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Type II focal cortical dysplasia (FCD) is a neuropathological entity characterised by cortical dyslamination with the presence of dysmorphic neurons only (FCDIIA) or the presence of both dysmorphic neurons and balloon cells (FCDIIB). The year 2021 marks the 50th anniversary of the recognition of FCD as a cause of drug resistant epilepsy, and it is now the most common reason for epilepsy surgery. The causes of FCD remained unknown until relatively recently. The study of resected human FCD tissue using novel genomic technologies has led to remarkable advances in understanding the genetic basis of FCD. Mechanistic parallels have emerged between these non-neoplastic lesions and neoplastic disorders of cell growth and differentiation, especially through perturbations of the mammalian target of rapamycin (mTOR) signalling pathway. This narrative review presents the advances through which the aetiology of FCDII has been elucidated in chronological order, from recognition of an association between FCD and the mTOR pathway to the identification of somatic mosaicism within FCD tissue. We discuss the role of a two-hit mechanism, highlight current challenges and future directions in detecting somatic mosaicism in brain and discuss how knowledge of FCD may inform novel precision treatments of these focal epileptogenic malformations of human cortical development.

Both invasive and non-invasive electroencephalographic (EEG) recordings from the human brain have an increasingly important role in neuroscience research and are candidate modalities for medical brain–machine interfacing. It is often assumed that the major artifacts that compromise non-invasive EEG, such as caused by blinks and eye movement, are absent in invasive EEG recordings. Quantitative investigations on the signal quality of simultaneously recorded invasive and non-invasive EEG in terms of artifact contamination are, however, lacking. Here we compared blink related artifacts in non-invasive and invasive EEG, simultaneously recorded from prefrontal and motor cortical regions using an approach suitable for detection of small artifact contamination. As expected, we find blinks to cause pronounced artifacts in non-invasive EEG both above prefrontal and motor cortical regions. Unexpectedly, significant blink related artifacts were also found in the invasive recordings, in particular in the prefrontal region. Computing a ratio of artifact amplitude to the amplitude of ongoing brain activity, we find that the signal quality of invasive EEG is 20 to above 100 times better than that of simultaneously obtained non-invasive EEG. Thus, while our findings indicate that ocular artifacts do exist in invasive recordings, they also highlight the much better signal quality of invasive compared to non-invasive EEG data. Our findings suggest that blinks should be taken into account in the experimental design of ECoG studies, particularly when event related potentials in fronto-anterior brain regions are analyzed. Moreover, our results encourage the application of techniques for reducing ocular artifacts to further optimize the signal quality of invasive EEG.

Hemispherotomy is a neurosurgical procedure for treating refractory epilepsy, which entails disconnecting a significant portion of the cortex, potentially encompassing an entire hemisphere, from its cortical and subcortical connections. While this intervention prevents the spread of seizures, it raises important questions. Given the complete isolation from sensory-motor pathways, it remains unclear whether the disconnected cortex retains any form of inaccessible awareness. More broadly, the activity patterns that large portions of the deafferented cortex can sustain in awake humans remain poorly understood. We address these questions by exploring for the first time the electroencephalographic (EEG) state of the isolated cortex during wakefulness before and after surgery in 10 pediatric patients, focusing on non-epileptic background activity. Post-surgery, the isolated cortex exhibited prominent slow oscillations (<2 Hz) and a steeper broad-band spectral decay, reflecting a redistribution of power toward lower frequencies. This broad-band EEG slowing resulted in a marked decrease of the spectral exponent, a validated consciousness marker, reaching values characteristic of deep anesthesia and the vegetative state. When compared with a reference pediatric sample across the sleep–wake cycle, the spectral exponent of the contralateral cortex aligned with wakefulness, whereas that of the isolated cortex was consistent with deep NREM sleep. The findings of prominent slow oscillations and broad-band slowing provisionally support inferences of absent or reduced awareness in the isolated cortex. Moreover, the persistence of unihemispheric sleep-like patterns years after surgery provides unique insights into the long-term electrophysiological effects of cortical disconnections in the human brain.

Cortico-cortical evoked potentials (CCEPs) elicited by single-pulse electric stimulation (SPES) are widely used to assess effective connectivity between cortical areas and are also implemented in the presurgical evaluation of epileptic patients. Nevertheless, the cortical generators underlying the various components of CCEPs in humans have not yet been elucidated. Our aim was to describe the laminar pattern arising under SPES evoked CCEP components (P1, N1, P2, N2, P3) and to evaluate the similarities between N2 and the downstate of sleep slow waves. We used intra-cortical laminar microelectrodes (LMEs) to record CCEPs evoked by 10 mA bipolar 0.5 Hz electric pulses in seven patients with medically intractable epilepsy implanted with subdural grids. Based on the laminar profile of CCEPs, the latency of components is not layer-dependent, however their rate of appearance varies across cortical depth and stimulation distance, while the seizure onset zone does not seem to affect the emergence of components. Early neural excitation primarily engages middle and deep layers, propagating to the superficial layers, followed by mainly superficial inhibition, concluding in a sleep slow wave-like inhibition and excitation sequence.

Background Intractable epilepsy in children poses significant clinical challenges due to limited efficacy of conventional anti-epileptic drugs (AEDs), leading to persistent neurodevelopmental impairments. This study investigated the therapeutic effects of ketogenic diet (KD), lacosamide (LCM), and their combination on refractory epilepsy, with comprehensive assessment of seizure control, EEG dynamics (including epileptiform patterns and spectral characteristics), cognitive function, lipid metabolism, and endothelial health. Methods Ninety children with refractory epilepsy were divided into three treatment groups: KD ( n  = 30), LCM ( n  = 30), and KD + LCM ( n  = 30). Assessments included detailed EEG characterization (seizure types, interictal discharges, spectral bands), cognitive testing (attention/memory), lipid profiles, and endothelial markers at baseline, 3-, and 6-months post-treatment. Results The KD + LCM group showed superior seizure reduction at 3/6 months (t = 2.171, P  = 0.035; t = 3.177, P  = 0.003), with 76.7% achieving ≥ 50% interictal discharge reduction ( P  = 0.008) and 63.3% seizure type simplification ( P  = 0.003) at 6 months. Cognitive performance significantly improved (attention: Δ=-10.8 ± 2.0; memory: Δ=-9.4 ± 1.8; both P  < 0.001), strongly correlating with frontal θ-band modulation (|r|>0.68). Combination therapy also enhanced α/β/δ/θ spectral power ( P  ≤ 0.019), improved lipid profiles, and restored endothelial function versus monotherapies (all P  < 0.05). Conclusions KD and LCM combination therapy provides comprehensive benefits—superior seizure control, EEG normalization, cognitive enhancement, metabolic optimization, and vascular protection—making it a promising multimodal approach for refractory epilepsy management.

Statistical parametric mapping (SPM) is a technique with which one can delineate brain activity statistically deviated from the normative mean, and has been commonly employed in noninvasive neuroimaging and EEG studies. Using the concept of SPM, we developed a novel technique for quantification of the statistical deviation of an intracranial electrocorticography (ECoG) measure from the nonepileptic mean. We validated this technique using data previously collected from 123 patients with drug-resistant epilepsy who underwent resective epilepsy surgery. We determined how the measurement of statistical deviation of modulation index (MI) from the non-epileptic mean (rated by z-score) improved the performance of seizure outcome classification model solely based on conventional clinical, seizure onset zone (SOZ), and neuroimaging variables. Here, MI is a summary measure quantifying the strength of in-situ coupling between high-frequency activity at >150 Hz and slow wave at 3–4 Hz. We initially generated a normative MI atlas showing the mean and standard deviation of slow-wave sleep MI of neighboring non-epileptic channels of 47 patients, whose ECoG sampling involved all four lobes. We then calculated ‘MI z-score’ at each electrode site. SOZ had a greater ‘MI z-score’ compared to non-SOZ in the remaining 76 patients. Subsequent multivariate logistic regression analysis and receiver operating characteristic analysis to the combined data of all patients revealed that the full regression model incorporating all predictor variables, including SOZ and ‘MI z-score’, best classified the seizure outcome with sensitivity/specificity of 0.86/0.76. The model excluding ‘MI z-score’ worsened its sensitivity/specificity to 0.86/0.48. Furthermore, the leave-one-out analysis successfully cross-validated the full regression model. Measurement of statistical deviation of MI from the non-epileptic mean on invasive recording is technically feasible. Our analytical technique can be used to evaluate the utility of ECoG biomarkers in epilepsy presurgical evaluation.

Epilepsy is a prevalent brain disorder, characterized by sudden, abnormal brain activity, making it difficult to live with. One-third of people with epilepsy do not respond to anti-epileptic drugs. Drug-resistant epilepsy is treated with brain surgery. Successful surgical treatment relies on identifying brain regions responsible for seizure onset, known as epileptogenic zones (EZ). Despite various methods for EZ estimation, evaluating their efficacy remains challenging due to a lack of ground truth for empirical data. To address this, we generated and evaluated a cohort of 30 virtual epilepsy patients, using patient-specific anatomical and functional data from 30 real drug-resistant epilepsy patients. This personalized modeling approach, based on each patient’s brain data, is called a virtual brain twin. For each virtual patient, we provided data that included anatomically parcellated brain regions, structural connectivity, reconstructed intracranial electrodes, simulated brain activity at both the brain region and electrode levels, and key parameters of the virtual brain twin. These key parameters, which include the EZ hypothesis, serve as the ground truth for simulated brain activity. For each virtual brain twin, we generated synthetic spontaneous seizures, stimulation-induced seizures and interictal activity. We systematically evaluated these simulated brain signals by quantitatively comparing them against their corresponding empirical intracranial recordings. Simulated signals based on patient-specific EZ captured spatio-temporal seizure generation and propagation. Through in-silico exploration of stimulation parameters, we also demonstrated the role of patient-specific stimulation location and amplitude in reproducing empirically stimulated seizures. The virtual epileptic cohort is openly available, and can be used to systematically evaluate methods for the estimation of EZ or source localization using ground truth EZ parameters and source signals.

Focal cortical dysplasia type I (FCD I) is the most common cause of pharmaco-resistant epilepsy with the poorest prognosis. To understand the epileptogenic mechanisms of FCD I, we obtained tissue resected from patients with FCD I epilepsy, and from tumor patients as control. Using whole-cell patch clamp in acute human brain slices, we investigated the cellular properties of fast-spiking interneurons (FSINs) and pyramidal neurons (PNs) within the ictal onset zone. In FCD I epilepsy, FSINs exhibited lower firing rates from slower repolarization and action potential broadening, while PNs had increased firing. Importantly, excitatory synaptic drive of FSINs increased progressively with the scale of cortical activation as a general property across species, but this relationship was inverted towards net inhibition in FCD I epilepsy. Further comparison with intracranial electroencephalography (iEEG) from the same patients revealed that the spatial extent of pathological high-frequency oscillations (pHFO) was associated with synaptic events at FSINs. Changes in FSIN physiology and cortical E–I balance underlying pHFO generation are not fully understood. Here authors show net synaptic drive at FSINs from excitation to inhibition represents the major epileptogenic mechanism of FCD I epilepsy.

Acute seizures after a severe brain insult can often lead to epilepsy and cognitive impairment. Aberrant hippocampal neurogenesis follows the insult but the role of adult-generated neurons in the development of chronic seizures or associated cognitive deficits remains to be determined. Here we show that the ablation of adult neurogenesis before pilocarpine-induced acute seizures in mice leads to a reduction in chronic seizure frequency. We also show that ablation of neurogenesis normalizes epilepsy-associated cognitive deficits. Remarkably, the effect of ablating adult neurogenesis before acute seizures is long lasting as it suppresses chronic seizure frequency for nearly 1 year. These findings establish a key role of neurogenesis in chronic seizure development and associated memory impairment and suggest that targeting aberrant hippocampal neurogenesis may reduce recurrent seizures and restore cognitive function following a pro-epileptic brain insult. Aberrant hippocampal neurogenesis often occurs after acute seizures that produce epilepsy and cognitive impairment but the role of neurogenesis in the development of epilepsy is unclear. Here the authors suppress adult neurogenesis in mice preceding seizures and show that it reduces subsequent chronic seizure frequency and epilepsy-associated cognitive decline.

Objective Frequency properties of the EEG characteristics of different seizure types including absence seizures have been described for various rodent models of epilepsy. However, little attention has been paid to the frequency properties of individual spike–wave complexes (SWCs), the constituting elements characterizing the different generalized seizure types. Knowledge of their properties is not only important for understanding the mechanisms underlying seizure generation but also for the identification of epileptiform activity in various seizure types. Here, we compared the frequency properties of SWCs in different epilepsy models. Methods A software package was designed and used for the extraction and frequency analysis of SWCs from long‐term EEG of four spontaneously seizing, chronic epilepsy models: a post‐status epilepticus model of temporal lobe epilepsy, a lateral fluid percussion injury model of post‐traumatic epilepsy, and two genetic models of absence epilepsy—GAERS and rats of the WAG/Rij strain. The SWCs within the generalized seizures were separated into fast (three‐phasic spike) and slow (mostly containing the wave) components. Eight animals from each model were used (32 recordings, 104 510 SWCs in total). A limitation of our study is that the recordings were hardware‐filtered (high‐pass), which could affect the frequency composition of the EEG. Results We found that the three‐phasic spike component was similar in all animal models both in time and frequency domains, their amplitude spectra showed a single expressed peak at 18–20 Hz. The slow component showed a much larger variability across the rat models. Significance Despite differences in the morphology of the epileptiform activity in different models, the frequency composition of the spike component of single SWCs is identical and does not depend on the particular epilepsy model. This fact may be used for the development of universal algorithms for seizure detection applicable to different rat models of epilepsy. Plain Language Summary There is a large variety between people with epilepsy regarding the clinical manifestations and the electroencephalographic (EEG) phenomena accompanying the epileptic seizures. Here, we show that one of the EEG signs of epilepsy, an epileptic spike, is universal, since it has the same shape and frequency characteristics in different animal models of generalized epilepsies, despite differences in recording sites and location.