Theta-burst direct electrical stimulation remodels human brain networks.

Theta-burst stimulation (TBS), a patterned brain stimulation technique that mimics rhythmic bursts of 3-8 Hz endogenous brain rhythms, has emerged as a promising therapeutic approach for treating a wide range of brain disorders, though the neural mechanism of TBS action remains poorly understood. We investigated the neural effects of TBS using intracranial EEG (iEEG) in 10 pre-surgical epilepsy participants undergoing intracranial monitoring. Here we show that individual bursts of direct electrical TBS at 29 frontal and temporal sites evoked strong neural responses spanning broad cortical regions. These responses exhibited dynamic local field potential voltage changes over the course of stimulation presentations, including either increasing or decreasing responses, suggestive of short-term plasticity. Stronger stimulation augmented the mean TBS response amplitude and spread with more recording sites demonstrating short-term plasticity. TBS responses were stimulation site-specific with stronger TBS responses observed in regions with strong baseline stimulation effective (cortico-cortical evoked potentials) and functional (low frequency phase locking) connectivity. Further, we could use these measures to predict stable and varying (e.g. short-term plasticity) TBS response locations. Future work may integrate pre-treatment connectivity alongside other biophysical factors to personalize stimulation parameters, thereby optimizing induction of neuroplasticity within disease-relevant brain networks.

Impact of seizure onset zone and intracranial electroencephalography ictal characteristics on epilepsy surgery outcomes in tuberous sclerosis complex.

Ninety percent of tuberous sclerosis complex (TSC) patients have seizures, with ∼50 % developing drug refractory epilepsy. Surgical intervention aims to remove the seizure onset zone (SOZ). This retrospective study investigated the relationship of SOZ size, ictal pattern, and extent of resection with surgical outcomes. TSC patients undergoing resective/ablative surgery with >1-year follow-up and adequate imaging were included. Preoperative iEEG data were reviewed to determine ictal pattern and SOZ location. For outcomes, an ILAE score of 1-3 was defined as good and 4-6 as poor. Forty-four patients were included (age 117.4 ± 110.8 months). Of these, 59.1 % achieved a good outcome, while 40.9 % had a poor outcome. Size of SOZ was a significant factor (p = 0.009), with the poor outcome group having a larger SOZ (11.9 ± 6.7 electrode contacts) than the good outcome group (7.3 ± 7.2). SOZ number was significant (p = 0.020); >1 SOZ was associated with poor outcome. These results demonstrate extent of SOZ as a predictor of seizure freedom following epilepsy surgery in a mostly pediatric TSC cohort. We hypothesize that these features represent biomarkers of focality of the epileptogenic zone and can be used to sharpen prognosis for epilepsy surgery outcomes in this cohort.

Stage-dependent role of interhemispheric pathway for motor recovery in primates.

Whether and how the non-lesional sensorimotor cortex is activated and contributes to post-injury motor recovery is controversial. Here, we investigated the role of interhemispheric pathway from the contralesional to ipsilesional premotor cortex in activating the ipsilesional sensorimotor cortex and promoting recovery after lesioning the lateral corticospinal tract at the cervical cord, by unidirectional chemogenetic blockade in macaques. The blockade impaired dexterous hand movements during the early recovery stage. Electrocorticographical recording showed that the low frequency band activity of the ipsilesional premotor cortex around movement onset was decreased by the blockade during the early recovery stage, while it was increased by blockade during the intact state and late recovery stage. These results demonstrate that action of the interhemispheric pathway changed from inhibition to facilitation, to involve the ipsilesional sensorimotor cortex in hand movements during the early recovery stage. The present study offers insights into the stage-dependent role of the interhemispheric pathway and a therapeutic target in the early recovery stage after lesioning of the corticospinal tract.

Net synaptic drive of fast-spiking interneurons is inverted towards inhibition in human FCD I epilepsy.

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.

Primary somatosensory cortex CB1 and 5­HT1A receptors interaction in the penicillin model of epilepsy.

Cannabinoid and serotonin systems regulate many biological processes. The aim of the present study was to investigate the functional interaction between the cannabinoid and serotonergic systems of the primary somatosensory region (S1) of the brain in epileptiform activity caused by penicillin. The ACEA (an agonist of CB1 receptor), AM­251 (an antagonist of CB1 receptor), 8­OH­DPAT (an agonist of 5­HT1A receptor) and WAY­100635 (an antagonist of 5­HT1A receptor) were administered into the S1 after the same site administration of penicillin in urethane­anesthetized rats. Electrocorticographic recording was done for a 90­min period. The spike waves number and amplitude were recorded in 15­min intervals. Areas under the curve (AUC) of the above­mentioned spike alterations was calculated in 90 min. Spike waves with frequency of 30/min and amplitude of 1.3 mV were appeared after penicillin microinjection. The ACEA (50 ng), 8­OH­DPAT (500 ng) and ACEA (10 ng) plus 8­OH­DPAT (100 ng) reduced epileptiform activity. The AM­251 (50 ng) and WAY­100365 (500 ng) prevented the reducing effects of ACEA (50 ng) and 8­OH­DPAT (500 ng). The AM­251 alone increased spike waves frequency. The AUC results supported the effects of the above­mentioned treatments. The results showed that activating CB1 and 5­HT1A receptors in the S1 may reduce the epileptiform activity caused by penicillin. Therefore, alone and together activation of central CB1 and 5­HT1A receptors might be considered in the management of epilepsy treatment.

Imagined speech event detection from electrocorticography and its transfer between speech modes and subjects.

Speech brain-computer interfaces aim to support communication-impaired patients by translating neural signals into speech. While impressive progress was achieved in decoding performed, perceived and attempted speech, imagined speech remains elusive, mainly due to the absence of behavioral output. Nevertheless, imagined speech is advantageous since it does not depend on any articulator movements that might become impaired or even lost throughout the stages of a neurodegenerative disease. In this study, we analyzed electrocortigraphy data recorded from 16 participants in response to 3 speech modes: performed, perceived (listening), and imagined speech. We used a linear model to detect speech events and examined the contributions of each frequency band, from delta to high gamma, given the speech mode and electrode location. For imagined speech detection, we observed a strong contribution of gamma bands in the motor cortex, whereas lower frequencies were more prominent in the temporal lobe, in particular of the left hemisphere. Based on the similarities in frequency patterns, we were able to transfer models between speech modes and participants with similar electrode locations.

A Review of Motor Brain-Computer Interfaces Using Intracranial Electroencephalography Based on Surface Electrodes and Depth Electrodes.

Brain-computer interfaces (BCIs) provide a communication interface between the brain and external devices and have the potential to restore communication and control in patients with neurological injury or disease. For the invasive BCIs, most studies recruited participants from hospitals requiring invasive device implantation. Three widely used clinical invasive devices that have the potential for BCIs applications include surface electrodes used in electrocorticography (ECoG) and depth electrodes used in Stereo-electroencephalography (SEEG) and deep brain stimulation (DBS). This review focused on BCIs research using surface (ECoG) and depth electrodes (including SEEG, and DBS electrodes) for movement decoding on human subjects. Unlike previous reviews, the findings presented here are from the perspective of the decoding target or task. In detail, five tasks will be considered, consisting of the kinematic decoding, kinetic decoding,identification of body parts, dexterous hand decoding, and motion intention decoding. The typical studies are surveyed and analyzed. The reviewed literature demonstrated a distributed motor-related network that spanned multiple brain regions. Comparison between surface and depth studies demonstrated that richer information can be obtained using surface electrodes. With regard to the decoding algorithms, deep learning exhibited superior performance using raw signals than traditional machine learning algorithms. Despite the promising achievement made by the open-loop BCIs, closed-loop BCIs with sensory feedback are still in their early stage, and the chronic implantation of both ECoG surface and depth electrodes has not been thoroughly evaluated.

Origami-inspired soft fluidic actuation for minimally invasive large-area electrocorticography.

Electrocorticography is an established neural interfacing technique wherein an array of electrodes enables large-area recording from the cortical surface. Electrocorticography is commonly used for seizure mapping however the implantation of large-area electrocorticography arrays is a highly invasive procedure, requiring a craniotomy larger than the implant area to place the device. In this work, flexible thin-film electrode arrays are combined with concepts from soft robotics, to realize a large-area electrocorticography device that can change shape via integrated fluidic actuators. We show that the 32-electrode device can be packaged using origami-inspired folding into a compressed state and implanted through a small burr-hole craniotomy, then expanded on the surface of the brain for large-area cortical coverage. The implantation, expansion, and recording functionality of the device is confirmed in-vitro and in porcine in-vivo models. The integration of shape actuation into neural implants provides a clinically viable pathway to realize large-area neural interfaces via minimally invasive surgical techniques.

Gamma amplitude-envelope correlations are strongly elevated within hyperexcitable networks in focal epilepsy.

Methods to quantify cortical hyperexcitability are of enormous interest for mapping epileptic networks in patients with focal epilepsy. We hypothesize that, in the resting state, cortical hyperexcitability increases firing-rate correlations between neuronal populations within seizure onset zones (SOZs). This hypothesis predicts that in the gamma frequency band (40-200 Hz), amplitude envelope correlations (AECs), a relatively straightforward measure of functional connectivity, should be elevated within SOZs compared to other areas. To test this prediction, we analyzed archived samples of interictal electrocorticographic (ECoG) signals recorded from patients who became seizure-free after surgery targeting SOZs identified by multiday intracranial recordings. We show that in the gamma band, AECs between nodes within SOZs are markedly elevated relative to those elsewhere. AEC-based node strength, eigencentrality, and clustering coefficient are also robustly increased within the SOZ with maxima in the low-gamma band (permutation test Z-scores > 8) and yield moderate discriminability of the SOZ using ROC analysis (maximal mean AUC ~ 0.73). By contrast to AECs, phase locking values (PLVs), a measure of narrow-band phase coupling across sites, and PLV-based graph metrics discriminate the seizure onset nodes weakly. Our results suggest that gamma band AECs may provide a clinically useful marker of cortical hyperexcitability in focal epilepsy.

SEEG-RFTC in patients with refractory focal epilepsy: real-world outcomes from 121 cases.

OBJECTIVE: Radiofrequency thermocoagulation (RFTC) has emerged as an effective and safe treatment method for patients with refractory focal epilepsy, when stereo-electroencephalography (SEEG) is implanted. Although real-world research results are still limited, a considerable number of patients have shown favorable outcomes with this less invasive method. This study aims to describe the outcomes and predictive factors of SEEG-RFTC in real-world research. METHODS: A retrospective observational study was conducted on patients in the authors' epilepsy center. In total, 121 patients who underwent RFTC were included in the study. Post-RFTC outcomes were evaluated using the seizure-free rate and response rate (seizure frequency reduction more than 50%). Predictive factors influencing post-RFTC outcome were considered by comparing different variables. RESULTS: The mean follow-up period was 18.3 months. Eighty-two patients (67.8%) were responders and 54 (44.6%) were seizure free. In 36 patients with malformation of cortical development, the seizure-free rate and the response rate were 69.44% and 83.33%, respectively. In 20 patients with hippocampal sclerosis, 19 patients were responders and 14 (70%) patients were seizure free at the last follow-up. The MRI feature and etiology of epilepsy are correlated with the outcome. MR-positive is a predictive factor for seizure freedom (p < 0.01) and responders (p < 0.01). Other factors have no predictive value for post-RFTC outcome. INTERPRETATION: SEEG-RFTC is a safe procedure and yields favorable outcomes in numerous cases of focal DRE. The MRI feature and etiology of epilepsy are correlated with the seizure-free rate and response rate. And MRI positivity is the predictor for good RFTC outcome.

Frequency-specific directed connectivity between the hippocampus and parietal cortex during verbal and spatial episodic memory: an intracranial EEG replication.

Hippocampus-parietal cortex circuits are thought to play a crucial role in memory and attention, but their neural basis remains poorly understood. We employed intracranial intracranial electroencephalography (iEEG) to investigate the neurophysiological underpinning of these circuits across three memory tasks spanning verbal and spatial domains. We uncovered a consistent pattern of higher causal directed connectivity from the hippocampus to both lateral parietal cortex (supramarginal and angular gyrus) and medial parietal cortex (posterior cingulate cortex) in the delta-theta band during memory encoding and recall. This connectivity was independent of activation or suppression states in the hippocampus or parietal cortex. Crucially, directed connectivity from the supramarginal gyrus to the hippocampus was enhanced in participants with higher memory recall, highlighting its behavioral significance. Our findings align with the attention-to-memory model, which posits that attention directs cognitive resources toward pertinent information during memory formation. The robustness of these results was demonstrated through Bayesian replication analysis of the memory encoding and recall periods across the three tasks. Our study sheds light on the neural basis of casual signaling within hippocampus-parietal circuits, broadening our understanding of their critical roles in human cognition.

Speech and music recruit frequency-specific distributed and overlapping cortical networks.

To what extent does speech and music processing rely on domain-specific and domain-general neural networks? Using whole-brain intracranial EEG recordings in 18 epilepsy patients listening to natural, continuous speech or music, we investigated the presence of frequency-specific and network-level brain activity. We combined it with a statistical approach in which a clear operational distinction is made between shared, preferred, and domain-selective neural responses. We show that the majority of focal and network-level neural activity is shared between speech and music processing. Our data also reveal an absence of anatomical regional selectivity. Instead, domain-selective neural responses are restricted to distributed and frequency-specific coherent oscillations, typical of spectral fingerprints. Our work highlights the importance of considering natural stimuli and brain dynamics in their full complexity to map cognitive and brain functions.

Causal Brain Network Predicts Surgical Outcomes in Patients With Drug-Resistant Epilepsy: A Retrospective Comparative Study.

Network neuroscience, especially causal brain network, has facilitated drug-resistant epilepsy (DRE) studies, while surgical success rate in patients with DRE is still limited, varying from 30%  âˆ¼  70 %. Predicting surgical outcomes can provide additional guidance to adjust treatment plans in time for poorly predicted curative effects. In this retrospective study, we aim to systematically explore biomarkers for surgical outcomes by causal brain network methods and multicenter datasets. Electrocorticogram (ECoG) recordings from 17 DRE patients with 58 seizures were included. Ictal ECoG within clinically annotated epileptogenic zone (EZ) and non-epileptogenic zone (NEZ) were separately computed using six different algorithms to construct causal brain networks. All the brain network results were divided into two groups, successful and failed surgeries. Statistical results based on the Mann-Whitney-U-test show that: causal connectivity of α -frequency band ( 8  âˆ¼  13 Hz) in EZ calculated by convergent cross mapping (CCM) gains the most significant differences between the surgical success and failure groups, with a P value of 7.85e-08 and Cohen's d effect size of 0.77. CCM-defined EZ brain network can also distinguish the successful and failed surgeries considering clinical covariates (clinical centers, DRE types) with [Formula: see text]. Based on the brain network features, machine learning models were developed to predict the surgical outcomes. Among them, the SVM classifier with Gaussian kernel function and Bayesian optimization demonstrates the highest average accuracy of 84.48% by 5-fold cross-validation, further indicating that the CCM-defined EZ brain network is a reliable biomarker for predicting DRE surgical outcomes.

Erroneous predictive coding across brain hierarchies in a non-human primate model of autism spectrum disorder.

In autism spectrum disorder (ASD), atypical sensory experiences are often associated with irregularities in predictive coding, which proposes that the brain creates hierarchical sensory models via a bidirectional process of predictions and prediction errors. However, it remains unclear how these irregularities manifest across different functional hierarchies in the brain. To address this, we study a marmoset model of ASD induced by valproic acid (VPA) treatment. We record high-density electrocorticography (ECoG) during an auditory task with two layers of temporal control, and applied a quantitative model to quantify the integrity of predictive coding across two distinct hierarchies. Our results demonstrate a persistent pattern of sensory hypersensitivity and unstable predictions across two brain hierarchies in VPA-treated animals, and reveal the associated spatio-spectro-temporal neural signatures. Despite the regular occurrence of imprecise predictions in VPA-treated animals, we observe diverse configurations of underestimation or overestimation of sensory regularities within the hierarchies. Our results demonstrate the coexistence of the two primary Bayesian accounts of ASD: overly-precise sensory observations and weak prior beliefs, and offer a potential multi-layered biomarker for ASD, which could enhance our understanding of its diverse symptoms.

Recording of single-unit activities with flexible micro-electrocorticographic array in rats for decoding of whole-body navigation.

Objective.Micro-electrocorticographic (µECoG) arrays are able to record neural activities from the cortical surface, without the need to penetrate the brain parenchyma. Owing in part to small electrode sizes, previous studies have demonstrated that single-unit spikes could be detected from the cortical surface, and likely from Layer I neurons of the neocortex. Here we tested the ability to useµECoG arrays to decode, in rats, body position during open field navigation, through isolated single-unit activities.Approach. µECoG arrays were chronically implanted onto primary motor cortex (M1) of Wistar rats, and neural recording was performed in awake, behaving rats in an open-field enclosure. The signals were band-pass filtered between 300-3000 Hz. Threshold-crossing spikes were identified and sorted into distinct units based on defined criteria including waveform morphology and refractory period. Body positions were derived from video recordings. We used gradient-boosting machine to predict body position based on previous 100 ms of spike data, and correlation analyses to elucidate the relationship between position and spike patterns.Main results.Single-unit spikes could be extracted during chronic recording fromµECoG, and spatial position could be decoded from these spikes with a mean absolute error of prediction of 0.135 and 0.090 in the x- and y- dimensions (of a normalized range from 0 to 1), and Pearson's r of 0.607 and 0.571, respectively.Significance. µECoG can detect single-unit activities that likely arise from superficial neurons in the cortex and is a promising alternative to intracortical arrays, with the added benefit of scalability to cover large cortical surface with minimal incremental risks. More studies should be performed in human related to its use as brain-machine interface.

Gamma Responses to Colored Natural Stimuli Can Be Predicted from Local Low-Level Stimulus Features.

The role of gamma rhythm (30-80 Hz) in visual processing is debated; stimuli like gratings and hue patches generate strong gamma, but many natural images do not. Could image gamma responses be predicted by approximating images as gratings or hue patches? Surprisingly, this question remains unanswered, since the joint dependence of gamma on multiple features is poorly understood. We recorded local field potentials and electrocorticogram from two female monkeys while presenting natural images and parametric stimuli varying along several feature dimensions. Gamma responses to different grating/hue features were separable, allowing for a multiplicative model based on individual features. By fitting a hue patch to the image around the receptive field, this simple model could predict gamma responses to chromatic images across scales with reasonably high accuracy. Our results provide a simple "baseline" model to predict gamma from local image properties, against which more complex models of natural vision can be tested.

Assessing expert reliability in determining intracranial EEG channel quality and introducing the automated bad channel detection algorithm.

Objective.To evaluate the inter- and intra-rater reliability for the identification of bad channels among neurologists, EEG Technologists, and naïve research personnel, and to compare their performance with the automated bad channel detection (ABCD) algorithm for detecting bad channels.Approach.Six Neurologists, ten EEG Technologists, and six naïve research personnel (22 raters in total) were asked to rate 1440 real intracranial EEG channels as good or bad. Intra- and interrater kappa statistics were calculated for each group. We then compared each group to the ABCD algorithm which uses spectral and temporal domain features to classify channels as good or bad.Main results.Analysis of channel ratings from our participants revealed variable intra-rater reliability within each group, with no significant differences across groups. Inter-rater reliability was moderate among neurologists and EEG Technologists but minimal among naïve participants. Neurologists demonstrated a slightly higher consistency in ratings than EEG Technologists. Both groups occasionally misclassified flat channels as good, and participants generally focused on low-frequency content for their assessments. The ABCD algorithm, in contrast, relied more on high-frequency content. A logistic regression model showed a linear relationship between the algorithm's ratings and user responses for predominantly good channels, but less so for channels rated as bad. Sensitivity and specificity analyses further highlighted differences in rating patterns among the groups, with neurologists showing higher sensitivity and naïve personnel higher specificity.Significance.Our study reveals the bias in human assessments of intracranial electroencephalography (iEEG) data quality and the tendency of even experienced professionals to overlook certain bad channels, highlighting the need for standardized, unbiased methods. The ABCD algorithm, outperforming human raters, suggests the potential of automated solutions for more reliable iEEG interpretation and seizure characterization, offering a reliable approach free from human biases.

Stimulation of caudal inferior and middle frontal gyri disrupts planning during spoken interaction.

Turn-taking is a central feature of conversation across languages and cultures.1,2,3,4 This key social behavior requires numerous sensorimotor and cognitive operations1,5,6 that can be organized into three general phases: comprehension of a partner's turn, preparation of a speaker's own turn, and execution of that turn. Using intracranial electrocorticography, we recently demonstrated that neural activity related to these phases is functionally distinct during turn-taking.7 In particular, networks active during the perceptual and articulatory stages of turn-taking consisted of structures known to be important for speech-related sensory and motor processing,8,9,10,11,12,13,14,15,16,17 while putative planning dynamics were most regularly observed in the caudal inferior frontal gyrus (cIFG) and the middle frontal gyrus (cMFG). To test if these structures are necessary for planning during spoken interaction, we used direct electrical stimulation (DES) to transiently perturb cortical function in neurosurgical patient-volunteers performing a question-answer task.7,18,19 We found that stimulating the cIFG and cMFG led to various response errors9,13,20,21 but not gross articulatory deficits, which instead resulted from DES of structures involved in motor control8,13,20,22 (e.g., the precentral gyrus). Furthermore, perturbation of the cIFG and cMFG delayed inter-speaker timing-consistent with slowed planning-while faster responses could result from stimulation of sites located in other areas. Taken together, our findings suggest that the cIFG and cMFG contain critical preparatory circuits that are relevant for interactive language use.

Intracranial EEG signals disentangle multi-areal neural dynamics of vicarious pain perception.

Empathy enables understanding and sharing of others' feelings. Human neuroimaging studies have identified critical brain regions supporting empathy for pain, including the anterior insula (AI), anterior cingulate (ACC), amygdala, and inferior frontal gyrus (IFG). However, to date, the precise spatio-temporal profiles of empathic neural responses and inter-regional communications remain elusive. Here, using intracranial electroencephalography, we investigated electrophysiological signatures of vicarious pain perception. Others' pain perception induced early increases in high-gamma activity in IFG, beta power increases in ACC, but decreased beta power in AI and amygdala. Vicarious pain perception also altered the beta-band-coordinated coupling between ACC, AI, and amygdala, as well as increased modulation of IFG high-gamma amplitudes by beta phases of amygdala/AI/ACC. We identified a necessary combination of neural features for decoding vicarious pain perception. These spatio-temporally specific regional activities and inter-regional interactions within the empathy network suggest a neurodynamic model of human pain empathy.

Predictors of SOZ localization, subsequent surgical intervention, and seizure outcomes in iEEG.

OBJECTIVE: A third of the patients who undergo intracranial EEG (iEEG) for seizure-onset zone (SOZ) localization do not proceed to resective surgery for epilepsy, and over half of those who do continue to have seizures following treatment. To better identify candidates who are more likely to see benefits from undergoing iEEG, we investigated preoperative and iEEG peri-operative features associated with the localization of a putative SOZ, undergoing subsequent surgical treatment, and seizure outcomes. METHODS: We conducted a retrospective cohort study of consecutive patients who underwent iEEG from 2001 to 2022 at two institutions. Outcomes included SOZ identification, proceeding to surgical treatment (resection vs. neuromodulation), and subsequent seizure freedom. RESULTS: We identified 329 unique patients who were followed for a median of 3.9 (IQR:7) years, with a minimum of 2-year follow-up for seizure outcomes analyses. Multivariate analysis identified lateralized and lobar localization on scalp EEG (OR 3.8, p = 0.001) to be associated with SOZ localization. Patients with unilateral localization on scalp EEG (OR 3.0, p = 0.003), unilateral preimplantation hypothesis (OR 3.1, p = 0.001), and lesional preoperative MRI (OR 2.1, p = 0.033) were more likely to undergo resection than neuromodulation. Similarly, a unilateral pre-implantation hypothesis (OR 2.6, p < 0.001) favored seizure freedom, whereas prior neuromodulation (OR 0.3, p = 0.013) decreased the odds. Larger number of preoperative anti-seizure medications (ASMs) did not influence seizure freedom rates but did decrease favorable (Engel I, II) seizure outcomes (OR 0.7, p = 0.026). INTERPRETATION: Non-invasive localization data prior to iEEG are associated with subsequent resection and seizure freedom, independent of iEEG localization. Factors predictive of SOZ localization are not necessarily predictive of post-operative seizure freedom.