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