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Backgroud Temporal lobe epilepsy (TLE) is associated with abnormal dynamic functional connectivity patterns, but the dynamic changes in brain activity at each time point remain unclear, as does the potential molecular mechanisms associated with the dynamic temporal characteristics of TLE. Methods Resting-state functional magnetic resonance imaging (rs-fMRI) was acquired for 84 TLE patients and 35 healthy controls (HCs). The data was then used to conduct HMM analysis on rs-fMRI data from TLE patients and an HC group in order to explore the intricate temporal dynamics of brain activity in TLE patients with cognitive impairment (TLE-CI). Additionally, we aim to examine the gene expression profiles associated with the dynamic modular characteristics in TLE patients using the Allen Human Brain Atlas (AHBA) database. Results Five HMM states were identified in this study. Compared with HCs, TLE and TLE-CI patients exhibited distinct changes in dynamics, including fractional occupancy, lifetimes, mean dwell time and switch rate. Furthermore, transition probability across HMM states were significantly different between TLE and TLE-CI patients ( p < 0.05). The temporal reconfiguration of states in TLE and TLE-CI patients was associated with several brain networks (including the high-order default mode network (DMN), subcortical network (SCN), and cerebellum network (CN). Furthermore, a total of 1580 genes were revealed to be significantly associated with dynamic brain states of TLE, mainly enriched in neuronal signaling and synaptic function. Conclusions This study provides new insights into characterizing dynamic neural activity in TLE. The brain network dynamics defined by HMM analysis may deepen our understanding of the neurobiological underpinnings of TLE and TLE-CI, indicating a linkage between neural configuration and gene expression in TLE. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-024-05580-2.
Backgroud Temporal lobe epilepsy (TLE) is associated with abnormal dynamic functional connectivity patterns, but the dynamic changes in brain activity at each time point remain unclear, as does the potential molecular mechanisms associated with the dynamic temporal characteristics of TLE. Methods Resting-state functional magnetic resonance imaging (rs-fMRI) was acquired for 84 TLE patients and 35 healthy controls (HCs). The data was then used to conduct HMM analysis on rs-fMRI data from TLE patients and an HC group in order to explore the intricate temporal dynamics of brain activity in TLE patients with cognitive impairment (TLE-CI). Additionally, we aim to examine the gene expression profiles associated with the dynamic modular characteristics in TLE patients using the Allen Human Brain Atlas (AHBA) database. Results Five HMM states were identified in this study. Compared with HCs, TLE and TLE-CI patients exhibited distinct changes in dynamics, including fractional occupancy, lifetimes, mean dwell time and switch rate. Furthermore, transition probability across HMM states were significantly different between TLE and TLE-CI patients ( p < 0.05). The temporal reconfiguration of states in TLE and TLE-CI patients was associated with several brain networks (including the high-order default mode network (DMN), subcortical network (SCN), and cerebellum network (CN). Furthermore, a total of 1580 genes were revealed to be significantly associated with dynamic brain states of TLE, mainly enriched in neuronal signaling and synaptic function. Conclusions This study provides new insights into characterizing dynamic neural activity in TLE. The brain network dynamics defined by HMM analysis may deepen our understanding of the neurobiological underpinnings of TLE and TLE-CI, indicating a linkage between neural configuration and gene expression in TLE. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-024-05580-2.
Background: Alzheimer’s disease (AD) and epilepsy represent two complex neurological disorders with distinct clinical manifestations, yet recent research has highlighted their intricate interplay. This review examines the association between AD and epilepsy, with particular emphasis on late-onset epilepsy of unknown etiology, increasingly acknowledged as a prodrome of AD. It delves into epidemiology, pathogenic mechanisms, clinical features, diagnostic characteristics, treatment strategies, and emerging biomarkers to provide a comprehensive understanding of this relationship. Methods: A comprehensive literature search was conducted, identifying 128 relevant articles published between 2018 and 2024. Results: Findings underscore a bidirectional relationship between AD and epilepsy, indicating shared pathogenic pathways that extend beyond traditional amyloid-beta and Tau protein pathology. These pathways encompass neuroinflammation, synaptic dysfunction, structural and network alterations, as well as molecular mechanisms. Notably, epileptic activity in AD patients may exacerbate cognitive decline, necessitating prompt detection and treatment. Novel biomarkers, such as subclinical epileptiform activity detected via advanced electroencephalographic techniques, offer promise for early diagnosis and targeted interventions. Furthermore, emerging therapeutic approaches targeting shared pathogenic mechanisms hold potential for disease modification in both AD and epilepsy. Conclusions: This review highlights the importance of understanding the relationship between AD and epilepsy, providing insights into future research directions. Clinical data and diagnostic methods are also reviewed, enabling clinicians to implement more effective treatment strategies.
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