Sink-index: a network-based EEG marker for frontotemporal dementia and Alzheimer’s disease

Frontotemporal dementia is a complex neurodegenerative illness characterized by a progressive deterioration in temperament, judgement, behaviour, and communication. Misdiagnosis and late diagnosis occur frequently due to the complexity of the phenotypes, overlaps of features with other neurodegenerative syndromes and psychiatric disorders, and ill-defined preclinical phases of the illness. Diagnosis relies on structural or functional brain imaging to show characteristic atrophy, hypoperfusion or hypometabolism profiles. The sensitivity of neuroimaging is lower in the earliest phases of the illness, and there are few alternatives. Scalp electroencephalography (EEG) is a widely available, low-cost technology, but its utility in the differential diagnosis of dementia will require EEG indices of high sensitivity and discriminatory value. We have used scalp EEG to develop subject-specific Dynamic Network Models, from which we summarize the reciprocal relationships between the nodes (defined by the EEG channel). This index, the 'Sink-Index', characterizes how activity in each node (or channel) responds to activity in other nodes in the network. In this context, 'sources' are nodes that exert significant influence on the activity of different regions but are not themselves influenced, whereas 'sinks' represent influenced regions that do not affect activity in others. We hypothesized that brain regions associated with Frontotemporal dementia and Alzheimer's disease syndromes behave as sinks and have higher sink indices than healthy brain regions. This hypothesis was tested in a cohort of 88 subjects: 23 with frontotemporal dementia, 36 with Alzheimer's disease, and 29 healthy controls. The Sink-Index of nodes in the frontal-temporal and central-parietal-occipital brain regions differed between Frontotemporal dementia (1.3389 ± 0.0895 versus 0.8444 ± 0.0651), Alzheimer's disease (0.6015 ± 0.0188 versus 0.7766 ± 0.0158), and healthy controls (0.8978 ± 0.0453 versus 0.9116 ± 0.0457). These findings suggest the Sink-Index is an EEG marker with utility for the differential diagnosis of dementia syndromes.

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Journal
Brain Communications
Published
2025-01-01
DOI
https://doi.org/10.1093/braincomms/fcaf259
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Sink-index: a network-based EEG marker for frontotemporal dementia and Alzheimer’s disease

Amir Hossein Daraie, Chiadi U. Onyike, Sridevi V. Sarma, Adrian Williams et al.
Brain Communications
Functional Brain Connectivity Studies
article

Sink-index: a network-based EEG marker for frontotemporal dementia and Alzheimer’s disease

Amir Hossein Daraie, Chiadi U. Onyike, Sridevi V. Sarma, Adrian Williams, Luis A. Sánchez, Surya Pandiaraju
article en

Abstract

Frontotemporal dementia is a complex neurodegenerative illness characterized by a progressive deterioration in temperament, judgement, behaviour, and communication. Misdiagnosis and late diagnosis occur frequently due to the complexity of the phenotypes, overlaps of features with other neurodegenerative syndromes and psychiatric disorders, and ill-defined preclinical phases of the illness. Diagnosis relies on structural or functional brain imaging to show characteristic atrophy, hypoperfusion or hypometabolism profiles. The sensitivity of neuroimaging is lower in the earliest phases of the illness, and there are few alternatives. Scalp electroencephalography (EEG) is a widely available, low-cost technology, but its utility in the differential diagnosis of dementia will require EEG indices of high sensitivity and discriminatory value. We have used scalp EEG to develop subject-specific Dynamic Network Models, from which we summarize the reciprocal relationships between the nodes (defined by the EEG channel). This index, the 'Sink-Index', characterizes how activity in each node (or channel) responds to activity in other nodes in the network. In this context, 'sources' are nodes that exert significant influence on the activity of different regions but are not themselves influenced, whereas 'sinks' represent influenced regions that do not affect activity in others. We hypothesized that brain regions associated with Frontotemporal dementia and Alzheimer's disease syndromes behave as sinks and have higher sink indices than healthy brain regions. This hypothesis was tested in a cohort of 88 subjects: 23 with frontotemporal dementia, 36 with Alzheimer's disease, and 29 healthy controls. The Sink-Index of nodes in the frontal-temporal and central-parietal-occipital brain regions differed between Frontotemporal dementia (1.3389 ± 0.0895 versus 0.8444 ± 0.0651), Alzheimer's disease (0.6015 ± 0.0188 versus 0.7766 ± 0.0158), and healthy controls (0.8978 ± 0.0453 versus 0.9116 ± 0.0457). These findings suggest the Sink-Index is an EEG marker with utility for the differential diagnosis of dementia syndromes.

Brain CommunicationsVol. 7(4)
Johns Hopkins University (US), Johns Hopkins Medicine (US), Behavioral Pharma (United States) (US)
National Institutes of Health
Reduced inequalities
Openalex Percentile: Top 84%
Functional Brain Connectivity Studies
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