BACKGROUND: 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.

BACKGROUND: Temporal lobe epilepsy (TLE), a prevalent neurological disorder, is associated with hippocampal oxidative stress and inflammation. A recent study reveals that the long noncoding RNA ILF3 divergent transcript (ILF3-AS1) level is elevated in the hippocampus of TLE patients; however, the functional roles of ILF3-AS1 in TLE and underlying mechanisms deserve further investigation. Hence, this study aimed to elucidate whether ILF3-AS1 is involved in the pathogenesis of TLE by regulating oxidative stress and inflammation and to explore its underlying mechanism in vitro.
METHODS: Human hippocampal neurons were subjected to a magnesium-free (Mg2+-free) solution to establish an in vitro model of TLE. The potential binding sites between ILF3-AS1 and miRNA were predicted by TargetScan/Starbase and confirmed by dual luciferase reporter assay. Cell viability and damage were assessed by cell counting kit-8 and lactate dehydrogenase assay kits, respectively. Levels of reactive oxygen species, malondialdehyde, and superoxide dismutase were determined by commercial kits. Levels of Interleukin-6 (IL-6), IL-1β, and tumor necrosis factor-alpha were quantified by enzyme-linked immunosorbent assay. The expressions of gene and protein were determined by quantitative real-time polymerase chain reaction and Western blot analysis.
RESULTS: In Mg2+-free-treated hippocampal neurons, both ILF3-AS1 and HMGB1 were highly up-regulated, whereas miR-504-3p was down-regulated. ILF3-AS1 knockdown ameliorated Mg2+-free-induced cellular damage, oxidative stress, and inflammatory response. Bioinformatics analysis revealed that miR-504-3p was a target of ILF3-AS1 and was negatively regulated by ILF3-AS1. MiR-504-3p inhibitor blocked the protection of ILF3-AS1 knockdown against Mg2+-free-induced neuronal injury. Further analysis presented that ILF3-AS1 regulated HMGB1 expression by sponging miR-504-3p. Moreover, HMGB1 overexpression reversed the protective functions of ILF3-AS1 knockdown.
CONCLUSIONS: Our findings indicate that ILF3-AS1 contributes to Mg2+-free-induced hippocampal neuron injuries, oxidative stress, and inflammation by targeting the miR-504-3p/HMGB1 axis. These results provide a novel mechanistic understanding of ILF3-AS1 in TLE and suggest potential therapeutic targets for the treatment of epilepsy.

OBJECTIVE: To expand the clinical phenotype and mutation spectrum of familial mesial temporal lobe epilepsy (FMTLE) and provide a new perspective for exploring the pathological mechanisms of epilepsy caused by leucine-rich glioma inactivated 1 (LGI1) variants.
METHODS: We reported clinical data from two families with FMTLE and screened patients for variants in the LGI1 gene using Whole-exome sequencing and Sanger sequencing. The clinical features of FMTLE were analysed. The pathogenicity of the causative loci was assessed according to the American College of Medical Genetics and Genomics guidelines, and potential pathogenic mechanisms were predicted through multiple bioinformatics and molecular dynamics software.
RESULTS: We identified two novel LGI1 truncating variants within two large families with FMTLE: LGI1 (c.1174C>T, p.Q392X) and LGI1 (c.703C>T, p.Q235X). Compared to previous reports, we found that focal to bilateral tonic-clonic seizures are a common type of seizure in FMTLE. The clinical phenotypes of patients with FMTLE caused by LGI1 variants were relatively mild, and all patients responded well to valproic acid. Bioinformatics analyses and molecular dynamics simulations showed that protein structure and interactions were considerably weakened or damaged as a result of both variants.
CONCLUSIONS: This study presents the first report identifying LGI1 as a potential novel pathogenic gene within FMTLE families, thereby broadening the mutation spectrum associated with FMTLE. The findings of this study offer novel insights and avenues for understanding the intricate molecular mechanisms underlying LGI1 variants and their correlations with patient phenotypes. This study proposes the possibility of familial focal epilepsy syndromes overlapping.

OBJECTIVE: To explore multiple features of attention impairments in patients with temporal lobe epilepsy (TLE).
METHODS: A total of 93 patients diagnosed with TLE at Xiangya Hospital during May 2022 and December 2022 and 85 healthy controls were included in this study. Participants were asked to complete neuropsychological scales and attention network test (ANT) with recording of eye-tracking and electroencephalogram.
RESULTS: All means of evaluation showed impaired attention functions in TLE patients. ANT results showed impaired orienting (p < 0.001) and executive control (p = 0.041) networks. Longer mean first saccade time (p = 0.046) and more total saccadic counts (p = 0.035) were found in eye-tracking results, indicating abnormal alerting and orienting networks. Both alerting, orienting and executive control networks were abnormal, manifesting as decreased amplitudes (N1 & P3, p < 0.001) and extended latency (P3, p = 0.002). The energy of theta, alpha and beta were all sensitive to the changes of alerting and executive control network with time, but only beta power was sensitive to the changes of orienting network.
CONCLUSIONS: Our findings are helpful for early identification of patients with TLE combined with attention impairments, which have strong clinical guiding significance for long-term monitoring and intervention.

Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed 116 TLE patients compared with 51 healthy controls. Employing microstate analysis, we assessed brain dynamic disparities between TLE patients and healthy controls, as well as between drug-resistant epilepsy (DRE) and drug-sensitive epilepsy (DSE) patients. We constructed dynamic functional connectivity networks based on microstates and quantified their spatial and temporal variability. Utilizing these brain network features, we developed machine learning models to discriminate between TLE patients and healthy controls, and between DRE and DSE patients. Temporal dynamics in TLE patients exhibited significant acceleration compared to healthy controls, along with heightened synchronization and instability in brain networks. Moreover, DRE patients displayed notably lower spatial variability in certain parts of microstate B, E and F dynamic functional connectivity networks, while temporal variability in certain parts of microstate E and G dynamic functional connectivity networks was markedly higher in DRE patients compared to DSE patients. The machine learning model based on these spatiotemporal metrics effectively differentiated TLE patients from healthy controls and discerned DRE from DSE patients. The accelerated microstate dynamics and disrupted microstate sequences observed in TLE patients mirror highly unstable intrinsic brain dynamics, potentially underlying abnormal discharges. Additionally, the presence of highly synchronized and unstable activities in brain networks of DRE patients signifies the establishment of stable epileptogenic networks, contributing to the poor responsiveness to antiseizure medications. The model based on spatiotemporal metrics demonstrated robust predictive performance, accurately distinguishing both TLE patients from healthy controls and DRE patients from DSE patients.

Over the past decades, the immune responses have been suspected of participating in the mechanisms for epilepsy. To assess the immune related pathway in temporal lobe epilepsy (TLE), we explored the altered immune pathways in TLE patients with and without hippocampal sclerosis (HS). We analyzed RNA-seq data from 3 TLE-HS and 3 TLE-nonHS patients, including identification of differentially expressed RNA, function pathway enrichment, the protein-protein interaction network and construction of ceRNA regulatory network. We illustrated the immune related landscape of molecules and pathways on human TLE-HS. Also, we identified several differential immune related genes like HSP90AA1 and SOD1 in TLE-HS patients. Further ceRNA regulatory network analysis found SOX2-OT connected to miR-671-5p and upregulated the target gene SPP1 in TLE-HS patients. Also, we identified both SOX2-OT and SPP1 were significantly upregulated in five different databases including TLE-HS patients and animal models. Our findings established the first immune related genes and possible regulatory pathways in TLE-HS patients and animal models, which provided a novel insight into disease pathogenesis in both patients and animal models. The immune related SOX2-OT/miR-671-5p/SPP1 axis may be the potential therapeutic target for TLE-HS.

OBJECTIVE: Temporal lobe epilepsy (TLE) patients often exhibit varying degrees of cognitive impairments. This study aims to predict cognitive performance in TLE patients by applying a connectome-based predictive model (CPM) to whole-brain resting-state functional connectivity (RSFC) data.
METHODS: A CPM was established and leave-one-out cross-validation was employed to decode the cognitive performance of patients with TLE based on the whole-brain RSFC.
RESULTS: Our findings indicate that cognitive performance in TLE can be predicted through the internal and network connections of the parietal lobe, limbic lobe, and cerebellum systems. These systems play crucial roles in cognitive control, emotion processing, and social perception and communication, respectively. In the subgroup analysis, CPM successfully predicted TLE patients with and without focal to bilateral tonic-clonic seizures (FBCTS). Additionally, significant differences were noted between the two TLE patient groups and the normal control group.
CONCLUSIONS: This data-driven approach provides evidence for the potential of predicting brain features based on the inherent resting-state brain network organization. Our study offers an initial step towards an individualized prediction of cognitive performance in TLE patients, which may be beneficial for diagnosis, prognosis, and treatment planning.

The patients with temporal lobe epilepsy (TLE) admitted in the Department of Neurology, Zhongshan Hospital, Fudan University from June 2009 to February 2012 were prospectively enrolled. The diffusion tensor imaing was performed on the patients at the time of enrollment and 3 years later. The fractional anisotropy (FA) values of the white matter connecting fibers(bilateral hooked, arcuate, cingulate, and superior longitudinal tracts), the connecting fibers of both hemispheres(anterior union, anterior callosal forceps, posterior forceps, and bilateral fornix), and fibers of perirhinal cortices system(bilateral radiating crown and anterior limb of the internal capsule) were measured by the region of interest method. The severity of epilepsy was evaluated using the Veterans Administration Seizure Type and Frequency Rating Scale(VA-2) and National Hospital Seizure Severity Scale (NHS3). A total of 51 patients with TLE were screened, with 27 patients completing the 3-year follow-up. There were 13 males and 14 females with an age of (32±11) years and a follow-up duration of (39.1±1.1) months. During the follow-up, 6 patients had increased/unchanged NHS3 or VA-2 scores, while 21 patients had decreased scores. Three years later, the FA values of the bilateral arcuate fasciculus, the right superior longitudinal fasciculus, the right radial coronal and corpus callosum anterior forceps in TLE patients decreased compared to baseline(P<0.05). However, compared to the patients with decreased VA-2 scores during the follow-up, the degree of increase in FA values (ΔFA, follow-up FA value-baseline FA value) of the ipsilateral hook bundle caused by epilepsy was more significant in the group with increased/unchanged VA-2 scores (decreased score group vs increased/unchanged score group:-0.032±0.063 vs 0.018±0.043, t=2.305, P=0.035). The value of ΔFA in epileptic patients with increased/unchanged NHS3 scores (0.075±0.113) was higher compared to those with decreased scores (-0.079±0.099, t=2.804, P=0.010). Correlation analysis also showed the changes in FA values of epileptic lateral fasciculus (r=0.503, P=0.009) and arcuate fasciculus (r=0.602, P=0.001)were positively correlated with the changes in VA-2 and HNS3 scores, respectively. The seizure severity in patients with TLE was closely associated with the microstructure changes in the frontal and temporal white matter, especially the arcuate and uncinate tracts, on the same side that caused seizures, which may indicate the white matter remodeling and abnormal network reformation associated with seizures.
前瞻性入组2009年6月至2012年2月在复旦大学附属中山医院神经内科就诊的颞叶癫痫患者，分别在入组时及3年后对患者进行弥散张量成像检查。通过感兴趣区法测定白质联络纤维（双侧钩束、弓状束、扣带束及上纵束）、两侧半球的连合纤维（前联合、胼胝体前钳、后钳及双侧穹窿）、嗅旁皮质系统纤维（双侧放射冠及内囊前肢）的部分各向异性（FA）值。采用退伍军人管理局癫痫发作类型和频率评定量表（VA-2）以及国立医院癫痫严重程度评分量表（NHS3）评估患者的癫痫严重程度。共筛查51例颞叶癫痫患者，其中27例完成3年随访。男13例，女14例，年龄（32±11）岁，随访时间（39.1±1.1）个月。3年随访期NHS3或VA-2评分增加/不变的患者各6例，NHS3或VA-2评分减少的患者各21例。3年后颞叶癫痫患者双侧弓状束、右侧上纵束、右侧放射冠、胼胝体前钳的FA值均较基线期下降（均P<0.05）。但在随访期与VA-2评分降低的患者相比，VA-2评分增高/不变组致痫同侧钩束FA值增加程度（ΔFA，随访期FA值-基线期FA值）更显著（评分降低组比增高/不变组：-0.032±0.063比0.018±0.043，t=2.305，P=0.035）；在NHS3评分增高/无变化的癫痫患者致痫侧弓状束ΔFA值（0.075±0.113）高于评分降低的癫痫患者（-0.079±0.099，t=2.804，P=0.010）。相关性分析亦提示致痫侧钩束（r=0.503，P=0.009）及弓状束（r=0.602，P=0.001）FA值的变化分别与VA-2及HNS3评分的改变呈正相关。颞叶癫痫患者发作的严重程度与致痫同侧额颞白质，尤其弓状束、钩束的微结构改变密切相关，可能提示了癫痫发作相关的白质重塑、异常网络形成。.

BACKGROUND: Hippocampal sclerosis (HS) is a prevalent cause of temporal lobe epilepsy (TLE). However, up to 30% of individuals with TLE present negative magnetic resonance imaging (MRI) findings. A comprehensive grasp of the similarities and differences in brain activity among distinct TLE subtypes holds significant clinical and scientific importance.
OBJECTIVE: To comprehensively examine the similarities and differences between TLE with HS (TLE-HS) and MRI-negative TLE (TLE-N) regarding static and dynamic abnormalities in spontaneous brain activity (SBA). Furthermore, we aimed to determine whether these alterations correlate with epilepsy duration and cognition, and to determine a potential differential diagnostic index for clinical utility.
METHODS: We measured 12 SBA metrics in 38 patients with TLE-HS, 51 with TLE-N, and 53 healthy volunteers. Voxel-wise analysis of variance (ANOVA) and post-hoc comparisons were employed to compare these metrics. The six static metrics included amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), voxel-mirrored homotopic connectivity (VMHC), degree centrality (DC), and global signal correlation (GSCorr). Additionally, six corresponding dynamic metrics were assessed: dynamic ALFF (dALFF), dynamic fALFF (dfALFF), dynamic ReHo (dReHo), dynamic DC (dDC), dynamic VMHC (dVMHC), and dynamic GSCorr (dGSCorr). Receiver operating characteristic (ROC) curve analysis of abnormal indices was employed. Spearman correlation analyses were also conducted to examine the relationship between the abnormal indices, epilepsy duration and cognition scores.
RESULTS: Both TLE-HS and TLE-N presented as extensive neural network disorders, sharing similar patterns of SBA alterations. The regions with increased fALFF, dALFF, and dfALFF levels were predominantly observed in the mesial temporal lobe, thalamus, basal ganglia, pons, and cerebellum, forming a previously proposed mesial temporal epilepsy network. Conversely, decreased SBA metrics (fALFF, ReHo, dReHo, DC, GSCorr, and VMHC) consistently appeared in the lateral temporal lobe ipsilateral to the epileptic foci. Notably, SBA alterations were more obvious in patients with TLE-HS than in those with TLE-N. Additionally, patients with TLE-HS exhibited reduced VMHC in both mesial and lateral temporal lobes compared with patients with TLE-N, with the hippocampus displaying moderate discriminatory power (AUC = 0.759). Correlation analysis suggested that alterations in SBA indicators may be associated with epilepsy duration and cognitive scores.
CONCLUSIONS: The simultaneous use of static and dynamic SBA metrics provides evidence supporting the characterisation of both TLE-HS and TLE-N as complex network diseases, facilitating the exploration of mechanisms underlying epileptic activity and cognitive impairment. Overall, SBA abnormality patterns were generally similar between the TLE-HS and TLE-N groups, encompassing networks related to TLE and auditory and occipital visual functions. These changes were more pronounced in the TLE-HS group, particularly within the mesial and lateral temporal lobes.

OBJECTIVE: Cognitive impairment is a common comorbidity in individuals with temporal lobe epilepsy (TLE), yet the underlying mechanisms remain unknown. This study explored the putative association between in vivo synaptic loss and cognitive outcomes in TLE patients by PET imaging of synaptic vesicle glycoprotein 2A (SV2A).
METHODS: We enrolled 16 TLE patients and 10 cognitively normal controls. All participants underwent SV2A PET imaging using [18F]SynVesT-1 and cognitive assessment. Lithium chloride-pilocarpine-induced rats with status epilepticus (n = 20) and controls (n = 6) rats received levetiracetam (LEV, specifically binds to SV2A), valproic acid (VPA), or saline for 14 days. Then, synaptic density was quantified by [18F]SynVesT-1 micro-PET/CT. The novel object recognition and Morris water maze tests evaluated TLE-related cognitive function. SV2A expression was examined and confirmed by immunohistochemistry.
RESULTS: Temporal lobe epilepsy patients showed significantly reduced synaptic density in hippocampus, which was associated with cognitive performance. In the rat model of TLE, the expression of SV2A and synaptic density decreased consistently in a wider range of brain regions, including the entorhinal cortex, insula, hippocampus, amygdala, thalamus, and cortex. We treated TLE animal models with LEV or VPA to explore whether synaptic loss contributes to cognitive deficits. It was found that LEV significantly exerted protective effects against brain synaptic deficits and cognitive impairment.
CONCLUSIONS: This is the first study to link synaptic loss to cognitive deficits in TLE, suggesting [18F]SynVesT-1 PET could be a promising biomarker for monitoring synaptic loss and cognitive dysfunction. LEV might help reverse synaptic deficits and ameliorate learning and memory impairments in TLE patients.