Faculty Bibliography

PURPOSE/OBJECTIVE:Surgical planning for people with drug resistant non-lesional focal epilepsy can be challenging. Prior studies focus on cases that are only MRI-negative or MRI-negative with PET-positive imaging, but little is known about outcomes in patients with non-lesional findings on both MRI and PET imaging. In this study, we investigate 5-year surgical outcomes in patients who underwent epilepsy surgery for drug resistant MRI/PET-negative focal epilepsy. METHODS:We collected clinical and testing data on 131 consecutive patients with drug resistant non-lesional epilepsy who were presented at a multidisciplinary epilepsy surgery conference at the New York University Comprehensive Epilepsy Center between 2010 and 2014, and identified those who underwent epilepsy surgery in order to review 5-year surgical outcomes. RESULTS:There were 103 with non-lesional MRI studies, and of these, 22 had corresponding non-lesional PET imaging. 14 MRI/PET-negative patients pursued a surgical treatment option and 9 underwent resections after intracranial EEG. At 5 years, 77.8 % of patients had favorable (ILAE class 1 and 2) outcomes. Most (77.8 %) had focal cortical dysplasia type Ia (FCDIa) on pathology. CONCLUSION/CONCLUSIONS:These findings suggest that with careful planning and patient selection, surgery for patients with drug resistant MRI/PET-negative focal epilepsy can be successful.

Drug-resistant focal epilepsy (DRFE) in children can impair cognition and behavior, and lead to premature death. Increased pediatric epilepsy surgery numbers reflect the improvements in seizure control and long-term developmental outcomes. Yet, many children with DRFE are not candidates for surgical resection due to overlap of the seizure network with eloquent cortex or multiple seizure-onset zones, making surgery dangerous or ineffective. In adults, responsive neurostimulation (RNS System) therapy is safe and effective treatment for DRFE with one or two seizure foci, especially when the seizure focus is in eloquent cortex. We present six pediatric patients with DRFE who underwent RNS implantation. Our outcomes demonstrate safety, decreased clinical seizure frequency, as well as improved functional status and quality of life. Changes in the clinical seizure semiology and frequency occurred in conjunction with adjustments to the stimulation parameters, supporting the efficacy of responsive neuromodulation in children.

PURPOSE/OBJECTIVE:A phase I feasibility study to determine the accuracy of identifying seizures based on audio recordings. METHODS:We systematically generated 166 audio clips of 30 s duration from 83 patients admitted to an epilepsy monitoring unit between 1/2015 and 12/2016, with one clip during a seizure period and one clip during a non-seizure control period for each patient. Five epileptologists performed a blinded review of the audio clips and rated whether a seizure occurred or not, and indicated the confidence level (low or high) of their rating. The accuracy of individual and consensus ratings were calculated. RESULTS:The overall performance of the consensus rating between the five epileptologists showed a positive predictive value (PPV) of 0.91 and a negative predictive value (NPV) of 0.66. The performance improved when confidence was high (PPV of 0.96, NPV of 0.70). The agreement between the epileptologists was moderate with a kappa of 0.584. Hyperkinetic (PPV 0.92, NPV 0.86) and tonic-clonic (PPV and NPV 1.00) seizures were most accurately identified. Seizures with automatisms only and non-motor seizures could not be accurately identified. Specific seizure-related sounds associated with accurate identification included disordered breathing (PPV and NPV 1.00), rhythmic sounds (PPV 0.93, NPV 0.80), and ictal vocalizations (PPV 1.00, NPV 0.97). CONCLUSION/CONCLUSIONS:This phase I feasibility study shows that epileptologists are able to accurately identify certain seizure types from audio recordings when the seizures produce sounds. This provides guidance for the development of audio-based seizure detection devices and demonstrate which seizure types could potentially be detected.

BACKGROUND:Early accounts of forced thought were reported at the onset of a focal seizure, and characterized as vague, repetitive, and involuntary intellectual auras distinct from perceptual or psychic hallucinations or illusions. Here, we examine the neural underpinnings involved in conceptual thought by presenting a series of 3 patients with epilepsy reporting intrusive thoughts during electrical stimulation of the left lateral prefrontal cortex (PFC) during invasive surgical evaluation. We illustrate the widespread networks involved through two independent brain imaging modalities: resting state functional magnetic resonance imaging (fMRI) (rs-fMRI) and task-based meta-analytic connectivity modeling (MACM). METHODS:We report the clinical and stimulation characteristics of three patients with left hemispheric language dominance who demonstrate forced thought with functional mapping. To examine the brain networks underlying this phenomenon, we used the regions of interest (ROI) centered at the active electrode pairs. We modeled functional networks using two approaches: (1) rs-fMRI functional connectivity analysis, representing 81 healthy controls and (2) meta-analytic connectivity modeling (MACM), representing 8260 healthy subjects. We also determined the overlapping regions between these three subjects' rs-fMRI and MACM networks through a conjunction analysis. RESULTS:We identified that left PFC was associated with a large-scale functional network including frontal, temporal, and parietal regions, a network that has been associated with multiple cognitive functions including semantics, speech, attention, working memory, and explicit memory. CONCLUSIONS:We illustrate the neural networks involved in conceptual thought through a unique patient population and argue that PFC supports this function through activation of a widespread network.

Dynamic interactions between remote but functionally specialized brain regions enable complex information processing. This intercortical communication is disrupted in the neural networks of patients with focal epilepsy, and epileptic activity can exert widespread effects within the brain. Using large-scale human intracranial electroencephalography recordings, we show that interictal epileptiform discharges (IEDs) are significantly coupled with spindles in discrete, individualized brain regions outside of the epileptic network. We found that a substantial proportion of these localized spindles travel across the cortical surface. Brain regions that participate in this IED-driven oscillatory coupling express spindles that have a broader spatial extent and higher tendency to propagate than spindles occurring in uncoupled regions. These altered spatiotemporal oscillatory properties identify areas that are shaped by epileptic activity independent of IED or seizure detection. Our findings suggest that IED-spindle coupling may be an important mechanism of interictal global network dysfunction that could be targeted to prevent disruption of normal neural activity.

We studied the relationship between uninstructed, unstructured movements and neural activity in three epilepsy patients with intracranial electroencephalographic (iEEG) recordings. We used a custom system to continuously record high definition video precisely time-aligned to clinical iEEG data. From these video recordings, movement periods were annotated via semi-automatic tracking based on dense optical flow. We found that neural signal features (8--32 Hz and 76--100 Hz power) previously identified from task-based experiments are also modulated before and during a variety of movement behaviors. These movement behaviors are coarsely labeled by time period and movement side (e.g. `Idle' and `Move', `Right' and `Left'); movements within a label can include a wide variety of uninstructed behaviors. A rigorous nested cross-validation framework was used to classify both movement onset and lateralization with statistical significance for all subjects. We demonstrate an evaluation framework to study neural activity related to natural movements not evoked by a task, annotated over hours of video. This work further establishes the feasibility to study neural correlates of unstructured behavior through continuous recording in the epilepsy monitoring unit. The insights gained from such studies may advance our understanding of how the brain naturally controls movement, which may inform the development of more robust and generalizable brain-computer interfaces.

Magnetic resonance imaging (MRI)-negative temporal lobe epilepsy (TLE) may be a distinct syndrome from TLE with mesial temporal sclerosis (TLE-MTS). Imaging and neuropsychological features of TLE-MTS are well-known; yet, these features are only beginning to be described in MRI-negative TLE. This study examined whether a quantitative measure of cortical gray and white matter blurring (GWB) was elevated in the temporal lobes ipsilateral to the seizure onset zone of individuals with MRI-negative TLE relative to TLE-MTS and healthy controls (HCs) and whether GWB elevations were associated with neuropsychological comorbidity. Gray-white matter blurring from 34 cortical regions and hippocampal volumes were quantified and compared across 28 people with MRI-negative TLE, 15 people with TLE-MTS, and 51 HCs. Declarative memory was assessed with standard neuropsychological tests and the intracarotid amobarbital procedure (IAP). In the group with MRI-negative TLE (left and right onsets combined), hippocampal volumes were within normal range but GWB was elevated, relative to HCs, across several mesial and lateral temporal lobe regions ipsilateral to the seizure onset zone. Gray-white matter blurring did not differ between the groups with TLE-MTS and HC or between the groups with TLE-MTS and MRI-negative TLE. The group with MRI-negative TLE could not be distinguished from the group with TLE-MTS on any of the standard neuropsychological tests; however, ipsilateral hippocampal volumes and IAP memory scores were lower in the group with TLE-MTS than in the group with MRI-negative TLE. The group with left MRI-negative TLE had lower general cognitive abilities and verbal fluency relative to the HC group, which adds to the characterization of neuropsychological comorbidities in left MRI-negative TLE. In addition, ipsilateral IAP memory performance was reduced relative to contralateral memory performance in MRI-negative TLE, indicating some degree of ipsilateral memory dysfunction. There was no relationship between hippocampal volume and IAP memory scores in MRI-negative TLE; however, decreased ipsilateral IAP memory scores were correlated with elevated GWB in the ipsilateral superior temporal sulcus of people with left MRI-negative TLE. In sum, GWB elevations in the ipsilateral temporal lobe of people with MRI-negative TLE suggest that GWB may serve as a marker for reduced structural integrity in regions in or near the seizure onset zone. Although mesial temporal abnormalities might be the major driver of memory dysfunction in TLE-MTS, a loss of structural integrity in lateral temporal lobe regions may contribute to IAP memory dysfunction in MRI-negative TLE.

Electrical stimulation in the anterior nucleus of the thalamus (ANT) has previously been found to be efficacious for reducing seizure frequency in patients with epilepsy. Bilateral deep brain stimulation (DBS) of the ANT is an open-loop system that can be used in the management of treatment-resistant epilepsy. In contrast, the responsive neurostimulation (RNS) system is a closed-loop device that delivers treatment in response to prespecified electrocorticographic triggers. The efficacy and safety of RNS targeting the ANT is unknown. We describe 3 patients with treatment-resistant multifocal epilepsy who were implanted with an RNS system, which included unilateral stimulation of the ANT. After >33 months of follow-up, there were no adverse effects on mood, memory or behavior. Two patients had ≥50% reduction in disabling seizures and one patient had a 50% reduction compared to pretreatment baseline. Although reduction in seizure frequency has been modest to date, these findings support responsive neurostimulation of the ANT as feasible, safe, and well-tolerated. Further studies are needed to determine optimal stimulation parameters.

OBJECTIVE:Current brain-computer interface (BCI) studies demonstrate the potential to decode neural signals obtained from structured and trial-based tasks to drive actuators with high performance within the context of these tasks. Ideally, to maximize utility, such systems will be applied to a wide range of behavioral settings or contexts. Thus, we explore the potential to augment such systems with the ability to decode abstract behavioral contextual states from neural activity. APPROACH/METHODS:To demonstrate the feasibility of such context decoding, we used electrocorticography (ECoG) and stereo-electroencephalography (sEEG) data recorded from the cortical surface and deeper brain structures, respectively, continuously across multiple days from three subjects. During this time, the subjects were engaged in a range of naturalistic behaviors in a hospital environment. Behavioral contexts were labeled manually from video and audio recordings; four states were considered: engaging in dialogue, rest, using electronics, and watching television. We decode these behaviors using a factor analysis and support vector machine (SVM) approach. MAIN RESULTS/RESULTS:We demonstrate that these general behaviors can be decoded with high accuracies of 73% for a four-class classifier for one subject and 71% and 62% for a three-class classifier for two subjects. SIGNIFICANCE/CONCLUSIONS:To our knowledge, this is the first demonstration of the potential to disambiguate abstract naturalistic behavioral contexts from neural activity recorded throughout the day from implanted electrodes. This work motivates further study of context decoding for BCI applications using continuously recorded naturalistic activity in the clinical setting.