. The organization of cognitive control processes in lateral frontal cortex (LFC) has been described in both regional and network models. Regionally, different types of control are organized hierarchically along a rostrocaudal axis2-8. At the network level, LFC is segregated into two functional networks, the fronto- parietal (FP) and cingulo-opercular (CO), which support control at two different timescales9-10. Despite similarities between the these models, there is no parsimonious model that accounts for both scales. A novel perspective that allows networks to overlap (i.e., share regions) can serve as a basis for their reconciliation13. Based on evidence from a preliminary analysis of overlapping network membership in LFC, I have proposed a novel two- scale model of LFC functional organization. LFC regions form a previously unidentified task network that overlaps the FP and CO networks. The task network supports tasks that engage the LFC, and connects LFC regions hierarchically. This proposal will test this model and its overlapping networks by (1) comparing changes in network integration and regional hierarchical influence at rest and during tasks with different control demands, and (2) causally testing how overlapping network membership predicts changes in network connectivity after regional perturbation.
In Aim 1, I will partially replicate a previous study18 to assess task-related network integration between the task network and FP and CO networks and its relationship with hierarchical strength between LFC regions. I will collect resting state data in 32 participants as well as two sessions of fMRI data recorded during a behavioral task whose conditions have different control demands and therefore engage distinct LFC regions. Graph theory measures of integration will be applied to task data within each condition11-12. For this analysis, I predict that integration of the task network with the FP and/or CO networks will be greater in conditions with demands that recruit LFC regions in each network. I will also correlate the change in network-specific integration from rest to each task condition with the change in regional hierarchical strength in each region. For this analysis, I predict that the change in FP and CO network integration with the task network will be positively correlated with the hierarchical strength of the LFC regions they contain.
For Aim 2, I will expand on previously reported work from our lab23 to assess how network connectivity changes when regions with different overlapping network membership profiles are perturbed with transcranial magnetic stimulation (TMS). I will collect three sessions of fMRI data in 32 participants. Session 1 will be used to identify separate TMS targets in the FP network that are and are not a part of the task network. In sessions 2 and 3, I will collect data before and after stimulation of one of these targets. I predict that TMS to the site that is part of the task network will replicate the previous results, while TMS to the site that is not will cause changes limited to the FP network. The proposed studies will provide support for my novel model of LFC, and will be the first direct tests of the relationship between functional organization of regions and networks.

Public Health Relevance

A plethora of previous research has described the functional organization of lateral frontal cortex (LFC) at both the regional and network scales, but there is no parsimonious model for both. I take a novel overlapping network perspective and propose that LFC regions form a previously unidentified network that overlaps other networks and supports tasks that engage the LFC by organizing its regions hierarchically. The projects proposed here aim to test this model by: (1) testing the relationship between network integration and regional hierarchy with changing cognitive control demands; and (2) causally testing how overlapping networks can account for connectivity changes within and between cognitive control networks after regional activity disruption.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
1F32MH119761-01A1
Application #
9911123
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Van'T Veer, Ashlee V
Project Start
2020-01-09
Project End
2023-01-08
Budget Start
2020-01-09
Budget End
2021-01-08
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California Berkeley
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704