• Fiest, K. M. et al. Prevalence and incidence of epilepsy: a systematic review and meta-analysis of international studies. Neurology 88, 296–303 (2017).


    Google Scholar
     

  • Begley, C. E. & Beghi, E. The economic cost of epilepsy: a review of the literature. Epilepsia 43, 3–9 (2002).


    Google Scholar
     

  • Tavakol, S. et al. Neuroimaging and connectomics of drug-resistant epilepsy at multiple scales: from focal lesions to macroscale networks. Epilepsia 60, 593–604 (2019).


    Google Scholar
     

  • Fiest, K. M., Birbeck, G. L., Jacoby, A. & Jette, N. Stigma in epilepsy. Curr. Neurol. Neurosci. Rep. 14, 444 (2014).


    Google Scholar
     

  • Tellez-Zenteno, J. F., Patten, S. B., Jetté, N., Williams, J. & Wiebe, S. Psychiatric comorbidity in epilepsy: a population-based analysis. Epilepsia 48, 2336–2344 (2007).


    Google Scholar
     

  • Sultana, B. et al. Incidence and prevalence of drug-resistant epilepsy: a systematic review and meta-analysis. Neurology 96, 805–817 (2021).


    Google Scholar
     

  • Kwan, P. et al. Definition of drug resistant epilepsy: consensus proposal by the ad hoc Task Force of the ILAE Commission on Therapeutic Strategies. Epilepsia 51, 1069–1077 (2010).


    Google Scholar
     

  • Engel, J. What can we do for people with drug-resistant epilepsy? The 2016 Wartenberg Lecture. Neurology 87, 2483–2489 (2016).


    Google Scholar
     

  • Perucca, P., Bahlo, M. & Berkovic, S. F. The genetics of epilepsy. Annu. Rev. Genom. Hum. Genet. 21, 205–230 (2020).


    Google Scholar
     

  • Qiu, Y. et al. On-demand cell-autonomous gene therapy for brain circuit disorders. Science 378, 523–532 (2022).


    Google Scholar
     

  • International League Against Epilepsy Consortium on Complex Epilepsies. GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture. Nat Genet. 55, 1471–1482 (2023).

  • Li, R. et al. Transcriptionally downregulated GABAergic genes associated with synaptic density network dysfunction in temporal lobe epilepsy. Eur. J. Nucl. Med. Mol. Imaging https://doi.org/10.1007/s00259-024-07054-5 (2025).

  • François, L. et al. Identification of gene regulatory networks affected across drug-resistant epilepsies. Nat. Commun. 15, 2180 (2024).


    Google Scholar
     

  • Alsubhi, S. et al. Utility of genetic testing in the pre-surgical evaluation of children with drug-resistant epilepsy. J. Neurol. 271, 2503–2508 (2024).


    Google Scholar
     

  • Li, Y. et al. Alterations in spontaneous brain activity and functional network reorganization following surgery in children with medically refractory epilepsy: a resting-state functional magnetic resonance imaging study. Front. Neurol. 8, 374 (2017).


    Google Scholar
     

  • Larivière, S., Bernasconi, A., Bernasconi, N. & Bernhardt, B. C. Connectome biomarkers of drug-resistant epilepsy. Epilepsia 62, https://doi.org/10.1111/epi.16753 (2021).

  • Johnson, G. W., Doss, D. J. & Englot, D. J. Network dysfunction in pre and postsurgical epilepsy: connectomics as a tool and not a destination. Curr. Opin. Neurol. 35, 196–201 (2022).


    Google Scholar
     

  • Shao, R. et al. Alteration in early resting‑state functional MRI activity in comatose survivors of cardiac arrest: a prospective cohort study. Crit. Care 28, 260 (2024).


    Google Scholar
     

  • Jing, J. et al. Central vein sign and trigeminal lesions of multiple sclerosis visualised by 7T MRI. J. Neurol. Neurosurg. Psychiatry 95, 761–766 (2024).


    Google Scholar
     

  • Hagen, J. et al. Phenomena of hypo- and hyperconnectivity in basal ganglia-thalamo-cortical circuits linked to major depression: a 7T fMRI study. Mol. Psychiatry 30, 158–167 (2025).


    Google Scholar
     

  • Khoshkhoo, S. et al. Contribution of somatic Ras/Raf/mitogen-activated protein kinase variants in the hippocampus in drug-resistant mesial temporal lobe epilepsy. JAMA Neurol. 80, 578–587 (2023).


    Google Scholar
     

  • Pfisterer, U. et al. Identification of epilepsy-associated neuronal subtypes and gene expression underlying epileptogenesis. Nat. Commun. 11, 5038 (2020).


    Google Scholar
     

  • Sunkin, S. M. et al. Allen brain Atlas: an integrated spatio-temporal portal for exploring the central nervous system. Nucleic Acids Res. 41, https://doi.org/10.1093/nar/gks1042 (2013).

  • Estevez-Fraga, C. et al. Genetic topography and cortical cell loss in Huntington’s disease link development and neurodegeneration. Brain 146, 4532–4546 (2023).


    Google Scholar
     

  • Arnatkeviciute, A., Markello, R. D., Fulcher, B. D., Misic, B. & Fornito, A. Toward best practices for imaging transcriptomics of the human brain. Biol. Psychiatry 93, 391–404 (2023).


    Google Scholar
     

  • Hawrylycz, M. J. et al. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 489, 391–399 (2012).


    Google Scholar
     

  • Williams, J. A. et al. Inflammation and brain structure in schizophrenia and other neuropsychiatric disorders: a mendelian randomization study. JAMA Psychiatry 79, 498–507 (2022).


    Google Scholar
     

  • Qin, L. et al. Dynamic functional connectivity and gene expression correlates in temporal lobe epilepsy: insights from hidden Markov models. J. Transl. Med. 22, 763 (2024).


    Google Scholar
     

  • Sun, F. et al. Hippocampal gray matter volume alterations in patients with first-episode and recurrent major depressive disorder and their associations with gene profiles. BMC Psychiatry 25, 134 (2025).


    Google Scholar
     

  • Zhu, J. et al. Transcriptomic decoding of regional cortical vulnerability to major depressive disorder. Commun. Biol. 7, 960 (2024).


    Google Scholar
     

  • Knowles, J. K. et al. Precision medicine for genetic epilepsy on the horizon: recent advances, present challenges, and suggestions for continued progress. Epilepsia 63, 2461–2475 (2022).


    Google Scholar
     

  • Blokland, G. A. M., de Zubicaray, G. I., McMahon, K. L. & Wright, M. J. Genetic and environmental influences on neuroimaging phenotypes: a meta-analytical perspective on twin imaging studies. Twin Res. Hum. Genet. 15, 351–371 (2012).


    Google Scholar
     

  • Arnatkeviciute, A., Fulcher, B. D. & Fornito, A. A practical guide to linking brain-wide gene expression and neuroimaging data. Neuroimage 189, 353–367 (2019).


    Google Scholar
     

  • Li, J. et al. Cortical structural differences in major depressive disorder correlate with cell type-specific transcriptional signatures. Nat. Commun. 12, 1647 (2021).


    Google Scholar
     

  • Menon, V. 20 years of the default mode network: a review and synthesis. Neuron 111, 2469–2487 (2023).


    Google Scholar
     

  • Li, Q. et al. Linked patterns of symptoms and cognitive covariation with functional brain controllability in major depressive disorder. EBioMedicine 106, 105255 (2024).


    Google Scholar
     

  • Jiang, L. et al. Multimodal covariance network reflects individual cognitive flexibility. Int. J. Neural Syst. 34, 2450018 (2024).


    Google Scholar
     

  • Sun, C.-C. et al. Modified constraint-induced movement therapy enhances cortical plasticity in a rat model of traumatic brain injury: a resting-state functional MRI study. Neural Regen. Res. 18, 410–415 (2023).


    Google Scholar
     

  • Luo, G. et al. Abnormal ReHo and ALFF values in drug-naïve depressed patients with suicidal ideation or attempts: evidence from the REST-meta-MDD consortium. Prog. Neuropsychopharmacol. Biol. Psychiatry 136, 111210 (2024).


    Google Scholar
     

  • Qin, Y. et al. Rhythmic network modulation to thalamocortical couplings in epilepsy. Int. J. Neural Syst. 30, 2050014 (2020).


    Google Scholar
     

  • Li, R. et al. Epileptic discharge related functional connectivity within and between networks in benign epilepsy with centrotemporal spikes. Int. J. Neural Syst. 27, 1750018 (2017).


    Google Scholar
     

  • Akyuz, E., Arulsamy, A., Hasanli, S., Yilmaz, E. B. & Shaikh, M. F. Elucidating the visual phenomena in epilepsy: a mini review. Epilepsy Res. 190, 107093 (2023).


    Google Scholar
     

  • Wang, K. et al. Vagus nerve stimulation balanced disrupted default-mode network and salience network in a postsurgical epileptic patient. Neuropsychiatr. Dis. Treat. 12, 2561–2571 (2016).


    Google Scholar
     

  • Bacon, E. J. et al. Functional and effective connectivity analysis of drug-resistant epilepsy: a resting-state fMRI analysis. Front. Neurosci. 17, 1163111 (2023).


    Google Scholar
     

  • Widjaja, E., Zamyadi, M., Raybaud, C., Snead, O. C. & Smith, M. L. Impaired default mode network on resting-state FMRI in children with medically refractory epilepsy. AJNR Am. J. Neuroradiol. 34, 552–557 (2013).


    Google Scholar
     

  • Zhou, H.-X. et al. Rumination and the default mode network: meta-analysis of brain imaging studies and implications for depression. Neuroimage 206, 116287 (2020).


    Google Scholar
     

  • Zhang, Z. et al. Longitudinal assessment of resting-state fMRI in temporal lobe epilepsy: a two-year follow-up study. Epilepsy Behav. 103, 106858 (2020).


    Google Scholar
     

  • Dosenbach, N. U. F., Raichle, M. E. & Gordon, E. M. The brain’s action-mode network. Nat. Rev. Neurosci. https://doi.org/10.1038/s41583-024-00895-x (2025).

  • Englot, D. J. et al. Functional connectivity disturbances of the ascending reticular activating system in temporal lobe epilepsy. J. Neurol. Neurosurg. Psychiatry 88, 925–932 (2017).


    Google Scholar
     

  • Motelow, J. E. et al. Decreased subcortical cholinergic arousal in focal seizures. Neuron 85, 561–572 (2015).


    Google Scholar
     

  • Englot, D. J. et al. Remote effects of focal hippocampal seizures on the rat neocortex. J. Neurosci. 28, 9066–9081 (2008).


    Google Scholar
     

  • Sainburg, L. E. et al. Structural disconnection relates to functional changes after temporal lobe epilepsy surgery. Brain 146, 3913–3922 (2023).


    Google Scholar
     

  • Ganos, C. et al. A neural network for tics: insights from causal brain lesions and deep brain stimulation. Brain 145, 4385–4397 (2022).


    Google Scholar
     

  • Henshall, D. C. & Kobow, K. Epigenetics and epilepsy. Cold Spring Harb Perspect Med. 5, https://doi.org/10.1101/cshperspect.a022731 (2015).

  • Dhureja, M., Chaturvedi, P., Choudhary, A., Kumar, P. & Munshi, A. Molecular insights of drug resistance in epilepsy: multi-omics unveil. Mol. Neurobiol. 62, https://doi.org/10.1007/s12035-024-04220-6 (2025).

  • Luo, Y.-F. et al. Divergent projections of the prelimbic cortex mediate autism- and anxiety-like behaviors. Mol. Psychiatry 28, 2343–2354 (2023).


    Google Scholar
     

  • Sun, Y. et al. TMEM74 promotes tumor cell survival by inducing autophagy via interactions with ATG16L1 and ATG9A. Cell Death Dis. 8, e3031 (2017).


    Google Scholar
     

  • Mochel, F. et al. Variants in the SK2 channel gene (KCNN2) lead to dominant neurodevelopmental movement disorders. Brain 143, 3564–3573 (2020).


    Google Scholar
     

  • Cho, L. T. Y. et al. An intracellular allosteric modulator binding pocket in SK2 ion channels is shared by multiple chemotypes. Structure 26 https://doi.org/10.1016/j.str.2018.02.017 (2018).

  • Pascual Cuadrado, D., Wierczeiko, A., Hewel, C., Gerber, S. & Lutz, B. Dichotomic hippocampal transcriptome after glutamatergic vs. GABAergic deletion of the cannabinoid CB1 receptor. Front. Synaptic Neurosci. 13, 660718 (2021).


    Google Scholar
     

  • Gokce-Samar, Z. et al. Molecular and phenotypic characterization of the rorb-related disorder. Neurology 102, e207945 (2024).


    Google Scholar
     

  • Vuong, C. K. et al. Rbfox1 regulates synaptic transmission through the inhibitory neuron-specific vSNARE Vamp1. Neuron 98, https://doi.org/10.1016/j.neuron.2018.03.008 (2018).

  • Ma, M.-G. et al. RYR2 mutations are associated with benign epilepsy of childhood with centrotemporal spikes with or without arrhythmia. Front. Neurosci. 15, 629610 (2021).


    Google Scholar
     

  • Wang, S. et al. A novel BCL11A polymorphism influences gene expression, therapeutic response and epilepsy risk: a multicenter study. Front. Mol. Neurosci. 15, 1010101 (2022).


    Google Scholar
     

  • Hein, R. F. C. et al. R-SPONDIN2+ mesenchymal cells form the bud tip progenitor niche during human lung development. Dev. Cell 57, https://doi.org/10.1016/j.devcel.2022.05.010 (2022).

  • Chen, Y., Xu, C., Harirforoosh, S., Luo, X. & Wang, K.-S. Analysis of PTPRK polymorphisms in association with risk and age at onset of Alzheimer’s disease, cancer risk, and cholesterol. J. Psychiatr. Res. 96, 65–72 (2018).


    Google Scholar
     

  • Johannesen, K. M. et al. Genotype-phenotype correlations in SCN8A-related disorders reveal prognostic and therapeutic implications. Brain 145, 2991–3009 (2022).


    Google Scholar
     

  • Yang, N. et al. Antioxidants targeting mitochondrial oxidative stress: promising neuroprotectants for epilepsy. Oxid. Med. Cell Longev. 2020, 6687185 (2020).


    Google Scholar
     

  • Liu, H. et al. Prohibitin 1 regulates mtDNA release and downstream inflammatory responses. EMBO J. 41, e111173 (2022).


    Google Scholar
     

  • Fulton, R. E. et al. Neuron-specific mitochondrial oxidative stress results in epilepsy, glucose dysregulation and a striking astrocyte response. Neurobiol. Dis. 158, 105470 (2021).


    Google Scholar
     

  • Skwarzynska, D., Sun, H., Williamson, J., Kasprzak, I. & Kapur, J. Glycolysis regulates neuronal excitability via lactate receptor, HCA1R. Brain 146, 1888–1902 (2023).


    Google Scholar
     

  • Kumar, A. et al. NaCT/SLC13A5 facilitates citrate import and metabolism under nutrient-limited conditions. Cell Rep. 36, 109701 (2021).


    Google Scholar
     

  • Qiao, Y.-N. et al. Ketogenic diet-produced β-hydroxybutyric acid accumulates brain GABA and increases GABA/glutamate ratio to inhibit epilepsy. Cell Discov. 10, 17 (2024).


    Google Scholar
     

  • Rho, J. M. & Boison, D. The metabolic basis of epilepsy. Nat. Rev. Neurol. 18, 333–347 (2022).


    Google Scholar
     

  • Cai, J. et al. Assessing the causal association between human blood metabolites and the risk of epilepsy. J. Transl. Med. 20, 437 (2022).


    Google Scholar
     

  • Pugacheva, E. M. et al. BORIS/CTCFL epigenetically reprograms clustered CTCF binding sites into alternative transcriptional start sites. Genome Biol. 25, 40 (2024).


    Google Scholar
     

  • Păun, O. et al. Pioneer factor ASCL1 cooperates with the mSWI/SNF complex at distal regulatory elements to regulate human neural differentiation. Genes Dev. 37, 218–242 (2023).


    Google Scholar
     

  • Li, L., Miao, W., Huang, M., Williams, P. & Wang, Y. Integrated genomic and proteomic analyses reveal novel mechanisms of the methyltransferase SETD2 in renal cell carcinoma development. Mol. Cell Proteom. 18, 437–447 (2019).


    Google Scholar
     

  • Du, X., Wang, Y., Wang, X., Tian, X. & Jing, W. Neural circuit mechanisms of epilepsy: maintenance of homeostasis at the cellular, synaptic, and neurotransmitter levels. Neural Regen. Res. 21, 455–465 (2026).


    Google Scholar
     

  • Xiong, H., Tang, F., Guo, Y., Xu, R. & Lei, P. Neural circuit changes in neurological disorders: evidence from in vivo two-photon imaging. Ageing Res. Rev. 87, 101933 (2023).


    Google Scholar
     

  • Wu, Z. et al. FAM69C functions as a kinase for eIF2α and promotes stress granule assembly. EMBO Rep. 24, e55641 (2023).


    Google Scholar
     

  • Kelvington, B. A. & Abel, T. hnRNPH2 gain-of-function mutations reveal therapeutic strategies and a role for RNA granules in neurodevelopmental disorders. J. Clin. Investig. 133, https://doi.org/10.1172/JCI171499 (2023).

  • Kiebler, M. A. & Bauer, K. E. RNA granules in flux: dynamics to balance physiology and pathology. Nat. Rev. Neurosci. 25, 711–725 (2024).


    Google Scholar
     

  • Zaidi, D. et al. Forebrain Eml1 depletion reveals early centrosomal dysfunction causing subcortical heterotopia. J. Cell Biol. 223, https://doi.org/10.1083/jcb.202310157 (2024).

  • Bojja, S. L. et al. Metformin ameliorates the status epilepticus-induced hippocampal pathology through possible mTOR modulation. Inflammopharmacology 29, 137–151 (2021).


    Google Scholar
     

  • Wang, X., Hu, Y. & Xu, R. The pathogenic mechanism of TAR DNA-binding protein 43 (TDP-43) in amyotrophic lateral sclerosis. Neural Regen. Res. 19, 800–806 (2024).


    Google Scholar
     

  • Sharma, D., Wangoo, N. & Sharma, R. K. Ultrasensitive NIR fluorometric assay for inorganic pyrophosphatase detection via Cu2+-PPi interaction using bimetallic Au-Ag nanoclusters. Anal. Chim. Acta 1305, 342584 (2024).


    Google Scholar
     

  • Tong, X. et al. TRPM7 contributes to pyroptosis and its involvement in status epilepticus. J. Neuroinflam. 21, 315 (2024).


    Google Scholar
     

  • Kong, Z., Jiang, J., Deng, M., Deng, M. & Wu, H. Improving epilepsy management by targeting P2 × 7 receptor with ROS/electric responsive nanomicelles. J. Nanobiotechnol. 23, 332 (2025).


    Google Scholar
     

  • Schwer, B. et al. Tandem inactivation of inositol pyrophosphatases Asp1, Siw14, and Aps1 illuminates functional redundancies in inositol pyrophosphate catabolism in fission yeast. mBio 16, e0038925 (2025).


    Google Scholar
     

  • Lankinen, K. et al. Cortical depth profiles of auditory and visual 7 T functional MRI responses in human superior temporal areas. Hum. Brain Mapp. 44, 362–372 (2023).


    Google Scholar
     

  • Esteban, O. et al. fMRIPrep: a robust preprocessing pipeline for functional MRI. Nat. Methods 16, 111–116 (2019).


    Google Scholar
     

  • Mehta, K. et al. XCP – D: A robust pipeline for the post – processing of fMRI data. Imaging Neurosci (Camb). 2, imag – 2 – 00257 (2024).

  • Ciric, R. et al. Mitigating head motion artifact in functional connectivity MRI. Nat. Protoc. 13, 2801–2826 (2018).


    Google Scholar
     

  • Worsley, K. J., Taylor, J. E., Tomaiuolo, F. & Lerch, J. Unified univariate and multivariate random field theory. Neuroimage 23, S189–S195 (2004).


    Google Scholar
     

  • Markello, R. D. et al. Standardizing workflows in imaging transcriptomics with the abagen toolbox. Elife 10, https://doi.org/10.7554/eLife.72129 (2021).

  • Gordon, E. M. et al. Generation and evaluation of a cortical area parcellation from resting-state correlations. Cereb. Cortex 26, 288–303 (2016).


    Google Scholar
     

  • Colombani, C. et al. A comparison of partial least squares (PLS) and sparse PLS regressions in genomic selection in French dairy cattle. J. Dairy Sci. 95, 2120–2131 (2012).


    Google Scholar
     

  • Romero-Garcia, R. et al. Schizotypy-related magnetization of cortex in healthy adolescence is colocated with expression of schizophrenia-related genes. Biol. Psychiatry 88, 248–259 (2020).


    Google Scholar
     

  • Morgan, S. E. et al. Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes. Proc. Natl. Acad. Sci. USA 116, 9604–9609 (2019).


    Google Scholar
     

  • Zhou, Y. et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 10, 1523 (2019).


    Google Scholar
     

  • Mao, H. Decoding of regional cortical vulnerability to drug-resistant epilepsy using 7T MRI. OSF https://doi.org/10.17605/OSF.IO/6SGWV (2025).