Circadian changes in aperiodic activity are correlated with seizure reduction in patients with mesial temporal lobe epilepsy treated with responsive neurostimulation.

Objectives: Responsive neurostimulation (RNS) is an established therapy for drug-resistant epilepsy that delivers direct electrical brain stimulation in response to detected epileptiform activity. However, despite an overall reduction in seizure frequency, clinical outcomes are variable, and few patients become seizure-free. The aim of this retrospective study was to evaluate aperiodic electrophysiological activity, associated with excitation/inhibition balance, as a novel electrographic biomarker of seizure reduction to aid early prognostication of the clinical response to RNS.

A novel naïve Bayes approach to identifying grooming behaviors in the force-plate actometric platform.

Background: Self-grooming behavior in rodents serves as a valuable behavioral index for investigating stereotyped and perseverative responses. Most current grooming analyses rely on video observation, which lacks standardization, efficiency, and quantitative information about force. To address these limitations, we developed an automated paradigm to analyze grooming using a force-plate actometer.

Closed-loop stimulation in periods with less epileptiform activity drives improved epilepsy outcomes.

In patients with drug-resistant epilepsy, electrical stimulation of the brain in response to epileptiform activity can make seizures less frequent and debilitating. This therapy, known as closed-loop responsive neurostimulation (RNS), aims to directly halt seizure activity via targeted stimulation of a burgeoning seizure. Rather than immediately stopping seizures as they start, many RNS implants produce slower, long-lasting changes in brain dynamics that better predict clinical outcomes.

A novel naïve Bayes approach to identifying grooming behaviors in the force-plate actometric platform.

Background: Self-grooming behavior in rodents serves as a valuable model for investigating stereotyped and perseverative responses. Most current grooming analyses primarily rely on video observation, which lacks standardization, efficiency, and quantitative information about force. To address these limitations, we developed an automated paradigm to analyze grooming using a force-plate actometer.

Chronic intracranial recordings after resection for epilepsy reveal a "running down" of epileptiform activity.

We describe an electrical "running down" phenomenon and also a consistent spectral change (in the aperiodic component of the power spectrum) derived from chronic interictal electrocorticography (ECoG) after surgery in a patient with drug-resistant epilepsy. These data were recorded using a closed-loop neurostimulation system that was implanted after resection. The patient has been seizure-free for 2.

Macroscale traveling waves evoked by single-pulse stimulation of the human brain.

Understanding the spatiotemporal dynamics of neural signal propagation is fundamental to unraveling the complexities of brain function. Emerging evidence suggests that cortico-cortical evoked potentials (CCEPs) resulting from single-pulse electrical stimulation may be used to characterize the patterns of information flow between and within brain networks. At present, the basic spatiotemporal dynamics of CCEP propagation cortically and subcortically are incompletely understood.

Patient-specific structural connectivity informs outcomes of responsive neurostimulation for temporal lobe epilepsy.

Objective: Responsive neurostimulation is an effective therapy for patients with refractory mesial temporal lobe epilepsy. However, clinical outcomes are variable, few patients become seizure-free, and the optimal stimulation location is currently undefined. The aim of this study was to quantify responsive neurostimulation in the mesial temporal lobe, identify stimulation-dependent networks associated with seizure reduction, and determine if stimulation location or stimulation-dependent networks inform outcomes.

Corrigendum: LeGUI: A Fast and Accurate Graphical User Interface for Automated Detection and Anatomical Localization of Intracranial Electrodes.

[This corrects the article DOI: 10.3389/fnins.2021.

LeGUI: A Fast and Accurate Graphical User Interface for Automated Detection and Anatomical Localization of Intracranial Electrodes.

Accurate anatomical localization of intracranial electrodes is important for identifying the seizure foci in patients with epilepsy and for interpreting effects from cognitive studies employing intracranial electroencephalography. Localization is typically performed by coregistering postimplant computed tomography (CT) with preoperative magnetic resonance imaging (MRI). Electrodes are then detected in the CT, and the corresponding brain region is identified using the MRI.

Probabilistic comparison of gray and white matter coverage between depth and surface intracranial electrodes in epilepsy.

In this study, we quantified the coverage of gray and white matter during intracranial electroencephalography in a cohort of epilepsy patients with surface and depth electrodes. We included 65 patients with strip electrodes (n = 12), strip and grid electrodes (n = 24), strip, grid, and depth electrodes (n = 7), or depth electrodes only (n = 22). Patient-specific imaging was used to generate probabilistic gray and white matter maps and atlas segmentations.

Computational investigation of the impact of deep brain stimulation contact size and shape on neural selectivity.

Understanding neural selectivity is essential for optimizing medical applications of deep brain stimulation (DBS). We previously showed that modulation of the DBS waveform can induce changes in orientation-based selectivity, and that lengthening of DBS pulses or directional segmentation can reduce preferential selectivity for large axons. In this work, we sought to investigate a simple, but important question from a generalized perspective: how do the size and shape of the contact influence neural selectivity?We created multicompartment neuron models for several axon diameters and used finite element modeling with standard-sized cylindrical leads to determine the effects on changing contact size and shape on axon activation profiles and volumes of tissue activated.

Neural selectivity, efficiency, and dose equivalence in deep brain stimulation through pulse width tuning and segmented electrodes.

Background: Achieving deep brain stimulation (DBS) dose equivalence is challenging, especially with pulse width tuning and directional contacts. Further, the precise effects of pulse width tuning are unknown, and recent reports of the effects of pulse width tuning on neural selectivity are at odds with classic biophysical studies.

Methods: We created multicompartment neuron models for two axon diameters and used finite element modeling to determine extracellular influence from standard and segmented electrodes.

Activation robustness with directional leads and multi-lead configurations in deep brain stimulation.

Objective: Clinical outcomes from deep brain stimulation (DBS) can be highly variable, and two critical factors underlying this variability are the location and type of stimulation. In this study we quantified how robustly DBS activates a target region when taking into account a range of different lead designs and realistic variations in placement. The objective of the study is to assess the likelihood of achieving target activation.

The μDBS: Multiresolution, Directional Deep Brain Stimulation for Improved Targeting of Small Diameter Fibers.

Directional deep brain stimulation (DBS) leads have recently been approved and used in patients, and growing evidence suggests that directional contacts can increase the therapeutic window by redirecting stimulation to the target region while avoiding side-effect-inducing regions. We outline the design, fabrication, and testing of a novel directional DBS lead, the μDBS, which utilizes microscale contacts to increase the spatial resolution of stimulation steering and improve the selectivity in targeting small diameter fibers. We outline the steps of fabrication of the μDBS, from an integrated circuit design to post-processing and validation testing.

Evaluation of methodologies for computing the deep brain stimulation volume of tissue activated.

Objective: Computational models are a popular tool for predicting the effects of deep brain stimulation (DBS) on neural tissue. One commonly used model, the volume of tissue activated (VTA), is computed using multiple methodologies. We quantified differences in the VTAs generated by five methodologies: the traditional axon model method, the electric field norm, and three activating function based approaches-the activating function at each grid point in the tangential direction (AF-Tan) or in the maximally activating direction (AF-3D), and the maximum activating function along the entire length of a tangential fiber (AF-Max).

A retrospective evaluation of automated optimization of deep brain stimulation parameters.

Objective: We performed a retrospective analysis of an optimization algorithm for the computation of patient-specific multipolar stimulation configurations employing multiple independent current/voltage sources. We evaluated whether the obtained stimulation configurations align with clinical data and whether the optimized stimulation configurations have the potential to lead to an equal or better stimulation of the target region as manual programming, while reducing the time required for programming sessions.

Approach: For three patients (five electrodes) diagnosed with essential tremor, we derived optimized multipolar stimulation configurations using an approach that is suitable for the application in clinical practice.

Anodic stimulation misunderstood: preferential activation of fiber orientations with anodic waveforms in deep brain stimulation.

Objective: During deep brain stimulation (DBS), it is well understood that extracellular cathodic stimulation can cause activation of passing axons. Activation can be predicted from the second derivative of the electric potential along an axon, which depends on axonal orientation with respect to the stimulation source. We hypothesize that fiber orientation influences activation thresholds and that fiber orientations can be selectively targeted with DBS waveforms.

Optimized programming algorithm for cylindrical and directional deep brain stimulation electrodes.

Objective: Deep brain stimulation (DBS) is a growing treatment option for movement and psychiatric disorders. As DBS technology moves toward directional leads with increased numbers of smaller electrode contacts, trial-and-error methods of manual DBS programming are becoming too time-consuming for clinical feasibility. We propose an algorithm to automate DBS programming in near real-time for a wide range of DBS lead designs.

Subthalamic deep brain stimulation reduces pathological information transmission to the thalamus in a rat model of parkinsonism.

The degeneration of dopaminergic neurons in the substantia nigra pars compacta leads to parkinsonian motor symptoms via changes in electrophysiological activity throughout the basal ganglia. High-frequency deep brain stimulation (DBS) partially treats these symptoms, but the mechanisms are unclear. We hypothesize that motor symptoms of Parkinson's disease (PD) are associated with increased information transmission from basal ganglia output neurons to motor thalamus input neurons and that therapeutic DBS of the subthalamic nucleus (STN) treats these symptoms by reducing this extraneous information transmission.