000256427 001__ 256427
000256427 005__ 20181203025024.0
000256427 0247_ $$2doi$$a10.1016/j.neuroimage.2018.07.055
000256427 02470 $$a10.1016/j.neuroimage.2018.07.055$$2DOI
000256427 037__ $$aARTICLE
000256427 245__ $$aHuman EEG reveals distinct neural correlates of power and precision grasping types
000256427 260__ $$c2018-11-11
000256427 269__ $$a2018-11-11
000256427 336__ $$aJournal Articles
000256427 520__ $$aHand grasping is a sophisticated motor task that has received much attention by the neuroscientific community, which demonstrated how grasping activates a network involving parietal, pre-motor and motor cortices using fMRI, ECoG, LFPs and spiking activity. Yet, there is a need for a more precise spatio-temporal analysis as it is still unclear how these brain activations over large cortical areas evolve at the sub-second level. In this study, we recorded ten human participants (1 female) performing visually-guided, self-paced reaching and grasping with precision or power grips. Following the results, we demonstrate the existence of neural correlates of grasping from broadband EEG in self-paced conditions and show how neural correlates of precision and power grasps differentially evolve as grasps unfold. 100 ms before the grasp is secured, bilateral parietal regions showed increasingly differential patterns. Afterwards, sustained differences between both grasps occurred over the bilateral motor and parietal regions, and medial pre-frontal cortex. Furthermore, these differences were sufficiently discriminable to allow single-trial decoding with 70% decoding performance. Functional connectivity revealed differences at the network level between grasps in fronto-parietal networks, in terms of upper-alpha cortical oscillatory power with a strong involvement of ipsilateral hemisphere. Our results supported the existence of fronto-parietal recurrent feedback loops, with stronger interactions for precision grips due to the finer motor control required for this grasping type.
000256427 6531_ $$aBrain-machine interfaces
000256427 6531_ $$aGrasping
000256427 6531_ $$aNeural correlates
000256427 6531_ $$aEEG
000256427 700__ $$aIturrate, Iñaki
000256427 700__ $$aChavarriaga, Ricardo
000256427 700__ $$aPereira, Michael
000256427 700__ $$aZhang, Huaijian
000256427 700__ $$aCorbet, Tiffany
000256427 700__ $$aLeeb, Robert
000256427 700__ $$aMillán, José del R.
000256427 773__ $$tNeuroImage$$j181$$q635-644
000256427 8560_ $$fjoelle.mottier@epfl.ch
000256427 909C0 $$pNCCR-ROBOTICS$$mjoelle.mottier@epfl.ch$$0252409$$xU12367
000256427 909C0 $$xU12103$$pCNBI$$mricardo.chavarriaga@epfl.ch$$0252018
000256427 909CO $$pSTI$$particle$$ooai:infoscience.epfl.ch:256427
000256427 960__ $$aricardo.chavarriaga@epfl.ch
000256427 961__ $$amanon.velasco@epfl.ch
000256427 973__ $$aEPFL$$sPUBLISHED$$rREVIEWED
000256427 980__ $$aARTICLE
000256427 981__ $$aoverwrite
000256427 999C0 $$xU12599$$pCNP$$mbruno.herbelin@epfl.ch$$0252517