BibTex format
@article{Luppi:2023:10.1016/j.neuroimage.2023.120162,
author = {Luppi, AI and Cabral, J and Cofre, R and Mediano, PAM and Rosas, FE and Qureshi, AY and Kuceyeski, A and Tagliazucchi, E and Raimondo, F and Deco, G and Shine, JM and Kringelbach, ML and Orio, P and Ching, S and Perl, YS and Diringer, MN and Stevens, RD and Sitt, JD},
doi = {10.1016/j.neuroimage.2023.120162},
journal = {NeuroImage},
title = {Computational modelling in disorders of consciousness: closing the gap towards personalised models for restoring consciousness},
url = {http://dx.doi.org/10.1016/j.neuroimage.2023.120162},
volume = {275},
year = {2023}
}
RIS format (EndNote, RefMan)
TY - JOUR
AB - Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges.
AU - Luppi,AI
AU - Cabral,J
AU - Cofre,R
AU - Mediano,PAM
AU - Rosas,FE
AU - Qureshi,AY
AU - Kuceyeski,A
AU - Tagliazucchi,E
AU - Raimondo,F
AU - Deco,G
AU - Shine,JM
AU - Kringelbach,ML
AU - Orio,P
AU - Ching,S
AU - Perl,YS
AU - Diringer,MN
AU - Stevens,RD
AU - Sitt,JD
DO - 10.1016/j.neuroimage.2023.120162
PY - 2023///
SN - 1053-8119
TI - Computational modelling in disorders of consciousness: closing the gap towards personalised models for restoring consciousness
T2 - NeuroImage
UR - http://dx.doi.org/10.1016/j.neuroimage.2023.120162
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:001015762700001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
UR - https://doi.org/10.1016/j.neuroimage.2023.120162
UR - http://hdl.handle.net/10044/1/107099
VL - 275
ER -
