Neurodegenerative Diseases Target Large-Scale Human Brain Networks
Open accessAbstract
During development, the healthy human brain constructs a host of large-scale, distributed, function-critical neural networks. Neurodegenerative diseases have been thought to target these systems, but this hypothesis has not been systematically tested in living humans. We used network-sensitive neuroimaging methods to show that five different neurodegenerative syndromes cause circumscribed atrophy within five distinct, healthy, human intrinsic functional connectivity networks. We further discovered a direct link between intrinsic connectivity and gray matter structure. Across healthy individuals, nodes within each functional network exhibited tightly correlated gray matter volumes. The findings suggest that human neural networks can be defined by synchronous baseline activity, a unified corticotrophic fate, and selective vulnerability to neurodegenerative illness. Future studies may clarify how these complex systems are assembled during development and undermined by disease.
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Human MRI-based studies rely on atrophy patterns or low-resolution PET imaging of tau deposition, and histopathological analysis of end-stage disease.
“Instead, they rely on atrophy patterns or relatively low-resolution positron emission tomography (PET) imaging of tau deposition, and histopathological analysis of end-stage disease (Seeley et al., 2009).”
From Spontaneous pathology in PS19 tauopathy mice progresses via brain networks (2025) · cites this paper as Seeley et al., 2009
The Results and Experimental Procedures (page unavailable) describe MRI-derived atrophy patterns in patients with neurodegenerative syndromes, supporting that part of the claim. The paper does not describe low-resolution PET imaging of tau deposition or reliance on histopathological analysis of end-stage disease; it distinguishes its clinical syndromes from histopathological entities. (LLM, conf=0.88)
Experimental — accuracy not yet measuredHuman studies based on functional connectivity and tractography have suggested brain networks could play a role in tauopathy progression, consistent with the prion hypothesis.
“Human studies based on functional connectivity and tractography have suggested brain networks could play a role in tauopathy progression, consistent with the prion hypothesis (Braak and Braak, 1991; Seeley et al., 2009; Drzezga, 2018; Frontzkowski et al., 2022).”
From Spontaneous pathology in PS19 tauopathy mice progresses via brain networks (2025) · cites this paper as Seeley et al., 2009
The Discussion reports that dementia-related atrophy patterns align with functional brain networks and proposes prion-like, transsynaptic spread of misfolded proteins, including tau, as a possible mechanism. But this study examined clinical dementia syndromes rather than directly tracking tauopathy progression, and its described methods use functional connectivity and structural covariance, not tractography. (LLM, conf=0.86)
Experimental — accuracy not yet measuredIn humans, MRI-based studies using fMRI and tractography cannot precisely map pathology at the cellular level.
“In humans, magnetic resonance imaging- (MRI) based studies using functional MRI (fMRI) and tractography cannot precisely map pathology at the cellular level.”
From Spontaneous pathology in PS19 tauopathy mice progresses via brain networks (2025) · cites this paper as Seeley et al., 2009
The Experimental Procedures (Image acquisition and Image preprocessing and analysis; page unavailable) describe millimeter-scale MRI and fMRI measurements, while the Subjects section distinguishes imaging-defined clinical syndromes from underlying histopathology and says predicting neuropathology was not a goal. This supports a limitation on what this study’s imaging maps establish, but the paper does not state the general claim about cellular-level precision or address tractography’s ability to map pathology. (LLM, conf=0.76)
Experimental — accuracy not yet measuredIn humans, studies of the role of network involvement have combined functional connectivity or tractography with imaging of tau pathology based on positron emission tomography, or, as a surrogate, brain atrophy.
“In humans, studies of the role of network involvement have combined functional connectivity or tractography, with imaging of tau pathology based on positron emission tomography, or, as a surrogate, brain atrophy (Seeley et al., 2009).”
From Spontaneous pathology in PS19 tauopathy mice progresses via brain networks (2025) · cites this paper as Seeley et al., 2009
The Results section (‘Syndromic atrophy foci anchor large-scale functional networks in the healthy brain’; page unavailable) describes comparing syndromic brain-atrophy patterns with fMRI functional-connectivity maps. The cited study does not describe tractography or tau PET imaging. Its Discussion also cautions that the syndromes can arise from diverse molecular pathologies, so it does not establish atrophy as a surrogate specifically for tau pathology. (LLM, conf=0.88)
Experimental — accuracy not yet measuredClinical syndromes are known to correspond more closely to neuroanatomical lesions as compared to neuropathology.
“Additionally, our classification of interest was clinical diagnosis, as clinical syndromes are known to correspond more closely to neuroanatomical lesions as compared to neuropathology (Seeley et al., 2009).”
From Differential diagnosis of frontotemporal dementia subtypes with explainable deep learning on structural MRI (2024) · cites this paper as Seeley et al., 2009
The spatial atrophy pattern of neurodegenerative diseases resembles a distinct intrinsic functional connectivity.
“the spatial atrophy pattern of neurodegenerative diseases resembles a distinct intrinsic functional connectivity (Buckner et al., 2005; Seeley et al., 2009)”
From Effects of Alzheimer’s and Vascular Pathologies on Structural Connectivity in Early- and Late-Onset Alzheimer’s Disease (2021) · cites this paper as Seeley et al., 2009
Alzheimer's disease pathology primarily affects the posterior cingulate cortex and the medial temporal subsystem.
“The pathology of AD primarily affects the PCC and the medial temporal subsystem.191,192,194”
From The default network and self-generated thought: component processes, dynamic control, and clinical relevance (2014) · cites this paper as [192]
Alzheimer's disease and frontotemporal lobar degeneration target relatively distinct regions within and outside the default network.
“Alzheimer’s disease (AD) and forms of frontotemporal lobar degeneration (FTLD), including semantic dementia (SD) and behavioral variant frontotemporal dementia (bv-FTD), are neurodegenerative disorders that target relatively distinct regions within and outside the DN.190–193”
From The default network and self-generated thought: component processes, dynamic control, and clinical relevance (2014) · cites this paper as [192]
Frontotemporal lobar degeneration more specifically affects the dorsal medial subsystem, anterior medial prefrontal cortex, and salience network, with degeneration extending from dorsal to ventral prefrontal regions and into lateral temporal cortex.
“In contrast to AD, FTLD more specifically affects the dorsal medial subsystem, the amPFC, and the salience network, with degeneration extending from dorsal to ventral prefrontal regions and into the lateral temporal cortex.43,192”
From The default network and self-generated thought: component processes, dynamic control, and clinical relevance (2014) · cites this paper as [192]
Subjects with bvFTD showed reduced connectivity in prefrontal, insular, and temporal regions in functional and structural networks, and reduction in global network degree and efficiency.
“The subjects with bvFTD showed reduced connectivity in the prefrontal, insular, and temporal regions in terms of the functional (Agosta et al., 2013; Jalilianhasanpour et al., 2019; Seeley et al., 2009; Whitwell, 2019) and structural (Dopper et al., 2014; Mahoney et al., 2015; Tovar-Moll et al., 2014; Whitwell, 2019) networks”
From Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference (2023) · cites this paper as Seeley et al., 2009
Many neurodegenerative diseases have known causes involving mutations in ubiquitously expressed proteins, yet they follow stereotyped degeneration patterns that selectively affect certain cell subsets, producing disease-specific spatial and temporal patterns.
“Many of these diseases have known causes that involve mutations in ubiquitously expressed proteins134, but they follow stereotyped patterns of degeneration that selectively affect certain cell subsets more severely, resulting in disease-specific spatial and temporal patterns of degeneration135–137 (BOX 1).”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [135]
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Network degeneration and dysfunction in presymptomatic C9ORF72 expansion carriers
Lee, S. E., Sias, A. C., Mandelli, M. L., Brown, J. A., Brown, A. B., Khazenzon, A. M., Vidovszky, A. A., Zanto, T. P., Karydas, A. M., Pribadi, M., et al. (2017) · NeuroImage: Clinical · doi:10.1016/j.nicl.2016.12.006 · Cited by 165 · see citing works
Self-citationBrain network connectivity assessed using graph theory in frontotemporal dementia
Agosta, F., Sala, S., Valsasina, P., Meani, A., Canu, E., Magnani, G., Cappa, S. F., Scola, E., Quatto, P., Horsfield, M. A., et al. (2013) · Neurology · doi:10.1212/wnl.0b013e31829a33f8 · Cited by 168 · see citing works
Grayson, D. S., Bliss-Moreau, E., Machado, C. J., Bennett, J., Shen, K., Grant, K. A., Fair, D. A., & Amaral, D. G. (2016) · Neuron · doi:10.1016/j.neuron.2016.06.005 · Cited by 172 · see citing works
Clinical prediction from structural brain MRI scans: A large-scale empirical study
Initiative, F. T. A. D. N., Sabuncu, M. R., & Konukoglu, E. (2015) · Neuroinformatics · doi:10.1007/s12021-014-9238-1 · Cited by 161 · see citing works
Local and distant relationships between amyloid, tau and neurodegeneration in Alzheimer's Disease
Iaccarino, L., Tammewar, G., Ayakta, N., Baker, S. L., Bejanin, A., Boxer, A. L., Gorno-Tempini, M. L., Janabi, M., Kramer, J. H., Lazaris, A., et al. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2017.09.016 · Cited by 165 · see citing works
Self-citationAnterior insula degeneration in frontotemporal dementia
Seeley, W. W. (2010) · Brain Structure and Function · doi:10.1007/s00429-010-0263-z · Cited by 162 · see citing works
Self-citationRedefining the multidimensional clinical phenotypes of frontotemporal lobar degeneration syndromes
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- Authors
- Seeley, W. W., Crawford, R. K., Zhou, J., Miller, B. L., & Greicius, M. D.
- Affiliations
- University of California, San Francisco (US)
- Stanford Medicine (US)
- Corresponding author
- Seeley, William W.
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2009-04
- Volume
- 62
- Issue
- 1
- Pages
- 42-52
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC2691647
- OpenAlex
- W2103717170
- Cited by
- 2,350
- References
- 68
- Citations by year
- 2026: 135 · 2025: 143 · 2024: 108 · 2023: 109 · 2022: 143 · 2021: 148 · 2020: 149 · 2019: 177 · 2018: 174 · 2017: 144 · 2016: 139 · 2015: 151 · 2014: 154 · 2013: 147 · 2012: 111
- FWCI
- 52.59
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 1568 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Neuron (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Neurological Disorders and Stroke (K23NS048302)
- Larry L. Hillblom Foundation
- National Institute on Aging (K08 AG027086, P01 AG19724, P50 AG1657303-75271)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- neurodegenerative diseases, large-scale brain networks, intrinsic functional connectivity, gray matter atrophy, gray matter volume, human brain development
- MeSH terms
- Aged, Brain, Brain Mapping, Female, Humans, Image Processing, Computer-Assisted, Functional Laterality, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Neural Pathways, Oxygen, Case-Control Studies, Neurodegenerative Diseases
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