Faculty Bibliography

It has come to our attention that we did not specify whether the stimulation magnitudes we report in this Article are peak amplitudes or peak-to-peak. All references to intensity given in mA in the manuscript refer to peak-to-peak amplitudes, except in Fig. 2, where the model is calibrated to 1 mA peak amplitude, as stated. In the original version of the paper we incorrectly calibrated the computational models to 1 mA peak-to-peak, rather than 1 mA peak amplitude. This means that we divided by a value twice as large as we should have. The correct estimated fields are therefore twice as large as shown in the original Fig. 2 and Supplementary Figure 11. The corrected figures are now properly calibrated to 1 mA peak amplitude. Furthermore, the sentence in the first paragraph of the Results section 'Intensity ranged from 0.5 to 2.5 mA (current density 0.125-0.625 mA mA/cm²), which is stronger than in previous reports', should have read 'Intensity ranged from 0.5 to 2.5 mA peak to peak (peak current density 0.0625-0.3125 mA/cm²), which is stronger than in previous reports.' These errors do not affect any of the Article's conclusions.

The neocortex is composed of six anatomically and physiologically specialized layers. It has been proposed that integration of activity across cortical areas is mediated anatomically by associative connections terminating in superficial layers, and physiologically by slow cortical rhythms. However, the means through which neocortical anatomy and physiology interact to coordinate neural activity remains obscure. Using laminar microelectrode arrays in 19 human participants, we found that most EEG activity is below 10-Hz (delta/theta) and generated by superficial cortical layers during both wakefulness and sleep. Cortical surface grid, grid-laminar, and dual-laminar recordings demonstrate that these slow rhythms are synchronous within upper layers across broad cortical areas. The phase of this superficial slow activity is reset by infrequent stimuli and coupled to the amplitude of faster oscillations and neuronal firing across all layers. These findings support a primary role of superficial slow rhythms in generating the EEG and integrating cortical activity.

Reliable posture labels in hospital environments can augment research studies on neural correlates to natural behaviors and clinical applications that monitor patient activity. However, many existing pose estimation frameworks are not calibrated for these unpredictable settings. In this paper, we propose a semi-automated approach for improving upper-body pose estimation in noisy clinical environments, whereby we adapt and build around an existing joint tracking framework to improve its robustness to environmental uncertainties. The proposed framework uses subject-specific convolutional neural network models trained on a subset of a patient's RGB video recording chosen to maximize the feature variance of each joint. Furthermore, by compensating for scene lighting changes and by refining the predicted joint trajectories through a Kalman filter with fitted noise parameters, the extended system yields more consistent and accurate posture annotations when compared with the two state-of-the-art generalized pose tracking algorithms for three hospital patients recorded in two research clinics.

Transcranial electrical stimulation has widespread clinical and research applications, yet its effect on ongoing neural activity in humans is not well established. Previous reports argue that transcranial alternating current stimulation (tACS) can entrain and enhance neural rhythms related to memory, but the evidence from non-invasive recordings has remained inconclusive. Here, we measure endogenous spindle and theta activity intracranially in humans during low-frequency tACS and find no stable entrainment of spindle power during non-REM sleep, nor of theta power during resting wakefulness. As positive controls, we find robust entrainment of spindle activity to endogenous slow-wave activity in 66% of electrodes as well as entrainment to rhythmic noise-burst acoustic stimulation in 14% of electrodes. We conclude that low-frequency tACS at common stimulation intensities neither acutely modulates spindle activity during sleep nor theta activity during waking rest, likely because of the attenuated electrical fields reaching the cortical surface.

Although responsive neurostimulation (RNS) is approved for treatment of resistant focal epilepsy in adults, little is known about response to treatment of specific cortical targets. We describe the experience of RNS targeting the insular lobe. We identified patients who had RNS implantation with at least one electrode within the insula between April 2014 and October 2015. We performed a retrospective review of preoperative clinical features, imaging, electrocardiogram (EEG), intraoperative electrocorticography (ECoG), and postoperative seizure outcome. Eight patients with at least 6 months of postimplant follow-up were identified. Ictal localization was inconclusive with MRI or scalp EEG findings. Intracranial EEG monitoring or intraoperative ECoG demonstrated clear ictal onsets and/or frequent interictal discharges in the insula. Four patients demonstrated overall 50-75% reduction in seizure frequency. Two patients did not show appreciable seizure improvement. One patient has experienced a 75% reduction of seizure frequency, and another is nearly seizure free postoperatively. There were no reported direct complications of insular RNS electrode placement or stimulation, though two patients had postoperative complications thought to be related to craniotomy (hydrocephalus and late infection). Our study suggests that insular RNS electrode placement in selected patients is relatively safe and that RNS treatment may benefit selected patients with insular epilepsy.

OBJECTIVES: We assessed the efficacy and risks of diagnostic bilateral intracranial EEG (bICEEG) in treatment-resistant epilepsy (TRE) patients with poorly lateralized epileptogenic zone (EZ) on non-invasive studies as reflected by progress to resection, Engel outcome and complication rate. METHODS: This is a retrospective chart review of 199 patients with TRE who had diagnostic bICEEG at New York University Medical Center between 1994 and 2013. Study endpoints were progress to resection, surgical outcome and perioperative complications. Univariate analysis was performed with ANOVA, t-test or Fischer's Exact test; multivariable analysis was performed using discriminant function analysis. RESULTS: bICEEG lateralized the EZ and the patient had resection in 60.3% of cases. The number of depth electrodes used was positively correlated with resection, and surgical complications during bICEEG negatively correlated. Vagal nerve stimulators were implanted in 58.2% of patients who did not undergo resection and 20.7% of those who did. Among the 87 patients who progressed to resection and had more than 1-year follow-up, 47.1% were seizure free compared with 12.7% of the 55 who did not. Male sex correlated with good postoperative seizure control. The most common complication was infection requiring debridement, occurring in 3.1% of admissions (9 of 290). CONCLUSION: At our center, 60% of patients undergoing bICEEG progress to resection and 57% of these had more than 90% reduction in seizures. We conclude that bICEEG allows the benefits of epilepsy surgery to be extended to patients with poorly lateralized and localized TRE.

The differential contribution of medial-temporal lobe regions to verbal declarative memory is debated within the neuroscience, neuropsychology, and cognitive psychology communities. We evaluate whether the extent of surgical resection within medial-temporal regions predicts longitudinal verbal learning and memory outcomes. This single-center retrospective observational study involved patients with refractory temporal lobe epilepsy undergoing unilateral anterior temporal lobe resection from 2007 to 2015. Thirty-two participants with Engel Classes 1 and 2 outcomes were included (14 left, 18 right) and followed for a mean of 2.3 years after surgery (+/-1.5 years). Participants had baseline and postsurgical neuropsychological testing and high-resolution T1-weighted MRI scans. Postsurgical lesions were manually traced and coregistered to presurgical scans to precisely quantify resection extent of medial-temporal regions. Verbal learning and memory change scores were regressed on hippocampal, entorhinal, and parahippocampal resection volume after accounting for baseline performance. Overall, there were no significant differences in learning and memory change between patients who received left and right anterior temporal lobe resection. After controlling for baseline performance, the extent of left parahippocampal resection accounted for 27% (p = .021) of the variance in verbal short delay free recall. The extent of left entorhinal resection accounted for 37% (p = .004) of the variance in verbal short delay free recall. Our findings highlight the critical role that the left parahippocampal and entorhinal regions play in recall for verbal material.

Transcranial electric stimulation aims to stimulate the brain by applying weak electrical currents at the scalp. However, the magnitude and spatial distribution of electric fields in the human brain are unknown. We measured electric potentials intracranially in ten epilepsy patients and estimate electric fields across the entire brain by leveraging calibrated current-flow models. When stimulating at 2 mA, cortical electric fields reach 0.4 V/m, the lower limit of effectiveness in animal studies. When individual whole-head anatomy is considered, the predicted electric field magnitudes correlate with the recorded values in cortical (r=0.89) and depth (r=0.84) electrodes. Accurate models require adjustment of tissue conductivity values reported in the literature, but accuracy is not improved when incorporating white matter anisotropy or different skull compartments. This is the first study to validate and calibrate current-flow models with in vivo intracranial recordings in humans, providing a solid foundation to target stimulation and interpret clinical trials.

Verbal working memory (vWM) involves storing and manipulating information in phonological sensory input. An influential theory of vWM proposes that manipulation is carried out by a central executive while storage is performed by two interacting systems: a phonological input buffer that captures sound-based information and an articulatory rehearsal system that controls speech motor output. Whether, when and how neural activity in the brain encodes these components remains unknown. Here we read out the contents of vWM from neural activity in human subjects as they manipulated stored speech sounds. As predicted, we identified storage systems that contained both phonological sensory and articulatory motor representations. Unexpectedly, however, we found that manipulation did not involve a single central executive but rather involved two systems with distinct contributions to successful manipulation. We propose, therefore, that multiple subsystems comprise the central executive needed to manipulate stored phonological input for articulatory motor output in vWM.