Deep brain stimulation pulse sequences to optimally modulate frequency-specific neural activity.

OBJECTIVE: Precise neuromodulation systems are needed to identify the role of neural oscillatory dynamics in brain function and to advance the development of brain stimulation therapies tailored to each patient's signature of brain dysfunction. Low-frequency, local field potentials (LFPs) are of increasing interest for the development of these systems because they can reflect the synaptic inputs to a recorded neuronal population and can be chronically recorded in humans. In this computational study, we aim to identify stimulation pulse patterns needed to optimally maximize the suppression or amplification of frequency-specific neural activity. Approach: We derived DBS pulse patterns to minimize or maximize the 2-norm of frequency-specific neural oscillations using a generalized mathematical model of spontaneous and stimulation-evoked LFP activity, and a subject-specific model of neural dynamics in the pallidum of a Parkinson's disease patient. We leveraged convex and mixed-integer optimization tools to identify these pulse patterns, and employed constraints on the pulse frequency and amplitude that are required to keep electrical stimulation within its safety envelope. Main results: Our analysis revealed that a combination of phase, amplitude, and frequency pulse modulation is needed to attain optimal suppression or amplification of the targeted oscillations. Phase modulation is sufficient to modulate oscillations with a constant amplitude envelope. To attain optimal modulation for oscillations with a time-varying envelope, a trade-off between frequency and amplitude pulse modulation is needed. The optimized pulse sequences were invariant to changes in the dynamics of stimulation-evoked neural activity, including changes in damping and natural frequency or complexity (i.e., generalized vs. patient-specific model). Significance: Our results provide insight into the structure of pulse patterns for future closed-loop brain stimulation strategies aimed at controlling neural activity precisely and in real-time.

Paradoxical Modulation of STN ß-Band Activity with Medication Compared to Deep Brain Stimulation.

BACKGROUND: Excessive subthalamic nucleus (STN) ß-band (13-35 Hz) synchronized oscillations has garnered interest as a biomarker for characterizing disease state and developing adaptive stimulation systems for Parkinson's disease (PD). OBJECTIVES: To report on a patient with abnormal treatment-responsive modulation in the ß-band. METHODS: We examined STN local field potentials from an externalized deep brain stimulation (DBS) lead while assessing PD motor signs in four conditions (OFF, MEDS, DBS, and MEDS+DBS). RESULTS: The patient presented here exhibited a paradoxical increase in ß power following administration of levodopa and pramipexole (MEDS), but an attenuation in ß power during DBS and MEDS+DBS despite clinical improvement of 50% or greater under all three therapeutic conditions. CONCLUSIONS: This case highlights the need for further study on the role of ß oscillations in the pathophysiology of PD and the importance of personalized approaches to the development of ß or other biomarker-based DBS closed loop algorithms. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Low-frequency deep brain stimulation reveals resonant beta-band evoked oscillations in the pallidum of Parkinson's Disease patients.

Introduction: Evidence suggests that spontaneous beta band (11-35 Hz) oscillations in the basal ganglia thalamocortical (BGTC) circuit are linked to Parkinson's disease (PD) pathophysiology. Previous studies on neural responses in the motor cortex evoked by electrical stimulation in the subthalamic nucleus have suggested that circuit resonance may underlie the generation of spontaneous and stimulation-evoked beta oscillations in PD. Whether these stimulation-evoked, resonant oscillations are present across PD patients in the internal segment of the globus pallidus (GPi), a primary output nucleus in the BGTC circuit, is yet to be determined. Methods: We characterized spontaneous and stimulation-evoked local field potentials (LFPs) in the GPi of four PD patients (five hemispheres) using deep brain stimulation (DBS) leads externalized after DBS implantation surgery. Results: Our analyses show that low-frequency (2-4 Hz) stimulation in the GPi evoked long-latency (>50 ms) beta-band neural responses in the GPi in 4/5 hemispheres. We demonstrated that neural sources generating both stimulation-evoked and spontaneous beta oscillations were correlated in their frequency content and spatial localization. Discussion: Our results support the hypothesis that the same neuronal population and resonance phenomenon in the BGTC circuit generates both spontaneous and evoked pallidal beta oscillations. These data also support the development of closed-loop control systems that modulate the GPi spontaneous oscillations across PD patients using beta band stimulation-evoked responses.

Myogenic and cortical evoked potentials vary as a function of stimulus pulse geometry delivered in the subthalamic nucleus of Parkinson's disease patients.

Introduction: The therapeutic efficacy of deep brain stimulation (DBS) of the subthalamic nucleus (STN) for Parkinson's disease (PD) may be limited for some patients by the presence of stimulation-related side effects. Such effects are most often attributed to electrical current spread beyond the target region. Prior computational modeling studies have suggested that changing the degree of asymmetry of the individual phases of the biphasic, stimulus pulse may allow for more selective activation of neural elements in the target region. To the extent that different neural elements contribute to the therapeutic vs. side-effect inducing effects of DBS, such improved selectivity may provide a new parameter for optimizing DBS to increase the therapeutic window. Methods: We investigated the effect of six different pulse geometries on cortical and myogenic evoked potentials in eight patients with PD whose leads were temporarily externalized following STN DBS implant surgery. DBS-cortical evoked potentials were quantified using peak to peak measurements and wavelets and myogenic potentials were quantified using RMS. Results: We found that the slope of the recruitment curves differed significantly as a function of pulse geometry for both the cortical- and myogenic responses. Notably, this effect was observed most frequently when stimulation was delivered using a monopolar, as opposed to a bipolar, configuration. Discussion: Manipulating pulse geometry results in differential physiological effects at both the cortical and neuromuscular level. Exploiting these differences may help to expand DBS' therapeutic window and support the potential for incorporating pulse geometry as an additional parameter for optimizing therapeutic benefit.

The impact of pulse timing on cortical and subthalamic nucleus deep brain stimulation evoked potentials.

The impact of pulse timing is an important factor in our understanding of how to effectively modulate the basal ganglia thalamocortical (BGTC) circuit. Single pulse low-frequency DBS-evoked potentials generated through electrical stimulation of the subthalamic nucleus (STN) provide insight into circuit activation, but how the long-latency components change as a function of pulse timing is not well-understood. We investigated how timing between stimulation pulses delivered in the STN region influence the neural activity in the STN and cortex. DBS leads implanted in the STN of five patients with Parkinson's disease were temporarily externalized, allowing for the delivery of paired pulses with inter-pulse intervals (IPIs) ranging from 0.2 to 10 ms. Neural activation was measured through local field potential (LFP) recordings from the DBS lead and scalp EEG. DBS-evoked potentials were computed using contacts positioned in dorsolateral STN as determined through co-registered post-operative imaging. We quantified the degree to which distinct IPIs influenced the amplitude of evoked responses across frequencies and time using the wavelet transform and power spectral density curves. The beta frequency content of the DBS evoked responses in the STN and scalp EEG increased as a function of pulse-interval timing. Pulse intervals <1.0 ms apart were associated with minimal to no change in the evoked response. IPIs from 1.5 to 3.0 ms yielded a significant increase in the evoked response, while those >4 ms produced modest, but non-significant growth. Beta frequency activity in the scalp EEG and STN LFP response was maximal when IPIs were between 1.5 and 4.0 ms. These results demonstrate that long-latency components of DBS-evoked responses are pre-dominantly in the beta frequency range and that pulse interval timing impacts the level of BGTC circuit activation.

Controlling pallidal oscillations in real-time in Parkinson's disease using evoked interference deep brain stimulation (eiDBS): Proof of concept in the human.

Approaches to control basal ganglia neural activity in real-time are needed to clarify the causal role of 13-35 Hz ("beta band") oscillatory dynamics in the manifestation of Parkinson's disease (PD) motor signs. Here, we show that resonant beta oscillations evoked by electrical pulses with precise amplitude and timing can be used to predictably suppress or amplify spontaneous beta band activity in the internal segment of the globus pallidus (GPi) in the human. Using this approach, referred to as closed-loop evoked interference deep brain stimulation (eiDBS), we could suppress or amplify frequency-specific (16-22 Hz) neural activity in a PD patient. Our results highlight the utility of eiDBS to characterize the role of oscillatory dynamics in PD and other brain conditions, and to develop personalized neuromodulation systems.

Quantifying Viscous Damping and Stiffness in Parkinsonism Using Data-Driven Model Estimation and Admittance Control.

Rigidity of upper and lower limbs in Parkinson's disease (PD) is typically assessed via a clinical rating scale that is subject to human perception biases. Methodologies to quantify changes in rigidity associated with the angular position (stiffness) or velocity (viscous damping) are needed to enhance our understanding of PD pathophysiology and objectively assess therapies. In this proof of concept study, we developed a robotic system and a model-based approach to estimate viscous damping and stiffness of the elbow. Our methodology enables the subject to freely rotate the elbow using an admittance controller while torque perturbations tailored to identify the arm dynamics are delivered. The viscosity and stiffness are calculated based on the experimental data using least-squares estimation. We validated our technique using computer simulations and experiments with a nonhuman animal model of PD in the presence and absence of deep brain stimulation therapy. Our data show that stiffness and viscosity measurements can better differentiate rigidity changes than scores previously used for research, including the work and impulse scores, and the modified unified Parkinson's disease rating scale. Our estimation method is suitable for quantifying the effect of therapies on viscous damping and stiffness and studying the pathophysiological mechanisms underlying rigidity in PD.

High-Frequency Oscillations in the Pallidum: A Pathophysiological Biomarker in Parkinson's Disease?

BACKGROUND: Abnormal oscillatory neural activity in the beta-frequency band (13-35 Hz) is thought to play a role in Parkinson's disease (PD); however, increasing evidence points to alterations in high-frequency ranges (>100 Hz) also having pathophysiological relevance. OBJECTIVES: Studies have found that power in subthalamic nucleus (STN) high-frequency oscillations is increased with dopaminergic medication and during voluntary movements, implicating these brain rhythms in normal basal ganglia function. The objective of this study was to investigate whether similar signaling occurs in the internal globus pallidus (GPi), a nucleus increasingly used as a target for deep brain stimulation (DBS) for PD. METHODS: Spontaneous and movement-related GPi field potentials were recorded from DBS leads in 5 externalized PD patients on and off dopaminergic medication, as well as from 3 rhesus monkeys before and after the induction of parkinsonism with the neurotoxin 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine. RESULTS: In the parkinsonian condition, we identified a prominent oscillatory peak centered at 200-300 Hz that increased during movement. In patients the magnitude of high-frequency oscillation modulation was negatively correlated with bradykinesia. In monkeys, high-frequency oscillations were mostly absent in the naive condition but emerged after the neurotoxin 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine. In patients, spontaneous high-frequency oscillations were significantly attenuated on-medication. CONCLUSIONS: Our findings provide evidence in support of the hypothesis that exaggerated, movement-modulated high-frequency oscillations in the GPi are pathophysiological features of PD. These findings suggest that the functional role(s) of high-frequency oscillations may differ between the STN and GPi and motivate additional investigations into their relationship to motor control in normal and diseased states.

Parkinsonism Alters Beta Burst Dynamics across the Basal Ganglia-Motor Cortical Network.

Elevated synchronized oscillatory activity in the beta band has been hypothesized to be a pathophysiological marker of Parkinson's disease (PD). Recent studies have suggested that parkinsonism is closely associated with increased amplitude and duration of beta burst activity in the subthalamic nucleus (STN). How beta burst dynamics are altered from the normal to parkinsonian state across the basal ganglia-thalamocortical (BGTC) motor network, however, remains unclear. In this study, we simultaneously recorded local field potential activity from the STN, internal segment of the globus pallidus (GPi), and primary motor cortex (M1) in three female rhesus macaques, and characterized how beta burst activity changed as the animals transitioned from normal to progressively more severe parkinsonian states. Parkinsonism was associated with an increased incidence of beta bursts with longer duration and higher amplitude in the low beta band (8-20 Hz) in both the STN and GPi, but not in M1. We observed greater concurrence of beta burst activity, however, across all recording sites (M1, STN, and GPi) in PD. The simultaneous presence of low beta burst activity across multiple nodes of the BGTC network that increased with severity of PD motor signs provides compelling evidence in support of the hypothesis that low beta synchronized oscillations play a significant role in the underlying pathophysiology of PD. Given its immersion throughout the motor circuit, we hypothesize that this elevated beta-band activity interferes with spatial-temporal processing of information flow in the BGTC network that contributes to the impairment of motor function in PD.SIGNIFICANCE STATEMENT This study fills a knowledge gap regarding the change in temporal dynamics and coupling of beta burst activity across the basal ganglia-thalamocortical (BGTC) network during the evolution from normal to progressively more severe parkinsonian states. We observed that changes in beta oscillatory activity occur throughout BGTC and that increasing severity of parkinsonism was associated with a higher incidence of longer duration, higher amplitude low beta bursts in the basal ganglia, and increased concurrence of beta bursts across the subthalamic nucleus, globus pallidus, and motor cortex. These data provide new insights into the potential role of changes in the temporal dynamics of low beta activity within the BGTC network in the pathogenesis of Parkinson's disease.

Real-time suppression and amplification of frequency-specific neural activity using stimulation evoked oscillations.

BACKGROUND: Approaches to predictably control neural oscillations are needed to understand their causal role in brain function in healthy or diseased states and to advance the development of neuromodulation therapies. OBJECTIVE: We present a closed-loop neural control and optimization framework to actively suppress or amplify low-frequency neural oscillations observed in local field potentials in real-time by using electrical stimulation. The rationale behind this control approach and our working hypothesis is that neural oscillatory activity evoked by electrical pulses can suppress or amplify spontaneous oscillations via destructive or constructive interference when the pulses are continuously delivered with appropriate amplitudes and at precise phases of the modulated oscillations in a closed-loop scheme. METHODS: We tested our hypothesis in two nonhuman primates that exhibited a robust increase in low-frequency (8-30 Hz) oscillatory power in the subthalamic nucleus (STN) following administration of the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). To test our neural control approach, we targeted 8-17 Hz oscillations and used electrode arrays and electrical stimulation waveforms similar to those used in humans chronically implanted with brain stimulation systems. Stimulation parameters that maximize the suppression or amplification of neural oscillations were predicted using mathematical models of the stimulation evoked oscillations. RESULTS: Our neural control and optimization approach was capable of actively and robustly suppressing or amplifying oscillations in the targeted frequency band (8-17 Hz) in real-time in the studied subjects. CONCLUSIONS: The results from this study support our hypothesis and suggest that the proposed neural control framework allows one to characterize in controlled experiments the functional role of frequency-specific neural oscillations by using electrodes and stimulation waveforms currently being employed in humans.

Parkinsonism and vigilance: alteration in neural oscillatory activity and phase-amplitude coupling in the basal ganglia and motor cortex.

Oscillatory neural activity in different frequency bands and phase-amplitude coupling (PAC) are hypothesized to be biomarkers of Parkinson's disease (PD) that could explain dysfunction in the motor circuit and be used for closed-loop deep brain stimulation (DBS). How these putative biomarkers change from the normal to the parkinsonian state across nodes in the motor circuit and within the same subject, however, remains unknown. In this study, we characterized how parkinsonism and vigilance altered oscillatory activity and PAC within the primary motor cortex (M1), subthalamic nucleus (STN), and globus pallidus (GP) in two nonhuman primates. Static and dynamic analyses of local field potential (LFP) recordings indicate that 1) after induction of parkinsonism using the neurotoxin MPTP, low-frequency power (8-30 Hz) increased in the STN and GP in both subjects, but increased in M1 in only one subject; 2) high-frequency power (~330 Hz) was present in the STN in both normal subjects but absent in the parkinsonian condition; 3) elevated PAC measurements emerged in the parkinsonian condition in both animals, but in different sites in each animal (M1 in one subject and GPe in the other); and 4) the state of vigilance significantly impacted how oscillatory activity and PAC were expressed in the motor circuit. These results support the hypothesis that changes in low- and high-frequency oscillatory activity and PAC are features of parkinsonian pathophysiology and provide evidence that closed-loop DBS systems based on these biomarkers may require subject-specific configurations as well as adaptation to changes in vigilance.NEW & NOTEWORTHY Chronically implanted electrodes were used to record neural activity across multiple nodes in the basal ganglia-thalamocortical circuit simultaneously in a nonhuman primate model of Parkinson's disease, enabling within-subject comparisons of electrophysiological biomarkers between normal and parkinsonian conditions and different vigilance states. This study improves our understanding of the role of oscillatory activity and phase-amplitude coupling in the pathophysiology of Parkinson's disease and supports the development of more effective DBS therapies based on pathophysiological biomarkers.

The use of micro-CT with image segmentation to quantify leakage in dental restorations.

OBJECTIVE: To develop a method for quantifying leakage in composite resin restorations after curing, using non-destructive X-ray micro-computed tomography (micro-CT) and image segmentation. METHODS: Class-I cavity preparations were made in 20 human third molars, which were divided into 2 groups. Group I was restored with Z100 and Group II with Filtek LS. Micro-CT scans were taken for both groups before and after they were submerged in silver nitrate solution (AgNO3 50%) to reveal any interfacial gap and leakage at the tooth restoration interface. Image segmentation was carried out by first performing image correlation to align the before- and after-treatment images and then by image subtraction to isolate the silver nitrate penetrant for precise volume calculation. Two-tailed Student's t-test was used to analyze the results, with the level of significance set at p<0.05. RESULTS: All samples from Group I showed silver nitrate penetration with a mean volume of 1.3 ± 0.7mm(3). In Group II, only 2 out of the 10 restorations displayed infiltration along the interface, giving a mean volume of 0.3 ± 0.3mm(3). The difference between the two groups was statistically significant (p<0.05). The infiltration showed non-uniform patterns within the interface. SIGNIFICANCE: We have developed a method to quantify the volume of leakage using non-destructive micro-CT, silver nitrate infiltration and image segmentation. Our results confirmed that substantial leakage could occur in composite restorations that have imperfections in the adhesive layer or interfacial debonding through polymerization shrinkage. For the restorative systems investigated in this study, this occurred mostly at the interface between the adhesive system and the tooth structure.