Structural desegregation of intrinsic brain networks in behavioral variant frontotemporal dementia
Poster No:
199
Submission Type:
Abstract Submission
Authors:
Melanie Matyi1, Hamsanandini Radhakrishnan1, Jeffrey Phillips1, Philip Cook1, Emma Rhodes1, David Irwin1, Corey McMillan1, Lauren Massimo1
Institutions:
1University of Pennsylvania, Philadelphia, PA
First Author:
Co-Author(s):
Introduction:
Behavioral variant frontotemporal dementia (bvFTD) is a neurodegenerative disease associated with significant changes in behavior and personality (Rascovsky et al., 2011). Prior work suggests that variability in the behavioral features of bvFTD may, in part, result from differences in the organization of intrinsic brain networks, particularly of the salience network (Ferreira et al., 2022). The characteristic of intrinsic network organization that supports functional specialization of cognitive domains is known as modular segregation (Sporns, 2013). In the aging brain, loss of network segregation contributes to cognitive decline, but this has not been investigated in bvFTD (Chan et al., 2014). Examination of network segregation may provide insights into the variability of behavioral symptoms observed in bvFTD. We hypothesized that patterns of structural network desegregation will be associated with distinct behavioral features in bvFTD patients.
Methods:
Participants (90 bvFTD and 48 controls) underwent diffusion MRI and a carepartner or participant completed the Neuropsychiatric Inventory (NPI). Structural connectivity was derived from deterministic tracking among 100 regions mapped to 7 intrinsic networks (Yeo et al., 2011) using DSI-Studio (Yeh et al., 2013) as implemented in QSIPrep (Cieslak et al., 2021). The default mode, frontoparietal control, limbic, somatomotor and salience networks were examined. Graph metrics included within network connectivity (mean connections of regions within a network), between network connectivity with the salience network (mean connections of regions from one network to salience network), and segregation ((within – between) / within network connectivity). Integration of salience network was examined as functional integration of this network is disturbed in bvFTD (Ferreira et al., 2022). A series of one-way ANOVAs were conducted, first to establish divergent patterns of network desegregation in bvFTD by comparing bvFTD and control participants, and next, to assess the effect of presence of NPI items characteristic of bvFTD (apathy, elation, motor, disinhibition, irritability, eating) on segregation metrics within bvFTD. All analyses controlled for age, motion, and disease severity.
Results:
Compared to controls, bvFTD patients were characterized by network desegregation as exhibited by desegregation of salience and frontoparietal control networks, reduced connectivity between salience and default mode network, and increased connectivity between salience and somatomotor network (see Fig.1). Within bvFTD patients, symptoms characteristic of bvFTD, including presence of apathy, elated mood, motor disturbance and disinhibition were all associated with desegregation of key intrinsic networks (see Fig. 2). Specifically, patients with apathy exhibited desegregation of default mode network, elated mood exhibited desegregation of limbic, default mode, and salience networks, motor disturbance exhibited desegregation of default mode network, and disinhibition exhibited desegregation of limbic network. Additionally, bvFTD patients with irritability exhibited segregation of salience network and increased connectivity between salience and somatomotor network.
·Fig. 1 Segregation of structural intrinsic networks differ between bvFTD patients and healthy control (HC) participants. DMN=default mode network. *=p<.05, **=p<.01, ***=p<.001.
·Fig. 2 Desegregation of structural intrinsic networks are associated with presence of bvFTD features. *=p<.05, **=p<.01, ***=p<.001.
Conclusions:
Results indicated that greater network desegregation, particularly of salience network, is characteristic of bvFTD. Additionally, presence of features characteristic of bvFTD were associated with desegregation of related networks. Future studies examining network associations longitudinally may provide more nuanced understanding of these relationships. Overall, loss of specialized processing within networks posited to underlie features characteristic of bvFTD (e.g., limbic network and elated mood) were associated with the presence of those features. Results underscore the importance of intrinsic network integrity in bvFTD and suggest that desegregation of intrinsic networks may represent a mechanism of disease progression.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Lifespan Development:
Aging
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Diffusion MRI Modeling and Analysis
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
White Matter Anatomy, Fiber Pathways and Connectivity
Keywords:
Aging
Degenerative Disease
MRI
Psychiatric
Systems
Tractography
White Matter
1|2Indicates the priority used for review
Provide references using author date format
Cieslak, M., et al. (2021), ‘QSIPrep: An Integrative Platform for Preprocessing and Reconstructing Diffusion MRI Data’, Nature Methods, vol. 18, no. 7.
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Sporns, O. (2013), ‘Network Attributes for Segregation and Integration in the Human Brain’, Current Opinion in Neurobiology, vol. 23, no. 2, pp. 162–171.
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