Neurophysiological Correlates of Trait Impulsivity in Parkinson's Disease

Basal ganglia theta power indexes trait anxiety in people with Parkinson's disease

Background

Neuropsychiatric symptoms are common and disabling in Parkinson's disease (PD), with troublesome anxiety occurring in one-third of patients. Management of anxiety in PD is challenging, hampered by insufficient insight into underlying mechanisms, lack of objective anxiety measurements, and largely ineffective treatments.In this study, we assessed the intracranial neurophysiological correlates of anxiety in PD patients treated with deep brain stimulation (DBS) in the laboratory and at home. We hypothesized that low-frequency (theta-alpha) activity would be associated with anxiety.

Methods

We recorded local field potentials (LFP) from the subthalamic nucleus (STN) or the globus pallidus pars interna (GPi) DBS implants in three PD cohorts: 1) patients with recordings (STN) performed in hospital at rest via perioperatively externalized leads, without active stimulation, both ON or OFF dopaminergic medication; 2) patients with recordings (STN or GPi) performed at home while resting, via a chronically implanted commercially available sensing-enabled neurostimulator (Medtronic Percept TM device), ON dopaminergic medication, with stimulation both ON or OFF; 3) patients with recordings performed at home while engaging in a behavioral task via STN and GPi leads and electrocorticography paddles (ECoG) over premotor cortex connected to an investigational sensing-enabled neurostimulator, ON dopaminergic medication, with stimulation both ON or OFF. Trait anxiety was measured with validated clinical scales in all participants, and state anxiety was measured with momentary assessment scales at multiple time points in the two at-home cohorts. Power in theta (4-8 Hz) and alpha (8-12 Hz) ranges were extracted from the LFP recordings, and their relation with anxiety ratings was assessed using linear mixed-effects models.

Results

In total, 33 PD patients (59 hemispheres) were included. Across three independent cohorts, with stimulation OFF, basal ganglia theta power was positively related to trait anxiety (all p<0.05). Also in a naturalistic setting, with individuals at home at rest with stimulation and medication ON, basal ganglia theta power was positively related to trait anxiety (p<0.05). This relationship held regardless of the hemisphere and DBS target. There was no correlation between trait anxiety and premotor cortical theta-alpha power. There was no within-patient association between basal ganglia theta-alpha power and state anxiety.

Conclusion

We showed that basal ganglia theta activity indexes trait anxiety in PD. Our data suggest that theta could be a possible physiomarker of neuropsychiatric symptoms and specifically of anxiety in PD, potentially suitable for guiding advanced DBS treatment tailored to the individual patient's needs, including non-motor symptoms.

Neuromodulation techniques - From non-invasive brain stimulation to deep brain stimulation

Over the past 30 years, the field of neuromodulation has witnessed remarkable advancements. These developments encompass a spectrum of techniques, both non-invasive and invasive, that possess the ability to both probe and influence the central nervous system. In many cases neuromodulation therapies have been adopted into standard care treatments. Transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), and transcranial ultrasound stimulation (TUS) are the most common non-invasive methods in use today. Deep brain stimulation (DBS), spinal cord stimulation (SCS), and vagus nerve stimulation (VNS), are leading surgical methods for neuromodulation. Ongoing active clinical trials using are uncovering novel applications and paradigms for these interventions.

Impulsivity Traits in Parkinson's Disease: A Systematic Review and Meta-Analysis

Background

In Parkinson's disease (PD), impulsivity as a personality trait may be linked to the risk of developing impulse control disorders (ICDs) during dopaminergic therapy. However, studies evaluating differences in trait impulsivity between patients with PD and healthy controls or between patients with PD with and without ICDs reported partly inconsistent findings.

Objectives

We conducted a systematic review and meta-analysis (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) of studies comparing Barratt Impulsiveness Scale (BIS-11) scores between patients with PD and healthy controls and between patients with PD with and without ICDs.

Methods

Eligible studies were identified through a systematic search in 3 databases. Mean differences with 95% confidence intervals (CIs) for BIS-11 total and subscale scores were separately calculated for studies comparing patients with PD and healthy controls and patients with PD with and without ICDs. Meta-regressions were performed to explore sources of heterogeneity (percentage of men, age, disease duration, and levodopa equivalent daily dose).

Results

A total of 40 studies were included in the quantitative analyses. BIS-11 total scores were significantly higher in patients with PD compared with healthy controls (mean difference 2.43; 95% CI, 1.03, 3.83), and in patients with PD with active ICDs compared with patients without ICDs (6.62; 95% CI, 5.01, 8.23). No significant moderators emerged by meta-regression analyses.

Conclusions

The present meta-analysis supports that impulsivity, as a personality trait, may characterize patients with PD, even in the absence of ICDs. Moreover, these data corroborate findings of clinical studies reporting higher levels of trait impulsivity in PD patients with ICDs compared with patients without ICDs.

Uncovering the neurophysiology of mood, motivation and behavioral symptoms in Parkinson's disease through intracranial recordings

Neuropsychiatric mood and motivation symptoms (depression, anxiety, apathy, impulse control disorders) in Parkinson's disease (PD) are highly disabling, difficult to treat and exacerbated by current medications and deep brain stimulation therapies. High-resolution intracranial recording techniques have the potential to undercover the network dysfunction and cognitive processes that drive these symptoms, towards a principled re-tuning of circuits. We highlight intracranial recording as a valuable tool for mapping and desegregating neural networks and their contribution to mood, motivation and behavioral symptoms, via the ability to dissect multiplexed overlapping spatial and temporal neural components. This technique can be powerfully combined with behavioral paradigms and emerging computational techniques to model underlying latent behavioral states. We review the literature of intracranial recording studies investigating mood, motivation and behavioral symptomatology with reference to 1) emotional processing, 2) executive control 3) subjective valuation (reward & cost evaluation) 4) motor control and 5) learning and updating. This reveals associations between different frequency specific network activities and underlying cognitive processes of reward decision making and action control. If validated, these signals represent potential computational biomarkers of motivational and behavioural states and could lead to principled therapy development for mood, motivation and behavioral symptoms in PD.

Subacute alpha frequency (10Hz) subthalamic stimulation for emotional processing in Parkinson's disease

BACKGROUND

Psychiatric comorbidities are common in Parkinson's disease (PD) and may change with high-frequency stimulation targeting the subthalamic nucleus. Numerous accounts indicate subthalamic alpha-frequency oscillation is implicated in emotional processing. While intermittent alpha-frequency (10Hz) stimulation induces positive emotional effects, with more ventromedial contacts inducing larger effects, little is known about the subacute effect of ventral 10Hz subthalamic stimulation on emotional processing.

OBJECTIVE/HYPOTHESIS

To evaluate the subacute effect of 10Hz stimulation at bilateral ventral subthalamic nucleus on emotional processing in PD patients using an affective task, compared to that of clinical-frequency stimulation and off-stimulation.

METHODS

Twenty PD patients with bilateral subthalamic deep brain stimulation for more than six months were tested with the affective task under three stimulation conditions (10Hz, 130Hz, and off-stimulation) in a double-blinded randomized design.

RESULTS

While 130Hz stimulation reduced arousal ratings in all patients, 10Hz stimulation increased arousal selectively in patients with higher depression scores. Furthermore, 10Hz stimulation induced a positive shift in valence rating to negative emotional stimuli in patients with lower apathy scores, and 130Hz stimulation led to more positive valence to emotional stimuli in the patients with higher apathy scores. Notably, we found correlational relationships between stimulation site and affective rating: arousal ratings increase with stimulation from anterior to posterior site, and positive valence ratings increase with stimulation from dorsal to ventral site of the ventral subthalamic nucleus.

CONCLUSIONS

Our findings highlight the distinctive role of 10Hz stimulation on subjective emotional experience and unveil the spatial organization of the stimulation effect.

Clinical neurophysiological interrogation of motor slowing: A critical step towards tuning adaptive deep brain stimulation

OBJECTIVE

Subthalamic nucleus (STN) beta activity (13-30 Hz) is the most accepted biomarker for adaptive deep brain stimulation (aDBS) for Parkinson's disease (PD). We hypothesize that different frequencies within the beta range may exhibit distinct temporal dynamics and, as a consequence, different relationships to motor slowing and adaptive stimulation patterns. We aim to highlight the need for an objective method to determine the aDBS feedback signal.

METHODS

STN LFPs were recorded in 15 PD patients at rest and while performing a cued motor task. The impact of beta bursts on motor performance was assessed for different beta candidate frequencies: the individual frequency strongest associated with motor slowing, the individual beta peak frequency, the frequency most modulated by movement execution, as well as the entire-, low- and high beta band. How these candidate frequencies differed in their bursting dynamics and theoretical aDBS stimulation patterns was further investigated.

RESULTS

The individual motor slowing frequency often differs from the individual beta peak or beta-related movement-modulation frequency. Minimal deviations from a selected target frequency as feedback signal for aDBS leads to a substantial drop in the burst overlapping and in the alignment of the theoretical onset of stimulation triggers (to ∼ 75% for 1 Hz, to ∼ 40% for 3 Hz deviation).

CONCLUSIONS

Clinical-temporal dynamics within the beta frequency range are highly diverse and deviating from a reference biomarker frequency can result in altered adaptive stimulation patterns.

SIGNIFICANCE

A clinical-neurophysiological interrogation could be helpful to determine the patient-specific feedback signal for aDBS.

Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation

Closed-loop adaptive deep brain stimulation (aDBS) can deliver individualized therapy at an unprecedented temporal precision for neurological disorders. This has the potential to lead to a breakthrough in neurotechnology, but the translation to clinical practice remains a significant challenge. Via bidirectional implantable brain-computer-interfaces that have become commercially available, aDBS can now sense and selectively modulate pathophysiological brain circuit activity. Pilot studies investigating different aDBS control strategies showed promising results, but the short experimental study designs have not yet supported individualized analyses of patient-specific factors in biomarker and therapeutic response dynamics. Notwithstanding the clear theoretical advantages of a patient-tailored approach, these new stimulation possibilities open a vast and mostly unexplored parameter space, leading to practical hurdles in the implementation and development of clinical trials. Therefore, a thorough understanding of the neurophysiological and neurotechnological aspects related to aDBS is crucial to develop evidence-based treatment regimens for clinical practice. Therapeutic success of aDBS will depend on the integrated development of strategies for feedback signal identification, artifact mitigation, signal processing, and control policy adjustment, for precise stimulation delivery tailored to individual patients. The present review introduces the reader to the neurophysiological foundation of aDBS for Parkinson's disease (PD) and other network disorders, explains currently available aDBS control policies, and highlights practical pitfalls and difficulties to be addressed in the upcoming years. Finally, it highlights the importance of interdisciplinary clinical neurotechnological research within and across DBS centers, toward an individualized patient-centered approach to invasive brain stimulation. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Spectral Topography of the Subthalamic Nucleus to Inform Next-Generation Deep Brain Stimulation

BACKGROUND

The landscape of neurophysiological symptoms and behavioral biomarkers in basal ganglia signals for movement disorders is expanding. The clinical translation of sensing-based deep brain stimulation (DBS) also requires a thorough understanding of the anatomical organization of spectral biomarkers within the subthalamic nucleus (STN).

OBJECTIVES

The aims were to systematically investigate the spectral topography, including a wide range of sub-bands in STN local field potentials (LFP) of Parkinson's disease (PD) patients, and to evaluate its predictive performance for clinical response to DBS.

METHODS

STN-LFPs were recorded from 70 PD patients (130 hemispheres) awake and at rest using multicontact DBS electrodes. A comprehensive spatial characterization, including hot spot localization and focality estimation, was performed for multiple sub-bands (delta, theta, alpha, low-beta, high-beta, low-gamma, high-gamma, and fast-gamma (FG) as well as low- and fast high-frequency oscillations [HFO]) and compared to the clinical hot spot for rigidity response to DBS. A spectral biomarker map was established and used to predict the clinical response to DBS.

RESULTS

The STN shows a heterogeneous topographic distribution of different spectral biomarkers, with the strongest segregation in the inferior-superior axis. Relative to the superiorly localized beta hot spot, HFOs (FG, slow HFO) were localized up to 2 mm more inferiorly. Beta oscillations are spatially more spread compared to other sub-bands. Both the spatial proximity of contacts to the beta hot spot and the distance to higher-frequency hot spots were predictive for the best rigidity response to DBS.

CONCLUSIONS

The spatial segregation and properties of spectral biomarkers within the DBS target structure can additionally be informative for the implementation of next-generation sensing-based DBS. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A systematic review of local field potential physiomarkers in Parkinson's disease: from clinical correlations to adaptive deep brain stimulation algorithms

Deep brain stimulation (DBS) treatment has proven effective in suppressing symptoms of rigidity, bradykinesia, and tremor in Parkinson's disease. Still, patients may suffer from disabling fluctuations in motor and non-motor symptom severity during the day. Conventional DBS treatment consists of continuous stimulation but can potentially be further optimised by adapting stimulation settings to the presence or absence of symptoms through closed-loop control. This critically relies on the use of 'physiomarkers' extracted from (neuro)physiological signals. Ideal physiomarkers for adaptive DBS (aDBS) are indicative of symptom severity, detectable in every patient, and technically suitable for implementation. In the last decades, much effort has been put into the detection of local field potential (LFP) physiomarkers and in their use in clinical practice. We conducted a research synthesis of the correlations that have been reported between LFP signal features and one or more specific PD motor symptoms. Features based on the spectral beta band (~ 13 to 30 Hz) explained ~ 17% of individual variability in bradykinesia and rigidity symptom severity. Limitations of beta band oscillations as physiomarker are discussed, and strategies for further improvement of aDBS are explored.

Impulsivity is associated with firing regularity in parkinsonian ventral subthalamic nucleus

Impulsive–compulsive behaviors (ICB) are over‐represented in Parkinson's disease (PD) patients. Neurons in the ventral subthalamic nucleus (STN) might play a predominant role in the modulation of impulsivity. We characterized the firing regularity of 742 subthalamic neurons from 24 PD patients (12 ICB+ and 12 ICB‐) in an OFF medication state. We computed the firing regularity in the dorsal and ventral STN regions, and we compared their performance in discriminating ICB patients. Regularity of ventral neurons in ICB+ patients is higher and supports a significant discrimination between the two cohorts. These results substantiate a ventral location of neurons involved in impulsivity.

Combining Multimodal Biomarkers to Guide Deep Brain Stimulation Programming in Parkinson Disease

BACKGROUND

Deep brain stimulation (DBS) programming of multicontact DBS leads relies on a very time-consuming manual screening procedure, and strategies to speed up this process are needed. Beta activity in subthalamic nucleus (STN) local field potentials (LFP) has been suggested as a promising marker to index optimal stimulation contacts in patients with Parkinson disease.

OBJECTIVE

In this study, we investigate the advantage of algorithmic selection and combination of multiple resting and movement state features from STN LFPs and imaging markers to predict three relevant clinical DBS parameters (clinical efficacy, therapeutic window, side-effect threshold).

MATERIALS AND METHODS

STN LFPs were recorded at rest and during voluntary movements from multicontact DBS leads in 27 hemispheres. Resting- and movement-state features from multiple frequency bands (alpha, low beta, high beta, gamma, fast gamma, high frequency oscillations [HFO]) were used to predict the clinical outcome parameters. Subanalyses included an anatomical stimulation sweet spot as an additional feature.

RESULTS

Both resting- and movement-state features contributed to the prediction, with resting (fast) gamma activity, resting/movement-modulated beta activity, and movement-modulated HFO being most predictive. With the proposed algorithm, the best stimulation contact for the three clinical outcome parameters can be identified with a probability of almost 90% after considering half of the DBS lead contacts, and it outperforms the use of beta activity as single marker. The combination of electrophysiological and imaging markers can further improve the prediction.

CONCLUSION

LFP-guided DBS programming based on algorithmic selection and combination of multiple electrophysiological and imaging markers can be an efficient approach to improve the clinical routine and outcome of DBS patients.