A connectional hub in the rostral anterior cingulate cortex links areas of emotion and cognitive control
Abstract
We investigated afferent inputs from all areas in the frontal cortex (FC) to different subregions in the rostral anterior cingulate cortex (rACC). Using retrograde tracing in macaque monkeys, we quantified projection strength by counting retrogradely labeled cells in each FC area. The projection from different FC regions varied across injection sites in strength, following different spatial patterns. Importantly, a site at the rostral end of the cingulate sulcus stood out as having strong inputs from many areas in diverse FC regions. Moreover, it was at the integrative conjunction of three projection trends across sites. This site marks a connectional hub inside the rACC that integrates FC inputs across functional modalities. Tractography with monkey diffusion magnetic resonance imaging (dMRI) located a similar hub region comparable to the tracing result. Applying the same tractography method to human dMRI data, we demonstrated that a similar hub can be located in the human rACC.
Data availability
All data analysed during this study are included in the manuscript and supporting files. FreeSurfer label files have been provided for Figure 8A.
Article and author information
Author details
Funding
National Institute of Mental Health (MH106435)
- Wei Tang
- Ziyi Zhu
- Julia F Lehman
- Suzanne N Haber
National Institute of Mental Health (MH045573)
- Wei Tang
- Ziyi Zhu
- Julia F Lehman
- Suzanne N Haber
Medical Research Council (MR/L009013/1)
- Saad Jbabdi
National Institute of Mental Health (U01-MH109589)
- Michiel Cottaar
NIH Blueprint for Neuroscience Research (U01-MH093765)
- Giorgia Grisot
- Anastasia Yendiki
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All nonhuman primate experiments were performed in accordance with the Institute of Laboratory Animal Resources Guide for the Care and Use of Laboratory Animals and approved by the University Committee on Animal Resources at University of Rochester (Protocol Number UCAR-2008-122R).
Human subjects: The human data were obtained from the publicly available Human Connectome Project database. All procedures conformed to ethical standards approved by the Institutional Review Board of Partners Healthcare. All human subjects have provided written informed consent.
Reviewing Editor
- David Badre, Brown University, United States
Publication history
- Received: November 19, 2018
- Accepted: June 18, 2019
- Accepted Manuscript published: June 19, 2019 (version 1)
- Version of Record published: July 11, 2019 (version 2)
Copyright
© 2019, Tang et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Further reading
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Background: The heterogeneity of white matter damage and symptoms in concussion has been identified as a major obstacle to therapeutic innovation. In contrast, most diffusion MRI (dMRI) studies on concussion have traditionally relied on group-comparison approaches that average out heterogeneity. To leverage, rather than average out, concussion heterogeneity, we combined dMRI and multivariate statistics to characterize multi-tract multi-symptom relationships.
Methods: Using cross-sectional data from 306 previously-concussed children aged 9-10 from the Adolescent Brain Cognitive Development Study, we built connectomes weighted by classical and emerging diffusion measures. These measures were combined into two informative indices, the first representing microstructural complexity, the second representing axonal density. We deployed pattern-learning algorithms to jointly decompose these connectivity features and 19 symptom measures.
Results: Early multi-tract multi-symptom pairs explained the most covariance and represented broad symptom categories, such as a general problems pair, or a pair representing all cognitive symptoms, and implicated more distributed networks of white matter tracts. Further pairs represented more specific symptom combinations, such as a pair representing attention problems exclusively, and were associated with more localized white matter abnormalities. Symptom representation was not systematically related to tract representation across pairs. Sleep problems were implicated across most pairs, but were related to different connections across these pairs. Expression of multi-tract features was not driven by sociodemographic and injury-related variables, as well as by clinical subgroups defined by the presence of ADHD. Analyses performed on a replication dataset showed consistent results.
Conclusions: Using a double-multivariate approach, we identified clinically-informative, cross-demographic multi-tract multi-symptom relationships. These results suggest that rather than clear one-to-one symptom-connectivity disturbances, concussions may be characterized by subtypes of symptom/connectivity relationships. The symptom/connectivity relationships identified in multi-tract multi-symptom pairs were not apparent in single-tract/single-symptom analyses. Future studies aiming to better understand connectivity/symptom relationships should take into account multi-tract multi-symptom heterogeneity.
Funding: financial support for this work from a Vanier Canada Graduate Scholarship from the Canadian Institutes of Health Research (GIG), an Ontario Graduate Scholarship (SS), a Restracomp Research Fellowship provided by the Hospital for Sick Children (SS), an Institutional Research Chair in Neuroinformatics (MD), as well as a Natural Sciences and Engineering Research Council CREATE grant (MD).