Emad N. Eskandar

The subthalamic nucleus (STN) is a small almond-shaped subcortical structure classically known for its role in motor inhibition through the indirect pathway within the basal ganglia. Little is known about the role of the STN in mediating cognitive functions in humans. Here, we explore the role of the STN in human subjects making decisions under conditions of uncertainty using single-neuron recordings and intermittent deep brain stimulation (DBS) during a financial decision-making task. Intraoperative single-neuronal data from the STN reveals that on high-uncertainty trials, spiking activity encodes the upcoming decision within a brief (500 ms) temporal window during the choice period, prior to the manifestation of the choice. Application of intermittent DBS selectively prior to the choice period alters decisions and biases subject behavior towards conservative wagers.

During awake consciousness, the brain intrinsically maintains a dynamical state in which it can coordinate complex responses to sensory input. How the brain reaches this state spontaneously is not known. General anesthesia provides a unique opportunity to examine how the human brain recovers its functional capabilities after profound unconsciousness. We used intracranial electrocorticography and scalp EEG in humans to track neural dynamics during emergence from propofol general anesthesia. We identify a distinct transient brain state that occurs immediately prior to recovery of behavioral responsiveness. This state is characterized by large, spatially distributed, slow sensory-evoked potentials that resemble the K-complexes that are hallmarks of stage two sleep. However, the ongoing spontaneous dynamics in this transitional state differ from sleep. These results identify an asymmetry in the neurophysiology of induction and emergence, as the emerging brain can enter a state with a sleep-like sensory blockade before regaining responsivity to arousing stimuli.

Deep brain stimulation therapies for Parkinson's disease utilize hardware that, from a packaging perspective, resembles those that are used in cardiac pacemakers. A hermetic package that contains stimulation electronics and a primary battery supply is implanted under the scalp into a recess formed in the skull. Stimulation probes, each with up to four electrodes, are inserted into the brain and connected to the electronics package via a plug and cable system. Unlike single-target devices such as cochlear implants and pacemakers, achieving this type of neuropsychiatric therapy requires the ability to record and stimulate in multiple and distributive areas of the brain, both cortical and subcortical. By contrast, the closed-loop neural stimulator being developed under the DARPA SUBNETS program utilizes probes, each of which carries up to 64 electrodes that can be switched between recording and stimulation functions. This capability necessitates locating low-noise amplifiers, switching and communication electronics in close proximity to each probe site. Each of these satellite electronics packages requires 10 electrical connections to the hub package, which significantly increases the complexity of the interconnect system relative to the current practice. The power requirements of this system preclude the use of a primary battery supply, so a large lithium ion battery is used, with a recharging coil and electronics. The hub system is composed of a connector header, electronics package, and battery pack that are fabricated separately and are interconnected by a flex circuit board, to allow it to conform to the skull for implanting. The standardized feedthrough substrate on the satellite, which can interface with multiple types of electrodes, along the system being reconfigurable, enables our architecture to support this new clinical research. It also allows the clinician to select satellite-electrode system based on a patient's needs, thus providing a customized, patient-specific therapeutic system. In this article, we have described the various packaging components of this system and the design considerations that drove our technology choices.

Deep brain stimulation therapies for Parkinson's disease utilize hardware, which from a packaging perspective, resembles that used in cardiac pacemakers. A hermetic package that contains stimulation electronics and a primary battery supply is implanted under the scalp in a recess cut into the skull. Stimulation probes, each with up to four electrodes, are inserted into the brain and connected to the electronics package via a plug and cable system. By contrast, the closed loop neural stimulator being developed under the DARPA SUBNETS program utilizes probes, which each carry up to 64 electrodes that can be switched between recording and stimulation functions. This capability necessitates locating low noise amplifiers, switching and communication electronics in close proximity to each probe. Each of these satellite electronics packages requires ten electrical connections to the hub package, which significantly increases the complexity of the interconnect system relative to current practice. The power requirements of this system preclude the use of a primary battery supply so instead, a large lithium ion battery is used with a recharging coil and electronics. The hub system is fabricated as a separate connector header, electronics package and battery pack that are interconnected by a flex circuit to allow it to conform to the skull for implanting. In this paper, we will describe the various packaging components of the system and the design considerations that drove our technology choices.

Approximately 50 million people in the world suffer from epileptic seizures. Reliable early seizure detection could bring significantly beneficial therapeutic alternatives. In recent decades, most approaches have relied on scalp EEG and intracranial EEG signals, but practical early detection for closed-loop seizure control remains challenging. In this study, we present preliminary analyses of an early detection approach based on intracortical neuronal multiunit activity (MUA) recorded from a 96-microelectrode array (MEA). The approach consists of (1) MUA detection from broadband field potentials recorded at 30 kHz by the MEA; (2) MUA feature extraction; (3) cost-sensitive support vector machine classification of ictal and interictal samples; and (4) Kalman-filtering postprocessing. MUA was here defined as the number of threshold crossing (spike counts) applied to the 300 Hz-6 kHz bandpass filtered local field potentials in 0.1 sec time windows. MUA features explored in this study included the mean, variance, and Fano-factor, computed across the MEA channels. In addition, we used the leading eigenvalues of MUA spatial and temporal correlation matrices computed in 1-sec moving time windows. We assessed the seizure detection approach on out-of-sample data from one-participant recordings with six seizure events and 4.73-hour interictal data. The proposed MUA-based detection approach yielded a 100% sensitivity (6/6) and no false positives, and a latency of 4.17 ± 2.27 sec (mean ± SD) with respect to ECoG-identified seizure onsets. These preliminary results indicate intracortical MUA may be a useful signal for early detection of human epileptic seizures.

The nucleus accumbens core (NAcc) has been implicated in learning associations between sensory cues and profitable motor responses. However, the precise mechanisms that underlie these functions remain unclear. We recorded single-neuron activity from the NAcc of primates trained to perform a visual-motor associative learning task. During learning, we found two distinct classes of NAcc neurons. The first class demonstrated progressive increases in firing rates at the go-cue, feedback/tone and reward epochs of the task, as novel associations were learned. This suggests that these neurons may play a role in the exploitation of rewarding behaviors. In contrast, the second class exhibited attenuated firing rates, but only at the reward epoch of the task. These findings suggest that some NAcc neurons play a role in reward-based reinforcement during learning.

Object: Cingulotomy and limbic leucotomy are lesioning surgeries with demonstrated benefit for medically intractable psychiatric illnesses. They represent significant refinements of the prefrontal lobotomy used from the 1930s through the 1950s. However, the associations between anatomical characterization of these lesions and outcome data are not well understood. To elucidate these procedures and associations, the authors sought to define and compare the neuroanatomy of cingulotomy and limbic leucotomy and to test a method that uses neuroanatomical data and voxel-based lesion–symptom mapping (VLSM) to reveal potential refinements to modern psychiatric neurosurgical procedures. Methods: T1-weighted MR images of patients who had undergone cingulotomy and limbic leucotomy were segmented and registered onto the Montreal Neurological Institute T1-weighted template brain MNI152. Using an atlas-based approach, the authors calculated, by case, the percentage of each anatomical structure affected by the lesion. Because of the infrequency of modern lesion procedures and the requirement for higher-resolution clinical imaging, the sample size was small. The pilot study correlated cingulotomy and limbic leucotomy lesion characteristics with clinical outcomes for patients with obsessive-compulsive disorder. For this study, preoperative and postoperative Yale-Brown Obsessive Compulsive Scale scores for 11 cingulotomy patients and 8 limbic leucotomy patients were obtained, and lesion masks were defined and compared anatomically by using an atlas-based method. Statistically significant voxels were additionally calculated by using VLSM techniques that correlated lesion characteristics with postoperative scores. Results: Mean lesion volumes were 13.3 ml for cingulotomy and 11.8 ml for limbic leucotomy. As expected, cingulotomy was isolated to the anterior cingulum. The subcaudate tractotomy portion of limbic leucotomy additionally affected Brodmann area 25, the medial orbitofrontal cortex, and the nucleus accumbens. Initial results indicated that the dorsolateral regions of the cingulotomy lesion and the posteroventral regions of the subcaudate tractotomy lesion were associated with improved postoperative Yale-Brown Obsessive Compulsive Scale scores. Conclusions: Cingulotomy and limbic leucotomy are lesioning surgeries that target pathological circuits implicated in psychiatric disease. Lesion analysis and VLSM contextualize outcome data and have the potential to be useful for improving lesioning neurosurgical procedures.

Tracking spectral changes in neural signals, such as local field potentials (LFPs) and scalp or intracranial electroencephalograms (EEG, iEEG), is an important problem in early detection and prediction of seizures. Most approaches have focused on either parametric or nonparametric spectral estimation methods based on moving time windows. Here, we explore an adaptive (time-varying) parametric ARMA approach for tracking spectral changes in neural signals based on the fixed-interval Kalman smoother. We apply the method to seizure detection based on spectral features of intracortical LFPs recorded from a person with pharmacologically intractable focal epilepsy. We also devise and test an approach for real-time tracking of spectra based on the adaptive parametric method with the fixed-interval Kalman smoother. The order of ARMA models is determined via the AIC computed in moving time windows. We quantitatively demonstrate the advantages of using the adaptive parametric estimation method in seizure detection over nonparametric alternatives based exclusively on moving time windows. Overall, the adaptive parametric approach significantly improves the statistical separability of interictal and ictal epochs.