Three large-scale brain networks are considered essential to cognitive flexibility: the ventral and dorsal attention (VANet and DANet) and salience (SNet) networks. The ventrolateral prefrontal cortex (vlPFC) is a known component of the VANet and DANet, but there is an important gap in the current knowledge regarding its involvement in the SNet. In this study, we used a translational and multimodal approach to fulfill this gap and demonstrate the existence of a SNet node within the vlPFC. First, we used tract-tracing methods in non-human primates (NHP) to quantify the anatomical connectivity strength between the different vlPFC areas and the frontal and insular cortices. The strongest connections with the dorsal anterior cingulate cortex (dACC) and anterior insula (AI) locations comprising the two main cortical SNet nodes were derived from the caudal area 47/12. This location also has strong axonal projections to subcortical structures of the salience network, including the dorsomedial thalamus, hypothalamus, sublenticular extended amygdala, and periaqueductal gray. Second, we used a seed-based functional connectivity analysis in NHP resting-state functional MRI (rsfMRI) data to validate the caudal area 47/12 as an SNet node. Third, we used the same approach in human rsfMRI data to identify a homologous structure in caudal area 47/12, also showing strong connections with the SNet cortical nodes, thus confirming the caudal area 47/12 as the SNet node in the vlPFC. Taken together, the vlPFC contains nodes for all three cognitive networks, the VANet, DANet, and SNet. Thus, the vlPFC is in a position to switch between these three cognitive networks, pointing to a key role as an attentional hub. Its tight additional connections to the orbitofrontal, dorsolateral, and ventral premotor cortices, places the vlPFC at the center for switching behaviors based on environmental stimuli, computing value and cognitive control.
All anatomical data analysed during this study are included in the manuscript and supporting files.Functional connectivity analyses utilized publicly available datasets:PRIME-DE:https://fcon_1000.projects.nitrc.org/indi/indiPRIME.htmlGSP:https://www.nature.com/articles/sdata201531
Brain Genomics Superstruct Project initial data release with structural, functional, and behavioral measuresBrain Genomics Superstruct Project.
PRIMatE Data Exchange (PRIME-DE)PRIMatE Data Exchange (PRIME-DE).
- Suzanne N Haber
- Suzanne N Haber
- Hesheng Liu
- Charles E Schroeder
- Charles E Schroeder
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Animal experimentation: All tracer experiments and animal care were approved by the University Committee on Animal Resources at University of Rochester (protocol number UCAR-2008-122R).The NKI Institutional Animal Care and Use Committee (IACUC) protocol approved all imaging methods and procedures in NHP (protocol numbers AP2016-568 and AP2019-642). All experiments were conducted following the National Guide for the Care and Use of Laboratory Animals.
- Birte U Forstmann, University of Amsterdam, Netherlands
© 2022, Trambaiolli 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.
Resolving trajectories of axonal pathways in the primate prefrontal cortex remains crucial to gain insights into higher-order processes of cognition and emotion, which requires a comprehensive map of axonal projections linking demarcated subdivisions of prefrontal cortex and the rest of brain. Here, we report a mesoscale excitatory projectome issued from the ventrolateral prefrontal cortex (vlPFC) to the entire macaque brain by using viral-based genetic axonal tracing in tandem with high-throughput serial two-photon tomography, which demonstrated prominent monosynaptic projections to other prefrontal areas, temporal, limbic, and subcortical areas, relatively weak projections to parietal and insular regions but no projections directly to the occipital lobe. In a common 3D space, we quantitatively validated an atlas of diffusion tractography-derived vlPFC connections with correlative green fluorescent protein-labeled axonal tracing, and observed generally good agreement except a major difference in the posterior projections of inferior fronto-occipital fasciculus. These findings raise an intriguing question as to how neural information passes along long-range association fiber bundles in macaque brains, and call for the caution of using diffusion tractography to map the wiring diagram of brain circuits.
Background: Deep Brain Stimulation (DBS) electrode implant trajectories are stereotactically defined using preoperative neuroimaging. To validate the correct trajectory, microelectrode recordings (MER) or local field potential recordings (LFP) can be used to extend neuroanatomical information (defined by magnetic resonance imaging) with neurophysiological activity patterns recorded from micro- and macroelectrodes probing the surgical target site. Currently, these two sources of information (imaging vs. electrophysiology) are analyzed separately, while means to fuse both data streams have not been introduced.
Methods: Here we present a tool that integrates resources from stereotactic planning, neuroimaging, MER and high-resolution atlas data to create a real-time visualization of the implant trajectory. We validate the tool based on a retrospective cohort of DBS patients (𝑁 = 52) offline and present single use cases of the real-time platform. Results: We establish an open-source software tool for multimodal data visualization and analysis during DBS surgery. We show a general correspondence between features derived from neuroimaging and electrophysiological recordings and present examples that demonstrate the functionality of the tool.
Conclusions: This novel software platform for multimodal data visualization and analysis bears translational potential to improve accuracy of DBS surgery. The toolbox is made openly available and is extendable to integrate with additional software packages.
Funding: Deutsche Forschungsgesellschaft (410169619, 424778381), Deutsches Zentrum für Luftund Raumfahrt (DynaSti), National Institutes of Health (2R01 MH113929), Foundation for OCD Research (FFOR).