Neurophysiologic Characteristics of the Anterior Nucleus of the Thalamus during Deep Brain Stimulation Surgery for Epilepsy.

INTRODUCTION: Anterior nucleus of the thalamus (ANT) deep brain stimulation (DBS) is an increasingly promising treatment option for refractory epilepsy. Optimal therapeutic benefit has been associated with stimulation at the junction of ANT and the mammillothalamic tract (mtt), but electrophysiologic markers of this target are lacking. The present study examined microelectrode recordings (MER) during DBS to identify unique electrophysiologic characteristics of ANT and the ANT-mtt junction. METHODS: Ten patients with medically refractory epilepsy underwent MER during ANT-DBS implantation under general anesthesia. MER locations were determined based on coregistration of preoperative MRI, postoperative CT, and a stereotactic atlas of the thalamus (Morel atlas). Several neurophysiological parameters including single unit spiking rate, bursting properties, theta and alpha power and cerebrospinal fluid (CSF)-normalized root mean square (NRMS) of multiunit activity were characterized at recording depths and compared to anatomic boundaries. RESULTS: From sixteen hemispheres, 485 recordings locations were collected from a mean of 30.3 (15.64 ± 5.0 mm) recording spans. Three-hundred and ninety-four of these recording locations were utilized further for analysis of spiking and bursting rates, after excluding recordings that were more than 8 mm above the putative ventral ANT border. The ANT region exhibited discernible features including: (1) mean spiking rate (7.52 Hz ± 6.9 Hz; one-way analysis of variance test, p = 0.014 when compared to mediodorsal nucleus of the thalamus [MD], mtt, and CSF), (2) the presence of bursting activity with 40% of ANT locations (N = 59) exhibited bursting versus 24% the mtt (χ2; p < 0.001), and 32% in the MD (p = 0.38), (3) CSF-NRMS, a proxy for neuronal density, exhibited well demarcated changes near the entry and exit of ANT (linear regression, R = -0.33, p < 0.001). Finally, in the ANT, both theta (4-8 Hz) and alpha band power (9-12 Hz) were negatively correlated with distance to the ventral ANT border (linear regression, p < 0.001 for both). The proportion of recordings with spiking and bursting activity was consistently highest 0-2 mm above the ventral ANT border with the mtt. CONCLUSION: We observed several electrophysiological markers demarcating the ANT superior and inferior borders including multiple single cell and local field potential features. A local maximum in neural activity just above the ANT-mtt junction was consistent with the previously described optimal target for seizure reduction. These features may be useful for successful targeting of ANT-DBS for epilepsy.

Brain Shift during Staged Deep Brain Stimulation for Movement Disorders.

INTRODUCTION: Deep brain stimulation (DBS) is a routine neurosurgical procedure utilized to treat various movement disorders including Parkinson's disease (PD), essential tremor (ET), and dystonia. Treatment efficacy is dependent on stereotactic accuracy of lead placement into the deep brain target of interest. However, brain shift attributed to pneumocephalus can introduce unpredictable inaccuracies during DBS lead placement. This study aimed to determine whether intracranial air is associated with brain shift in patients undergoing staged DBS surgery. METHODS: We retrospectively evaluated 46 patients who underwent staged DBS surgery for PD, ET, and dystonia. Due to the staged nature of DBS surgery at our institution, the first electrode placement is used as a concrete fiducial marker for movement in the target location. Postoperative computed tomography (CT) images after the first electrode implantation, as well as preoperative, and postoperative CT images after the second electrode implantation were collected. Images were analyzed in stereotactic targeting software (BrainLab); intracranial air was manually segmented, and electrode shift was measured in the x, y, and z plane, as well as a Euclidian distance on each set of merged CT scans. A Pearson correlation analysis was used to determine the relationship between intracranial air and brain shift, and student's t test was used to compare means between patients with and without radiographic evidence of intracranial air. RESULTS: Thirty-six patients had pneumocephalus after the first electrode implantation, while 35 had pneumocephalus after the second electrode implantation. Accumulation of intracranial air following the first electrode implantation (4.49 ± 6.05 cm3) was significantly correlated with brain shift along the y axis (0.04 ± 0.35 mm; r (34) = 0.36; p = 0.03), as well as the Euclidean distance of deviation (0.57 ± 0.33 mm; r (34) = 0.33; p = 0.05) indicating statistically significant shift on the ipsilateral side. However, there was no significant correlation between intracranial air and brain shift following the second electrode implantation, suggesting contralateral shift is minimal. Furthermore, there was no significant difference in brain shift between patients with and without radiographic evidence of intracranial air following both electrode implantation surgeries. CONCLUSION: Despite observing volumes as high as 22.0 cm3 in patients with radiographic evidence of pneumocephalus, there was no significant difference in brain shift when compared to patients without pneumocephalus. Furthermore, the mean magnitude of brain shift was <1.0 mm regardless of whether pneumocephalus was presenting, suggesting that intracranial air accumulation may not produce clinical significant brain shift in our patients.

Pilot Study to Investigate the Use of In-Clinic Sensing to Identify Optimal Stimulation Parameters for Deep Brain Stimulation Therapy in Parkinson's Disease.

BACKGROUND: Deep brain stimulation (DBS) programming is time intensive. Recent advances in sensing technology of local field potentials (LFPs) may enable improvements. Few studies have compared the use of this technology with standard of care. OBJECTIVE/HYPOTHESIS: Sensing technology of subthalamic nucleus (STN) DBS leads in Parkinson's disease (PD) is reliable and predicts the optimal contacts and settings as predicted by clinical assessment. MATERIALS AND METHODS: Five subjects with PD (n = 9 hemispheres) with bilateral STN DBS and sensing capable battery replacement were recruited. An LFP sensing review of all bipolar contact pairs was performed three times. Contact with the maximal beta peak power (MBP) was then clinically assessed in a double-blinded fashion, and five conditions were tested: 1) entry settings, 2) off stimulation, 3) MBP at 30 µs, 4) MBP at 60 µs, and 5) MBP at 90 µs. RESULTS: Contact and frequency of the MBP power in all hemispheres did not differ across sessions. The entry settings matched with the contact with the MBP power in 5 of 9 hemispheres. No clinical difference was evident in the stimulation conditions. The clinician and subject preferred settings determined by MBP power in 7 of 9 and 5 of 7 hemispheres, respectively. CONCLUSIONS: This study indicates that STN LFPs in PD recorded directly from contacts of the DBS lead provide consistent recordings across the frequency range and a reliably detected beta peak. Furthermore, programming based on the MBP power provides at least clinical equivalence to standard of care programming with STN DBS.

Oscillatory beta dynamics inform biomarker-driven treatment optimization for Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.

Utility and lower limits of frequency detection in surface electrode stimulation for somatosensory brain-computer interface in humans.

OBJECTIVE: Stimulation of the primary somatosensory cortex (S1) has been successful in evoking artificial somatosensation in both humans and animals, but much is unknown about the optimal stimulation parameters needed to generate robust percepts of somatosensation. In this study, the authors investigated frequency as an adjustable stimulation parameter for artificial somatosensation in a closed-loop brain-computer interface (BCI) system. METHODS: Three epilepsy patients with subdural mini-electrocorticography grids over the hand area of S1 were asked to compare the percepts elicited with different stimulation frequencies. Amplitude, pulse width, and duration were held constant across all trials. In each trial, subjects experienced 2 stimuli and reported which they thought was given at a higher stimulation frequency. Two paradigms were used: first, 50 versus 100 Hz to establish the utility of comparing frequencies, and then 2, 5, 10, 20, 50, or 100 Hz were pseudorandomly compared. RESULTS: As the magnitude of the stimulation frequency was increased, subjects described percepts that were "more intense" or "faster." Cumulatively, the participants achieved 98.0% accuracy when comparing stimulation at 50 and 100 Hz. In the second paradigm, the corresponding overall accuracy was 73.3%. If both tested frequencies were less than or equal to 10 Hz, accuracy was 41.7% and increased to 79.4% when one frequency was greater than 10 Hz (p = 0.01). When both stimulation frequencies were 20 Hz or less, accuracy was 40.7% compared with 91.7% when one frequency was greater than 20 Hz (p < 0.001). Accuracy was 85% in trials in which 50 Hz was the higher stimulation frequency. Therefore, the lower limit of detection occurred at 20 Hz, and accuracy decreased significantly when lower frequencies were tested. In trials testing 10 Hz versus 20 Hz, accuracy was 16.7% compared with 85.7% in trials testing 20 Hz versus 50 Hz (p < 0.05). Accuracy was greater than chance at frequency differences greater than or equal to 30 Hz. CONCLUSIONS: Frequencies greater than 20 Hz may be used as an adjustable parameter to elicit distinguishable percepts. These findings may be useful in informing the settings and the degrees of freedom achievable in future BCI systems.

Gamma-band modulation in the human amygdala during reaching movements.

OBJECTIVE: Motor brain-computer interface (BCI) represents a new frontier in neurological surgery that could provide significant benefits for patients living with motor deficits. Both the primary motor cortex and posterior parietal cortex have successfully been used as a neural source for human motor BCI, leading to interest in exploring other brain areas involved in motor control. The amygdala is one area that has been shown to have functional connectivity to the motor system; however, its role in movement execution is not well studied. Gamma oscillations (30-200 Hz) are known to be prokinetic in the human cortex, but their role is poorly understood in subcortical structures. Here, the authors use direct electrophysiological recordings and the classic "center-out" direct-reach experiment to study amygdaloid gamma-band modulation in 8 patients with medically refractory epilepsy. METHODS: The study population consisted of 8 epilepsy patients (2 men; age range 21-62 years) who underwent implantation of micro-macro depth electrodes for seizure localization and EEG monitoring. Data from the macro contacts sampled at 2000 Hz were used for analysis. The classic center-out direct-reach experiment was used, which consists of an intertrial interval phase, a fixation phase, and a response phase. The authors assessed the statistical significance of neural modulation by inspecting for nonoverlapping areas in the 95% confidence intervals of spectral power for the response and fixation phases. RESULTS: In 5 of the 8 patients, power spectral analysis showed a statistically significant increase in power within regions of the gamma band during the response phase compared with the fixation phase. In these 5 patients, the 95% bootstrapped confidence intervals of trial-averaged power in contiguous frequencies of the gamma band during the response phase were above, and did not overlap with, the confidence intervals of trial-averaged power during the fixation phase. CONCLUSIONS: To the authors' knowledge, this is the first time that direct neural recordings have been used to show gamma-band modulation in the human amygdala during the execution of voluntary movement. This work indicates that gamma-band modulation in the amygdala could be a contributing source of neural signals for use in a motor BCI system.

Electrocorticographic changes in field potentials following natural somatosensory percepts in humans.

OBJECTIVE: Restoration of somatosensory deficits in humans requires a clear understanding of the neural representations of percepts. To characterize the cortical response to naturalistic somatosensation, we examined field potentials in the primary somatosensory cortex of humans. METHODS: Four patients with intractable epilepsy were implanted with subdural electrocorticography (ECoG) electrodes over the hand area of S1. Three types of stimuli were applied, soft-repetitive touch, light touch, and deep touch. Power in the alpha (8-15 Hz), beta (15-30 Hz), low-gamma (30-50 Hz), and high-gamma (50-125 Hz) frequency bands were evaluated for significance. RESULTS: Seventy-seven percent of electrodes over the hand area of somatosensory cortex exhibited changes in these bands. High-gamma band power increased for all stimuli, with concurrent alpha and beta band power decreases. Earlier activity was seen in these bands in deep touch and light touch compared to soft touch. CONCLUSIONS: These findings are consistent with prior literature and suggest a widespread response to focal touch, and a different encoding of deeper pressure touch than soft touch.

Potentially preventable complications in epilepsy admissions: The "weekend effect".

INTRODUCTION: Epilepsy affects approximately 1% of the population in the United States with frequent hospital admissions accounting for a significant burden on patients and society as a whole. Weekend admissions have generally been found to have poorer outcomes compared to weekday admissions with increased rates of preventable complications, such as nationally identified "hospital-acquired conditions" (HAC). OBJECTIVE: This study aimed to assess the impact of weekend admission on HACs and mortality in the adult epilepsy population. PARTICIPANTS: All adult patients with epilepsy hospitalized in the U.S. from 2000 to 2010 in the Nationwide Inpatient Sample. RESULTS: There were 12,997,181 admissions for epilepsy with 10,106,152 (78%) weekday, 2,891,019 (22%) weekend, and 10 (<0.1%) missing admissions. Weekend admissions saw a 10% increased likelihood of both HACs (RR=1.10, 95% CI:1.09, 1.11, p<0.01) and mortality (RR=1.10, 95% CI: 1.09, 1.11, p<0.01) compared to weekday admissions. The occurrence of HAC was associated with higher inpatient charges (RR=1.36, 95% CI: 1.35, 1.36, p<0.01), pLOS (RR=1.21, 95% CI: 1.21, 1.22, p<0.01), and higher mortality (RR=1.13, 95% CI: 1.12, 1.14, p<0.01). CONCLUSION: Prior studies have shown weekend admissions are usually associated with higher rates of complications leading to higher costs and a longer hospital stay. Likewise, weekend admissions for epilepsy were associated with increased rates of HACs and mortality; however, they were also negatively associated with LOS and total charge. Thus, weekend admissions for epilepsy should be considered high risk with greater effort made to mitigate these risks.

Interplay between Cortical Spreading Depolarization and Seizures.

Cortical spreading depolarization (CSD) is an electrophysiologic phenomenon found mostly in the setting of neurologic injury resulting in the disturbance of ion homeostasis and leading to changes in the local vascular response. The bioelectric etiology of CSD shares similarities to those in epileptic disorders, yet the relationship between seizures and CSD is unclear, with several studies observing cortical depression before, during, and after seizure activity, thus obscuring our understanding of whether CSD activity potentiates or limits seizures and vice versa. Cortical sampling has exhibited how the redistribution of ion concentrations in the intra- and extracellular environments interplay between the excitation of seizures and the electrical depression of CSD. Modeling of both environments has suggested that CSD synchronizes the affected tissue, creating a favorable environment for seizure activity; however, other studies have demonstrated the opposite: epileptiform activity initiating waves of CSD. Further studies have underscored the role of the vascular response and subsequent ischemia in CSD that contributes to epileptogenesis. Investigations in migraine, traumatic brain injury, and other neurologic injuries suggest that several drugs may target CSD. Manipulations in the occurrence and nature of CSD can potentially alter the threshold for seizure activity, and perhaps minimize immediate and long-term sequelae associated with epilepsy.

Primary somatosensory cortex organization for engineering artificial somatosensation.

Somatosensory deficits from stroke, spinal cord injury, or other neurologic damage can lead to a significant degree of functional impairment. The primary (SI) and secondary (SII) somatosensory cortices encode information in a medial to lateral organization. SI is generally organized topographically, with more discrete cortical representations of specific body regions. SII regions corresponding to anatomical areas are less discrete and may represent a more functional rather than topographic organization. Human somatosensory research continues to map cortical areas of sensory processing with efforts primarily focused on hand and upper extremity information in SI. However, research into SII and other body regions is lacking. In this review, we synthesize the current state of knowledge regarding the cortical organization of human somatosensation and discuss potential applications for brain computer interface. In addition to accurate individualized mapping of cortical somatosensation, further research is required to uncover the neurophysiological mechanisms of how somatosensory information is encoded in the cortex.

Subthalamic nucleus synchronization between beta band local field potential and single-unit activity in Parkinson's disease.

Local field potential (LFP) oscillations in the beta band (13-30 Hz) in the subthalamic nucleus (STN) of Parkinson's disease patients have been implicated in disease severity and treatment response. The relationship between single-neuron activity in the STN and regional beta power changes remains unclear. We used spike-triggered average (STA) to assess beta synchronization in STN. Beta power and STA magnitude at the beta frequency range were compared in three conditions: STN versus other subcortical structures, dorsal versus ventral STN, and high versus low beta power STN recordings. Magnitude of STA-LFP was greater within the STN compared to extra-STN structures along the trajectory path, despite no difference in percentage of the total power. Within the STN, there was a higher percent beta power in dorsal compared to ventral STN but no difference in STA-LFP magnitude. Further refining the comparison to high versus low beta peak power recordings inside the STN to evaluate if single-unit activity synchronized more strongly with beta band activity in areas of high beta power resulted in a significantly higher STA magnitude for areas of high beta power. Overall, these results suggest that STN single units strongly synchronize to beta activity, particularly units in areas of high beta power.

Comparison of beta peak detection algorithms for data-driven deep brain stimulation programming strategies in Parkinson's disease.

Oscillatory activity within the beta frequency range (13-30 Hz) serves as a Parkinson's disease biomarker for tailoring deep brain stimulation (DBS) treatments. Currently, identifying clinically relevant beta signals, specifically frequencies of peak amplitudes within the beta spectral band, is a subjective process. To inform potential strategies for objective clinical decision making, we assessed algorithms for identifying beta peaks and devised a standardized approach for both research and clinical applications. Employing a novel monopolar referencing strategy, we utilized a brain sensing device to measure beta peak power across distinct contacts along each DBS electrode implanted in the subthalamic nucleus. We then evaluated the accuracy of ten beta peak detection algorithms against a benchmark established by expert consensus. The most accurate algorithms, all sharing similar underlying algebraic dynamic peak amplitude thresholding approaches, matched the expert consensus in performance and reliably predicted the clinical stimulation parameters during follow-up visits. These findings highlight the potential of algorithmic solutions to overcome the subjective bias in beta peak identification, presenting viable options for standardizing this process. Such advancements could lead to significant improvements in the efficiency and accuracy of patient-specific DBS therapy parameterization.

Corrigendum: The role of the piriform cortex in temporal lobe epilepsy: A current literature review.

[This corrects the article DOI: 10.3389/fneur.2022.1042887.].

Comparison of Monopolar Review to Fixed Parameter Fractionation in Deep Brain Stimulation.

Background: Technological advancements in deep brain stimulation (DBS) require methodological changes in programming. Fractionalization poses significant practical challenges for the most common approach for assessing DBS efficacy, monopolar review (MR). Objectives: Two DBS programming methods: MR and fixed parameter vertical and horizontal fractionalization (FPF) were compared. Methods: A two-phase process of vertical and horizontal FPF was performed. MR was conducted thereafter. After a short wash-out period, both optimal configurations determined by MR and FPF were tested in a double-blind randomized manner. Results: Seven PD patients were enrolled, providing 11 hemispheres to compare the two conditions. In all subjects, the blinded examiner selected a directional or fractionalization configuration. There was no significant difference in clinical benefits between MR and FPF. FPF was the preferred method for initial programming as selected by subject and clinician. Conclusions: FPF programming is a viable and efficient methodology that may be incorporated into clinical practice.

The effect of intraventricular trajectory on brain shift in deep brain stimulation.

BACKGROUND: Brain shift during deep brain stimulation (DBS) surgery may compromise target localization. Loss of cerebrospinal fluid is believed to be the underlying mechanism, thus an intraventricular trajectory during DBS surgery may be associated with increased shift, in addition to other complications, such as intraventricular hemorrhage. OBJECTIVE: We set out to assess the effect of traversing the lateral ventricle on brain shift during DBS surgery. METHODS: We performed a retrospective review of 65 pre- and postoperative MR images of patients who underwent bilateral subthalamic nucleus deep brain stimulator placement to treat advanced Parkinson's disease. Patients were separated into two groups: Group A (intraventricular trajectory, n = 46) and Group B (no intraventricular trajectory, n = 19). In these patients, we compared pre- and postoperative frame coordinates of the red nucleus (RN). RESULTS: Group B demonstrated significantly more posterior shift of the center of the RN (1.40 ± 1.32 mm) than Group A (0.64 ± 1.76 mm; p < 0.02). We found no increase in incidence of intraventricular hemorrhage or the number of microelectrode trajectory attempts. CONCLUSIONS: Intraventricular trajectories during DBS surgery do not appear to compromise safety or targeting accuracy.

Error reduction with routine checklist use during deep brain stimulation surgery.

BACKGROUND: The use of checklists to reduce error rates in procedural literature has led our group to employ this strategy during deep brain stimulation (DBS) surgery. OBJECTIVES: We sought to examine the improvement in the number of errors made during DBS surgery after long-term use of a checklist. METHODS: Our checklist has been used for all DBS cases at our institution since the beginning of this study's enrollment in 2008. The number of cases in which errors were detected after 1 year of routine use (group B, n = 11) was compared in one cohort of DBS subjects to that of an earlier cohort of patients (group A, n = 17), which underwent DBS exactly 1 year prior. RESULTS: Eleven of the 14 cases where major errors were detected occurred in group A; 6 of the 9 cases where only minor errors were detected were also in group A; of the patients without any error, all 5 were in group B. We found a significant difference in these proportions between group A and group B [χ(2)(2) = 9.73; p < 0.008]. CONCLUSIONS: After 1 year of checklist use, the total number of major and minor errors made was reduced, indicating an improvement in error rate after long-term routine incorporation of this checklist.

Automatic extraction of upper-limb kinematic activity using deep learning-based markerless tracking during deep brain stimulation implantation for Parkinson's disease: A proof of concept study.

Optimal placement of deep brain stimulation (DBS) therapy for treating movement disorders routinely relies on intraoperative motor testing for target determination. However, in current practice, motor testing relies on subjective interpretation and correlation of motor and neural information. Recent advances in computer vision could improve assessment accuracy. We describe our application of deep learning-based computer vision to conduct markerless tracking for measuring motor behaviors of patients undergoing DBS surgery for the treatment of Parkinson's disease. Video recordings were acquired during intraoperative kinematic testing (N = 5 patients), as part of standard of care for accurate implantation of the DBS electrode. Kinematic data were extracted from videos post-hoc using the Python-based computer vision suite DeepLabCut. Both manual and automated (80.00% accuracy) approaches were used to extract kinematic episodes from threshold derived kinematic fluctuations. Active motor epochs were compressed by modeling upper limb deflections with a parabolic fit. A semi-supervised classification model, support vector machine (SVM), trained on the parameters defined by the parabolic fit reliably predicted movement type. Across all cases, tracking was well calibrated (i.e., reprojection pixel errors 0.016-0.041; accuracies >95%). SVM predicted classification demonstrated high accuracy (85.70%) including for two common upper limb movements, arm chain pulls (92.30%) and hand clenches (76.20%), with accuracy validated using a leave-one-out process for each patient. These results demonstrate successful capture and categorization of motor behaviors critical for assessing the optimal brain target for DBS surgery. Conventional motor testing procedures have proven informative and contributory to targeting but have largely remained subjective and inaccessible to non-Western and rural DBS centers with limited resources. This approach could automate the process and improve accuracy for neuro-motor mapping, to improve surgical targeting, optimize DBS therapy, provide accessible avenues for neuro-motor mapping and DBS implantation, and advance our understanding of the function of different brain areas.

The role of the piriform cortex in temporal lobe epilepsy: A current literature review.

Temporal lobe epilepsy is the most common form of focal epilepsy and can have various detrimental consequences within many neurologic domains. Recent evidence suggests that the piriform cortex may also be implicated in seizure physiology. The piriform cortex is a primary component of the olfactory network and is located at the junction of the frontal and temporal lobes, wrapping around the entorhinal sulcus. Similar to the hippocampus, it is a tri-layered allocortical structure, with connections to many adjacent regions including the orbitofrontal cortex, amygdala, peri- and entorhinal cortices, and insula. Both animal and human studies have implicated the piriform cortex as a critical node in the temporal lobe epilepsy network. It has additionally been shown that resection of greater than half of the piriform cortex may significantly increase the odds of achieving seizure freedom. Laser interstitial thermal therapy has also been shown to be an effective treatment strategy with recent evidence hinting that ablation of the piriform cortex may be important for seizure control as well. We propose that sampling piriform cortex in intracranial stereoelectroencephalography (sEEG) procedures with the use of a temporal pole or amygdalar electrode would be beneficial for further understanding the role of the piriform cortex in temporal lobe epilepsy.

Quantifying neuro-motor correlations during awake deep brain stimulation surgery using markerless tracking.

The expanding application of deep brain stimulation (DBS) therapy both drives and is informed by our growing understanding of disease pathophysiology and innovations in neurosurgical care. Neurophysiological targeting, a mainstay for identifying optimal, motor responsive targets, has remained largely unchanged for decades. Utilizing deep learning-based computer vision and related computational methods, we developed an effective and simple intraoperative approach to objectively correlate neural signals with movements, automating and standardizing the otherwise manual and subjective process of identifying ideal DBS electrode placements. Kinematics are extracted from video recordings of intraoperative motor testing using a trained deep neural network and compared to multi-unit activity recorded from the subthalamic nucleus. Neuro-motor correlations were quantified using dynamic time warping with the strength of a given comparison measured by comparing against a null distribution composed of related neuro-motor correlations. This objective measure was then compared to clinical determinations as recorded in surgical case notes. In seven DBS cases for treatment of Parkinson's disease, 100 distinct motor testing epochs were extracted for which clear clinical determinations were made. Neuro-motor correlations derived by our automated system compared favorably with expert clinical decision making in post-hoc comparisons, although follow-up studies are necessary to determine if improved correlation detection leads to improved outcomes. By improving the classification of neuro-motor relationships, the automated system we have developed will enable clinicians to maximize the therapeutic impact of DBS while also providing avenues for improving continued care of treated patients.

Mapping of primary somatosensory cortex of the hand area using a high-density electrocorticography grid for closed-loop brain computer interface.

Objective.The ideal modality for generating sensation in sensorimotor brain computer interfaces (BCI) has not been determined. Here we report the feasibility of using a high-density 'mini'-electrocorticography (mECoG) grid in a somatosensory BCI system.Approach.Thirteen subjects with intractable epilepsy underwent standard clinical implantation of subdural electrodes for the purpose of seizure localization. An additional high-density mECoG grid was placed (Adtech, 8 by 8, 1.2 mm exposed, 3 mm center-to-center spacing) over the hand area of primary somatosensory cortex. Following implantation, cortical mapping was performed with stimulation parameters of frequency: 50 Hz, pulse-width: 250µs, pulse duration: 4 s, polarity: alternating, and current that ranged from 0.5 mA to 12 mA at the discretion of the epileptologist. Location of the evoked sensory percepts was recorded along with a description of the sensation. The hand was partitioned into 48 distinct boxes. A box was included if sensation was felt anywhere within the box.Main results.The percentage of the hand covered was 63.9% (± 34.4%) (mean ± s.d.). Mean redundancy, measured as electrode pairs stimulating the same box, was 1.9 (± 2.2) electrodes per box; and mean resolution, measured as boxes included per electrode pair stimulation, was 11.4 (± 13.7) boxes with 8.1 (± 10.7) boxes in the digits and 3.4 (± 6.0) boxes in the palm. Functional utility of the system was assessed by quantifying usable percepts. Under the strictest classification, 'dermatomally exclusive' percepts, the mean was 2.8 usable percepts per grid. Allowing 'perceptually unique' percepts at the same anatomical location, the mean was 5.5 usable percepts per grid.Significance.Compared to the small area of coverage and redundancy of a microelectrode system, or the poor resolution of a standard ECoG grid, a mECoG is likely the best modality for a somatosensory BCI system with good coverage of the hand and minimal redundancy.