List of publications for the week of October 13, 2021
Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior
(2021) Cerebral Cortex, 31 (10), pp. 4477-4500.
Kong, R.a b c , Yang, Q.a b c , Gordon, E.d , Xue, A.a b c , Yan, X.a b c e , Orban, C.a b c , Zuo, X.-N.f g , Spreng, N.h i j , Ge, T.k l , Holmes, A.m , Eickhoff, S.n o , Yeo, B.T.T.a b c d e l
a Department of Electrical and Computer Engineering, National University of Singapore, Singapore, 117583, Singapore
b Centre for Sleep and Cognition (CSC) and Centre for Translational Magnetic Resonance Research (TMR), National University of Singapore, Singapore, 117549, Singapore
c N.1 Institute for Health and Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, 117456, Singapore
d Department of Radiology, Washington University School of Medicine, St. Louis, MO 63130, United States
e Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, 119077, Singapore
f State Key Lab. of Cognitive Neuroscience and Learning/IDG McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China
g National Basic Public Science Data Center, Chinese Academy of Sciences, Beijing, 100101, China
h Department of Neurology and Neurosurgery, Laboratory of Brain and Cognition, McGill University, Montreal, QC H3A 2B4, Canada
i Departments of Psychiatry and Psychology, Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
j McConnell Brain Imaging Centre, Montreal Neurological Institute (MNI), McGill University, Montreal, QC H3A 2B4, Canada
k Center for Genomic Medicine, Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, United States
l Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, United States
m Department of Psychology, Yale University, New Haven, CT 06520, United States
n Medical Faculty, Institute for Systems Neuroscience, Heinrich-Heine University D sseldorf, D sseldorf, 40225, Germany
o Research Center J lich, Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), J lich, 52425, Germany
Abstract
Resting-state functional magnetic resonance imaging (rs-fMRI) allows estimation of individual-specific cortical parcellations. We have previously developed a multi-session hierarchical Bayesian model (MS-HBM) for estimating high-quality individual-specific network-level parcellations. Here, we extend the model to estimate individual-specific areal-level parcellations. While network-level parcellations comprise spatially distributed networks spanning the cortex, the consensus is that areal-level parcels should be spatially localized, that is, should not span multiple lobes. There is disagreement about whether areal-level parcels should be strictly contiguous or comprise multiple noncontiguous components; therefore, we considered three areal-level MS-HBM variants spanning these range of possibilities. Individual-specific MS-HBM parcellations estimated using 10 min of data generalized better than other approaches using 150 min of data to out-of-sample rs-fMRI and task-fMRI from the same individuals. Resting-state functional connectivity derived from MS-HBM parcellations also achieved the best behavioral prediction performance. Among the three MS-HBM variants, the strictly contiguous MS-HBM exhibited the best resting-state homogeneity and most uniform within-parcel task activation. In terms of behavioral prediction, the gradient-infused MS-HBM was numerically the best, but differences among MS-HBM variants were not statistically significant. Overall, these results suggest that areal-level MS-HBMs can capture behaviorally meaningful individual-specific parcellation features beyond group-level parcellations. Multi-resolution trained models and parcellations are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Kong2022_ArealMSHBM). © 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Author Keywords
behavioral prediction; brain parcellation; difference; individual; resting-state functional connectivity
Document Type: Article
Publication Stage: Final
Source: Scopus
In Vitro and in Vivo Investigation of S1PR1 Expression in the Central Nervous System Using [3H]CS1P1 and [11C]CS1P1
(2021) ACS Chemical Neuroscience, .
Jiang, H.a , Joshi, S.a , Liu, H.a , Mansor, S.a , Qiu, L.a , Zhao, H.a , Whitehead, T.a , Gropler, R.J.a , Wu, G.F.b , Cross, A.H.b , Benzinger, T.L.S.a c , Shoghi, K.I.a , Perlmutter, J.S.a b , Tu, Z.a
a Department of Radiology, Washington University School of Medicine, St Louis, MO 63110, United States
b Department of Neurology, Washington University School of Medicine, St Louis, MO 63110, United States
c Department of Neurological Surgery, Washington University School of Medicine, St Louis, MO 63110, United States
Abstract
Sphingosine-1-phosphate receptor 1 (S1PR1) is ubiquitously expressed among all tissues and plays key roles in many physiological and cellular processes. In the central nervous system (CNS), S1PR1 is expressed in different types of cells including neurons, astrocytes, and oligodendrocyte precursor cells. S1PR1 has been recognized as a novel therapeutic target in multiple sclerosis and other diseases. We previously reported a promising S1PR1-specific radioligand, [11C]CS1P1 (previously named [11C]TZ3321), which is under clinical investigation for human use. In the current study, we performed a detailed characterization of [3H]CS1P1 for its binding specificity to S1PR1 in CNS using autoradiography and immunohistochemistry in human and rat CNS tissues. Our data indicate that [3H]CS1P1 binds to S1PR1 in human frontal cortex tissue with a Kd of 3.98 nM and a Bmax of 172.5 nM. The distribution of [3H]CS1P1 in human and rat CNS tissues is consistent with the distribution of S1PR1 detected by immunohistochemistry studies. Our microPET studies of [11C]CS1P1 in a nonhuman primate (NHP) show a standardized uptake value of 2.4 in the NHP brain, with test-retest variability of 0.23% among six different NHPs. Radiometabolite analysis in the plasma samples of NHP and rat, as well as in rat brain samples, showed that [11C]CS1P1 was stable in vivo. Kinetic modeling studies using a two-compartment tissue model showed that the positron emission tomography (PET) data fit the model well. Overall, our study provides a detailed characterization of [3H]CS1P1 binding to S1PR1 in the CNS. Combined with our microPET studies in the NHP brain, our data suggest that [11C]CS1P1 is a promising radioligand for PET imaging of S1PR1 in the CNS. © 2021 American Chemical Society.
Author Keywords
central nervous system; positron emission tomography; radiopharmaceutical; sphingosine-1-phosphate receptor 1; [11C]CS1P1 PET imaging; [3H]CS1P1 autoradiography
Funding details
National Institutes of Health NIHEB025815, NS075527, NS103957, NS103988
Document Type: Article
Publication Stage: Article in Press
Source: Scopus