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Studies to improve the efficacy of epilepsy surgery have focused on better refining the localization of the epileptogenic zone (EZ) with the aim of effectively resecting it. However, in a considerable number of patients, EZs are distributed across multiple brain regions and may involve eloquent areas that cannot be removed due to the risk of neurological complications. There is a clear need for developing alternative approaches to induce seizure relief, but minimal impact on normal brain functions. Here, we develop a personalized in-silico network approach, that suggests effective and safe surgical interventions for each patient. Based on the clinically identified EZ, we employ modularity analysis to identify target brain regions and fiber tracts involved in seizure propagation. We then construct and simulate a patient-specific brain network model comprising phenomenological neural mass models at the nodes, and patient-specific structural brain connectivity using the neuroinformatics platform The Virtual Brain (TVB), in order to evaluate effectiveness and safety of the target zones (TZs). In particular, we assess safety via electrical stimulation for pre- and post-surgical condition to quantify the impact on the signal transmission properties of the network. We demonstrate the existence of a large repertoire of efficient surgical interventions resulting in reduction of degree of seizure spread, but only a small subset of them proves safe. The identification of novel surgical interventions through modularity analysis and brain network simulations may provide exciting solutions to the treatment of inoperable epilepsies.

Verbal memory decline is a significant concern following temporal lobe surgeries in patients with epilepsy, emphasizing the need for precision presurgical verbal memory mapping to optimize functional outcomes. However, the inter‐individual variability in functional networks and brain function‐structural dissociations pose challenges when relying solely on group‐level atlases or anatomical landmarks for surgical guidance. Here, we aimed to develop and validate a personalized functional mapping technique for verbal memory using precision resting‐state functional MRI (rs‐fMRI) and neurosurgery. A total of 38 patients with refractory epilepsy scheduled for surgical interventions were enrolled and 28 patients were analyzed in the study. Baseline 30‐min rs‐fMRI scanning, verbal memory and language assessments were collected for each patient before surgery. Personalized verbal memory networks (PVMN) were delineated based on preoperative rs‐fMRI data for each patient. The accuracy of PVMN was assessed by comparing post‐operative functional impairments and the overlapping extent between PVMN and surgical lesions. A total of 14 out of 28 patients experienced clinically meaningful declines in verbal memory after surgery. The personalized network and the group‐level atlas exhibited 100% and 75.0% accuracy in predicting postoperative verbal memory declines, respectively. Moreover, six patients with extra‐temporal lesions that overlapped with PVMN showed selective impairments in verbal memory. Furthermore, the lesioned ratio of the personalized network rather than the group‐level atlas was significantly correlated with postoperative declines in verbal memory (personalized networks: r = −0.39, p = .038; group‐level atlas: r = −0.19, p = .332). In conclusion, our personalized functional mapping technique, using precision rs‐fMRI, offers valuable insights into individual variability in the verbal memory network and holds promise in precision verbal memory network mapping in individuals. We used precision resting‐state functional MRI to map personalized verbal memory network (PVMN) for each treatment‐resistant epilepsy patient. PVMN, instead of group‐level functional atlases, effectively predicted post‐operative verbal memory impairments according to its spatial overlap with surgical lesions, indicating the precision PVMN mapping in individuals.

Seizure freedom after resective epilepsy surgery is not obtained in a substantial number of patients with medically intractable epilepsy. Functional neural network analysis is a promising technique for more accurate identification of the target areas for epilepsy surgery, but a better understanding of the correlations between changes in functional network organization due to surgery and postoperative seizure status is required. We explored these correlations in longitudinal magnetoencephalography (MEG) recordings of 20 lesional epilepsy patients. Resting-state MEG recordings were obtained at baseline (preoperatively; T0) and at 3–7 (T1) and 9–15months after resection (T2). We assessed frequency-specific functional connectivity and performed a minimum spanning tree (MST) network analysis. The MST captures the most important connections in the network. We found a significant positive correlation between functional connectivity in the lower alpha band and seizure frequency at T0, especially in regions where lesions were located. MST leaf fraction, a measure of integration of information in the network, was significantly increased between T0 and T2, only for the seizure-free patients. This is in line with previous work, which showed that lower functional network integration in lesional epilepsy patients is related to higher epilepsy burden. Finally, eccentricity and betweenness centrality, which are measures of hub-status, decreased between T0 and T2 in seizure free patients, also in regions that were anatomically close to resection cavities. Our results increase insight into functional network changes in successful epilepsy surgery and might eventually be utilized for optimization of neurosurgical approaches. •We studied connectivity and networks in lesional epilepsy patients using MEG.•Lower alpha band connectivity was positively correlated with seizure frequency.•Minimum spanning tree topology changed after surgery only for seizure free patients.•Betweenness centrality decreased in regions close to resection cavities.•Network alterations may reflect a neurophysiological correlate of surgical outcome.

Epileptic seizures are known to follow specific changes in brain dynamics. While some algorithms can nowadays robustly detect these changes, a clear understanding of the mechanism by which these alterations occur and generate seizures is still lacking. Here, we provide crossvalidated evidence that such changes are initiated by an alteration of physiological network state dynamics. Specifically, our analysis of long intracranial electroencephalography (iEEG) recordings from a group of 10 patients identifies a critical phase of a few hours in which time-dependent network states become less variable (\"degenerate\"), and this phase is followed by a global functional connectivity reduction before seizure onset. This critical phase is characterized by an abnormal occurrence of highly correlated network instances and is shown to be particularly associated with the activity of the resected regions in patients with validated postsurgical outcome. Our approach characterizes preseizure network dynamics as a cascade of 2 sequential events providing new insights into seizure prediction and control.

Objective To determine if properties of epileptic networks could be delineated using interictal spike propagation seen on stereo‐electroencephalography (SEEG) and if these properties could predict surgical outcome in patients with drug‐resistant epilepsy. Methods We studied the SEEG of 45 consecutive drug‐resistant epilepsy patients who underwent subsequent epilepsy surgery: 18 patients with good post‐surgical outcome (Engel I) and 27 with poor outcome (Engel II–IV). Epileptic networks were derived from interictal spike propagation; these networks described the generation and propagation of interictal epileptic activity. We compared the regions in which spikes were frequent and the regions responsible for generating spikes to the area of resection and post‐surgical outcome. We developed a measure termed source spike concordance, which integrates information about both spike rate and region of spike generation. Results Inclusion in the resection of regions with high spike rate is associated with good post‐surgical outcome (sensitivity = 0.82, specificity = 0.73). Inclusion in the resection of the regions responsible for generating interictal epileptic activity independently of rate is also associated with good post‐surgical outcome (sensitivity = 0.88, specificity = 0.82). Finally, when integrating the spike rate and the generators, we find that the source spike concordance measure has strong predictability (sensitivity = 0.91, specificity = 0.94). Interpretations Epileptic networks derived from interictal spikes can determine the generators of epileptic activity. Inclusion of the most active generators in the resection is strongly associated with good post‐surgical outcome. These epileptic networks may aid clinicians in determining the area of resection during pre‐surgical evaluation.

Abstract BACKGROUND Focal seizures in temporal lobe epilepsy (TLE) are associated with widespread brain network perturbations and neurocognitive problems. OBJECTIVE To determine whether brainstem connectivity disturbances improve with successful epilepsy surgery, as recent work has demonstrated decreased brainstem connectivity in TLE that is related to disease severity and neurocognitive profile. METHODS We evaluated 15 adult TLE patients before and after (>1 yr; mean, 3.4 yr) surgery, and 15 matched control subjects using magnetic resonance imaging to measure functional and structural connectivity of ascending reticular activating system (ARAS) structures, including cuneiform/subcuneiform nuclei (CSC), pedunculopontine nucleus (PPN), and ventral tegmental area (VTA). RESULTS TLE patients who achieved long-term postoperative seizure freedom (10 of 15) demonstrated increases in functional connectivity between ARAS structures and fronto-parietal-insular neocortex compared to preoperative baseline (P = .01, Kruskal–Wallis), with postoperative connectivity patterns resembling controls’ connectivity. No functional connectivity changes were detected in 5 patients with persistent seizures after surgery (P = .9, Kruskal–Wallis). Among seizure-free postoperative patients, larger increases in CSC, PPN, and VTA functional connectivity were observed in individuals with more frequent seizures before surgery (P < .05 for each, Spearman's rho). Larger postoperative increases in PPN functional connectivity were seen in patients with lower baseline verbal IQ (P = .03, Spearman's rho) or verbal memory (P = .04, Mann–Whitney U). No changes in ARAS structural connectivity were detected after successful surgery. CONCLUSION ARAS functional connectivity disturbances are present in TLE but may recover after successful epilepsy surgery. Larger increases in postoperative connectivity may be seen in individuals with more severe disease at baseline.

Prominent neuropathology following trauma, stroke, and various neurodegenerative diseases includes neuronal degeneration as well as loss of long-distance axonal connections. While cell replacement and axonal pathfinding strategies are often explored independently, there is no strategy capable of simultaneously replacing lost neurons and re-establishing long-distance axonal connections in the central nervous system. Accordingly, we have created micro-tissue engineered neural networks (micro-TENNs), which are preformed constructs consisting of long integrated axonal tracts spanning discrete neuronal populations. These living micro-TENNs reconstitute the architecture of long-distance axonal tracts, and thus may serve as an effective substrate for targeted neurosurgical reconstruction of damaged pathways in the brain. Cerebral cortical neurons or dorsal root ganglia neurons were precisely delivered into the tubular constructs, and properties of the hydrogel exterior and extracellular matrix internal column (180–500 μm diameter) were optimized for robust neuronal survival and to promote axonal extensions across the 2.0 cm tube length. The very small diameter permits minimally invasive delivery into the brain. In this study, preformed micro-TENNs were stereotaxically injected into naive rats to bridge deep thalamic structures with the cerebral cortex to assess construct survival and integration. We found that micro-TENN neurons survived at least 1 month and maintained their long axonal architecture along the cortical–thalamic axis. Notably, we also found neurite penetration from micro-TENN neurons into the host cortex, with evidence of synapse formation. These micro-TENNs represent a new strategy to facilitate nervous system repair by recapitulating features of neural pathways to restore or modulate damaged brain circuitry.

To investigate the altered intrinsic functional connectivity (iFC) of the primary visual cortex (V1) in primary angle-closure glaucoma (PACG) patients before and after surgery using resting-state functional MRI. Twenty-five preoperative PACG (pre-PACG) patients and 25 well-matched healthy controls (HCs) were included in this study, and 9 PACG patients were assessed again at least 3 months after treatment (post-PACG). We generated the iFC maps of the seed regions in the centers of the left and right V1 and conducted group comparisons. Then, the relationships between the altered iFC coefficients and clinical variables were investigated in the pre-PACG patients. Compared with the HCs, the pre-PACG patients showed decreased iFC between the left V1 and right V2 (covering the cuneus, calcarine and lingual gyrus) and increased iFC between the left V1 and left temporal-parietal region, left frontal opercula-insula-basal ganglia region, right insula-basal ganglia region, and right inferior parietal lobule (P < 0.01, corrected). Compared with the pre-PACG patients, the post-PACG patients showed increased iFC between the left V1 and bilateral V2, and between the left V1 and left or right postcentral gyrus; in addition, they showed decreased iFC between the left V1 and the dorsal-attention and frontoparietal-control networks. In the pre-PACG patients, visual activity (VA) was positively correlated with increased iFC between the left V1 and the left temporal-parietal region or the right inferior parietal lobule. Similar patterns of alterations were observed in the right V1-iFC in both the pre- and post-PACG patients. The primary findings have demonstrated a gradual decrease in visual information integration in the left V1-V2 pathway and VA-related functional compensation in the pre-PACG patients, generating further evidence of functional restoration in post-PACG patients.

Mathematical modelling has been widely used to predict the effects of perturbations to brain networks. An important example is epilepsy surgery, where the perturbation in question is the removal of brain tissue in order to render the patient free of seizures. Different dynamical models have been proposed to represent transitions to ictal states in this context. However, our choice of which mathematical model to use to address this question relies on making assumptions regarding the mechanism that defines the transition from background to the seizure state. Since these mechanisms are unknown, it is important to understand how predictions from alternative dynamical descriptions compare. Herein we evaluate to what extent three different dynamical models provide consistent predictions for the effect of removing nodes from networks. We show that for small, directed, connected networks the three considered models provide consistent predictions. For larger networks, predictions are shown to be less consistent. However consistency is higher in networks that have sufficiently large differences in ictogenicity between nodes. We further demonstrate that heterogeneity in ictogenicity across nodes correlates with variability in the number of connections for each node.

Background Repetitive navigated transcranial magnetic stimulation (rTMS) was recently described for mapping of human language areas. However, its capability of detecting language plasticity in brain tumor patients was not proven up to now. Thus, this study was designed to evaluate such data in order to compare rTMS language mapping to language mapping during repeated awake surgery during follow-up in patients suffering from language-eloquent gliomas. Methods Three right-handed patients with left-sided gliomas (2 opercular glioblastomas, 1 astrocytoma WHO grade III of the angular gyrus) underwent preoperative language mapping by rTMS as well as intraoperative language mapping provided via direct cortical stimulation (DCS) for initial as well as for repeated Resection 7, 10, and 15 months later. Results Overall, preoperative rTMS was able to elicit clear language errors in all mappings. A good correlation between initial rTMS and DCS results was observed. As a consequence of brain plasticity, initial DCS and rTMS findings only corresponded with the results obtained during the second examination in one out of three patients thus suggesting changes of language organization in two of our three patients. Conclusions This report points out the usefulness but also the limitations of preoperative rTMS language mapping to detect plastic changes in language function or for long-term follow-up prior to DCS even in recurrent gliomas. However, DCS still has to be regarded as gold standard.