contralateral M1 modulation promotes the prospect that the passive saltatory pneumotactile velocity arrays can be used to design sensorimotor rehabilitation protocols to activate M1. The effective connectivity from the right cerebellar lobule VI to other cortical regions demonstrates the cerebellum's role in the sensorimotor networks through feedforward and feedback neuronal pathways.
引用
收藏
页码:752 / 764
页数:13
相关论文
共 16 条
  • [1] Neural encoding of saltatory pneumotactile velocity in human glabrous hand
    Oh, Hyuntaek
    Custead, Rebecca
    Wang, Yingying
    Barlow, Steven
    [J]. PLOS ONE, 2017, 12 (08):
  • [2] fMRI Data Analysis with Dynamic Causal Modeling and Bayesian Networks
    Mane, T. N.
    Nagori, M. B.
    Agrawal, S. A.
    [J]. MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8, 2012, 433-440 : 5303 - 5307
  • [3] Dynamic causal modeling of touch-evoked potentials in the rubber hand illusion
    Zeller, Daniel
    Friston, Karl J.
    Classen, Joseph
    [J]. NEUROIMAGE, 2016, 138 : 266 - 273
  • [4] Dynamic Causal Modeling of Brain Electrical Responses Elicited by Simple Stimuli in Visual Oddball Paradigm
    Sharaev, M. G.
    Mnatsakanian, E. V.
    [J]. ZHURNAL VYSSHEI NERVNOI DEYATELNOSTI IMENI I P PAVLOVA, 2014, 64 (06) : 627 - 638
  • [5] Dynamic Causal Modeling on the Identification of Interacting Networks in the Brain: A Systematic Review
    Wang, Duojin
    Liang, Sailan
    [J]. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2021, 29 : 2299 - 2311
  • [6] Dynamic causal modeling of reorganization of memory and language networks in temporal lobe epilepsy
    Fallahi, Alireza
    Hoseini-Tabatabaei, Narges
    Eivazi, Fatemeh
    Mobarakeh, Neda Mohammadi
    Dehghani-Siahaki, Hamed
    Alibiglou, Laila
    Rostami, Reza
    Habibabadi, Jafar Mehvari
    Hashemi-Fesharaki, Seyed-Sohrab
    Joghataei, Mohammad Taghi
    Nazem-Zadeh, Mohammad-Reza
    [J]. ANNALS OF CLINICAL AND TRANSLATIONAL NEUROLOGY, 2023, 10 (12): : 2238 - 2254
  • [7] Neural networks for action representation: a functional magnetic-resonance imaging and dynamic causal modeling study
    Sasaki, Akihiro T.
    Kochiyama, Takanori
    Sugiura, Motoaki
    Tanabe, Hiroki C.
    Sadato, Norihiro
    [J]. FRONTIERS IN HUMAN NEUROSCIENCE, 2012, 6
  • [8] Effective connectivity decreases in specific brain networks with postparalysis facial synkinesis: a dynamic causal modeling study
    Zhen-Zhen Ma
    Ye-Chen Lu
    Jia-Jia Wu
    Xu-Yun Hua
    Si-Si Li
    Wei Ding
    Jian-Guang Xu
    [J]. Brain Imaging and Behavior, 2022, 16 : 748 - 760
  • [9] Effective connectivity decreases in specific brain networks with postparalysis facial synkinesis: a dynamic causal modeling study
    Ma, Zhen-Zhen
    Lu, Ye-Chen
    Wu, Jia-Jia
    Hua, Xu-Yun
    Li, Si-Si
    Ding, Wei
    Xu, Jian-Guang
    [J]. BRAIN IMAGING AND BEHAVIOR, 2022, 16 (02) : 748 - 760
  • [10] Dynamic causal modeling and Granger causality Comments on: The identification of interacting networks in the brain using fMRI: Model selection, causality and deconvolution
    Friston, Karl J.
    [J]. NEUROIMAGE, 2011, 58 (02) : 303 - 305